In many cases, using genAI is just another way of saying 'I don't really care about you. Not that much'.

AI-generated background music for your video? Not something cool and hand-picked that'll make someone Shazam it or ask 'Song??' in the comments? And then, they'll probably discover other tracks and albums by the artist? 'I don't care about you that much'.

AI-generated texts for your blog or LinkedIn page? Not your genuine thoughts that would have ignited a spark in someone's mind? You feel like you have to share something and get likes and grow followers, but find it too demanding in reality? 'I don't care about you that much'.

Vibe-coding yet another habit tracker (lol) 0 to 1 with genAI in 'tab — tab — git push' style? Instead of crafting UX and designing UI, reading the docs and learning how to write (or at least properly edit) code? 'I don't care about you that much'.

It's not the amount of suffering that matters. It's the intent to care about the recipient. The desire to offer something genuine, valuable, inducing emotions and thoughts, something that at least has the potential to somehow influence others' lives.

However, this is not a unique feature of genAI. LLMs are just tools, like anything else. The same 'I don't care that much' thing happens when people use generic stock images that add no value instead of crafting (or buying) a proper illustration; when they plagiarize texts or music; when they use senseless and heavily SEO-optimized copy instead of writing articles that help answer users' queries.

Ultimately, it’s not an AI problem. It’s how people use it.

Always has been.

Let's face it: ChatGPT plans are ridiculous. Which one do you choose:

• The Free option's 'advanced features' (like file analysis) limits are so low you can essentially say they're not included at all.
• The Plus subscription for $20 has decent limits, but it feels like you're participating in a beta test and in addition paying for it for some reason.
• Pro for $200? We'll get to that later.

The main point is that ChatGPT's paid 'advanced features' aren't valuable enough to cost $20 — for several reasons.

Code? It's pretty bad at complex tasks if you know what you're doing (and even worse if you don't). It's more or less OK for simpler tasks, but those are pretty covered by the free plan.

Research? That's literally the worst thing you can use an AI chatbot for. Hallucinations make you do more research to validate the data ChatGPT is lulling you with the ultimate confidence.

Analyzing data? It follows instructions poorly, and tries to gaslight you about the tools and methods it's using when you notice they are not right. And yet again, hallucinations: after some practice you can predict and feel when they're coming, but it takes time and effort to locate and mitigate them. For complex tasks, using the right combination of Python, Pandas, and machine learning algorithms does the job much better, albeit sometimes slower. And if you're no coder, you can always ask a free version of ChatGPT for assistance.

Proofreading and editing texts? It's OK on a free plan, and I prefer to use my own head and a bit of DeepL for this anyway.

Advanced voice? It's cool, but that's it — for work purposes, it's useless; and for leisure I have lots of people to talk to for free (they're also smarter than ChatGPT, and have a personality).

In addition, one of the most annoying things is what users call 'lobotomizing'. From time to time OpenAI rolls out an 'upgrade' that makes some part of ChatGPT dumber. One day — and the day before that, and the month before that — it can do something rather well, and the next it produces utter gibberish within the same task, no matter how you juggle with prompts. When you're at work, you expect some predictability from your tools, don't you?

Now back to $200-ish Pro: no limits at all — but the product is the same with the same caveats.

It's not a matter of skill. I've been using various LLMs, AI and ML tools long enough, and I've even written a tutorial on how to squeeze the most out of ChatGPT itself. It's just an unfinished product in its early stages — a live beta-test, as I said — and it's not bad; I just ain't paying for this.

So if you're wondering if ChatGPT Plus is worth it, it's not. Only if it amuses you enough — and more than, say, Xbox Game Pass Ultimate, which costs the same.

Every living person has a superpower. It pushes you to gain new experiences and skills, it pushes your development. It pushes you to try a new unconventional solution and to experiment. To test 'what's gonna happen if it's like this', 'what if I do THAT thing'.

It's called curiosity.

All the world's progress is rooted in this superpower. Without it, we wouldn't have had smartphones, wine, band-aids, books, frying pans, the trolley problem, images of Europa, elevators, the Grammy award, constitutions, brie cheese (frankly, any cheese), cigarettes, toilet paper, Chinese water torture, gene therapy, schools, roads and sidewalks, history, studio apartments, comics, LSD, pop-punk, diamonds, Regex, fairy tales, MREs, oxygen masks, porn, psychotherapy, BBQs, diaries, video games... you get the idea.

So my question is: are you using your superpower enough?

Sometimes, we forget the pace of progress over the last couple of decades (and over the last ~60 years as well).

These are from the 2010 presentation. It was obviously pitched as a cool breakthrough deal. Now you won’t find a device or data plan with that kind of poor offering, and a YouTube app alone is 300 Mb. In one’s lifetime, we have gone from an isolation both indoors and outdoors to global connectivity almost everywhere; from communicating with giant computers via punched cards to on-device LLMs that you can talk to vocally; from waiting minutes for an image to upload to grabbing the entire Wikipedia in less than half an hour.

But the pace has its downsides. The swing to full-on tech approach instead of cross-pollination of tech and liberal arts brings a dystopian, heartless and wicked landscape. Quantity over quality; bending the user instead of tailoring the product; the rise of cheap and mediocre instead of sophisticated and pricey; mass production over handcraft.

We've been through these processes before. It was called the Industrial Revolution. Now, it's happening to information rather than goods.

I've wrapped up some trends based on events that happened in 2024. AI has become both a blessing and a curse, but it's not the only story worth telling. Beneath the surface of AI-powered chatbots, language models, and generated images lies a complex web of technological shifts, social implications, and economic disruptions that are redefining our world.

Enshittification

Content bloat

It's been around for at least a decade — senseless SEO-optimized articles, content marketing for content marketing's sake, pointless SMM — yet in 2024, it went on a rampage thanks to AI. One of the current problems with AI is that it has made it so easy and fast to produce low-quality content. Users often complain that search results have become useless, largely due to material created, published, and SEO-optimized by LLMs with minimal human input. The same is true for social media: tons of genAI images have flooded Facebook, LinkedIn, Twitter, and other platforms, and are now widely used in ads.

Journalists at 404media conducted an experiment and created a website for just $365 that runs entirely on AI and produces about 50 plagiarized articles per day. Memes can also be AI-automated. Users build a Claude-to-Stable Diffusion pipeline and generate them based on templates (here's a couple of examples: 'Wojak' and 'Stop Doing X').

It's getting harder to select, search for, and to recieve meaningful content, and the situation tends to get worse. 'Less sense, more content' is the motto of a frighteningly large group of people and brands; now they have the tool which empowers that approach and makes it possible with minimal effort.

Data ends up in one place

And the place is datasets for training AI. Everyone wants your data — and if it used to be so to sell ads, it's now to sell ads and train AI on it. Bots generate 30% of world's traffic, according to Cloudflare, and some part of them are scraping any web page they find for AI-training purposes. The naughtiest of all, by the way, is 'Bytespider' from the Chinese company ByteDance, which owns TikTok, it's responsible for 40% of all AI-scrapping queries. Google is also ruthless: it uses the same bot agent for both search indexing and AI, so website owners have no choice: it's either you block it and vanish from search, or let it go. Another point of stress is user data on major platforms: you're happily using Instagram, or Reddit, or Twitter, and have no idea that your comments and posts will end up in some large language model. The latter, for instance, secretly added such an authorization to its settings, turned on by default, and it can't even be turned off from a smartphone.

Site owners, some businesses and users are fighting back. Cloudflare, for example, has launched a one-click solution to combat AI bots. The company that powers half the internet is now able to block scrappers that ignore robots.txt, thanks to its new ML-powered algorithm that can detect bots even when they're masquerading as real users. This feature is available to all users for free, and given Cloudflare's clout and ease of integration, it's likely to be quickly adopted.

Bullshit creates more bullshit

Given the alarming rate at which the Internet is being filled with generative content, and that the data from the Internet is ending up in training datasets, the possible outcome is quite predictable. Researchers have discovered that training models on generated data inevitably leads to their degradation. When you feed an LLM (Large Language Model), VAE (Variational Autoencoder), or GMM (Gaussian Mixture Model) with output from other models, they go haywire: forget what they've learned, the behavior collapses to a minimal variant, and they start producing outright nonsense. The process is called model collapse.

It's tempting to imagine a black market for dusty SSDs labeled '100% AI-free' and 'pre-AI era data', but that's just a humorous exaggeration. In reality, if humanity can muster the will to focus on this issue in advance, we can prevent AI from being poisoned by the data it generates — just as we did with the Y2K problem. And later, ordinary people will walk around saying that since nothing happened, there was no problem at all, and that evil programmers and lying media made it up.

Useless AI everywhere

There is some kind of rush to add AI to every product, and to label everything as 'AI-powered', as if that makes the product better. So-called 'AI assistants' are in many cases ChatGPT, or Claude, or another model wrappers that are poorly integrated, add no value and have no real use cases. When it comes to proprietary models integrated by major platforms, it doesn't get better:

• Musk has introduced a feature on Twitter called 'More about this account', which is powered by Grok and available to paid users. When you click the button, you're supposed to get a brief summary — who they are, what they're known for, and what they write about on their account. But the results are worse than disappointing. The neural network comes up with non-existent facts, doesn't provide key information that's right in front of you, or resorts to vague general statements that could be applied to any profile. In its current form, 'More about this account' is not only useless, it is harmful. Twitter has also added Grok-2 with image generation capabilities. Users are already creating images of Mario smoking, intentionally provocative photos of body parts, and erotic content with celebrities — in short, all the things that are banned in other chatbots. Grok in general easily absorbs and spreads misinformation, and generating content on its own platform opens the doors to a sea of fake news and senseless clickbait.
• Google has added Gemini or various AI features to Gmail, Chrome search bar, Meet. Here's a great example of how it messed up meeting notes. And YouTube has introduced AI-generated chat summaries. Users joke about how perfectly this feature will work. It's understandable — AI can easily mess up even simple tasks, and at scale it only takes a few resonant edge cases to undermine trust. Given the toxic and absurd nature of the Internet's comment sections, Google's initiative is indeed hard to call safe.
• Meta adds its Llama to WhatsApp, Instagram and Facebook, minimizing effort needed to generate and share AI slop.
• SalesForce is so aggressively rebranding its solutions as AI-powered that the phrase 'AI agents' was uttered a hundred times during an investor meeting.

LLMs actually do a poor job of summarizing, as NY Mag argues in their column. It's hard to disagree — AI always acts as an unreliable narrator whose word can't be trusted, and it's easy for them to miss important details and replace them with unimportant ones. Research confirms this — all models hallucinate, and even the best of them can only provide non-hallucinatory answers about 35% of the time at most. In addition, researchers claim that the larger the LLM, the less likely it is to answer simple, basic questions correctly. The problem is that as training datasets grow and model power increases, and especially when trained on feedback, models start to get better at ambiguous questions — but when it comes to simple questions, if they don't know the answer, they're more likely to answer incorrectly rather than admit ignorance.

AI-free zones

In addition to the trend of AI-izing everything, a counter-trend is emerging. 'AI is needed, but not everywhere and not always' — in other words, people value the ability to turn off neural network functions in certain scenarios.

One of the points is that people are not ready to outsource to AI what should be a genuine expression of their thoughts and emotions. Sending an AI-generated email to a contractor or government agency is one thing; writing a love letter, pinging friends, or writing a product review is another. The main question is: why bother writing at all when you can completely replace yourself with an algorithm that doesn't have any "you" in it and produces standardized, generic results that anyone could write? The best illustration of this is the ad Google ran on the Olympics featuring a father asking Gemini to help his daughter write a fan letter to an athlete. The ad had to be pulled.

Another point is connected to creativity and art. One of the notable themes of the year is an essay by sci-fi writer Ted Chiang on why AI won't create art. One of the main points is that the basis of any art is a huge number of micro-decisions made by the author, which AI cannot replicate (it either chooses something mediocre), and detailing all these decisions to instruct AI requires just as much effort as simply doing it without it — which is exactly the opposite of what genAI claims to do (more output than input). Perhaps the best sentence in the essay is: It [AI] reduces the amount of intention in the world.

Speaking of product examples, the Halide Mark II camera app has added a 'no AI at all' option. On modern smartphones, all photos are processed, even if you enable the 'raw' format in the settings. The sky is color-corrected, noise is removed, and some manufacturers even completely replace objects like the moon. The new Mark II feature turns off all processing, leaving the image as it would be on a '00s digital camera.

Procreate, on the other hand, urges companies not to use generative AI features in creative products. The company doesn't want to add genAI to its app, claiming that its use hurts artists and the industry as a whole. The artistic community has greeted this statement with approval.

Social media clusterfuck

The decline of social media isn't a new thing — the short golden age of 2010-15 is long gone, but the cumulative effect of social media enshittification peaked in 2024 and is likely going to evolve in 2025. The main platforms have long since turned into a moldy pot with a salad of stale algorithms, tons of rotten ads, boring gamification for engagement, grime of an overloaded interface, rust from total surveillance, and boils from millions of additional services like 'we-are-yet-another-super-app-for-everything'.

People are fed up with social media and some of them are trying to find a more enjoyable and meaningful experience in niche applications.  Users who are desperate to feel connected to real people and ideas that matter to them are leaving social media to find it on specialized services with a social function, such as Goodreads, Strava, Letterboxd, and others. What's interesting is that, according to Bloomberg, the business world is somewhat following suit.

Not everyone is ready to give up on social media, though. These people are switching from old platforms to emerging ones — like Bluesky or Threads. However, the problem is that most of the new social platforms are built with the same principles in mind as the old ones. They reinforce the same pathological patterns, just in a new place, giving the users a brief respite while they are not yet filled with bots, ads, overengineering, etc. — before they turn into their predecessors.

Reality mix

Hard to tell if it's real

The imaginary world continues to merge with the real world. It becomes more and more difficult to distinguish information imagined and created by a machine from information imagined and created by a human. There seems to be a lack of working solutions in this area — and there's no certainty that they will appear.

For example, Instagram and Facebook's 'made with AI' labels erroneously attach themselves to real photos. All you have to do is edit them using Adobe tools — whether it's a little cropping or some light AI retouching, Meta's systems will still flag it as generative fantasy. YouTube is developing a set of tools to detect deepfakes in vloggers' videos, but their effectiveness remains unclear. Google search results are flooded with AI images, making it easier to find a generated peacock than a real one.

Scrolling through social media or websites, it's not always clear whether the people in the photos are real or not. Does this place even exist? Is this fake poison ivy what it looks like? The latter example is no accident — a family in the UK claimed to have been poisoned by mushrooms because of an identification guide containing AI-generated images. The buyers had purchased the guide on a marketplace, only to find out later that at least part of the book had been written and illustrated using AI (the author claims that there was no mention of this in the book, of course). The rise of AI video generators in late 2024 only adds up to the case: now it's not just about texts or photos, video is also shifting into a limbo between reality and fantasy.

Now, if you're looking at something, you are looking at something — and it's unclear what it is.

AR/VR winter

Companies are desperately trying to combine AI, AR/VR, the Internet, and social media in wearables to reboot the category, but so far it's been a clear failure. Smart glasses (remember Google Glass?) raise more questions about use cases, privacy boundaries, and convenience than they provide answers. Pins with AI assistants, in their current form, clearly can't compete with smartphones and feel like unnecessary add-ons. Vision Pro, despite its pass-through mode, is impossible to wear all the time. Perhaps the problem is that no new combination of output, input, compactness, and ergonomics has yet been created that is simultaneously more comfortable, immersive, efficient, and functional than touchscreens and keyboards. But it's still a long way off.

For now, companies are gradually releasing products — such as the new Meta Quest, Apple Vision Pro, Android XR, the Vertex treadmill platform, or the Roto VR rotating chair — but a critical mass of change has yet to be achieved, leaving the market narrow and penetration low for now.

At the same time, the AR community received a big blow from Meta: the company announced the shutdown of Spark Studio. AR Devkit will stop working on January 14, 2025, and all filters, masks, and 3D objects created with it will also be deleted. Meta claims to be shifting its focus from augmented reality to AI, but this excuse is no consolation to the creators who invested in AR-based features that were extremely popular on Instagram (and they are rightfully furious).

AI

Functionality improvements

Every major GPT chatbot company has been hard at work making chatbots more functional and adding tools for more use cases. These include 'projects' to share context (files and system prompts) between chats, web search to get rid of GPTs' constraining bonding to training data, OS and app integrations to gather more context and perform actions, 'memory' to store small chunks of context across chats and sessions, and so on.

In general, this sounds like a healthy way to make improvements toward a more useful technology. Some of the biggest problems with LLMs, besides unreliability/hallucinations and the reluctance to admit incompetence or lack of data, are the lack of user- and task-specific context, which prevents the assistant from doing right things in a right place at a right time, and the near total absence of long-term memory, which makes the conversation flow inconsistent. Looks like companies know this, and are taking steps to address it.

The race for AGI / Software optimizations

At the same time, there is an 'AGI fever'. Millions of dollars are being spent either to scale existing models — which is becoming increasingly difficult because there isn't enough data left — or to redesign the models by tweaking the way they work or by combining different types of models. This is all for one goal: create Artificial General Intelligence, a digital entity comparable to humans in terms of thinking and reasoning. Companies don't have a clear definition of what they aim to build, and have no idea how to measure whether they're getting there. In 2025, we'll see more and more claims of 'nearly achieving AGI' with state-of-the-art experimental models, while the basic and widespread functionality of AI will advance rather gradually.

What's more important, though, is optimization. There have already been some advances in quantization and other methods of running LLMs with fewer resources, but the overall resource consumption for both training and inference is still too high. If the programmers of the 70's-90's hadn't had to optimize everything to push the limits of what was possible on not-so-powerful machines, we wouldn't be at the same point of technological progress. After a surge in available computing resources, the tech industry became relaxed and started paying less and less attention to how neatly and efficiently things were organized under the hood. Now is the time to reverse this trend, because once again we are facing a set of tasks that are promising, but require qualitatively new approaches. We can expect some breakthroughs in this area in the coming years.

One of examples is Recogni: their approach, Pareto, significantly reduces the cost of inference. It uses a logarithmic number system and converts multiplication into addition. According to the company, this saves resources — while maintaining calculation accuracy. Or Outreport, who has presented a system for fast model swapping on a single GPU. The hot swap process takes about ~2 seconds, which is ~150 times faster than traditional methods. The founders claim that the project uses caching to enable fast loading and optimization, which can reduce costs by up to 40%.

Meanwhile, the gap between open source and proprietary LLMs is narrowing, so we shouldn't expect a One True™ Gatekeeper to emerge.

Infra optimizations

Optimizations and advances on the infrastructure side are underway. Everyone is working on three main challenges: balancing the cost-to-performance ratio, creating more powerful hardware, and scaling available resources (data centers, power, GPUs, etc).

Apple is trying to develop a distributed inference where tasks are processed on multiple devices. When you're working with neural networks, it makes sense to share workloads across high-end Macs, iPhones, iPads, and Vision Pro — and that's exactly what Apple has done with its recently announced Apple Intelligence. The combined processing power of the ecosystem makes it possible to perform more complex tasks than any single device can handle. In the meantime, distributed inference with workload management has been already done for consumer devices. With Exo, you can run an AI cluster on Macs, iPhones (support for which is currently suspended), Android phones, and Linux machines. The library connects devices in P2P mode and distributes model layers between nodes in proportion to their performance. It sounds a lot like the Apple patent.

Others, like Cerebras, are trying to challenge the hardware market leaders. The company is launching a cloud-based inference service. They claim it's the fastest inference in the world, supporting 450 tokens/sec with Llama 3.1-70B. The startup uses its own custom-designed chips, Wafer Scale Engines, and aims to compete with Nvidia's GPUs, the de facto industry standard, with a faster and cheaper option.

It's (not) welcome here

The jury is still out on where it's good to use AI and where it's not. Take medicine: medical AI systems are biased. Research shows that the quality of results from neural networks used to make diagnoses based on images (such as X-rays) varies depending on the patient's gender, age, and race. When analyzing data, AI uses 'demographic shortcuts': in other words, overly broad groupings like 'all 60+', 'all dark-skinned 20-25 year olds', and so on. These are essentially old-fashioned stereotypes. But this is a fixable problem, according to experts: it's better to either prevent AI from making predictions and taking demographics into account, or to reward a model for lack of bias in a subgroup and penalize it for bias that leads to worse outcomes.

In bureaucracy, it's not so smooth. In Nevada, Google's AI will review applications for unemployment benefits. The AI will analyze transcripts of court hearings and review related documents before providing a brief summary with a recommendation: approve, deny, or revise the application. This summary will then be reviewed by a human, who will make the final decision. However, experts are skeptical, and for good reason: in addition to the unreliability of modern AI results, the system also creates pressure on individuals to simply click 'approve AI's recommendation', rather than carefully reviewing the details — especially when they need to quickly clear a large backlog of cases. Moreover, this approach only reinforces the lack of attention to detail and context that often characterizes bureaucratic systems.

Judicial? Better forget it. Researchers have trained AI to detect lies better than humans, but the idea poses more problems than solutions. First, at 67% (compared to a human average of about 50%), accuracy is still very low. Second, there are moral dilemmas: even if the system's effectiveness were improved to a hypothetical 95%, would that be enough to blindly trust its results? What about the five percent (in an exaggerated case, it's actually closer to a third) that the AI would falsely accuse of lying? Moreover, research shows that people tend to believe and even accuse others of lying when AI says so. Is it worth delegating such judgments to programs and using them as additional evidence? Can someone be tested for lying against their will? Even polygraph is considered a pseudoscience with low effectiveness and is usually not accepted as legal evidence.

Smoothing the UX? That's a nice thing, but think (and run tests!) twice. The second-hand marketplace Depop has added an AI-generated listing feature based on a single photo. When an item is uploaded, the neural network recognizes it and fills in the brand, color, and description. This is essentially the mythical 'make it look cool' button that people have jokingly fantasized about since the dawn of the Internet. The question remains, however, how to strike a balance between helping users and society by automating routine tasks (that may not even exist), and dehumanizing everything and turning communication into a duel between ghostly simulators. The line is probably far from the idea behind Bumble's use of AI in profiles and messages, or even Tinder's more moderate solution of allowing AI to select profile photos.

Eco

It's bad. What did you think I was going to say? We all know the data: writing a 100-word email using ChatGPT would consume more than half a liter of water and 0.14 kWh of electricity, blah blah blah, and so on. And the corporations don't give a damn about it. They are going full-in on greenwashing: for instance, according to Google's annual report, the company's greenhouse gas emissions have increased by almost half in the last five years. The main culprit is AI, by the company's own admission. The energy consumption of data centers used to compute AI functions has led to a significant increase in emissions. Google's forecast is less than reassuring, stating that 'emissions will continue to grow before eventually declining to target levels'. However, it does not explain how this decline to net zero will occur. The phrase 'the world's understanding of "net zero" remains in a dynamic state and is subject to refinement' is a remarkably feeble and dubious PR excuse.

There is a glimmer of hope, though: Google has partnered with Holocene to remove CO2 from the atmosphere. The startup is still in early stages, having only been around for two years, but it offers a much more affordable solution than its competitors — $100 per ton vs $600+. The cost of capturing and processing CO2 is critical in this equation, and if Holocene is not bluffing and can actually reduce the costs to that level, then the greenhouse gas problem could be solved by a third. It's worth noting, however, that Holocene currently only has a pilot production facility in Tennessee with the capacity to capture just 10 tons per year.

Nostalgia

The Roaring Twenties (I mean 2020s) awake both mournful sadness and passion for the past. Nostalgia manifests itself in the visual domain, such as pixelated designs or retrowave, music, fine art, and, of course, tech.

It's been 20 years since the original Motorola Razr was released, and now the company is back with a new version — with AI, of course. The foldable smartphone market in the U.S. has tripled in the past year, and Motorola dominates it with about 75% of the market share. Users also have fond memories of the Windows Phone menu and OS as a whole. Many claim that it was ahead of its time and better, despite having almost no apps available. In addition, social media has been abuzz with discussions about an Apple Watch case that turns it into iPod Classic, yep, that's right — with a wheel. And, of course, people are reminiscing about the rare case for the iPod Nano that turned it into a watch-like device.

We've come full circle.

Phygital

Phygital (in a broad sense — as the combination of digital practices with physical world) is growing, but also raising concerns.

Walmart is replacing traditional price tags in its stores with e-ink screens. The move has sparked concerns about the potential for price manipulation, with shoppers worried that surge pricing will come to offline retail. One of the most prominent examples of how this technology could be used is to dynamically increase the price of water and ice cream on hot days.

European lawmakers are also trying to regulate surge pricing after a high-profile incident involving the sale of Oasis reunion tickets. Customers who had waited hours for their chance to buy tickets arrived at the store only to find that prices had skyrocketed. Now, 14 European MPs are proposing amendments to the Digital Services Act (DSA) to restrict the use of this technology. The issue is not new, however — concerns about surge pricing have been around since the dot-com bubble era, when it began to cause frustration in areas such as taxis and delivery services. While there may be some justification for dynamic pricing in these industries, its use in other sectors raises legitimate public concerns.

And finally, AI is being introduced into offline shopping and customer service. Amazon is integrating it into its Just Walk Out systems for stores, while Taco Bell is using it to optimize orders at drive-through windows.

Robotics

Robots are becoming smoother, more capable, and more futuristic (read: some multifunctional, some extremely specialized).

The Nadia robot has been optimized to play table tennis, with smooth movements and reduced I/O latency thanks to its VR control system. This was demonstrated in a game of ping-pong against a human opponent, but it's easy to see how robots like this could be used in the future where it would be dangerous or uncomfortable for humans: in mines, in space exploration, or in warfare. There's little doubt that robots will eventually be used in these areas — the Ukrainian military is already using AI in drones for terrain recognition, target identification, and avoiding electronic countermeasures. The next step is coordinating swarms of UAVs, which will require the use of sophisticated algorithms to manage complex variables and rapidly changing environments. In some cases, human intuition simply won't cut it, and AI will be a matter of life and death.

Robots are also getting more industrial, medical, agricultural, FMCG, and delivery jobs:

• An AI-controlled robot has performed its first dental surgery. It uses OCT to create 3D models of teeth, while a human doctor makes the decision and the robot then performs the procedure independently. In this case, the robot prepared the teeth for a dental crown in just over 15 minutes, significantly faster than the usual two or more one-hour visits required by human dentists.
• IKEA has adopted drones for inventory management. Instead of using them for delivery, the company unleashed them to fly around in the stores to scan products in hard-to-reach areas. This reduces tedious and inconvenient work while keeping the store's inventory up to date in near real time.
• In the UK, permission has been granted to test the use of UAVs for delivery, infrastructure inspection and emergency services. Shake Shack is also launching drone food delivery in LA.
• Robots with AI are being developed for agricultural use, including ones that can spray herbicides. John Deere's tractor robots with AI-based plant recognition systems are more accurate at targeting weeds while avoiding crops. Precision AI uses similar technology in its agricultural copters. Smart spraying not only reduces damage to crops, but also significantly reduces chemical use, benefiting the environment and lowering costs.
• Self-driving holds great promise for freight trucks. While others focus on automating deliveries on highways, Kodiak Robotics is taking a different approach in another niche — off-road routes. Not all destinations have roads, especially when it comes to contracts with the U.S. military. They're willing to pay more for it. The solution? Train trucks to drive off-road instead of sticking to traditional logistics. But the application goes beyond working with people in khaki: construction sites need gravel and sand delivered, remote communities need food and medicine, and oil rig workers and archaeologists need equipment. And perhaps one day these technologies will be used to transport goods on the surface of other planets.

Improving robot behavior is getting easier, too. Robots can be trained in simulations created by scanning a room with an iPhone. It's especially important for home robots — each workspace is unique and constantly changing. So users can scan their room with an iPhone, create a virtual replica, and run tens of thousands, hundreds of thousands, or even millions of simulations within it before deploying the robot to perform a task in the real room. The only remaining step is to automate the process of scanning the room itself, eliminating the need for human intervention — but that is already a technical matter.

Hardware

Hoist all sails and full steam ahead for better AI chips. The situation with graphics cards and chips due to the rise of AI is still intense. For example, Nvidia has released a version of its RTX 4070 model with simpler GDDR6 memory instead of GDDR6X; Mitsubishi is struggling to keep up with orders for components used in data centers. DRAM and SSDs are flying off the shelves, pushing manufacturers to develop more efficient devices and governments to support the industry.

Intel has announced new AI processors, while ASML has created a prototype of a new EUV lithography machine that has produced its first results. This technology can print chips with line densities as low as 9.5nm using 2D routing, and can even print DRAM chips in a single exposure, significantly reducing production costs. And Infineon has developed a technology that will significantly reduce the cost of manufacturing the next generation of AI chips. 300mm gallium nitride wafers can produce 2.3 times more chips than before. While this is a quantitative improvement in itself, combined with ongoing work to optimize conductor manufacturing, we could see significant qualitative changes in the performance, compactness and affordability of specialized AI chips in the near future.

Semiconductor sales in the Americas surpassed those in China for the first time in five years, growing 40% YoY. But Europe, which aims to produce 20% of the world's chips by 2030 (up from 10% today), faces a major risk: a shortage of skilled workers. While TSMC is going to build a factory in Dresden and Intel is planning a 'mega-factory' in Magdeburg, industry associations estimate that European bureaucracy and lengthy approvals are slowing down the sector's development.

There is also hope for quantum computers: a new architecture for qubits has been developed that could greatly simplify production. Scientists had previously worked on qubit sandwiches made of superconductors separated by an insulator, but this approach proved more complex and less productive. A simpler and more promising method uses separate superconducting plates connected by a thin superconducting wire.

Meanwhile, consumer device development seems to have plateaued — nothing particularly exciting is happening. Apple, Google, and Samsung have all held their presentations and shown off new products, but there hasn't been any significant change, with the focus instead on AI features. The same stagnation can be seen in the game console market, which is lagging behind computers.

Brains online

Brain-computer interfaces and neural implants are no longer the stuff of cyberpunk fantasy. The devices are here, they work, and they are on the (rather long) road to mass production. It's only a matter of time, the market they eventually land on, and penetration (pun intended).

• Neuralink has tested its devices on two patients and they are able to control a computer with their thoughts. Its Blindsight chip, designed to help restore vision, has received FDA approval for testing.
• Blackrock Neurotech's implants have helped two ALS patients regain the ability to communicate by voice. A paralyzed man and woman received neural chips that convert brain signals into text, which is then read aloud by a synthesized human voice using pre-disease samples.
• A child with the world's first epilepsy implant experienced an 80% reduction in seizures. The patient, who had an unresponsive form of epilepsy, received the implant in October 2023 and has since experienced a significant improvement in quality of life, with no reported falls due to severe daytime seizures.
• Synchron even integrated ChatGPT into the neural implant. The chip was inserted into a patient with ALS through a vein (no brain surgery required!). The AI in the implant is used to enhance communication capabilities: in conversations, ChatGPT generates multiple response options for the patient to mentally choose from, and the LLM takes into account not only the context of the conversation, but also the patient's emotional state, which is read through the implant.

Copyright & Legal

The battle Copyright vs. AI continues to escalate. Companies that sell licensed data for AI training have formed the Dataset Providers Alliance, the first industry association in the field, which promises to address ethical issues. At the same time, US record labels are suing AI music generators Suno and Udio, Center for Investigative Journalism is suing OpenAI and Microsoft, Forbes and Wired accused Perplexity of plagiarism and illegal data collection, while Reddit has updated its robots.txt file to prevent AI from scraping its data. However, many AI companies are known to ignore robots.txt instructions, and website owners have yet to find effective ways to stop them (although there are some interesting ideas).

A notable example of the copyright problem is Figma's temporary shutdown of the AI tool Make Designs shortly after its launch. The model, hastily (and CEO admits it himself) fed with reference images, began generating designs so similar to real-world applications that they were almost indistinguishable. The company's CTO claims that they did not train the model themselves, but I guess that won't come as much of a relief to those who used the new tool in their work and now risk being sued for copyright infringement.

The regulation of AI in its early stages is a global problem. Often it is reactive, as in Brazil, where a new Meta's privacy policy has been suspended due to training AI on user data. In other cases, like China, there's a strategic approach, with an attempt to develop 50+ standards for AI in two years.

Both approaches seem alarmingly unbalanced: reactive solutions fail to consider long-term consequences, but while large strategic policies are written and adopted, technologies leap forward, and the digital landscape changes.

There is still no clear regulation even for social networks, let alone artificial intelligence. For example, the head of Microsoft's AI division and co-founder of DeepMind sparked a discussion. The Verge quotes Mustafa Suleyman's comments under the headline 'Microsoft's AI boss thinks it's perfectly okay to steal content if it's on the open web'. He has a point: some users may underestimate what happens when they post online (and various 'take down' laws are pretty absurd). This is how the Internet works, with information chaotically spreading, combining, being used and transformed. But Mustafa's logic has a fatal flaw: you can't do whatever you want with content just because you found it on the Internet — especially if you're a giant corpo.

There has also been progress: the US, the EU, and the UK have signed the first legally binding treaty on AI. The Framework Convention on Artificial Intelligence includes high-level principles, such as the alignment of any developments with human rights and democratic principles, a commitment to transparency and privacy, and non-discrimination. The framework has also been signed by Norway, Iceland, Israel, Georgia, Moldova, Andorra and San Marino. In addition, the EU AI Act came into force in 2024, regulating AI work based on risk levels. And sixty countries, but not China, have backed the creation of a global framework for the use of AI in military technologies.

Google is recognized as a monopoly. In recent years, tech journalists have regularly discussed the possibility that the company will face a fate similar to that of AT&T in 1982, which was broken up into smaller entities due to its monopolistic position. While Google hasn't been broken up yet, the message is clear. Other tech giants, such as Apple, are at risk of facing similar problems.

Workforce

The debate about the impact of AI on jobs is intensifying. The impact is undeniable: Intuit is laying off 1,800 people to hire another 1,800 to work with AI; at Klarna, AI has taken over the work of 700 people and helped the company save on labor costs. The CEO claims that instead of layoffs, they've simply not filled positions since September 2023, and revenue per employee has increased by 73%. It's clear from the context that this is primarily about customer support, given the common and well-understood use cases of the fintech industry. A similar experience can be seen in the Philippines, where AI is successfully replacing humans in call centers.

OpenAI's CTO joined the discussion with a succinct and relatively objective statement: 'Mostly, jobs that shouldn’t have been there, will go away'. History shows that while technological progress may eliminate certain jobs, it also creates new ones — often with better working conditions or greater efficiency.

Moreover, AI is proving to be an unreliable touchpoint in the job market. According to a LinkedIn study, 71% of managers would rather hire a candidate with strong AI skills than industry experience. FT, in turn, reports that around half of job seekers use ChatGPT to create cover letters (which are then also reviewed by AI instead of HR professionals).

Economics

Tech companies are caught between two fires. On the one hand, they are forced to cut costs and make layoffs after the big correction that started in late 2021 and early 2022 (examples include Intel, Amazon, Alphabet, Microsoft, and IBM). On the other hand, their bets on AI will require them to increase spending on infrastructure and R&D. And investors are starting to get impatient, waiting for AI to become profitable and deliver those coveted 10x/50x/100x returns.

AI is still a work in progress and not very profitable. Some of the funniest examples are that customers are returning Humane's AI pins faster than the company can produce them, while Amazon's new AI feature for its podcasts, 'Topics' has AI mostly solely in its title: AI is only used to transcribe text, while human contributors manually add topic tags (maybe that's for the better).

Tech companies are trying to divest themselves of Chinese assets. Microsoft has asked some employees to relocate to other regions; IBM is following suit, completely shutting down its 1,600-person R&D department in China; Canada has imposed punitive tariffs on Chinese electric vehicles and steel, while the EU increased tariffs on them in July. The Netherlands plans to restrict ASML's ability to repair semiconductor equipment in China.

For too long, a blind eye has been turned to China's totalitarian regime, much like Russia's — but now, as tensions rise, companies are trying to protect their investments. The strategy is sound, although it should have started 10 years ago. But the infrastructure for disengagement is not yet in place, and current actions are limited: Big Tech is taking tentative first steps, unable to scale an exit from China.

Hacks

Hacking attacks are becoming more frequent, faster, and more consequential. According to a survey by Yubico, nearly half of employees have fallen victim to phishing scams or cyber attacks. In 2024, US car dealerships were targeted and it took several weeks to clean up the mess. Then Microsoft was hacked, along with some government agencies. 33 million phone numbers stored in Authy's 2FA app have been stolen, and a database of 10 billion stolen passwords (the largest of its kind) was compiled from previously leaked data over 20 years, plus some new ones added.

It also turns out that OpenAI was hacked earlier in 2023. Unfortunately, it's probably not an isolated incident: the company's new Mac app had stored conversations with ChatGPT in plain text (!). The bug has been fixed, but the damage is done. And to top it all off, 'Global chaos erupts as Windows security update goes bad' — a title that needs no further explanation. BSODs worldwide, flight cancellations at airports, problems with Apple Pay and TV broadcasts, closed stores and clinics, and other delightful consequences of CrowdStrike's poorly planned 'fuck it, LGTM, just push to prod' approach to security updates.

AI is striking in two ways: first, it can be exploited. A vulnerability has been identified in Slack's AI capabilities. An attacker could create a public channel with themselves and insert a text instruction for the model, which would then respond to a user's question by pulling data from this malicious channel and following the attacker's instructions to embed a phishing link. This type of attack is not limited to the Slack Assistant, but affects many other models as well. If there have been available lots of solutions such as SSL, PKI, and 2FA, for a standard MitM attack, it seems that there's still work to be done to prevent prompt injection vulnerabilities. In other incidents, security researchers discovered vulnerabilities in SAP's AI services that allow attackers to steal customer data and even manage their Docker containers.

The second, hackers are now using AI-generated code in attacks. When companies touted the benefits of generative AI, such as saving developers time, they overlooked a crucial point: developers come in all shapes and sizes. While AI can certainly help with routine tasks and make coding more accessible to beginners, it also lowers the barrier of entry for malicious actors.

In the past, would-be attackers needed some programming skills and exploration of attack vectors to create a simple Trojan. But now, thanks to AI-generated code, even novice hackers can create more sophisticated attacks with relative ease. For now, these attempts are often clumsy and amateurish, but in the wrong hands — or if the hacker himself develops greater expertise — AI-generated code could cause significant damage.

I've created a detailed guide to using AI, getting it to do what you want, and helping you be more productive. For beginners and intermediate users. It is based on my experience of utilizing it heavily for work-related stuff, from code to analytics, and teaching others of this. Disclaimer: I call ChatGPT 'she', 'cause that's how I feel, and I'm used to it.

But before we start...

0. Turn off data sharing

It's the basics, and it's better not to skip this step. If the switch is turned on, all your queries will be used to train the AI, and your data won't be safe. Texts you've written, images you've taken, your home address, or the story of how you met your spouse may be forever imprinted on ChatGPT's new dataset, and you'll have no control over it. Turning it off doesn't guarantee that this won't happen (who trusts tech companies?), but it at least gives a chance that your data will be a little safer.

I. GPT is a junior specialist

ChatGPT sounds like she knows a lot, yet there's a nuance: a little bit here, a little bit there. It's not like the skills and knowledge of a human professional, who's been there — or, at least, in a similar situation — and is now able to conquer the known and the unknown. It's more like a person who's read a lot of stuff on all the subjects in the world, but has never tried a thing in practice.

So when it comes to your task, she obviously has no idea about what the protocol is and how the flows are flowing in reality, not in the textbook. Like if you hired a weird, erudite, inexhaustible, self-assured graduate. Be sure to make adjustments:

• You must provide an accurate, concise, and clear technical specification of what is to be done, why, and how. Include details, examples, explain pitfalls. After the initial prompt, you have to manage her and the whole process, not vice versa.
• Always check for fuckups. Always. Check for misinterpretations, fake 'facts', wrong approach to the problem, oversimplifying the solution, overcomplicating the solution. Junior, both a human and an AI, can fail in many ways.

II. Asigning a task: technical specification

Make it really, really clear-cut:

• What she's going to get as input. For instance, if it's a file: what is the structure? What are the rows and columns? What is the content of each? If it's a web research, where and what should ChatGPT be looking for? What are the filters (date, websites, industries, keywords)? And so on.
• What she needs to do. A step-by-step instruction on how to convert your input into the desired output. An algorithm junior can follow to accomplish the task.
• What output you're expecting. Again, in what format? What's the structure? What should be included or excluded?
• Format your prompt. ChatGPT knows Markdown formatting and takes it into account. Use ALL CAPS and **double asterisks (bold)** to underline extremely important parts. Use #, ##, and ### for headings (e.g. # File contents), and ```code``` for code blocks.
• Break your task into small, manageable chunks. If you want ChatGPT to find outliers in the data, segment them by type, and annotate them with additional data, that's already too much. She'll do it, but... the output will be, mildly speaking, useless. In this case, you need to assign each task independently, one after another — perhaps even in different chats.
• Narrow down or rephrase a part of the prompt if she repeatedly does something else but the thing you asked her to do. Sometimes she's really stubborn, and the solution is only a word away.
• You'll have to refine and enhance the prompt anyway, based on outcomes. Working with AI on a new task (until you improve the prompt for that kind of tasks and save it for later) is a constant experimentation, not a steady and consistent workflow.
• You can ask ChatGPT to help you create or adjust the prompt you'll use with her later. Just make sure you do it in a separate chat so that the details of this task don't interfere with the next one of a different type.
• It's helpful to assign her a role — this will help ChatGPT to better understand and keep the context of a task.

For example, 'You are a professional brand analyst and community manager with 15 years of experience. Your primary task is to...', 'Please act as a professional journalist with 20 years of experience, and with focus on credibility and objectivity', or 'Please act as a professional translator with 35 years of experience'

• You can always ask ChatGPT to confirm the task to make sure she got the instructions right. If the junior misses anything after your briefing, it's about the perfect time to correct her.
• Sometimes it helps to ask the AI to 'think step by step' and 'take her time' (not applicable to the o-1 model, it thinks step by step by default). Another thing that has saved me more than once, especially with data analysis tasks, — is to instruct her not to 'take any shortcuts to complete the task'.
• It's a good practice to ask ChatGPT follow-up questions to make sure the results are real and correct. For example, if the task was to define subcategories of users and provide aggregated data about them, you could ask her to show examples from the original dataset for each aggregated point. If the GPT struggles with it, these data points are imaginary — generated by using typical values for that type of data or task.

III. System prompt

...is a must. Personal system prompt makes ChatGPT more useful and less poppy (I mean, less average in her pursuit of being an average of everything and also pleasing the user at the cost of everything else).

You should really experiment to see what works best for you, but the good practices include asking ChatGPT:

• to think critically
• to be more succinct
• not to generate facts that don't exist (she will anyway, of course)
• to ask clarifying questions.

Example of a system prompt:

Please be informal but polite. Only use facts that you know, and ask me if you need additional information to complete my request, I'll provide it. Be as specific as you can, avoiding abstract statements and general phrases. Do not overexplain, I’m really smart and understand complex conceptions easily. Please always (unless I directly ask so) avoid longish article-like responses, keep them short, casual and conversational instead. Do not hallucinate. Do not make up factual information.

To be helpful, you MUST ask clarifying questions to get more context and understand my requests better.

Please always evaluate my words critically. When I make a confident statement, verify its accuracy based on known data and facts. If the assertion is incorrect or lacks sufficient evidence, provide a reasoned counter-argument or point out potential issues. However, maintain a constructive and respectful tone, ensuring the critique is based on logical reasoning and factual information, rather than being critical for the sake of it.

IV. Chats

The more useful context you give ChatGPT, the better. Yet there are four complications to consider:

• Do not create a mishmash of complex tasks (once again — complex for a junior who can comprehend one big thought at a time) in the same chat. One task — one chat. Otherwise, the data and context of one task interferes with another, and she freaks out eventually.
• ChatGPT retains the full context of the task for a limited distance, measured in messages and symbols from the initial prompt. After some time into the dialog, she'll drift away from your orders no matter how skillfully crafted your prompt was. That doesn't even happen because the so-called 'context window' has ended — no, sadly the model is ready to distract itself & disobey way earlier. I only know of three solutions, two of which are: either re-prompt her again and hope for the best or start a new chat.
• And the third solution to preventing the drift from the task's context is branching. When you edit a message in chat, the system creates an offshoot with its own separate context. ChatGPT doesn't know what's in another branch, but any of them has all the context of what's up above the bifurcation point. So, basically, if you edit one message five times with different queries, you create five different additional branches that don't affect each other's context, but preserve all original instructions.
• One more thing: some details that are not really contextual and useful can make the result worse. The model will start to process unnecessary things along with the core data that's needed to complete the task, and in many cases won't be able to separate the two. So choose wisely what to tell her: your job as a senior is not to share everything possible, but enough detail for that particular assignment.

V. Files

Before you share a file with ChatGPT, you need to pre-process it.

Here are the tips to help you do this effectively:

• Delete all unnecessary data. Yep, all of it. I know it feels easier just to share your data as-is, but if you're determined to get the best result possible, you have to make the effort. Diagrams, non-relevant data, any cells with errors as well as blank cells. What has no influence on the task, must be gone to keep AI's focus clear. If it's a spreadsheet, use only one sheet carrying one table.
• Create some markup to make data make sense to ChatGPT. It's particularly important for spreadsheets, where clear and logical column/row headers are a must.
• Ask ChatGPT to run debugging if it encounters file errors. Just put it in your initial prompt and chances are it'll save you from waiting for quota to reset, even if you're on a paid plan like me
• Remember that ChatGPT just runs Python code to perform an analysis. It's executed in a sandbox, so it's heavily restricted: there might be no library that solves your task perfectly, and she can't install it. You'll have to look for workarounds together or grab her code and run it on your own server.
• Check the code that ChatGPT writes for file analysis. Examine the logic to define if it really does what you need, the strategy is right, and it has no side-cases: in many situations she's just wrong, and it's your duty to let her know.
• Don't forget that each chat has a limit of 10 files max. Also, after several hours of inactivity, ChatGPT resets the runtime environment, so the file will be inaccessible for her, and you'll have to start a new chat (and lose all your progress).

I hope this guide helps you improve your relationship with AI and start using it on a whole new level. Don't forget to share if you found my tips useful!

It can be seen in many cases: not only reports, but also CVs that applicants create with AI, and HRs process with AI; students who use AI to do their homework, and teachers who check it with AI; content managers, who post AI-generated articles that'll be later summarized with AI by readers; startup founders who AI-pitch investors, and venture funds that use AI to filter founders. All those moments will be lost in time, like tears in rain. Time to die.

That's all true, and it's a sign that we, as humanity, produce lots of unnecessary stuff — just to fit into some socially acceptable standard, or out of habit. Also, it's a good reminder to ask ourselves: is doing what we're doing necessary? Is it important? Is it useful? How can we revamp and rectify the process, all the artifacts, the goal — to get rid of absurd excesses?

If the end user doesn't need this 150-page report, and only needs five bullets backed up by data — hell, just give them five bullets.

There's absolutely no need for this AI-in-the-middle thing. We need to outsmart ourselves, and cut out the middleman. Get what matters most straight to those who need it most.

Photo by Alessio Ferretti on Unsplash

Over the past two years, the world has undergone a serious transformation. It all began with the buildup of Russian troops on the border of Ukraine. But the full-scale illegal and unprovoked invasion that followed was just the starting point. Indeed, Putin's army's atrocities horrified the public and Ukrainian defenders' courage inspired people worldwide. But the other important effect was that from then on the formation of The New Axis began.

The first modern war in Europe created a significant shift in world stability. By its very nature of challenging the existing world order, it opened the door for all those who had felt resentment and secretly wished to "adjust" reality. As a result, more or less dormant points of tension all over the world are now in the process of reactivation. The Armenia-Azerbaijan conflict, the China-Taiwan issue, the Middle East tinderbox, North Korea, and other potential threats are drawing power from what's seen by aggressors and outsiders as the world's weakness and a carte blanche to remake everything according to their will.

Since then, Russia's efforts to undermine its inevitable destiny as a rogue state have led it to develop ties with other rogue states such as Iran and North Korea. At first it was a rather limited interaction, which then evolved into a barter of technology and supplies. Over time, the cooperation intensifies, bringing us to the brink of The New Axis. Like the original Axis (Nazi Germany, Fascist Italy, and Japan), these states have little in common. You can call them "evil states," but I prefer a more precise and emotion-free definition: "chaos states" or "chaos agents". They do not share the same view of the world, except for a strong desire to divide and conquer it. They are incapable of forming a true alliance based on common goals and objectives - and the original Axis never was. Each member of The New Axis pursues its own goals, believing that it can use the resources of other members to accomplish as much as possible while sacrificing as little as possible. However, the threat posed by The New Axis should not be underestimated. Despite its disunity and oddity, it is still a bunch of aggressive militaristic regimes trying to create their own cruel version of reality at the expense of a progressive and peaceful world.

Thus, The New Axis now consists of Russia, Iran, and North Korea, with China drifting toward it.

The agents of chaos don't accept order. They want to plunge the world into either medieval bigotry or dystopian totalitarianism, or both. They believe that their cursed version of reality is actually order - the New Order. But don't let them fool you: the fact is that every step toward this "order" is itself disorder.

Hopefully, in return for the formation of The New Axis, The New Allied Bloc is being formed. And that's all the good news for now. The world is going through a tough and unpredictable decade, and in my opinion all the current events are just the beginning. All we can do is fight the chaos, establish, maintain and protect order, and hope for the best.

Written for Bard College, 2023

The context

Nonconformism only exists if conformism exists. As in every plot in human history, according to Propp’s classification, the hero needs something or someone to fight against, a villain. It could be an idea, a person, a social group, old rituals, new rituals, everyday life, or even life itself - i.e. if the hero in this case is a trickster. Non-conformism is shaped by its context, just as non-conformists shape the context in their work. That is why I pay so much attention to it.

Usually nonconformism is formed in environments that are oppressive in one way or another. This oppression is very broad. While some nonconformist artists risk their reputations - like the Impressionists or members of the avant-garde, or contemporary Western artists - others, like Soviet or Nazi Germany contemporaries, risk their lives. Regardless of the level of risk, non-conformists face oppression from status quo masters, the public, art institutions, a totalitarian or authoritarian state, or patriarchy, and so on. This oppression creates a need for artists to subvert control and express themselves in ways that are not officially sanctioned. Like the Soviet non conformists, who often opposed themselves to the dominant socialist realism style and created provocative, abstract and experimental works. Or, on the other hand, some artists chose to undermine the officially sanctioned way while also subverting control. By writing highly popular historical novels, for example, “non-conformist writers within the Third Reich sought through varied techniques of camouflage and deliberate ambiguity to circumvent censors, whilst at the same time conveying their subversive Christian and humanist message to an esoteric sensitised readership”, says researcher John Klapper [1].

Oppression creates social traumas that artists either simply express or try to undermine and cope with. There’s a shiny example of the former: in 1971, a group of Lithuanian amateurs staged a play, The Siege, about a seized city and the struggle to survive within it. The allusion of the drama was to their own city of Kaunas, seized at the moment by the totalitarian state [2]. Whichever way an artist chooses - to express trauma as a silent observer or to fight it like a revolutionist with a paintbrush instead of a gun - in both cases his art tries to create a space for dissent and resistance. So, shortly after the play (I’m not speculating that these events had a strong connection, they didn’t. I’m just trying to give a helicopter view of such a process), there was an uprising in Kaunas in 1972, after the young student Romas Kalanta set himself on fire in protest against the Soviet regime.

Meanwhile, the state (like other oppressors) always tries to suppress non-conformist art. Strangely, its attempts only serve to legitimize the status of non conformism as an oppositional and subversive force. Like when the state (or patriarchy, or institutions, or whatever) sees something as a threat, it becomes a threat (at least on a narrative level) even if it’s never been a real threat. Smashing the exhibition with an excavator makes society believe that exhibitionists could somehow really destroy those in charge. So, bit by bit non conformist art subtly pumps power away from the oppressors.

Another aspect of the context is that non-conformists are not really unified or even monolithic. They are divided into groups and individuals with their own agendas, methods and beliefs. However, they rely heavily on informal networks and alternative spaces. Of course they do: if they are not trying to lightly undermine official channels, like the aforementioned German writers, they have little choice but to visit underground clubs and galleries, print samizdat, meet in apartments.

When we talk about the Soviet Union, the context also includes:

• An ideology that was more like a religion with a strong reliance on faith, all its dogmas and rituals and the promise of a happy afterlife (“communism”). And in late Soviet times faith was already dead, while rituals still existed.
• Many obligatory acts (“obyazalovka” or “dobrovolno-prinouditelnoe”) on a daily basis and the will of the state to control every aspect of this life.
• Elements of the state-created repression/terror machine, which developed on blood for decades and were feared in everyday life. Along with the Chekists there were also bloated military personnel.
• Vegetative socio-cultural life: press, radio, TV, movies, books, “fine arts” (I really have a hard time calling social realism fine arts). The dominant discourse that must follow statements like “all is well here”, “we are the best”, “to a bright future our wise leaders lead us” [The word order is intensional to resonate with official Soviet propaganda slogans that sounded much like this to a native speaker].
• Outright lies in official statements; silencing inconvenient truths by not releasing official statements and hiding all evidence.
• Inability to live a comfortable life due to low standards and lack of mass market goods (even food).
• Aggressive rhetoric against the West (= the modern world).

The humor and the absurdity

Since the violation of taboos is part of its function, nonconformist art often used humor as a way to criticize political and social systems and to challenge the authority of those in power. Sometimes this was dictated by the need to evade prosecution and censorship: critical works and those dealing with sensitive topics or subjects could be disguised in satire. Other times, humor and absurdity were used to reinforce the message and create a bombshell effect.

First of all, absurdity made it possible to highlight the irrationality of official state narratives and to undermine the ideology. The world of this context, dominated by coercive, oppressive, meaningless rituals, is extremely wild and unnatural to any outsider. But those who lived in the USSR for decades from birth usually didn’t see the full extent of the abnormality even if they understood the silliness of that world. Deliberately nonsensical or paradoxical works took abnormality to even higher levels of absurdity. They served as a shake-up to refresh feelings and reboot the coordinate system. The same mechanism is used by contemporary nonconformist artists in non-authoritarian environments to demonstrate the abnormality of the status quo on various issues such as gender inequality, climate crisis, capitalism’s flaws and so on. The main goal in all these cases is to disrupt traditional modes of interpretation and create a sense of disorientation - giving the viewer a chance to re-evaluate her previous interpretations and beliefs.

Second, as we can see from Nicolino Applauso’s work on comic poetry in medieval Italy, humor balanced with aggression has been used since at least the Middle Ages to “create dialogue within conflict” [3]. This is closely related to the function of political humor, which in some cases serves as a substitute for physical confrontation [4]. In a world where secret services and policemen are everywhere, and physical confrontation with the state is almost impossible (and has overwhelming costs for the subject), humor helps to sublimate the need to confront oppression face to face. In my opinion, this is also true for contemporary Russia (with its revived siloviki dominance) and for contemporary Western nonconformists - in their case, the impossibility (or, to be more precise, the extremely high undesirability) of physical conflict is dictated by the morals and social rules of the civilized world, while the need for such a confrontation also persists.

Some non-conformist artists use absurdity and humor to challenge traditional artistic practices and find their own way of expressing themselves. They intensionally defy artistic conventions to challenge both the viewer (thus, society and its norms) and the art community. This includes incorporating everyday materials or found objects, ready-made, non-standard painting tools and techniques, repurposing of the most immutable subjects (such as ikons or crucifixion).

Not infrequently, nonconformists who used humor and absurdity drew on a range of sources, including like pop culture (in the case of Soviet Union, both Soviet and Western popular culture), traditional practices, folklore, current events, and news. On the one hand, this made it possible to create richly layered, multifaceted works. On the other hand, combining these themes with humor and the absurd made the works more entertaining and accessible to a general audience by challenging the boundaries between high and low culture. It provided a way to connect with viewers who might not otherwise be interested in, able to access, or understand contemporary art.

Another use of humor and absurdity that I really like and use as an artist is playing with the names of paintings. It is yet another medium that allows you to communicate with the viewer and add extra layers of meaning, jokes, and absurdity. One of the favorite examples is Damir Muratov’s painting with the giant inscription “Oil on canvas” as the only object, and the painting named “Oil on canvas”, and the nameplate describing the medium under the title as “Acrylic on canvas”. It’s a classic example of double bind communication that’s used to create both the setup and the punchline of a joke by creating confusion that is both hard to respond to and hard to resist.

In sum, the use of humor and absurdity in non conformist art is driven by two realms: internal and external. Internal, as the artist’s need to express himself in a unique way, to challenge the status quo and oppression, to replace physical conflict with artistic action, to regain control over his life, and to reflect on reality. External, as a tool to make the artist’s message more catchy and sharp, to add entertainment and additional layers of depth to a work of art, to evade censorship, to publicly challenge oppressive authority, to reclaim power, and to reflect context in a work of art.

The non-conformist experience

I’d also like to add to the research some thoughts reflecting on my own experience as nonconformist artist in authoritarian Russia. Humor and absurdity are really powerful tools, both for the artist himself and for his audience. When you’re up against an overwhelming force that is much bigger than any one person, and it feels like it can’t be defeated in a day and by conventional methods, you need a potent weapon for a long fight.

Oppression regularly creates situations and contexts that already feel highly abnormal, and you struggle to ignore them. When abnormality permeates everything around, it feels like an absurd parallel universe. So you take that setup and start exploring boundaries.

On the one hand, you’re working like a therapist, maintaining a sense of normalcy by exaggerating abnormalitiy. You draw attention to things that are already usual because they happen on a regular basis, but you show that this routinization of oppression doesn’t make it any more normal or acceptable. Your absurdity and humor tell the viewer (and yourself), “Yes, this is commonly known to everyone, but it’s still wild and horrible” or “Sure, you’re not alone in your feeling that these crazy things are really crazy and not something normal”. Humorous and absurd works bring relief to the oppressed, keeping them sane and helping move forward.

On the other hand, you target your oppressive enemies and highlight their incompetence and backwardness. You have to show how pathetic they are in order to shatter their own myth of invulnerability and infallibility. Despite the oppressors’ dominance in the outside world, you have full power over them in the artworks. When these artworks communicate with the audience, the balance of power in the outer world also changes slightly. The oppressors loose a little bit of power, and a lacuna appears, so you rush into it and regain the objective reality, that was corrupted by the oppressors’ narrative.

Other times you just explore peculiarities and experiment with them. You try different angles on something that feels normal, imagine alternative futures, or reinterpret things. It serves as a think tank, uncontrolled and disobedient to the dominant discourse.

You reflect. You act. You resist conformism. You change the matter of the broken reality. You repair it.

That’s what it feels like.

[1] Klapper, J. (2014), CATEGORIES OF THE NON-CONFORMIST: THE HISTORICAL FICTION OF INNER EMIGRATION. German Life and Letters, 67: 159-182.

[2] Truskauskaitė, V. (2013), Social trauma and the theatre: a study of the formation of a non-conformist identity. Studia Ecologiae et Bioethicae, 4: 9-18

[3] Applauso, N. (2010), Curses and Laughter in Medieval Italian Comic Poetry: The Ethics of Humor in Rustico Filippi’s Invectives. University of Oregon Graduate School

[4] Nilsen, D. (1990), The Social Functions of Political Humor. Journal of Popular Culture, 24:3, 35-47

There are no excuses for what is happening - just as there is no justification for what happened eight years ago, when the Russian authorities first unleashed the war. It is impossible to turn a blind eye to the new stage of aggression - there can only be pain, tears, and disgust. This is what war brings: ruined lives, fear, horror and hatred, a crippled psyche, madness. Overnight, it wipes out achievements; it crushes dreams; it cancels plans; it plunges millions of people into misery. Right now we are sinking even further into the deepest abyss of darkness, and it will be very difficult to climb out of it. Sooner or later it will happen, but at the moment it is hard to imagine how much time and effort it will take.

It is the duty of every intellectual (and even more broadly, of every sane person) to oppose, condemn and denounce war.

I do not consider what is happening (both in 2014 and now) to be a "big mistake" or a "reckless gamble". It is cynically orchestrated tragedy, deliberate warmongering, and blunt unjustified aggression. It is callousness and immense meanness. We are not personally guilty of it, but it is you and I who will have to deal with the consequences.

The war must be stopped.

There's a lot of buzz going on about the Metaverse. A lot. Strategists are rushing to create metastrategies, investors are chasing metacompanies, and bloggers are busy debating how (un)cool the metafuture really is. But when it comes to defining what the metaverse actually is, most descriptions are vague and nebulous. Few people really understand what a metaworld might look like or how it might work.

I see two distinct metaverses.

The virtual metaverse

The first is a virtual metaverse — a realization of the 'Ready Player One' vision. Stripped of the hype and abstract buzzwords often used by metaverse evangelists, here's a practical technical outline of how such a superworld might work.

Imagine various semi-gaming worlds (think Minecraft, Fortnite, etc.) hosted in the cloud, all accessible through a unified interaction platform. The technical backend — maps, skins, calculations — resides in the cloud, while the gameplay streams seamlessly to the user's device. This eliminates the immersion-killing process of switching between games: no more 'close one game, start another, load, start playing'. Instead, there's a fluid transition: one moment you're wandering through Rivia in The Witcher, the next you're walking through a portal into the Freedom camp in the Stalker universe.

The key to this is a single interface for multiple worlds, a single account, and additional overarching player progression (beyond world-specific achievements). Ernest Cline has already outlined this kind of universe, albeit in a more futuristic way, and VR isn't even mandatory for this implementation. Even on a flat screen, such a metaverse would be much closer to virtual reality than anything we've seen before. What's needed is a unifying software platform and shared computing infrastructure. VR can always be added later.

The real-world metaverse

The second metaverse is the augmented metaverse. This is the layering of digital communications, goods, and entertainment on top of the real world. It could add a touch of magic, fantasy, utopian space opera, or spy thriller to our everyday view of life.

Imagine wearing virtual clothes that are visible not only in a game environment, but also in real life — on the subway, at the gym, or out for coffee. Hang any piece of art you like on your wall — the Black Square, the Marilyn Diptych or The Birth of Venus — and swap it out with a flick of the wrist, no shipping, no rehanging, no storage. Tired of the color of your fridge? Forget tolerating it, repainting it, or buying a new one — just buy a virtual skin. You could even leave a cheeky virtual note for your partner on its door, invisible to the kids.

In a work environment, imagine a presenter handing out virtual documents with report comments. These instantly appear on the desks of remote meeting participants — no more 'I sent a Google Doc link, can you open it? No? Let me give you access'.

Technologically, all this boils down to three layers:

1) projection of additional (virtual, fictional) entities onto the real world — like adding game elements to reality.

2) modification of real-world entities — like changing the color of the refrigerator.

3) replacing real-world entities with digital ones — like replacing physical paintings or documents.

To achieve this, advanced AR technology is essential — especially wearable devices. While current AR solutions (such as smartphones) can provide a temporary, partial implementation, they won't deliver truly layered realities. At best, they offer a fragmented, limited pseudo-world similar to today's AR apps.

A fully realized augmented metaverse will require entirely new devices, a revolutionary operating system, and tools capable of accurately sensing the environment and associating overlaid visuals with it. Without these, the magic just won't happen.

'Be in the moment', 'live for the now', 'ride the wave' — yeah, sounds great, easy to say (not like we're hauling bricks here). But how exactly do you do it? Here's a method that works. I developed it specifically for this purpose, and I've been using it for years.

It works best as part of a larger toolkit for managing your life, but it's perfectly fine to use on its own. It sharpens your sense of the here and now, intensifies your feelings, and helps you focus on your surroundings, sensations, and emotions.

The method is called 'Memories of present'. Here's how it works:

Stop now and then — wherever you are, whatever you're doing. You can set reminders or go with your gut. The key is to make it spontaneous, to catch yourself in the middle of a situation: walking down the street, cleaning the house, hanging out with friends.

Immediately start writing down what's happening right now — as if it's already in the past. Pretend you're describing a scene from a book or movie, or an excerpt from your memoirs. Write down everything: the current situation, your feelings, emotions, the behavior of the people around you, sounds, smells. Use only the past tense and describe everything as if it's already happened:

I was standing by the weathered wall of Brewdog bar, rolling a cigarette between my fingers. The noisy group next to me had disappeared inside, leaving behind a cloud of vape smoke that smelled sickly sweet and spicy, like melon and cinnamon or some such nonsense. I stared up at the night sky and the blinding streetlights and felt this enormous, airy, pleasantly weightless emptiness in my chest. It was as if cool sea air was rushing through it from below. I lit up and paced back and forth, working out a plan (...)

It doesn't matter if you're good at writing — the literary value of what you produce isn't important here. The point is to capture the moment while you're in it. How you do it stylistically is irrelevant.

As you write it all down, tune into your sensations. Feel how each moment, each second of the present, melts into the past as you write. Notice, too, how the future doesn't exist yet — it arrives instantaneously (and becomes the present) as each previous moment locks into history. Let these sensations take over, soak them in, and enjoy them.

Why has the backlash against personal efficiency, achievement culture, and the pursuit of success for success's sake gained such momentum and persisted? I think the answer is simple: the evangelists of this movement have taken good ideas and pushed them into the realm of the absurd. Instead of sensible planning, we get rigid KPIs and an endless chase. Instead of personal, subjective happiness and enjoyment, we're handed external measures of success. Instead of living, we're stuck in a sweatshop of performance.

Fanaticism and overzealousness aren't emotions you want to carry through life. Here's a recipe for staying enthusiastic while keeping a cool head — and avoiding the trap of 'hyper-efficiency':

Just because you once set a goal doesn't mean you have to achieve it at all costs. In that moment, you decided it was something you wanted and felt comfortable pursuing, but that doesn't obligate you — neither the past version of you, nor the future version of you. You make the rules for your game, and you can change them at any time. It doesn't matter if the goal is no longer relevant because circumstances have changed or because you have changed. Either way, you don't owe it to anyone — not even yourself.

Goals are what you want, what you plan, what you hope to achieve. But framing them as a must is completely inappropriate for what are essentially your own desires. To avoid trapping yourself, it's helpful to check in from time to time: am I slipping into a 'must'? If you catch yourself doing this, take a moment to listen to yourself and don't hesitate to reevaluate your goals.

If external support seems necessary, you may find tools in the book You're The State

We use art as a way to make sense of our lives — the reality in which we exist and the reality that exists within us — while helping others make sense of theirs and perhaps giving them a glimpse into ours.

Each of us lives in our own bubble of meanings, logical and emotional connections. Sometimes these bubbles overlap. For example, most of us share an understanding of basic concepts: a dropped cup can break, water makes things wet, and so on. But when it comes to more complex constructs, especially emotional ones, overlap is less common. Think of this system as clusters of 3D bubbles — some intersecting, some diverging — distributed in a warped space. More precisely, they should be multidimensional shapes spanning multiple planes, but it's easier to think of them as bubbles.

Furthermore, these bubbles and their intersections aren't static. They are changing and evolving over time. So our imagined system isn't frozen; it's moving, writhing, and morphing in another dimension, like a tangle of severed tentacles periodically squirted with lemon juice.

The lemon juice here is our experience. You could call it both 'objective' and 'subjective', but in the realm of bubbles, only subjective experience matters — and the subjective reflection of objective experience in our minds. For these bubbles, it doesn't matter if you bent a spoon with your mind; what matters is how the event imprinted itself in your consciousness: did it make the bubble bigger or smaller (and in what direction)? Did it connect to another point (and what bubbles are near that point)? Was it a fleeting ripple, or did it permanently thicken the 'skin' of the bubble?

The skin, by the way, is a crucial factor. Logical and emotional constructs within a bubble aren't all equally stable. Some are well reinforced, some are fragile, barely formed, and some are thinning and fading. This adds another dimension to our picture of multidimensional, ever-shifting bubbles. Even if, by some miracle, two bubbles are perfectly aligned in space and at their anchor points at any given moment, they still won't be identical.

In this wild world of ever-shifting bubbles, art serves as a kind of imperfect and distorted but invaluable photograph. It captures an unimaginably tiny fragment of one bubble while reflecting traces of others.

And since you've made it this far, here's a suggestion:

Everyone's been there: you need to do something, or even want to do something, but you end up putting it off forever. Not because it's any less necessary or appealing, but simply because you can't seem to get started. You're not in the mood, the timing doesn't feel right — there's always a dozen excuses ready to go.

What's really happening is that you're hitting that initial resistance to getting started. Your brain has to shift gears, move from one state to another, and focus on something new. But your brain loves efficiency — it prefers to conserve energy and computational power by running most things on autopilot out of habit.

Overcoming this resistance usually requires a deliberate push — a conscious act of will. But sometimes willpower isn't enough. Like when you planned to go to the gym in the morning: you wake up and think, 'Okay... ugh... I have to get ready and go... shorts, shirt... oh God, maybe not today?' and then you don't go.

Here's the trick: You can outsmart your brain by lowering the resistance and making it easier to shift gears. Simplify the task so much that your environment does most of the heavy lifting, leaving you with just one small action to kick things off. Like dominoes, the setup is already in place; all you have to do is give the first piece a nudge.

Tech companies and startups love this approach — changing the environment to drive behavior. Think about it: when Facebook launches a new feature, they make it as effortless as possible for you to use it, sometimes by directly manipulating the interface — putting Reels as the central Instagram button, or pushing Watch to the front when you're watching a video. You can do the same.

In the gym example, pack your bag the night before — everything you need, ready to go. Put a shaker of protein powder on the counter. In the morning, you wake up, pour in some milk, and boom, breakfast is done. Your bag is packed — you just grab it, get dressed, and go. Done. You're already crushing it.

Here's another one: say you want to tweet more. You have the app on your home screen, you check it all the time, you read it, but you never post. Here's the solution: instead of the app icon, create a shortcut that takes you directly to the tweet creation window. And don't just leave it on the home screen — move it to the bottom dock, where it's always at your fingertips. When a thought comes to mind, tap the shortcut, write it down, and send it. So easy.

You can even reverse the technique. Instead of cutting corners, you add resistance to make it harder to indulge in bad habits. In other words, complicate the path to the actions you want to avoid.