An Art fair is a booth-style marketplace offering a selection of artworks for sale, giving attendees the possibility to be key actors within the art world’s ecosystem. This club-like network encompasses individuals engaged in production, commission, presentation, preservation, promotion, documentation, critique, and the commercial aspects of art. It is bound by a shared conviction in the value and importance of Art.
Through buying and selling, Art fairs sustain the economic viability of artists and galleries while fostering an environment where art enthusiasts, collectors, and professionals can engage directly. This dynamic ecosystem plays a crucial role in shaping contemporary art trends, influencing both the market and artistic discourse. Art fairs are combining the role of a transactional space and a cultural institution that propels the art world forward.
The main actors involved in art fairs:
Organizers
Curators
Artists
Art dealers
Art critics
Art dealers
Collectors
Participants
Ordinary visitors
Are art fairs worth it?
Why do galleries pay a high fee and attend art fairs? Are art fairs good for artists? For example, to attend FIAC, the largest fair in France, costs around 15,000 EUR plus 20% tax for a 25-square-meter booth (the size of my kitchen). Not to mention the other associated costs.
1. Art fairs validate you as an artist
It’s hard to get into major international art fairs. Some art professionals would even call Art Basel Miami the Olympics of the art world. Usually, the organization sets a list of requirements such as being operational as a physical gallery for at least two years, having attended X number of similar art fairs, having several artists under the label, and the works must carry certain characteristics. To have exhibited at famous international art fairs like Art Basel Miami, FIAC, and in Spain, ARCO will bring you a reputation and respect in the industry.
2. They bring sales opportunity
Dealers are business owners; they make decisions based on financial outcomes. Dealers can make almost half of what they would make during the whole year by going to just five art fairs. Of course, these are just estimates and data from interviews with gallery owners. Regardless of the accuracy, it offers a snapshot of the economy behind art fairs. There is definitely a business drive behind paying tens of thousands of dollars to rent a booth and hire extra staff, not to mention the logistics!
3. They connect your art to the art world
ARCO alone can bring 100,000 art collectors to your booth, making it a great opportunity for exposure for networking. Art critics and journalists will be visiting the fair, generating some news pieces more likely to catch people’s attention. Also, internally, many artists will be more attracted to a gallery that brings their works to different fairs than the ones that don’t.
4. Be careful with the Fear of Missing Out (FOMO)
If you are not attending the larger fairs, you might be missing a lot of potential opportunities. In order to keep returning to large fairs, you need to attend smaller ones to be admitted. It goes into this “fair after fair” circle, and once you are used to it, you fear to change.
Christmas time is the best time of the year. We want to give something special to our family and friends. I’d like to include unusual gifts for him and her here that are more than the art supplies section, although getting a box of great art supplies is a big Christmas gift!!! In this post, I’m going to include artful gifts for artists and photo/video enthusiasts, content creators, and alike. These products are not cheap but of good if not excellent quality and can serve you for years to come. You can buy them all on Amazon. Links are included below. Let’s dive in.
I like this tripod because it’s stable. There are so many tripods out there that are flimsy and not suitable for a DSLR camera. This one is. I also love that it’s so compact and portable! It fits in a very small bag that comes with it that I can take with me whenever I travel. It loads up to 20 lbs of weight and comes with a mount for your phone as well. It’s made of aluminum and weighs under 3 pounds. Center support can be converted into a stand-alone monopod. There is a hook under it that allows for the placement of additional weight like a backpack if you’re hiking and want to add more weight to the tripod to stabilize it even more. It stretches much higher than a regular tripod and can sit super low, almost at the ground level if you want to shoot something from a different perspective.
The only thing I don’t like about this tripod is that it does take longer to set it up because of all the adjustable points in it. It takes a while to learn what knob to screw or unscrew. Otherwise, I’m glad I bought it for my studio. I can see that I’d been using it for many years.
Even if you’re not a photographer, you can use these memory cards with your computer for storage. Just plug in, drag, and drop files from your computer to those cards. They come in different sizes and price varies quite a lot. 128 GB is under $25 and 1TB is $139. You can pick the size of the card on Amazon. SanDisk Cards work very well and I often travel with them. Just be mindful that they do stop working in a few years because of solar flare damage and other issues.
This lamp will elevate your lighting experience because it features adjustable brightness, high-quality design, LED lifespan of up to 40,000 hours, gesture control, occupancy sensor (lights on when you sit down, off when you leave), night light, timer off, and auto-brightness adjustment. The desk light can be positioned at multiple angles. It can be placed way above the head to give a nice and even illumination. It has a stable base and is ideal for work at the desk, doing small painting, crafting, jewelry-making, or nail art.
This is a very small but powerful LED light lamp that fits in your pocket. It also mounts to a DSLR camera or any other mount that you have in your art and content creator studio. You can use it both inside and outside. It has a very nice, adjustable brightness and color temperature ranging from 3200K to 5600K. Its battery lasts for several hours but for extended use, simply plug it in and continue creating if you are out of battery time. This portable LED light comes with an extra light panel diffuser and shoe mount, designed for seamless integration with your LED video light. It charges via a USB port. I usually use it to have an additional light on my face or as a light for my Nikon to shoot outdoors at dusk.
This is a very versatile colorful light that you can use all around your studio and beyond. The light is bright but adjustable. There are many settings and colors to choose from and I have lots of fun using it in my video and photography. It charges via a USB port and it can be mounted if needed. Its length is about 22.7 inches (57.8cm). It’s light to carry around in a soft bag. You can use it with the app but I normally set it directly.
Bonus: colored pencils box & art instruction books
Prismacolor Premier colored pencils, I recommend a box of 36 or 72 colors. This is an official store page on Amazon where you can pick your favorite box.
Sabrina Shah’s previous exhibitions have drawn our attention to food and relationships, particularly the dinner table as a site charged with emotion and the potential for something, anything, to happen.This setting becomes a space where everything is “on the table”—an enticing yet petrifying prospect for many artists on the verge of laying themselves bare.
It’s perhaps for this reason that I’m not that surprised to see so many chickens in Shah’s workshop. Not real chickens, of course—that would be chaos. But chicken sculptures, chicken drawings, and even a broken chicken that Shah has been attempting to piece back together after it smashed in transit. Its cartoonish eyes eerily gaze up at me, its little chicken head caved into its pot body, awaiting its fate.
Detail from Chicken by Sabrina Shah (acrylic on canvas, 2023, 40 x 30 x 5 cm)
“I like chicken,” she tells me. “I like the word chicken, I like the way it sounds.” I reflect on this as I leave, swirling the word in my mouth; the snap of the tongue against the roof of the mouth, the closing of the jaw on the “ch,” and the pull back of the lips on the “ken,” almost like taking a bite. Even for a veggie, I admit the word is quite delicious to sound out.
But it’s more than just the sound that attracts Shah. Chicken, as a word and a concept, brims with topical and propositional possibilities. “I think I’m poking fun at the fear factor,” she muses. “You’re a chicken/you’re not a chicken!” This internal dialogue, I gather, is one Shah is all too familiar with when daring herself to take the next step with a piece. Will you be the chicken served up on the table of doom? Or will you be brave?
Takeaway by Sabrina Shah (acrylic and mixed media on canvas, 2023, 170 x 130 x 5 cm)
This playful yet poignant engagement transforms “Chicken” into a vehicle for deeper reflection, inviting viewers to consider the self-destructive mind games we play with ourselves and each other. Through this lens, “Chicken” becomes a symbol of the wider human experience, highlighting our fears about not being good enough, the complexities surrounding personal and social identity, and our innate ability to manipulate.
Life Cycle by Sabrina Shah (acrylic and photography on canvas, 2022, 115 x 85 cm)
Unlike any chicken I’ve ever met, Shah is a solitary creature. Announced if not by her quiet demeanour but the fact she’s chosen a storage unit as her studio. She prefers spaces away from the main road and the bustling environment of shared studios, where her work can be “safe” and uninterrupted by other humans. I suddenly feel very privileged to be in Shah’s personal space.
I’m openly intrigued by the contrast between the artist—polite, kind, and attentive to details, kindly offering me water, Coca-Cola, and fruit, on several occasions, to make sure I feel at ease—and her art, which is fierce, unapologetic, and sensorially demanding. Initially, it’s challenging to connect the two. Where Shah is softly spoken and mindful of her words, her work is loud and provocative.
Sabrina Shah in her workshop next to the broken chicken pot
Something that does strike me as a similarity is Shah’s non-linear thought-processing, a verbal accompaniment to the layered nature of her work. I can almost hear the cogs turning as she contemplates her response, connecting seemingly unrelated concepts before they dip back beneath her waves of consciousness, perhaps to resurface later. Her work, in tow, does not unfold in a clear sequential manner or unravel in straight lines. It weaves a complex narrative.
Juggling by Sabrina Shah (acrylic on board, 2024, 40 x 30 x 5 cm)
Shah’s work is inherently inconclusive; I think it’s fair to say that Shah does not draw conclusions. While her pieces are rich with hidden meaning and intricate in structure, they resist systematic composition. Through cutting, sticking, smudging, layering, and repeatedly deconstructing her work, Shah pulls in elements from various time periods, historical references, and phraseology. The result is art that communicates energetically—visually, emotionally, and intellectually—yet deliberately withholds answers, leaving the truth elusive and unsettling.
CHECK MATE (acrylic and fabric on canvas, 2024, 60 x 60 x 2 cm)
Indeed, Shah’s work is filled with contradictions, creating ambivalent and enigmatic storylines. In Bullseye, the word is imposed over a cheerful bull figure, subtly questioning power dynamics and (dis)honesty: Who holds the power? Who is the victim?
In Half Full, a frenzied feast takes place—Shah flipped the canvas over several times during its creation, a process consuming more than a few years—producing a topsy-turvy landscape where up and down, left and right resist meaning. Beneath its playful surface lies an unnerving darkness: gushing blood-red tones, violent shards of light, and glimpses of infamous cartoon characters like Tom and Jerry buried beneath layers of paint. Their half-obscured fight points a haunting finger at hidden conflict and unresolved hurt. Shah’s work powerfully embodies how joy can quickly twist into terror, how consumption can spiral into excess, and how the line between light and shadow is often blurred.
Bullseye by Sabrina Shah (acrylic and fabric on canvas, 2024, 70 x 50 x 4 cm)
I’m intrigued by Shah’s way of describing her creative process in terms of problem-solving; aesthetic elements or the placement of new figures “offering a way out” or “a way in,” depending on your perspective.
Further to this conundrum is her blend of stylistic and thematic tensions. Her artworks balance surface tension—with ripples of paint, impasto smudges, and collaged pieces like paper, fabric, and photographs—against thematic tensions that leave you questioning whether something is good or bad, happy or sad, excited or stressed, as inferred in Bullseye, above, and in Half Full, pictured below. Viewers can follow the evolution of each piece, challenged to abandon the need for control or resolution. Instead of approaching her art as a puzzle to be solved, I feel dared to surrender and embrace the uncertainty of it all.
Half Full by Sabrina Shah (acrylic on canvas, 2024, 170 x 120 x 5 cm) surrounded by smaller works by the artist
I’m conscious that for many artists, it’s uncomfortable to explain why they’ve done something in their work. I’m careful when asking what, exactly, needs to be solved, or where, exactly, there should be relief. “I don’t really know why I do things sometimes,” Shah quietly announces. We discuss how trying to theoretically deconstruct paintings can explain them away. Maybe this is why Shah sometimes prefers to be among her paintings rather than in society. Justifying your art is tiring, at times unproductive, and easily turns into a therapy session nobody asked for. We both agree—let the art speak for itself. If we rely too heavily on spoken language to understand art, we limit our ability to connect with it on a deeper level and, arguably, to connect with ourselves and others.
Mixed media paintings by Sabrina Shah, available individually and as a series. Contact us for more details.
“Do you know the Philip Guston quote?” She asks me.
When you’re in the studio painting, there are a lot of people in there with you – your teachers, friends, painters from history, critics… and one by one, if you’re really painting, they walk out.
Painting is one way to really get quiet. To let the deluge of inner thought and confusion out. To set all the voices and opinions you’ve consumed from those around you free.
And,if you’re really painting, you walk out too.
Shah’s paintings draw in all the noise and the chaos; they are not conductive, they absorb, insulate, and digest the external into their own hidden world beyond the exterior of the canvas. With their loudness and luminosity, they boldly stomach all that we’re trying to rid our minds of, allowing us to seek a little peace.
Interestingly, I don’t think it’s the chaos that scares us most. It’s the quiet. So maybe the closing question is: are you brave enough to seek peace? Or are you a chicken?
Plate 314. Machine Appropriate for Making Flat Wavy Mouldings
The following is an excerpt from “With All the Precision Possible: Roubo on Furniture.” This book is the result of more than a decade of work by an international team that produced the first English translation of the 18th-century woodworking masterpiece: “l’art du Menuisier” by André-Jacob Roubo. This translation covers Roubo’s writing on woodworking tools, the workshop, joinery and building furniture.
In addition to the translated text and color images from the original, “With All the Precision Possible: Roubo on Furniture” also includes five contemporary essays on Roubo’s writing by craftsmen Christopher Schwarz, Don Williams, Michael Mascelli, Philippe Lafargue and Jonathan Thornton.
The excerpt below details a machine that had gone out general use even before Roubo wrote the original text. However, there is no denying that the illustrations and explanation of the device are captivating. The details on it inspired Jonathan Thornton to recreate one of these machines and write an essay on it for “With All the Precision Possible.” A portion of the essay will be the excerpt for next week.
Description of the Machine commonly called the tool for waves, and the way of making use of it in different ways The machine that I am going to describe is the largest and the most complicated of all the cabinetry tools, which once were much used. Now they are not used much, since they are only used for works of applied wood [moldings] and they have, so to speak, combined all their science to veneer the wood properly. However, since this tool is ingenious, and you cannot find it anywhere, I thought I must include it here, in order to save it for posterity, supposing that this work succeeds.3
The use of the wave-cutting Tool represented in Fig. 1 is for cutting onto the wood wave-mouldings, or patterns, precise intricate repetitive designs, whether flat, on the face or even in both directions at the same time.
It is composed of a box from 7 to 8 feet in length, by one foot wide and 9 to 10 thumbs in height, exterior outside measurements. This box is open on top and at the ends, such that the distance between the two sides is retained only by cross-pieces A and B, Figs. 1 & 2, placed at two ends of the box, where they are assembled by mortise and tenon. At about the middle of the height of the box is placed a plank C–D, Fig. 2, about 2–thumbs thick, called a sommier [or platform, mattress; in similar machines for printing lithographs this is called the couch or the cooch]. This, for more strength, should be fit together at the ends and braced from below. This plank, or sommier [platform], is held in a groove in the two sides of the box (which should not be less than one–and-a-half thumb in thickness) and serves to hold the mouldings to be wave-cut, as I will explain later, and which you can see in Fig. 2, which represents the machine viewed from above.
In the middle of the box is placed a square frame of about a foot in width, viewed from the side, and which extends from 9 to 10 thumbs above the box, to the sides of which it is attached with some screws, and in which it enters by tenon and a notch, as you can see in the evolution of this machine, represented in the following Plate [315] Figs. 5 & 6.
The width of this frame is determined by the width of the box, the sides of which the uprights of the latter are flush on the interior. It is in this frame that is placed a spring which presses on the toolholder [the cutterhead] E, Fig. 1. This spring is raised and lowered by means of the screw F, Figs. 1 & 2.
The whole machine is held on a base of a solid construction and widened [splayed] in the form of a trestle to give it a better footing. The height of this base should be from 2 feet 8 to 10 thumbs, so that is has about 3 feet in height from the axis of the crank handle G to the ground. This is the most comfortable height for the person who turns this crank handle to have all his strength, whether raising or lowering it.
There are in this machine two movements: one is horizontal, which is done by means of the handle G, Fig. 1, which by making the pinion turn placed in the interior of the box, moves the sommier A–B, Fig. 2, and consequently the work which is held above.
The other movement is vertical, downwards, and depends on the first. The rod, or wave guide/ channel H–H, Figs. 1 & 2 [Plate 315], which is held on the sommier, moves therefore with the latter, is raising the tool-holder F, Fig. 1, left, which then lowers immediately by itself, both by its own weight and by the pressure of the spring placed above. See Fig. 4, which represents a wave channel the size of the execution [ full-size/scale] Fig. 5, [which] represents a moulding completely wave-formed, according to the sinuosity of the wave channel in Fig. 4. Also see Fig. 3, which represents the cross-section of the tool-holder, which I will describe here later.
Fig. 6 represents a cutting blade viewed with different profiles, as large as the execution [ full-size/scale].
Figures 1 & 2 of this plate represent one of the transverse cross-sections of the machine, taken at the location of the pinions and the other the longitudinal cross-section of the same machine, so as to better understand the details of its construction and the mechanism of its operations.
Axis A–B, should be placed in the copper collars, a, b, so that they turn more easily. One should note at one of the sides of the box [is] a squared opening capable of letting pass pinions C–D, supposing that it is necessary to remove the axis outside. Pinions C–D, engaged in the toothed rack c, d, Fig. 1, and E, F, Fig. 2, which are embedded on the underside of the carriage [platform] G–G, same Figure, about 9–lines deep, and are held there by pegs, placed together in the sides of the latter, observing that the toothed racks are well positioned vis-a-vis the other, so that the two pinions C–D, Fig. 1, are contacted equally by the racks [platform] above. However, as it can happen that the teeth of the pinions are not well positioned vis-a-vis the other, one would do well, after having stopped/blocked one of the toothed racks, not to attach [secure] the other until after verifying that it fits well with its pinions, so as to be able to set it back or advance it as necessary.
Plate 315. The Development of the Machine Represented in the Preceding Plate
These racks can be made of iron or copper, which makes no difference for the machine, however it would be good that they be made of copper, given that the rubbing of two different metals is smoother and wears less than if the two pieces, that is to say, the rack and pinions, be of the same metal. [See Plate 314.]
The rods or wave conduits [channels or guide rails for the work piece] e, f, Fig. 1, and H, H, Figs. 2 & 6, should be also made of copper, and they should be bent at a right angle to have the ability of attaching them with screws on the carriage [platform] in which they are notched in all their thickness, as one can see in Figs. 1 & 6.
When you put these [wave] channels on the platform, you must pay the greatest attention that the guilloche [pattern] be not only fit well together, but also that they match at the same point of their contour with the contact of the tool-stand which bears on top of it, as you can see in Fig. 4. This represents the machine viewed from the end, and even better in Fig. 7, which shows the toolstand [tracing and cutting head] where you have removed the cheek [ fence] which holds the iron in place, as I will explain later.
The tool-stand is a frame I–L, M–N, Figs. 2 & 5, of about 2 feet in length, by a width equal to the interior of the box, less the necessary play to prevent any rubbing, which you avoid by diminishing the thickness of the uprights in the entire length, and reserving there some heels at the ends, so that the frame is held against the sides of the box, and cannot get out of place when you move it.
The frame of the tool-stand is attached at the sides of the box by means of two threaded bolts, represented in Fig. 3, half as large as executed here, where the extremity o ends in a cone, and bears on a copper collar embedded in the side of the box.
This screw is held in place in the frame by a nut placed in the middle of its thickness, normally. To prevent the movement of the frame so that it does not turn the screw, you put a counter-screw P outside, which you tighten against the frame, which prevents the screw from making any movement. See Figs. 3 & 5.
As it is sometimes found where it is necessary to lift the point of the movement of the toolstand, you pierce many holes in the copper collar attached to the side of the box, as I did in Fig. 2.
At the other end of the tool-stand, that is to say, where the cutting iron is secured/fitted, the cross-piece I, Fig. 2, should be very strong and assembled with a cover from above so as to present a uniform surface all along the length, which is the width of the tool-stand. Then you apply from above a piece of iron attached with some screws with countersunk heads, of a length equal to the width of the latter. And you make it overlap by about 5 or 6 lines at both ends, to make two frets that bear on the wave pattern [channels], and you make a notch in the middle of this piece of the size of the iron for positioning the cutting iron of the tool, as you can see in Fig. 7.
This iron is held in place by a cheek [ fence] (whether of iron or copper, either is equal), that you hold in place by means of two square-headed screws, g–g, Figs. 2, 4 & 5, where the nut is placed in the thickness of the cross-piece of the frame. See Fig. 3 of Plate 314, where I showed the cross-section of the tool-stand, with the contact I, the iron L, and the exterior cheek [ fence] M, which comes down as low as possible, that is to say, just to the bottom of the part the most hollowed of the latter.
The bottom of contact I [Plate 314] should be the thinnest possible (without however being a sharp edge), so that it follows well all the contours of the wavy pattern N–O. You must take great care that the point of contact for the fret be in the same direction as the iron cutting edge [both bevels are in the same direction], as I noted in this figure, so that the movement of the tool (which is made in describing an arc, where the center is found at the end of the frame) be less noticeable. I have partially remedied this by lengthening the point of the center of movement as much as has been possible.
The weight of the tool-stand should be almost sufficient to make the cutting iron bite into the surface of the wood workpiece. However, one must always put a spring there, both for augmenting the weight of the tool, supposing that it be necessary, and preventing it [ from] jumping around.
This spring h–i, Fig. 2, does not bear immediately on the tool-stand, but on a lever where its arms are loosely attached to the uprights of the movable frame of the box at m, Figs. 2 & 5.
The other end bears on the cross-piece of the tool-stand at n, which augments at the same time the strength and the elasticity of the spring, where the upper part is held below the small shelf O, Fig. 2, with screw P, where the nut is placed in the top of the frame Q. This screw serves, as I already said, to increase or diminish the pressure of the spring. The small shelf O through which passes the lower end of the screw, serves nothing but to hold it in place, and to press the heel o of the spring. As this small shelf is movable, you hold it from the opposite side of the screw with two pins, which you place across the uprights of the frame, as indicated by points p–p.
I made the head of the screw P in the form of a screw-eye, so that one cannot tighten it or loosen it by simply touching it, and so that you have need for a little pry bar or crank handle to do it. Those who approach the machine while it is adjusted cannot disturb anything there by simply touching it.
It is for this same reason that I prefer the screws with squared heads for closing the cheek [ fence] of the tool-stand, because a wrench is necessary to move these sorts of screws. You can eliminate their access from everyone’s hands, and consequently prevent anyone from changing anything on the tool.
As to the manner of using this machine, it is very simple. You begin by planing some wooden strips to the thickness of the profile that you have chosen, and the projection of the waves. This being done, you put in the tool-stand a smooth iron, which you adjust to the height equal to the projection of the moulding. You hold the strip on the platform, by means of little iron points placed [on the latter by equal distances from each other], and you make the machine move by turning the crank handle, which advances the platform forward. Consequently, the strip that is attached to the platform, after having passed many times under the smooth iron, is found to be wavy on its surface.
When the strip is thus finished, you remove the smooth iron, and you substitute the one that is shaped with a profile, and you begin the operation again, just until the iron is not cutting the wood any more, and consequently the moulding is perfectly finished.
You must take great care before running the moulding to verify that the wooden strip is placed truly parallel, which you know by making it pass the entire length under the blade that you hold elevated above. You should secure the strip on the platform only after having taken this precaution. You must also note that the pins that you place in the platform to hold the mouldings are positioned in the middle of their width [thickness of the moulding stock], and that they do not project enough to be able to meet the blade and cause any breakage, which you must take great care to avoid.
The blade of the waving tool is always placed perpendicular to the workpiece, which makes it scrape enough to cut, which cannot be otherwise, given that if you slant it in the normal way with moulding planes, it would scratch/drag on the wood as it comes against the grain, which happens at each undulation. What’s more, the blade thus slanted will no more be found in the same direction in all parts, which you must avoid as much as possible.
Since you can make many different blades, you must pay attention that they be all the same width, so that they completely fill the notch made in the piece which makes the cuts. You must also pay attention that they are all the same thickness, and that this thickness be considerable, to better resist the force of the wood in passing below.
The handle with which you move the waving tool can be placed to the right of the machine, as in Fig. 6, or to the left, as in Figs. 1 & 4, which makes no difference.
Each of these ways placing the handle has its advantages and disadvantages. If you place it to the right, which is the most natural way (since you made some effort pushing it), you cannot see the work well, behind which you position yourself. If on the contrary you place it to the left, you see the work clearly, but you are required to turn the handle in reverse. That is why, in order to eliminate these two inconveniences, I believe it would be better to position the two ends of the axis so that each one can receive a handle, like in Fig. 5, such that you can use it as you judge appropriate, whether on the right or on the left, or even from both sides at the same time.
3 It has not been possible to find a surviving wave-cutting Tool to make a good description of it. I have had only two iron blades, sold with other scrap metal which have nevertheless been very useful for fixing certain sizes, that I could not have known except for the description that Mr. Felibien made of this tool, which is otherwise very succinct, but imprecise, such that it could serve only to give me an idea of this machine, which I have then arranged in such a manner that it appeared to me the most likely. It has been greatly wished that those who have described this Machine in the Encyclopedia [of Diderot] had done something other than copy Mr. Felibien, instead of adding to the obscurity and inexactitude, as they have done. It would have been very useful to the public, and in particular to cabinetmakers, for whom they would have saved, or better said, presented one of their principal tools.
In the summer of 2022, a team of deep-sea researchers spent six weeks in the North Atlantic Ocean at a remote site about 370 nautical miles off the coast of Newfoundland. The final resting place of RMS Titanic, which sank on April 14, 1912, the ocean floor bears the magnificent remains of the 883-foot-long vessel. When the ship disembarked from Southampton, England, it carried more than 2,200 passengers and crew, but only about 700 were rescued after it struck an iceberg.
Using remotely operated underwater vehicles, scientists explored the wreck from a range of vantage points, expanding their survey across a debris field that stretches as wide as three miles. The aim of this expedition revolved around capturing an unprecedented digital view of the ship, enabling a lifelike, virtual reconstruction.
Two submersibles captured a whopping 16 terabytes of data, comprising 715,000 images and a high-resolution video. The files were processed and assembled over the course of seven months to create what Atlantic Productions head Anthony Geffen describes as a “one-to-one digital copy, a ‘twin,’ of the Titanic in every detail.”
Released last Friday, Titanic: The Digital Resurrection chronicles the monumental task of capturing the footage and creating a never-before-seen view of the famous site. Produced by Atlantic Productions and National Geographic, the film follows the crew of deep-sea investigation outfit Magellan as they explored the iconic, hulking remains.
“Accurate to the rivet,” a statement says, the film traces nearly two years of research by historians, scientists, and engineers. “Their mission is to review and challenge long-held assumptions, including reconstructing a minute-by-minute timeline of the tragedy to uncover new insights into the ship’s final moments on that fateful night in 1912.”
Titanic: The Digital Resurrection is now streaming on Disney+ and Hulu.
It’s worth noting that this year’s ARCO has faced criticism, as is often the case, with two main points standing out:
Nothing really new
Firstly, there’s a noticeable lack of innovation. After almost half a century, things can start to feel repetitive. While consistency is reassuring, there’s a shortage of new ideas, media, and experimental endeavors. Despite being a trade show where sales are paramount, nurturing creativity and pushing boundaries is essential.
Costly
Secondly, accessibility has become a significant concern. With ticket prices soaring to 52 EUR per person at the ticket office and 44 EUR online (22 for students), it’s becoming increasingly inaccessible to those from more modest backgrounds. This high cost alienates potential art lovers and collectors, hindering the growth of the art community. Many online commenters have voiced their discontent with this issue.
The Rise (and Trap?) of Textile Art
Textile art is gaining traction at art fairs, often championed by women artists. They use weaving to revive traditional techniques or elevate craft as an art form. While the art world pushes for inclusivity, women are often confined to craft-based media. The trend reinforces a divide—textiles for women, painting and sculpture for men. How many male artists do you see weaving? Almost none. Instead of breaking barriers, this trend might be reinforcing them.
Women make up 40% of the artists at ARCO
A respectable percentage. But dig deeper: women dominate in the Opening section, which is dedicated to young galleries. Emerging platforms seem to embrace change faster than the establishment. Will this momentum carry over, or will the traditional market gatekeepers keep the balance lopsided?
The market still plays by old rules
Money speaks. The highest-priced pieces at ARCO remain in the hands of dead male giants from a long time ago. Joan Miró’s “Head with Three Hairs Facing the Moon” commands €1.6 million. A still life by Juan Gris, “Pipe et Paquet de Tabac” sits at €1.25 million.
I don’t know about you, but I find the subject of AI image generation fascinating. It’s a new realm of technological advancements, creativity, and ethical issues that many artists grapple with today. AI Art Generators like Midjourney, Stable Diffusion, Deep Dream Generator, and Dall-E 2 are popular tools, allowing users to create stunning images from simple text prompts. Although I’m not a scientist or software engineer, I’m interested in learning about this groundbreaking technology of AI image generation.
There is a growing concern about the use of AI. Joe Rogan often expresses his fear of humanity being taken over by the machines. As AI art becomes more sophisticated, there are serious concerns about copyright infringement, the potential for misuse, and the impact on us, real artists. While these are valid concerns, I think this topic is more nuanced and each question might have a different solution.
Joe Rogan, oil painting, 16x20in, Veronica Winters
Advantages of using AI art generators:
As a creator myself, I think that the AI image generation has several unique advantages that are not obvious. First of all, it’s a great tool to explore your creativity. Just like by looking at original art, you may feel inspired and hopeful by looking at generated images. There is quick satisfaction from the image generation process as you type in a text and see the immediate result on the screen with your participation. Therefore, AI image generation can offer instant psychological help when needed. I often render images when I feel down and need positive energy. To create art, you must dedicate considerable time to learning the skill, while AI image generation takes a few seconds to give instant results. Try DeepDream generator or other service to create stunning AI images and video.
Other obvious advantages include the low cost of image creation for small businesses, increased productivity for creators and video editors, a tool for the movie creation process, and a new income stream for companies selling generative AI models. Overall, it’s an exciting evolution in human development!
Blue lily dream, 20×30 inches, colored pencil on art board by Veronica Winters
I believe that Ai won’t replace us, humans and artists in terms of creativity, emotions, and intelligence. The reason is simple. We have a Divine Spark of the Creator or Higher Consciousness inside us that the algorithms and machines don’t possess. Is it possible to program emotions into the AI model to make it feel joy, excitement or suffering? Is it possible for AI models develop attachment, sense of meaning and time, or feelings of passion or loss? Can it become self-aware? Even if a complete awareness is possible for it, will AI models search for their true meaning or experience a crisis like a human being? It could probably learn to see the beautiful but unable to appreciate the miracle of life. What’s real is the legitimate fear of misuse and biased training of the AI-generative models.
Drawbacks:
I understand that many artists are frustrated with the use of AI art. It’s already tough to make a living doing art and this AI art generation idea feels like an assault on our creativity and job security. Sometimes, I get angry comments about my rare use of AI-generated images in videos to illustrate concepts. Other times, artists lash out at other artists who use AI to create digital art.
Besides legitimate ethical concerns about copyright infringement of original art taken without the artist’s permission to train the models, artists lose some freelance jobs that usually help us offset studio costs. For example, many writers self-publish today and don’t need to hire an artist for their book and cover illustration anymore. Music album covers, posters, and marketing materials can be done with the AI image generators, leaving real artists scraping by or searching for other paying gigs. Freelance photographers may be undercut doing product photography gigs as these images can be rendered. It takes many years to master the artistic skill, yet it passes by as a shiny object of AI image generation.
Also, AI image generators need a constant stream of new, quality data to create better imagery. Therefore, original art gets scrapped from all major social media platforms and image databases without the artist’s permission. Artists are not paid to “give” their images as we normally see in licensing agreements, yet these AI companies generate revenue by selling their services to us. I think this issue would be resolved legally at some point.
Finally, as humans program the models, we can see social biases in the generated images. Remember, the first images generated by Google’s AI? These were black Nazies, popes, Vikings, and the Founding Fathers!
AI-generated Image in Deep Dream Generator
Brief History
Deep learning and artificial intelligence (AI) imaging have evolved significantly since their inception. The origins of AI trace back to the mid-20th century, when Alan Turing’s 1950 paper, Computing Machinery and Intelligence, laid the foundation for machine learning concepts. In the 1950s and 1960s, pioneers like Marvin Minsky and John McCarthy developed early AI models, and coined the term “artificial intelligence” during the 1956 Dartmouth Workshop. Deep learning, a subset of AI, gained traction in the 1980s with Geoffrey Hinton’s revolutionary backpropagation algorithm, which allowed neural networks to adjust their weights through feedback. Hinton, along with Yann LeCun and Yoshua Bengio, is often regarded as one of the “godfathers of AI” for his contributions to deep learning. The modern renaissance of AI imaging began in the 2010s, fueled by advances in deep neural networks and datasets like ImageNet, developed by Fei-Fei Li, which enabled machines to surpass human capabilities in image recognition by 2015.
Deep learning’s impact on AI imaging has been transformative, enabling innovations across diverse fields such as medicine, biotech, art, and entertainment. Techniques like convolutional neural networks (CNNs), introduced by LeCun in the late 1980s, revolutionized image processing by mimicking how the human brain interprets visual information. Today, tools like GANs (Generative Adversarial Networks), popularized by Ian Goodfellow in 2014, create hyper-realistic AI-generated images. For those delving into the technical depths of these advancements, resources like course notes provide invaluable insights into the concepts and methodologies that drive this ever-evolving field. As AI imaging continues to evolve, it remains a testament to decades of innovation, collaboration, and curiosity in the pursuit of intelligent machines.
The process of AI image generation
AI image generation is a complex process. It involves training the Model and then using Image Generation.
To train the Model, companies collect a massive dataset of quality images and their corresponding text descriptions. Feature learning involves the AI model analyzing the images and text descriptions to learn patterns, styles, and relationships between visual and textual elements. The model training consists of deep learning, specifically using neural networks. This training process involves adjusting the model’s parameters to minimize the difference between its generated images and the real images in the dataset. The model needs a constant stream of quality data.
To generate the Image, the user enters a text prompt or description and the AI creates the visual result. It’s fascinating to learn that the AI starts with a random noise image, which is essentially a matrix of random numbers, in other words, layered mathematical matrices. The model iteratively refines the noise image based on the text prompt and its learned knowledge. It adjusts the pixels in the image to match the desired features, styles, and objects described in the prompt. After multiple iterations, the model produces a final image that aligns with the user’s input.
Types of AI image-generation techniques:
Generative Adversarial Networks (GANs): This technique involves two neural networks, a generator and a discriminator. The generator creates images, while the discriminator evaluates their realism. This competition between the two networks leads to the generation of increasingly realistic images.
Diffusion Models: These models start with a noisy image and gradually remove the noise to reveal the underlying image structure, guided by the text prompt.
Transformer-Based Models: These models, inspired by natural language processing, are tools for understanding the relationships between text and image.
The simplified process of AI image generation:
1. Text Encoding: The text prompt is broken down into smaller units, or tokens. Each token is mapped to a numerical representation (embedding), capturing its semantic meaning.
2. Image Encoding: The AI model analyzes a vast dataset of images to learn visual features like shapes, colors, and textures. These features are compressed into a latent space, a mathematical representation of the image’s essence.
3. Text-to-Image Translation: Text embedding guides the generation process, directing the model to create an image that aligns with the prompt’s meaning. The model iteratively refines the image, starting from a random noise image and gradually shaping it into the desired output.
4. Image Generation: The latent space representation is decoded into a pixel-level image. Techniques like super-resolution and noise reduction may be applied to enhance the final image quality.
The Mathematical Underpinnings:
AI image generation relies on:
Matrix Operations: To manipulate and process the numerical representations of images and text.
Gradient Descent: To optimize the model’s parameters and minimize the difference between the generated image and the desired output.
Probability Distributions: To model the uncertainty in the image generation process.
Loss Functions: To measure the discrepancy between the generated image and the ground truth.
Elevate your creativity with the AI inspiration app to create photo portraits like a pro
GenYOU was created by the team at Generated Media using cutting-edge AI and a custom-trained model designed specifically for identity preservation. The team spent countless hours developing and fine-tuning the model to ensure that every generated image captures not just your face but your entire essence—your features, expressions, and overall appearance.
We created GenYOU because most AI generators struggle to recreate the same person across multiple images accurately. Their results often feel random, inconsistent, or overly artificial. We wanted to change that by offering an app that delivers authentic, high-quality AI portraits where you are always the focal point.
Unlike simple apps that just swap faces or apply filters, GenYOU brings your identity to shine across various styles, outfits, and settings. Whether you’re experimenting with fashion, creating professional headshots, or stepping into a fantasy world, GenYOU produces stunningly realistic images that feel personal, lifelike, and unmistakably you.
4 advantages of using AI-Generated Photography like GenYOU
Traditional photography requires expertise, time, and expensive equipment. GenYOU simplifies this process, leveraging AI to create seamless, high-resolution portraits tailored to different purposes, including business, gaming, and social media.
1. Flawless Identity Preservation
One of the biggest challenges in AI-generated photography is maintaining an individual’s facial consistency. GenYOU’s advanced AI ensures natural symmetry and accurate facial replication, avoiding common distortions found in other AI tools.
2. A Plethora of Image Styles
GenYOU offers extensive customization options, allowing users to create business and corporate headshots, social media profile pictures, cinematic and editorial-style portraits, personalized avatars for gaming and digital identity and promotional images for e-commerce and marketing. For those seeking to design unique characters, GenYOU doubles as a robustcharacter generator, enabling users to craft highly detailed and customizable digital personas.
3. Unmatched AI Precision for Realistic Pictures
Unlike many AI tools that produce artificial-looking images, GenYOU uses advanced deep-learning algorithms to refine details like contrast, lighting, and texture, to create realistic images. Unlike tools that over-edit or distort features, GenYOU prioritizes natural appearance.
4. Cost-Effective Alternative to Traditional Photography
Gone are the days of expensive professional photoshoots. With GenYOU, users can create studio-quality images at low cost in minutes. By merging efficiency, accuracy, and creative flexibility, it provides an ideal solution for a broad range of users.
How it works:
Install GenYOU – Get the app and start generating AI-powered photos.
Upload 4 selfies to create your AI model – The AI captures your unique look for precise results.
Pick a template or customize your style – Choose from a variety of available designs or enter your idea.
Receive stunning, lifelike images of yourself – Get high-resolution photos that truly reflect you.
Know that the free version of the app is limited, the AI-generated model of you is shared with the community on a free plan, and you must sign in using a Google account.
What does latent space look like?
A latent space is a high-dimensional mathematical space where data, such as images or text, is represented in a compressed form. It’s a bit like a hidden world where similar data points are clustered together. It’s difficult to visualize this latent space. However, techniques like t-SNE (t-distributed Stochastic Neighbor Embedding) and UMAP (Uniform Manifold Approximation and Projection) can reduce the dimensionality of the space into 2D or 3D representations. These visualizations can provide insights into the structure of the latent space and how different data points relate to each other.
A simplified visual analogy of the latent space can be a city map. Each point on the map represents a specific location. The map itself is a 2D representation of a 3D space (the city). Similarly, a latent space is a multidimensional representation of data, where each point corresponds to a specific data point (e.g., an image or a text document).
As a result, latent spaces often have many dimensions. Data is compressed into a lower-dimensional space, capturing the essential features. Similar data points are clustered together in the latent space, reflecting their semantic similarity. By manipulating points in the latent space, the model can generate new data points – images, and text. While we cannot directly “see” this hidden, latent space, understanding how it works is crucial for developing advanced AI models.
A neural network is a computing system inspired by the biological neural network of the human brain. It consists of interconnected nodes, or neurons, organized into layers. These layers process information in a sequential manner, from input to output.
How Neural Networks work:
The input layer receives data.
The input data passes through the hidden layers, where each neuron applies a weighted sum of its inputs and activates if the result exceeds a threshold. This is called propagation.
The final layer produces the output, which can be a classification, a regression value, or another type of prediction.
Backpropagation is a learning algorithm that adjusts the weights and biases of the network to minimize the error between the predicted output and the actual output.
Deep Learning
Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers to learn complex patterns from large datasets. The “deep” in deep learning refers to the multiple layers of neurons in the network. In essence, deep learning leverages the power of neural networks with multiple layers to tackle complex problems that were previously difficult to solve.
How Deep Learning works:
Deep learning models learn features at multiple levels of abstraction which constitutes hierarchical learning.
The models automatically learn relevant features from the data without explicit feature engineering (feature learning).
Deep learning models can learn end-to-end mappings from raw input to output.
How Deep Learning is used:
Image and Video Recognition: Object detection, image classification, and video analysis.
Natural Language Processing: Language translation, sentiment analysis, and text generation.
Speech Recognition: Speech-to-text conversion and voice assistants.
Autonomous Vehicles: Self-driving cars and drones. Deep learning enables autonomous vehicles, such as drones and self-driving cars, to navigate complex environments and make real-time decisions.
Robotics: Deep learning can be used to develop robots capable of performing tasks in dangerous or inaccessible environments, such as bomb disposal or search and rescue operations.
Military & Security applications: Image and video analysis, signal intelligence, and cybersecurity. Deep learning algorithms can analyze vast amounts of satellite imagery, drone footage, and other visual data to identify patterns, anomalies, and potential threats. Deep learning can be used to analyze intercepted communications, such as phone calls, emails, and social media posts, to extract valuable intelligence. Deep learning can detect and respond to cyber threats, such as malware attacks and data breaches, by analyzing network traffic and identifying malicious patterns.
Predictive Maintenance: Deep learning can predict equipment failures, allowing for proactive maintenance and reducing downtime. Deep learning can optimize supply chains by predicting demand, reducing waste, and improving efficiency.
Training and Simulation: Deep learning can create highly realistic, individualized simulations for training soldiers and pilots.
Surveillance and Security: Deep learning can do facial recognition to identify individuals in real time, enabling law enforcement to track suspects and monitor public spaces. It can also detect objects of interest in surveillance footage, such as weapons or suspicious behavior.
Core Technical Skills:
If you are interested in getting a job in this field, these are some of the requirements. A deep understanding of machine learning concepts, including supervised and unsupervised learning, neural networks, and deep learning. Proficiency in deep learning frameworks like TensorFlow or PyTorch to build and train complex neural networks. Strong programming skills in Python, as it’s the primary language used in machine learning and AI. A solid grasp of linear algebra and calculus is essential for understanding the underlying principles of neural networks and optimization algorithms. Also, knowledge of data cleaning, preprocessing, and analysis techniques is crucial for preparing datasets for training. Plus,
Specialized Skills:
Generative Models: Familiarity with generative models like GANs, VAEs, and diffusion models, and their applications in image and text generation.
Latent Space Manipulation: Understanding how to navigate and manipulate latent spaces to generate new data, interpolate between existing data points, and control the style and content of generated outputs.
Computer Vision: Knowledge of computer vision techniques for image processing, feature extraction, and object recognition.
Natural Language Processing (NLP): For text-to-image generation, a strong foundation in NLP is necessary to understand and process text prompts.
Updating the Model with datasets:
AI image generation models require regular updates with new, quality data to improve their performance and generate more diverse and realistic images. These updates can involve adding new images and text descriptions to the model’s training data that can help it learn new styles, concepts, and techniques. It also improves the diversity of image generation capabilities. Regular updates lead to better image quality, style, faster image generation, coherence, and accuracy.
What Happens Without Updates?
If an AI image generation model doesn’t receive regular updates, it may experience stagnation of image generation. Image quality declines and the model becomes biased towards the original dataset it was trained on.
Publicly Available Datasets include:
ImageNet: A large database of images organized according to a hierarchical taxonomy.
COCO (Common Objects in Context): A dataset containing images with object annotations and scene captions.
LAION-5B: A massive dataset of images and text descriptions scraped from the internet.
User-generated content includes social media platforms and online forums like Instagram, X, Reddit, 4chan, etc. Proprietary Datasets include companies’ private datasets that they use for AIgenerative training.
In this podcast episode about the AI model named ‘Claude’, Lex Fridman interviews Dario Amodei, the CEO of Anthropic, a public benefit corporation dedicated to building AI systems. They discuss the fast-paced development of AI systems, datasets, ethics, model training, etc. Amodei earned his doctorate in biophysics from Princeton University as a Hertz Fellow and was a postdoctoral scholar at the Stanford University School of Medicine. He was a VP of Research at OpenAI and worked at Google Brain as a Senior Research Scientist.
In his essay, Machines of Loving Grace, Amodei sees great potential in the development of AI systems, especially in biology. He predicts that AI-enabled biology and medicine will compress the progress of 100 years into 5-10 years! In his essay, Amodei discusses a lot of different applications for AI models to help people live up to 150 years. Can he do it?
Who invented the AI image generation?
While many researchers and engineers have contributed to the development of AI image generation techniques, Ian Goodfellow seems to be the first figure who made a significant breakthrough in the development of Generative Adversarial Networks (GANs) in 2014. GANs revolutionized AI image generation by enabling the creation of highly realistic and diverse images.
Who invented facial recognition?
The pioneers of facial recognition technology were Woody Bledsoe, Helen Chan Wolf, and Charles Bisson. They began their groundbreaking work in the 1960s, focusing on teaching computers to recognize human faces.
Their early experiments involved manually marking facial features on photographs and feeding this data into a computer. While the technology was primitive by today’s standards, it laid the foundation for the advanced facial recognition systems we have today.
I found this fascinating episode about the early history of facial recognition technology. Karthik Cannon co-founded a facial recognition and computer vision startup called Envision. They make AI software with glasses for visually impaired people. The glasses read text, recognize objects, and do voice descriptions of the surroundings. He also has programmed the glasses to recognize and describe human faces! This project has built on the research of Woody Bledsoe, an obscure mathematician and computer scientist living in 1960s America, who did a lot of mathematical research about facial recognition.
While his body was ravaged by ALS and he couldn’t speak, Woody left his research papers in the garage for his son to discover. He left tons of images of people’s faces marked with math equations. Also, thousands of photos of marked-up, rotating faces he studied while he worked at the University of Texas. Woody had worked in a start-up in Palo Alto before his university career began, where he and his friends explored crazy ideas, among them pattern recognition. To sustain his company financially, Woody got support from CIA companies to work on facial recognition research over the years. The podcast episode discusses the complex facial recognition process Woody went through. When his company went out of business, he received a project to work on facial recognition for law enforcement, matching mug shots with potential criminals utilizing computer software that cut on time 100-fold!
Because of the CIA’s sponsorship of his company & research, Woody couldn’t publish any of his findings to make them public. As a result, it fell into obscurity for decades before interest in this subject re-emerged.
Create, a colored pencil drawing, 19×25 inches
How much power does it take to generate one image?
The amount of energy required to generate a single AI image can vary significantly depending on several factors, including:
More complex models, like Stable Diffusion XL, consume more energy than simpler ones.
Higher-resolution images require more computational power and energy.
The number of iterations the model goes through to refine the image affects energy consumption.
The efficiency of the hardware and software used can impact energy usage.
Generally, a single AI image can consume anywhere from 0.01 to 0.29 kilowatt-hours (kWh) of energy. Because of energy use, big techs like Amazon and Microsoft are exploring new options for building or reopening nuclear plants to support their AI systems.
What computers are used for AI image generation?
AI image generation is typically performed on computers with powerful graphics processing units (GPUs). These processors handle complex mathematical calculations and parallel processing. Common computers used for AI image generation include High-Performance Computing (HPC) Systems. These are large-scale systems with multiple servers often used by research institutions and big tech to train and run complex AI models. High-end gaming PCs with GPUs can be used for AI image generation for small projects and personal use. Popular GPUs for AI image generation include NVIDIA’s RTX series. Cloud computing platforms like Google Cloud, Amazon Web Services (AWS), and Microsoft Azure provide access to powerful computing resources, including GPUs. This allows users to rent computing power on demand.
Similarities and Differences in Logical Processes Between AI and Humans in Image Generation
While AI image generation has made significant strides, its underlying logic differs from human creativity in several ways.
Similarities: 1. Both AI and humans excel at recognizing patterns. AI models are trained on vast datasets of images, allowing them to identify recurring patterns like shapes, colors, and textures. Humans, too, learn to recognize patterns from their experiences and observations.
2. Both AI and humans learn from experience. AI models improve their image generation capabilities by training on more data and refining their algorithms. Similarly, human artists learn from their mistakes, experiment with different techniques, and refine their skills over time.
Differences: 1. AI relies heavily on data to learn patterns and generate images. It lacks a deep understanding of the world and often struggles with abstract concepts. Humans can generate images based on abstract concepts, emotions, and imagination, even without specific visual references. 2. AI struggles with understanding context and nuance in prompts. It may generate images that are technically correct but lack the emotional depth that a human artist can convey. People can interpret prompts with subtle sensitivity, considering culture, and history but most importantly, personal experiences and emotions that are channeled through original art. 3. While AI can generate creative and innovative images, its creativity is limited by the quality of data it’s trained on. Artists are unique and can think outside the box and feel and process their emotions to generate original art.
Moonlight, 22x30in, closeup, colored pencil on art board, Veronica Winters
How does this technology generate revenue for companies?
Companies sell AI-generated art to consumers as art prints or digital downloads.
Companies can license AI-generated art to other businesses for use in advertising, marketing materials, or product design.
Companies can offer AI art generation services to clients, charging fees for creating custom images based on specific prompts.
Many companies develop and sell software tools that allow users to create their AI-generated art. Other companies, incorporate AI image generation into their final product.
Companies integrate AI Art into other products they offer, like video games, virtual reality, and design software.
Companies also collect data from user interactions with AI art tools, which can be used to improve the technology and generate insights for future products and services.
Potential future applications of AI-generated images for companies to make money:
While content creation and marketing might become dominated by AI-driven art to cut costs and raise efficiency, human creativity, and emotional and thought processes can’t be replaced with AI. Thus, I believe that humans will always be in charge of originality but have AI models as a tool to speed up the creative process and deliver results.
AI can generate high-quality product images, reducing the need for expensive photo shoots. Some products we see in magazines and ads feature extreme close-ups. These are often 3D renders, not real pictures, like images of diamonds, watches, jewelry, etc. AI might generate similar images much faster being cost-efficient.
AI image generation will be used in game development and virtual reality experiences.
Product visualization is a natural extension of the online shopping experience.
AI can generate initial design concepts in architecture and design projects. AI can create realistic visualizations of interior design concepts, helping people visualize space.
AI can generate realistic simulations for training purposes, improving safety and efficiency.
In conclusion:
I think humanity will benefit greatly from AI systems, just like from having computers or automation. While AI can generate creative and innovative images, its creativity is limited by the dataset quality it’s trained on. Artists are unique and can think outside the box and feel and process their emotions to CREATE original art. Art is always based on layers of personal experiences and feelings that the machines don’t possess. Also, artists create tangible art while AI pictures exist in digital format that can be printed, of course, but AI art lacks the physicality of paint or other art materials used in the art creation process. We’ve already seen plenty of bad movies, probably based on AI writing ( the 2nd season of Locki, the latest Marvel movies, endless series on Netflix and Amazon that lack originality, etc).
We won’t see the birth of innovative artists inside the AI models because only our reality can give rise to such creative people. True innovators like the facial recognition trailblazer, and mathematician Woody Bledsoe were way ahead of their time but paved the way to a better future. And while all innovative applications can be used for good and bad, I hope AI tech will end up in good hands, letting societies flourish.
Tech parts of this article were written with the help of Gemini.
Your work delves into the invisible life of emotional and sensorial experiences. How do you translate such intangible feelings into the physical act of painting?
Well, it’s something I was doing without realising it at first. For me, painting is a physical activity. I don’t start with a thought—a plan—or the intention to translate something specific; I just prepare a canvas and begin, following my impulses and desires. I feel good when I’m fully immersed in this activity. Over the years, I’ve come to realise that I’ve been translating sensations. At different times, I’ve depicted my organs, like my lungs and kidneys. I even painted recognisable faces without noticing them at first; I had to turn the canvas to see them. So, essentially, I paint what impresses me—not by choice, but because it naturally emerges.
Laura Basterra Sanz in her studio
I’m a highly sensitive person, and that means many things—one of which is that my senses are heightened. I pick up much more information than the average person, whether it’s the energy in a room, or the subtle changes in people’s moods, feelings, or intentions. Painting is my way of digesting overstimulation. I think it’s fascinating to see these invisible aspects of life take shape in the form of an image. It’s like crossing senses—smelling music or tasting an image. It feels like an alchemical process as if I’m cooking a picture. I could probably paint something else, but it wouldn’t feel authentic. Plus, I love the thrill of watching something I’ve never seen before appear in front of me.
You describe your gestural abstract paintings as encouraging the “body’s intelligence to flourish.” How does your body inform your process, and do you see it as a tool of expression or a collaborator?
The way you ask the question makes it seem like my body is something separate from me, like a tool I use, almost as if my body were a brush. But it’s not like that. It’s more about creating space for my energy to extend onto the canvas. Through this, I depict who I am in all my complexity and context—beyond materialistic constructs like gender or belief systems. Maybe it operates on a more energetic level.
My studio is a safe space where I can explore authenticity, whatever that means in each moment, including authentic movement. Whether I feel like dancing one day or sitting still the next, all these emotional states find their way into my work.
My practice is also shaped by experimenting with my body—through yoga, meditation, and breathing exercises—that help me connect my mind and body. This connection is essential for my well-being, especially since I tend to live in my mind. Our bodies are incredibly intelligent, and if I pay attention, the sensations guide me toward the best choices and outcomes in my work.
How does your fascination with fluidity manifest in your painting practice, and do you see the concept of fluidity as a metaphor for your emotional or creative life?
Fluidity reflects the essence of life for me. In my painting practice, I pursue fluidity in both decision-making and materials. I seek to be in contact with water, both when I paint and in choosing the location of my studio, as context greatly inspires my work. This may explain why I don’t enjoy working with dry mediums or being in dry places and why I prefer paint.
Fleeting by Laura Basterra Sanz (Acrylic on Belgium linen, 2021, 130 x 160 cm)
Since moving to Belgium, I’ve become much more aware of the elements, especially water and wind, which are more present here than in Barcelona. Volunteering in two permaculture projects before moving also taught me a lot about nature. Now, I spend time wandering in the Sonian Forest, paying attention to trees, plants, insects, and animals, which deepens my connection to the natural world and the elements. I also go often to the coast to experience the empty vast beaches, tides, dunes and wind. Fluidity feels more literal than metaphoric, although perhaps it operates on both levels at once.
The concept of freedom is central to your exploration. In your opinion, is true freedom a physical experience or more of a mental construct? How do these philosophical questions unfold through your work?
I believe freedom needs to be a physical experience. I try to embody that sense of freedom through movement and action when I’m in the studio. It’s reflected in the way I work—my methodology when painting and using text—almost like nobody’s watching. My brushstrokes, in a way, carry this quality, as if freedom is part of the DNA embedded in them. It’s something I strive for in my practice, and I hope to bring that same experience of freedom into my relationships with others.
Colour plays a central role in your work as a representation of frequency or energy. Do you consciously select colours based on these energetic qualities, or do they emerge more intuitively through your process?
Lately, I’ve been grappling with the term “intuition.” It’s vital to both my artistic practice and my life, yet it can be undervalued in painting. Listening to my intuition often leads to choices that feel right and bring me joy; it feels like my best form of intelligence. However, I worry that relying solely on intuition might suggest a lack of effort or depth in my work.
I believe that truly engaging with my intuition is a significant undertaking. I often set aside time to wander the streets, allowing my instincts to guide me without a specific plan. It’s not only a way of living but also a quiet rebellion against the dominance of the rational mind—the left brain, which still holds too much sway in our lives. When I look at nature, I don’t see the rational mind at work, yet nature functions perfectly. Intelligence, to me, includes much more than just logic; intuition feels like a natural, inner intelligence.
When it comes to colour, I consciously select hues based on their energetic vibrations. I feel drawn to certain colours, and this attraction shifts frequently. I spend a lot of time painting in sketchbooks, experimenting with a broad palette to visually train myself. I’ve learned that relying solely on intellect in choosing colours can prevent the magic of unexpected discoveries during the process—especially when mixing colours in response to the moment.
The Way It Used To Be by Laura Basterra Sanz (Acrylic on Belgium linen, 2022, 140 x 120 cm)
You express a deep connection to the musicality of language in your text-based art. Could you explain how this sonority and rhythm influence the way you work with words, and does this overlap with your approach to visual art?
I think it’s about how much attention you pay to sound, how well-educated your ear is, and the subtle awareness of musicality. It may also have something to do with the way my brain works, but I can’t say much about that. When I was born, my older sister was already playing the piano at home, and she continued throughout my childhood. I also played the piano for a while, and music was always present—we had records playing constantly. In many ways, music has been my companion. It teaches me, helps me connect ideas, and evokes feelings. I’ve always been drawn to rhythmic sounds and patterns, and I think I naturally have a mind for beats.
In my artistic practice, text feels like the beat—structured and rhythmic—while abstract painting represents the melody, flowing and emotional. I often think of my work as creating visual music, where the two overlap. There’s a connection between text, sound, and visual art in my mind that I haven’t fully analysed yet, but I think it’s tied to the body-mind relationship that interests me deeply.
You say, “We are nature.” How do you see the role of nature, not just as a subject, but as an active participant in your art, particularly in your installations?
When I say, “We are nature,” I’m thinking about how our organic bodies function on their own, mirroring the rhythms and cycles of the natural world. It’s amazing to reflect on! In contrast, there’s a stark dissonance when we exist in concrete jungles, surrounded by car exhaust and hard edges—it feels so far from our essence.
In my installations, I strive to create spaces where people can connect with a sense of freedom and reflect on their emotional state in the present moment. I invite others to tune into their senses, encouraging a deeper presence. This approach is a natural extension of the way I’ve chosen to live my life.
Laura Basterra Sanz in front of The River by the artist (Acrylic on raw canvas, 2024, 170 x 140 cm). Contact an advisor for further details.
You mention that the resolution in your work must “organically grow from the process of painting itself.” Could you explain this approach?
In the beginning, my approach was more aligned with action painting. I had to physically throw away feelings of discomfort, and that technique appealed to me. Over time, I experimented with different supports and states of being—painting quietly, sitting or standing, on the floor, on the wall, on a table, or standing while painting on a table. I also explored painting from various emotional states, developing this vocabulary on my own. I’ve learned that overthinking a painting rarely leads to satisfying results, and I’ve recognised the importance of letting go when I get stuck.
Confidence, I believe, is key, and I’ve gained it through practice. My gestures have become bolder and more assured over time, allowing me to better distinguish what to keep and what to discard. I’ve also realised that my spontaneity and playfulness operate within a framework—a method I’ve developed that evolves with me. While my work may appear spontaneous, it’s built on preparation through bodywork, healthy habits, and exercises such as morning pages or intuitive walks. That doesn’t mean I don’t struggle; I often do, but always return to what feels right.
I’ve come to believe that every artist needs to find their own methodology for creating. I realised this after visiting many artists’ studios. I used to think it was obvious, but I’ve learned it’s not for everyone. Artists who feel lost in their practice might be forcing themselves into something that doesn’t come naturally, which, in my view, is the wrong approach. Whether in art or life, forcing things rarely leads to true, organic development.
Laura Basterra Sanz’s works on display at the “Coup De Coeur” group show, We ART XL 2024, held at the cloister of l’Abbaye de la Cambre in Brussels
How does your creative process serve as a means of introspection or personal transformation? Do you find that it helps you understand or process your own experiences as much as it expresses them to others?
For me, creating is a dialogue between my left and right brain—between thought and feeling, or what I see as a balance of masculine and feminine energies. This process feels like a form of self-therapy, a quiet yet profound way to understand myself better without needing to talk about it. This introspective journey aligns with what Dr. Elaine Aron describes as the experience of a highly sensitive person, where there’s a constant drive for insight and understanding.
Yes, I believe my work does help me process my experiences. I’m less certain about how much of that reaches others, though. While many artists hope their audience will find their own meanings, I’m less focused on any specific interpretation. My hope is simply that my work resonates on a sensory level.
I’ve found that people who share similar sensibilities tend to connect with my work. I’ve received positive feedback from respected industry figures, but I try not to dwell on how others perceive it. For me, the most important thing is that my creations feel true to who I am.
This comb-back stick chair is built entirely in American red elm, with the seat, arm and comb made from figured red elm, some of the most difficult wood I have ever saddled.
The chair is raked back for lounging, reading or sitting by the fire. The chair’s features heavily shaped arms, tapered octagonal stretchers and slightly proud and burnished tenons throughout.
I’m offering it for sale via a silent auction. The highest bid includes crating and shipping the chair to your door anywhere in the lower 48 states of the U.S. With no additional fees or charges. Details on the sale are at the bottom of this entry. First, some notes about the chair.
The chair is made from red elm, which is my favorite wood for chairmaking. The wood is strong, fairly lightweight and has a difficult interlocked grain that prevents the parts from ever splitting. The chair’s sticks are shaved and left octagonal. All the tenons are cut slightly proud and burnished. All the chair’s joints are assembled with animal glue, which is reversible, and wedged with hickory wedges selected for arrow-straight grain.
The seat is tilted 6.6°, with the chair’s back tilted 28° off the seat. The seat is 16-3/4” off the floor, making it comfortable for most sitters. The chair is 38-3/4” tall overall.
The chair is finished with a soft wax finish that I make here in our workshop. It offers a low lustre and looks better the more you use the chair. The finish isn’t terribly durable, but it is easily repaired (just add more soft wax).
Like all my chairs, I make them as best I can, but most of the work is by hand. So you will find an occasional stray tool mark or tiny imperfection. These are not left intentionally, but they are the result of hand work.
How to Buy the Chair
The chair is being sold via a silent auction. If you wish to buy the chair, send your bid via email to lapdrawing@lostartpress.com before 3 p.m. (Eastern) on Wednesday, April 24. Please use the subject line: “Elm Chair.” The opening bid is $500. In the email please include your:
Bid
U.S. shipping address
Daytime phone number (this is for the trucking quote only)
If you are the highest bidder, the chair will be shipped to your door. The price includes the crate and all shipping charges. Alternatively, the chair can be picked up at our storefront. (I’m sorry but the chair cannot be shipped outside the U.S.)
Storytelling is an art form. Crafting essays, speeches, YouTube video scripts or gripping novels demands through understanding of story concepts, human psychology, and practice. Here are five addictive storytelling techniques that can elevate your storytelling prowess.
#1. Start with a Hook
The “hook” or the opening lines of a story are crucial in capturing the person’s attention and drawing him into the narrative. A strong hook can be achieved through several techniques, such as presenting a conflict or dilemma, introducing a unique character, or plunging the reader into the heart of the action. The hook can be visual or written depending on the medium.
In literature:
Consider the opening of J.K. Rowling’s “Harry Potter and the Sorcerer’s Stone,” where we are immediately introduced to the orphaned Harry Potter living a miserable life with the Dursleys. This opening makes us curious to learn more about the boy from the start.
In “The Girl on the Train” by Paula Hawkins, “Rachel catches the same commuter train every morning. Every day, she rattles down the track, watching the same houses, the same people. Every day, she fantasizes about their lives. Every day, she feels herself slipping away.”
In “Gone Girl” by Gillian Flynn, you read: “You don’t know what you’ve got ’til it’s gone. I had it all. Now I have nothing.”
In “The Silent Patient” by Alex Michaelides: “Alicia Berenson hasn’t spoken a word in five years. Her husband was found dead in their bedroom, and she’s the prime suspect. Psychiatrist Theo Faber is determined to get her to talk.”
Visual Hooks:
The hook can be visual before the story unfolds. If we study action films, they start with a riveting action scene to pull us in. “The Mission Impossible” and “James Bond” movies always have an opening scene with lots of exhilarating action and only later on do we find out about the characters, story, and details.
In “Inception,” the movie opens with a breathtaking heist sequence that immediately immerses the audience in a world of confused reality.
The movie “Get Out” begins with a seemingly ordinary couple driving down a dark country road, setting the stage for a chilling and suspenseful horror film.
In “Parasite”, the film starts with the Kim family living in a cramped basement apartment, struggling to make ends meet. This stark contrast with the wealthy Park family sets the stage for a dark and satirical tale of class and inequality.
These hooks grab our attention and set the tone for the story to delve deeper into the world of the narrative.
#2. Build unusual but relatable characters
There is no story without well-developed characters that can resonate with readers on a deep emotional level. You can create interesting characters by exploring their motivations, fears, and desires. Give them unique quirks, flaws, and strengths that make them relatable and believable to us. The audience should see parts of themselves or people they know in story characters. Also, characters must go through a transformation process throughout the story. A protagonist who struggles and overcomes difficulties naturally appeals to the audience.
To emphasize emotional connection, include scenes or moments that evoke feelings of joy, fear, sadness, hope, frustration, etc. For example, a writer explaining climate change might share a personal story of a struggling family impacted by rising sea levels. This approach humanizes the issue and makes it relatable. Today, a lot of writing and headlines are fear-based in the media. Fear is a powerful psychological tool to keep viewers engaged throughout your video, story, or article.
Unforgettable characters have unique personalities that are not black-and-white. Consider the complex character of Severus Snape in the Harry Potter series. His conflicted loyalties, tragic backstory, and love for Lily Potter make him a mysterious figure who comes to light only at the end of the book. In the psychological thriller, the Joker, 2019, the main character is known as a ‘bad’ guy. However, as the story unfolds, we see the enormous weight and complexity of his character through some tragic events in his life. Let’s look at this character in greater detail.
Character Development in “Joker” (2019)
This film builds character through Arthur Fleck/Joker’s transformation in a profound psychological deconstruction of social marginalization, mental illness, and personal breakdown.
Key Character Development Techniques:
Psychological Descent
Gradual erosion of social boundaries
Mental illness portrayed as a product of systemic neglect
Character development driven by cumulative traumatic experiences
Slow transformation from vulnerable individual to violent persona
Societal Rejection as Catalyst
Character’s development emerges from consistent social exclusion
The mental health system’s failure becomes a transformative mechanism
Character development explores powerlessness transforming into violent empowerment
Social humiliation becomes the catalyst for radical identity reconstruction
Powerlessness converts into aggressive self-determination
Systemic violence reflected in individual psychological breakdown
Narrative Ambiguity
Blurs lines between reality and delusion
Unreliable narrative perspective
Character’s perception becomes the primary storytelling mechanism
Creates psychological complexity through narrative uncertainty
Philosophy of the character and movie:
Society creates its monsters
Marginalization generates destructive responses
Mental illness intersects with systemic violence
Distinctive Character Development Aspects:
Rejects traditional hero/villain dichotomy
Generates sympathy through psychological complexity
Explores societal mechanisms of psychological destruction
Transforms personal trauma into social commentary
Psychology & Performance:
Phoenix’s performance becomes a linguistic tool
Physical movements communicate psychological states
Reveals inner landscape through bodily expression
Transforms character development into visceral experience
#3. Use the Power of Conflict
Suspense is the art of creating anticipation and uncertainty, keeping the reader on the edge of their seat. Conflict can be suggested through a conversation tone and rhythm. To achieve uncertainty, use these techniques:
withhold information
introduce a time limit
create a sense of impending doom
In your storytelling, focus on presenting challenges that characters must resolve by the end of the story. These conflicts can be internal struggles, external challenges, or even societal issues. A master storyteller introduces the conflict early and resolves it in a way that aligns with the message or goal of the story. For example, in persuasive essays or presentations, conflict can represent opposing viewpoints. In movies, it’s often a dislike for each other at the beginning of a film and a resolve in the end. In novels, characters might have different motivations to achieve one goal.
Key Storytelling Techniques for Conflict Creation:
Introduce multiple layers of conflict (internal and external) and establish clear stakes
Create obstacles that challenge the protagonist’s goals. Create tension
Use conflict to drive multi-dimensional character development
Ensure that conflict resolution feels earned and meaningful
Show how characters grow and change through confronting conflicts and experiencing transformation throughout the story.
Examples of Conflict Creation in a story:
In “Pride and Prejudice”, Jane Austen creates social and romantic conflict in her book. Austen creates external conflict through social expectations and personal misunderstandings. She writes about social pressures around marriage, class, and reputation that create tension. Elizabeth and Darcy’s initial interactions are fraught with misunderstandings and social constraints. Her economic and social survival depends on making the right marriage choices. Jane Austen also explores the internal conflict in her characters. Elizabeth struggles with her preconceived notions about Darcy and Darcy battles his own pride and social conditioning that they overcome in the end. The author finds a resolution to their conflict through mutual understanding and personal growth, breaking down social barriers in their marriage. Both characters must overcome their initial prejudices and self-imposed limitations
Alfred Hitchcock, the master of suspense, was a master at building tension through his use of camera angles, music, and pacing. His films, such as “Psycho” and “Rear Window,” are renowned for their ability to keep audiences guessing.
Writing conflict-driven narratives can be challenging, especially when under tight deadlines. In this case, CustomWriting offers quick assistance. With an AI essay writer, college students can get online help to structure their thoughts, refine ideas, and learn how to apply storytelling techniques in academic work. Such a resource improves grades and builds skills in writing stories and more.
George R.R. Martin’s conflict creation:
Emilia Clarke as Khaleesi from the Game of Thrones, Veronica Winters
George R.R. Martin creates a rich conflict landscape in “A Song of Ice and Fire” series, popularly known through the “Game of Thrones” adaptation. He introduces multiple layers of external and internal conflicts. He uses unique conflict-creation strategies:
Personal choices have massive, often unexpected consequences
Power vs responsibility
Subverting traditional narrative expectations
No character is completely safe or guaranteed survival
Conflicts emerge from complex motivations, not simple good vs. evil dynamics
Martin’s approach to conflict-creation is different from other fantasy novels because his conflicts are multilayered and interconnected with complex characters that have shifting allegiances. He doesn’t use straightforward resolutions but rather intertwines personal and political motivations.
Political Conflict:
Multiple noble houses (Stark, Lannister, Baratheon, Targaryen) compete for control of the Iron Throne
The War of the Five Kings represents a complex, multi-sided political conflict
Each house has different motivations: revenge, power, legitimacy, survival
Triggered by complex family dynamics and political machinations
Ned Stark’s execution becomes a catalyst for widespread warfare
Demonstrates how personal betrayals can escalate into systemic conflict
Existential Conflict: Humans vs. White Walkers External Conflict:
An apocalyptic threat that transcends individual house rivalries
The White Walkers represent an existential challenge to human survival
Creates tension between immediate political struggles and a larger, more critical threat
3. Character Conflict:
Jon Snow emerges as a key character trying to unite warring factions against this ultimate threat
His struggle involves convincing people to look beyond immediate conflicts to face a greater danger
Daenerys Targaryen has an internal conflict between her desire for justice and her potential for destructive violence. Her character arc represents a complex exploration of power, idealism, and potential corruption
Tyrion Lannister’s conflict involves an internal struggle against family expectations and personal identity. He fights against being defined by his physical differences and his family’s perception. He uses wit and intelligence as weapons against social and familial prejudices
Resolution Techniques:
George R.R. Martin creates unique resolutions to conflicts, such as:
Moral ambiguity means that “winning” often comes with significant personal or collective cost
Conflicts often remain unresolved or have unexpected outcomes as system-level problems aren’t solved by individual heroism
Victory is rarely clean or complete
Characters are fundamentally changed by their experiences
Moreover, George R.R. Martin’s approach to conflict resolution follows a different strategy as he rejects classic heroic narratives where good always triumphs like in the “Lord of the Rings”. He kills major protagonists unexpectedly (like Ned Stark’s execution) and eliminates traditional hero types quickly. He also records the punishment of noble intentions rather than rewarding them. In non-linear storytelling, his characters have moral complexity and psychological dimensions like Jaime Lannister transforming from an apparent villain to a nuanced, sympathetic character. His heroes often experience brutal consequences for good actions and suffer genuine, long-term repercussions for their choices. In his story, the author demonstrates the fundamental corruption of power and treats medieval-style settings with historical realism to focus on human psychology over magical elements and settings. The author reveals the deep psychological motivations of characters who have flaws and multiple internal conflicts just as important as the external ones.
Vladimir Nabokov’s conflict creation:
Vladimir Nabokov‘s approach to conflict is uniquely psychological, morally complex, and linguistically sophisticated. In “Lolita”, he uses internal psychological tension as the primary driver of the protagonist. It exists in his mind. Nabokov uses unreliable narration to create moral ambiguity. He also challenges the reader’s moral boundaries through sophisticated narrative techniques making us “feel” for the pedophile. Throughout this book, Nabokov uses elegant prose to create dissonance between horrific actions and beautiful language as one of his conflict techniques.
In “Pale Fire”, Nabokov constructs unique conflict through the narrative structure, different perspectives, linguistic complexity, and blurred lines between reality and delusion.
His unique approach to conflict creation:
Conflict emerges through linguistic complexity
Uses unreliable narration as a primary conflict generator to create moral ambiguity
Creates tension through intellectual games or manipulation
Challenges reader’s moral and perceptual boundaries
#4. Become a master of the language & sensory details
Vivid descriptions and sensory details can transport the reader to another world, allowing them to experience the story firsthand. By appealing to the senses of sight, sound, smell, taste, and touch, you can create a more immersive reading experience. Consider the evocative descriptions of nature in J.R.R. Tolkien’s “The Lord of the Rings,” where the forests of Mirkwood and the plains of Rohan come alive with vivid detail. Or study the complex emotional landscapes of Nabokov’s characters.
Examples & analysis of Nabokov’s language use:
Russian novelist, Vladimir Nabokov was a master of language, and his prose is often characterized by its precision, lyricism, and playful wordplay. He wrote novels and short stories in 5 different languages and used innovative and complex storytelling methods. His beautiful descriptions often relied on unusual comparisons, wordplay, and symbolism to evoke feelings. His unique mastery of language becomes a microscope into the characters’ inner worlds in every story you read.
Language is his primary tool to create complex emotional landscapes of his characters. He often uses metaphors to reveal meaning or psychological states of mind. Punctuation and sentence structure often communicate psychological tension in his stories. He uses beautiful language that contrasts with disturbing content and creates feelings through word choice.
Here is a detailed analysis of Nabokov’s linguistic techniques using an excerpt from “Lolita” that demonstrates his psychological portraiture through language:
Original Passage: “Dolores, my daughter. Lo, my love. Lolita. The tip of the tongue taking a trip of three steps down the palate to tap, at three, on the teeth. Lo. Li. Ta.”
Linguistic Breakdown:
Layered Naming
Multiple names reveal psychological fragmentation
“Dolores” (pain) vs. “Lo” (intimate) vs. “Lolita” (sexualized)
Each name represents a different psychological projection
Demonstrates Humbert’s fractured perception of the girl
Phonetic Deconstruction
Breaks name into physical sound production
Describes linguistic mechanics of saying her name
Transforms name into a sensory, almost erotic experience
Sound becomes a metaphor for psychological obsession
Psychological Mapping
Language reveals the narrator’s disturbing fixation
Precise linguistic description masks deeper pathology
Creates intimacy through linguistic precision
Sound becomes a proxy for emotional/sexual possession
Syntactical Revelation
Short, rhythmic phrases
Suggests fragmented, obsessive thinking
Syntax mirrors the psychological state
Linguistic rhythm communicates internal tension
Deeper Psychological Insights:
Language as a form of control
Naming as a method of psychological possession
Sound becomes a metaphorical penetration
Linguistic precision masks moral complexity
Let’s analyze an excerpt from Nabokov’s “Pale Fire” to demonstrate his linguistic psychological portraiture:
Excerpt from “Pale Fire”: “I was the shadow of the waxwing slain / By the false azure in the windowpane”
Linguistic and Psychological Analysis:
Metaphorical Construction
Transforms personal experience into abstract imagery
“Shadow of the waxwing” becomes a multilayered psychological metaphor
Suggests themes of perception, illusion, and fatal misunderstanding
Bird’s death represents psychological disorientation
Linguistic Precision
Each word is carefully selected for maximum emotional resonance
“False azure” implies deception at a sensory level
Windowpane becomes a symbol of perceptual barriers
Language creates a complex emotional landscape in two lines
Psychological Mapping
Death metaphor represents psychological fragmentation
Suggests inner conflict between perception and reality
Bird’s death symbolizes the vulnerability of consciousness
Linguistic construction reveals the internal emotional state
Syntactical Nuance
Compact, precise language
Each word carries multiple semantic layers
Rhythm suggests internal psychological tension
Minimal words create maximum emotional complexity
Deeper Insights:
Perception as a potentially fatal experience
Consciousness as a fragile, easily deceived construct
Language as a mechanism of psychological exploration
Metaphor as a tool for revealing inner landscapes
Nabokov transforms a simple image into a profound psychological exploration, using language as a surgical instrument to dissect consciousness.
Let’s look at Nabokov’s linguistic techniques in “The Luzhin Defense” by focusing on how he creates a psychological portrait of the protagonist through language:
Key Linguistic Strategies:
Depicts Luzhin as a character trapped between mathematical precision and psychological fragility
Uses language to illustrate his disconnection from social reality
Portrays his inner world through fragmented, geometric linguistic patterns
Demonstrates how mental obsession (with chess) shapes perception
Psychological Conflict Techniques:
Language reflects Luzhin’s fracturing consciousness
Chess becomes a metaphorical language of psychological survival
Linguistic patterns mirror mathematical and chess-like thinking
Reveals the inner world through precise, almost clinical description
Narrative Approach:
Treats Luzhin’s psychological state as a complex system
Language becomes a method of mapping his internal landscape
Demonstrates how rigid thinking creates emotional isolation
Uses linguistic precision to expose psychological vulnerability
Thematic Linguistic Elements:
Fragmentation of consciousness
Obsessive pattern recognition
Emotional disconnection
Intellectual isolation
Unique Characteristics:
Language as a structural representation of mental state
Syntax that reflects mathematical thinking
Emotional depth revealed through intellectual precision
Psychological portrait created through linguistic construction
Core Linguistic Techniques:
Describes Luzhin’s perception as a series of geometric patterns
Language becomes a chess board of psychological movement
Transforms emotional experiences into abstract, structured representations
Uses precision to reveal psychological fragmentation
Specific Narrative Strategies:
Perception as a Mathematical Construct
Describes the world as a series of calculated moves
Emotions translated into strategic configurations
Personal interactions are viewed as complex problem-solving
Language mirrors his detached, analytical consciousness
Words arranged like chess pieces on an intellectual landscape
Metaphorical Mapping
Chess becomes a linguistic metaphor for psychological survival
Each interaction is described with strategic precision
Personal relationships converted into strategic encounters
Language reveals inner defensive mechanisms
Example Linguistic Technique: “He saw the world as a complex chess problem, each human interaction a potential gambit, each relationship a strategic configuration waiting to be solved.”
Psychological Revelations Through Language:
Intellectual defense as emotional protection
Mathematical thinking as a shield against psychological vulnerability
Language reveals profound social disconnection
Precise description masks deep emotional trauma
Philosophical Underpinnings:
Consciousness as a structured, calculable system
Emotional experiences can be mathematically interpreted
Human interaction as a series of strategic maneuvers
Intellectual precision as a survival mechanism
Nabokov transforms language into a diagnostic tool, using linguistic precision to map Luzhin’s fractured psychological landscape.
#5. Use symbolism to tell the story’s meaning in the end
Sacrifice, 18×24 in, oil on canvas, Veronica Winters
By paying attention to the subtle details and recurring motifs used as symbols throughout a story, viewers can uncover the hidden layers of a story and gain a more profound understanding of its themes. By using objects, characters, or events to represent abstract ideas, you can create a relatable and unique narrative. Consider the symbolism of the scarlet letter in Nathaniel Hawthorne’s “The Scarlet Letter,” which represents Hester Prynne’s sin, shame, and eventual redemption.
Examples of used symbolism to reveal the story’s meaning in famous movies:
The Matrix:
This iconic choice of the red or blue pill symbolizes the decision between reality and illusion, between waking up to the truth or remaining in a comfortable lie.
Inception:
Each character has a personal totem, a physical object that can be manipulated in a dream state to distinguish reality from dream. It symbolizes their identity and their struggle to maintain it.
The spinning top becomes a symbol of doubt and uncertainty, as its continuous spin leaves the viewer questioning the nature of reality.
Arrival:
The alien creatures represent the concept of time and language. Their circular writing system symbolizes the interconnectedness of all moments and the idea that the future can influence the past.
The glass of water becomes a symbol of the fragility of life.
Her:
The AI companion, Samantha, represents the evolving nature of human connection and the potential for love in the digital age.
The sprawling metropolis of LA symbolizes the loneliness and isolation of modern life, contrasting with the intimacy of the protagonist’s relationship with Samantha.
Moonlight:
The water is an element that symbolizes the fluidity of identity, the passage of time, and the cleansing power of emotions.
The moon represents the hidden depths of the characters’ desires and fears.
A weak ending can undo the impact of an excellent story. It must end with a message or purpose of the whole story. In stories and novels, the conclusion should resolve conflicts, tie up loose ends, and leave a lasting impression. In academic writing, conclusions often summarize key points and highlight implications. A well-crafted conclusion ensures the story feels complete, emotional, sincere, and thoughtful for the audience.
Freedom, 22x30inches, colored pencil drawing by Veronica Winters
Applying Storytelling Techniques to your YouTube Videos to create the best content
YouTube videos, like written stories, can benefit immensely from effective storytelling techniques. Personally, I write scripts to produce any new video I upload to YouTube.
Here’s how you can apply the five storytelling techniques to your YouTube videos:
Hooking the Viewer with a Compelling Beginning:
Engaging Intro: Start with a captivating question, a surprising fact, or a visually striking scene.
Strong Thesis Statement: Clearly state the main point of your video within the first 30 seconds.
Intriguing Teaser: Promise a solution to a problem or a unique perspective.
Creating Memorable Characters:
Relatable Characters: Use yourself as the main character, sharing personal experiences and emotions.
Distinct Personalities: Develop unique characters within your videos, whether they are guests, actors, or animated avatars.
Character Arcs: Show character growth or transformation throughout the video.
Building Suspense and Tension:
Cliffhangers: End segments with a cliffhanger to encourage viewers to watch the next part.
Mystery and Intrigue: Tease information or reveal it gradually, building anticipation.
Visual and Audio Cues: Use dramatic music, sound effects, and camera angles to heighten tension.
Using Vivid Descriptions and Sensory Details:
Visual Storytelling: Use high-quality visuals, including close-ups, wide shots, and dynamic camera movements.
Audio Immersion: Employ immersive sound design, including background music, sound effects, and voiceovers.
Sensory Language: Describe sights, sounds, smells, tastes, and textures in a way that evokes emotions.
Unveiling the Story’s Meaning Through Symbolism:
Symbolic Imagery: Use objects, colors, or locations to represent deeper meanings.
Metaphorical Language: Employ metaphors and similes to convey complex ideas in a relatable way.
Subtle Themes: Embed underlying themes throughout the video, such as love, loss, or redemption.
Additional Tips:
Tailor your storytelling style and content to your target audience’s interests and preferences.
Maintain a clear and concise structure, avoiding unnecessary tangents.
Engage with your audience through comments and feedback, using their insights to improve your storytelling. reply to your comments with questions!
Try new storytelling techniques and learn from your mistakes.
Here are some top YouTubers who are masterful storytellers:
Kurzgesagt – In a Nutshell: This channel uses animated, fast-paced visuals and narration to explain complex scientific and philosophical concepts.
Sam Dawson uses an unusual editing style to communicate his stories.
Vice: This channel produces a wide range of documentaries, from investigative journalism to cultural explorations, often featuring immersive storytelling and strong character development.
Casey Neistat is known for his cinematic style and honest storytelling, Neistat shares his emotions through personal experiences, travels, and creative projects.
Life of Riza:This is a very talented, young YouTuber who vlogs about her daily life experiences through beautiful, cinematic footage and simple stories.
Gawx Art: This young artist is a YouTube sensation who built his channel on his artistic approach to storytelling through movie-like videos.
National Geographic has well-produced videos about ancient history and more.
Check out one of my videos where I tell a story about the symbolism of white in art history and life:
![[Guide] What Is an Art Fair? Is It Really Worth Attending?](https://architectman.ir/wp-content/uploads/2025/04/what-is-an-art-fair-thumb.jpg)
