Wow, this is massive and unbelievable. 50 subscribers. i’m super thankful to all of you, seriously. it feels like i’m just getting started, and there’s more fun on the way. btw, those video clips you see on my feed every day? yes, they were edited by my junior (i paid him) so if you haven’t subscribed yet, please do. it helps support both the account and the effort behind each video. love and keep supporting.

the EU is absolutely cooked in AI the issue isn't public sentiment — in fact, most people are open to AI the bottleneck is policy: no clear plan to move forward, which is tied to arrogance and incompetence by contrast, the US invests heavily in its tech giants and moves faster, and remains the world's technology leader

sam altman, in his recent blog post: - AI will be able to make small scientific discoveries in 2026, and is expected to make major discoveries from 2028 onward based on our research - soon, AI will handle tasks that currently take days or weeks - cost per "unit of intelligence" has been dropping roughly 40x per year and is expected to keep falling fast

Microsoft AI CEO, Mustafa Suleyman: We can already imagine a time, just a few years ahead, when AI systems are trained on gigawatt-scale compute runs that are capable of self-improvement, setting goals, managing resources, and writing their own evals

is the recent "gemini-3-pro-preview-11-2025" leak fake? not sure what Logan meant, but Gemini 3 itself isn't fake; i think "this is fake" was about availability, not the model this is also the downside of vague hypeposting by some accounts, so it should stop until the official launch

we've already seen many researchers report that AI can generate novel hypotheses that suggests systems capable of real discoveries aren't far off but the real test will be when the wider public uses them and gets results sadly, most people may lack the background to benefit, but many researchers will adopt them quickly

another solid breakthrough from Google... they're introducing nested learning: "a new ML paradigm for continual learning" 'Hope' is a self-updating, long-context memory architecture that generalizes 'Titans' beyond two update levels, allowing continual learning without forgetting too early to say, but it seems a real step toward fixing the memory problem

the mysterious model on OpenRouter named "polaris alpha" is likely from OpenAI they're following a similar pattern to the GPT-4.1 summer pre-release called "quasar alpha" it's probably a non-reasoning model with a large context window but more leaks include: GPT-5.1 reasoning GPT-5.1 pro

Transformers still manage key parts needed for human-level AI such as language, pattern recognition, and basic functional abstraction but we still need strong capabilities in: - physics - causality - modeling - long-term memory - continuous learning - true symbolic reasoning

Elon Musk says, Neuralink could capture an approximate snapshot of a person's mind and upload it to an Optimus (robot) body It's not immediate, but it's possible and probably within 20 years

jensen huang is right china will likely win the AI race. they're releasing open-source models to weaken U.S. funding, while catching up in compute and next-gen models they already dominate in robotics and if AI levels out, they'll win through hardware strength

we need a full list of OpenAI projects and partners to know their investment and compute scale some call it hype, but no company takes such risks without confidence OpenAI seems sure it can build transformative AI, with 2026 crucial for the "AI research intern" if no breakthrough comes next year, doubt would be fair

robotics was once said to lag 2-3 years behind AI due to hardware and sensor limitations but the gap has narrowed fast. today's robots can walk, run, handle complex objects, and perform complex tasks that were limited to labs what's missing now is the "brain" a general AI capable of understanding goals, making decisions, and adapting on its own