Asimov walks through how they designed the legs for their humanoid robot v1.

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🗣Ex-Google executive Mo Gawdat defines Intelligence.

"If we accept that intelligence itself is not a physical property, then it does not matter whether that intelligence is produced on carbon-based computer structures like humans, silicon-based computer structures like today’s hardware running AI, or quantum-based computer structures in the future.

Intelligence is produced within machines when we stop imposing our own intelligence on them."

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Andrew Ng criticizes advice to stop learning coding

Andrew Ng has called recent advice to stop learning coding—due to AI automation—some of the “worst career advice ever.” He argues that when technology makes tasks easier, demand for those skills rises, not falls. Historically, advances like the move from punch cards to keyboards, or from assembly language to higher-level languages, increased the number of programmers and expanded the software market.

Ng warns that while AI changes the field, those most affected are coders who fail to adapt, not those who continue to learn. Senior engineers who master both system architecture and AI are valued more than ever. Junior developer job postings have dropped by 40% since 2022, and new graduates face higher unemployment than the national average.

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📈 AI is increasingly driving market profitability:

The S&P 500's net profit margin excluding financials is up to a record 15%. At the same time, the S&P 500's net margin excluding the Magnificent 7 and tech is down to 8%, near the lowest since the 2020 pandemic.

This marks a 7 percentage point gap between tech and non-tech sectors, the widest on record. This comes as margins for companies outside of tech have been trending down since 2022. Meanwhile, Magnificent 7 and tech firms have seen a rapid increase in margins over the last several quarters.

AI is all that matters right now.

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🗣Elon Musk: “For the next few years america is likely to win the race in AI. Then it will be a function of who controls the AI chip fabrication. If more of the factories are owned by China then China will win.”

“Right now all the chip fabs are in Taiwan. 100%.”

“If China invades Taiwan in the near term the world will be cut off from advanced AI chips.”

“I think it’s essential for national security that we begin manufacturing our own chips in the US.”

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China has introduced a registration system assigning 29-character identification codes to all humanoid robots. Over 28,000 robots have already received these unique codes.

Each identifier works as a digital passport, containing information about the robot’s country of origin, manufacturer, model, and serial number.

This initiative is intended to improve traceability as humanoid robots begin to take on public roles in factories, homes, services, and on roads. The system aims to ensure accountability in cases of technical failure, property damage, data leaks, modifications, or resale of the machines.

With this system, regulators and stakeholders can link a robot with its manufacturer, seller, operator, service records, and recycling status.

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Opus 4.8 model release introduced

Opus 4.8 is now available, featuring notable improvements in agentic coding performance. The update brings a new Fast mode, offering the same model but at approximately 2.5 times the previous speed and at a cost reduced to one-third of the original.

The new version builds on Opus 4.7, providing enhanced judgment, improved self-assessment regarding progress, and the capability to operate independently for extended periods compared to earlier versions.

Opus 4.8 is available immediately at the same price as before.

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Bro is adding in AI women to sell his surplus heavy equipment 😂

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Mathematician reacts to OpenAI's recent proof.

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💰 Anthropic has officially raised $65 billion at a $965 billion valuation

ARR crossed $47 billion this month. Anthropic is now officially bigger than OpenAI.

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🔥 Claude can now teach you any skill in 30 days for free.


1. Professional Skill Instructor

“Act as a professional instructor and practitioner with deep real-world experience in [skill]. Teach me this skill from beginner to advanced level in 30 days. Focus on practical understanding, correct fundamentals, and real application instead of theory or academic explanations.”

2. The 30-Day Skill Roadmap

“Create a detailed 30-day learning roadmap for mastering [skill]. Break it into daily or weekly stages, explain what to learn, what to practice, and what outcome I should achieve at each stage to progress correctly.”

3. Learn-by-Doing Practice

“Teach me [skill] primarily through practical exercises and hands-on practice. Design simple tasks, drills, or mini-projects that force me to apply what I learn instead of just reading or memorizing information.”

4. Skill Application & Real-World Use

“Show me how [Insert skill] is actually used in real-world situations. Give realistic examples, scenarios, or use cases and explain how to apply the skill correctly in each case.”

5. Expert Thinking & Skill Mastery

“Explain how experts think differently when using [skill]. Teach me the mindset, decision-making approach, and problem-solving style that separates professionals from beginners.”

6. Progress Check & Skill Assessment

“Test my current understanding of [skill]. Ask relevant questions or give tasks to assess my level, then tell me clearly what I need to improve before moving forward.”

7. Final Skill Readiness

“Evaluate whether I am ready to use [skill] confidently in real-world situations. Identify any remaining gaps and give a clear next-step plan to reach full competence.”

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🚀 Elon Musk just painted a future where money becomes obsolete.

Not because of inflation. Not because governments collapse. Because AI and robots could make scarcity disappear.

Musk says an AI-powered robotics economy could become a million times larger than today’s global economy. In that world, anything you want, food, housing, medicine, even trips to Saturn could simply be available on demand.

His conclusion? “I think things will just be free in the future.” That’s not just a tech prediction. It’s a direct attack on the foundation of civilization. Money exists because resources are limited. Politics, laws, markets, even wars are built around deciding who gets what when there isn’t enough to go around.

Musk is imagining a world where there is enough. Forever. But that creates a much stranger problem. If nobody has to struggle for survival anymore… what gives life meaning?

Musk referenced the sci-fi world of Culture series by Iain M. Banks, a civilization with unlimited wealth, energy, and technology. In those stories, the biggest challenge was no longer survival.

It was purpose. Because human ambition has always been powered by the gap between what we have and what we want. That tension built empires, inventions, symphonies, startups, and space programs.

Take away scarcity, and humanity may finally face its hardest question: Who are we when we no longer need anything?

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Insane idea from Opus 4.8.

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🤯 AI may have just triggered a domino effect in pure mathematics.

A few weeks ago, researchers at OpenAI revealed that one of their internal models found a radically new construction for the famous Erdős single-distance problem, overturning what mathematicians had believed for nearly 80 years. The shocking part wasn’t just the result, it was the method.

Instead of using the standard geometric approach, the AI connected the problem to deep algebraic number theory using towers of class fields, a direction many humans had apparently overlooked. Now the ripple effects are already showing up.

A new paper on arXiv claims to disprove the famous sum-product hypothesis over the real numbers using a similar field-tower strategy: And the authors openly admit what inspired them;

“We were inspired to reconsider the possibility of disproving the hypothesis thanks to the counterexample for the single-distance problem invented at OpenAI.”

That sentence alone feels historic. The researchers also mention using GPT-5.5 Pro during the work, though they emphasize the final proof was completed independently.

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🧠 Noam Brown thinks AI could make humans dramatically better at mathematics, not by replacing mathematicians, but by changing how they think.

Commenting on the recent wave of AI-inspired mathematical breakthroughs, Brown compared the moment to the arrival of AlphaGo:

“After the emergence of AlphaGo, players' Go skills improved significantly. I suspect we will see a similar pattern in mathematics.”

And history suggests he may be right. When AlphaGo defeated Lee Sedol, the shock wasn’t just that an AI won, it was how it won.

The system played moves that initially looked irrational or even bad to elite professionals. But over time, players realized many of those moves were brilliant. Entire generations of Go strategy evolved afterward. Top players like Ke Jie reportedly changed their overall style after studying AI gameplay.

Now something similar may be happening in mathematics.

A recent paper disproving a famous sum-product hypothesis openly stated that its authors were inspired by OpenAI’s AI-generated breakthrough on the Erdős single-distance problem. The key idea involved towers of class fields, an unexpected connection between geometry and algebraic number theory that many researchers had overlooked.

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🔍 Google introduced Google AI threat defense.

A new AI-powered cybersecurity solution designed to continuously monitor for and stop AI-powered threats before they impact businesses.

The system combines Wiz, Gemini, frontier AI models, CodeMender, and autonomous security agents to prioritize risks, scan applications, identify vulnerabilities, and accelerate fixes.

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AI-driven drug discovery in China reduces screening time

China has introduced an artificial intelligence platform aimed at transforming drug discovery. The system rapidly reviews extensive chemical compound libraries and reduces initial drug screening from months or years to just seconds.

This development reflects a major shift in research timelines. Tasks that once required years can now be completed almost instantly with AI-driven tools. The platform is part of a broader trend toward increased integration of artificial intelligence in biotechnology across the late 2020s.

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Codex adds Windows computer control via ChatGPT app

Codex now enables users to manage Windows computers directly, including through the ChatGPT mobile application. This update allows for the remote initiation, monitoring, and adjustment of coding tasks on a user's PC.

The new capabilities are designed to support users working on code tasks remotely, ensuring that work on the computer continues while actions are directed from another device.

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👁️ Nvidia is spending billions to replace copper with light inside AI data centers.

In just a few months, Nvidia reportedly committed over $6.5 billion toward photonics, technology that moves data using light instead of traditional electrical signals through copper cables.

The spending spree includes:

• $2B tied to Coherent and Lumentum
• $3.2B toward Corning
• $2B linked to Marvell Technology
• Participation in a $500M round for Ayar Labs

Modern AI clusters are becoming too massive for copper wiring alone. When thousands of GPUs communicate across racks, copper starts hitting physical limits:

• higher heat
• signal degradation
• power inefficiency
• slower long-distance bandwidth scaling

Photonics solves this by sending information as light through optical links. Faster communication between GPUs means larger AI systems can act like one giant computer. This is becoming critical for next-generation AI training.

The real power move is supply chain control. By locking in huge procurement commitments now, Nvidia is effectively securing a large share of the world’s advanced optical component capacity years in advance. That means competitors may not just be fighting for GPUs anymore, they may struggle to get the networking hardware needed to connect them.

Source.

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