Tag: AI

If you’ve used current AI models, you know that they can’t reason like a human. “But so what?,” you might say, “they’ll get there eventually.” I don’t think so. Today I have a look at three major problems blocking current AI tech progress that I think are fundamentally unsolvable.

The AI industry is an unsustainable economic bubble.

Host Adam Conover asserts that Sora is a morally and financially indefensible product. He highlights its immediate societal harms, which include:

• Enabling deepfakes, bullying, and the generation of racist content.
• The unauthorized use of real and deceased public figures’ likenesses (like Martin Luther King Jr.).
• Creating a massive potential for realistic fake news and political propaganda, thereby making the internet a less reliable source of information.

Economically, the app is considered a failure, costing OpenAI an estimated over $5 to generate every single video while having no clear plan for monetization. Conover contends that this lack of profitability, alongside the failure of recent models like GPT-5 to deliver on hype, shows the models are hitting a ceiling, failing to progress toward “super intelligence.”

The video claims the broader economy is being propped up by monumental, unsustainable investments in AI infrastructure. These companies need to generate an impossible $2 trillion in annual revenue by 2030—more than the combined revenue of the six largest tech companies—which they are currently failing to meet. Sora, therefore, serves only to generate hype and attention for Sam Altman, prolonging a bubble whose eventual collapse will primarily hurt the retirement funds of ordinary Americans, not the tech investors who profit from the speculation.

DeepMind’s Veo 3 text-to-video generative AI produces incredibly realistic footage, marking a huge leap in video generation fidelity.

The AI demonstrates an advanced, inherent understanding of physics, light transport, and material properties, generating consistent reflections and specular highlights. The most surprising discovery is that many of its advanced capabilities, such as image inpainting, outpainting, and segmentation, are emergent: the AI learned them autonomously from training on vast video data, rather than being explicitly programmed. The authors call this frame-by-frame reasoning process the “chain of frames”. Despite its power, the model is not flawless and still makes logical errors or fails simple IQ tests.

The massive valuation of the AI sector is an unsustainable economic bubble, driven by speculation rather than current financial performance. A recent MIT report showed that 95% of corporate generative AI pilots are not generating a measurable impact on profits, directly contradicting the market’s euphoria.

This optimism has led to a dangerous concentration of wealth, with the “Magnificent 7” tech giants now accounting for roughly 34% of the entire S&P 500, a level that has prompted warnings from bodies like the Bank of England. Furthermore, the video suggests that the massive infrastructure spending by these companies—projected to be around $400 billion in 2025—is artificially boosting US GDP growth, masking underlying economic weaknesses like rising unemployment and persistent inflation.

The core technology itself is criticized as being unreliable with a leading AI product being “confidently wrong” multiple times.

Financially, the situation is described as precarious, with companies like OpenAI reporting huge net losses despite high revenue projections. These businesses are relying on high-risk, circular investment deals with other big tech players to sustain their growth.

The bubble will inevitably burst, leading to the “incineration” of billions of dollars, negative impacts on retirement accounts, and significant job losses.

If AI succeeds in becoming ubiquitous, it will likely lead to greater economic inequality and a job crisis with no political consensus for solutions like Universal Basic Income.

For years, we’ve heard two major narratives about AI. One predicting the end of human work, the other dismissing it as hype. The truth is more nuanced, and more hopeful. From radiology to software engineering, the pattern repeats: as technology makes tasks cheaper and faster, demand for human creativity and judgment grows. YC’s Garry Tan explores what history, economics, and real companies show us— that technology doesn’t replace people, it redefines what we can do.

Google just shocked everyone. Gemini 3 is here, and it’s unlike anything we’ve seen. Early testers found hidden features like Agent Mode and Deep Think, proving this isn’t just a model upgrade but a full leap toward autonomous AI. It can write code, draw perfect visuals, and even control browsers, making it the most advanced system Google’s ever built. And while OpenAI studies which jobs AI will replace next, Gemini 3 is already showing what that future looks like.

In this video I show you how to create insanely cool motion graphics with Google’s Nano Banana and actually bring them to life & upscale them inside OpenArt!

Michael Wolf, Activate co-founder and CEO, joins ‘Squawk Box’ to discuss the recent AI partnerships, AI’s circular spending, state of AI tech race, and more.

Silicon Valley has pivoted to supporting the military for a predictable paycheck.

OpenAI just revealed exactly how it decides what ranks #1, and it’s not what you think. After analyzing over a million conversations, OpenAI exposed how people actually use ChatGPT to research, compare, and buy. This isn’t just a shift in behavior, it’s the birth of a new kind of search. In this video, you’ll learn how to position your business to show up inside ChatGPT’s answers (and Google’s new AI Overviews), before your competitors even realize what’s happening.