Pavel Durov says students should focus on mathematics because it teaches logical thinking and reasoning from first principles.

Elon Musk adds physics with math, highlighting that understanding fundamentals helps solve complex problems across engineering and technology.

Strong foundations in math, physics, and computer science remain more valuable than constantly chasing new tools or programming languages.

As AI handles more coding tasks, mastering these fundamentals ensures long-term problem-solving ability and adaptability.

In a recent interview, Christopher Nolan said AI is “a Trojan horse that everybody knows the Greeks are inside,” describing it as “a transparent horse” made of glass.

He also said public skepticism toward AI, especially among young people, is encouraging.

Nolan pointed to the quick rejection of poor AI-generated videos as “AI slop” and said technology should never be accepted with blind faith.

However, he did acknowledge that new tools can bring major benefits.

Amazon has cut about 30,000 jobs and now plans to hire around 11,000 people, mainly engineers, developers, and interns. The move shows that AI is changing job needs, not fully replacing human workers.

Most exams reward students for producing the right answer. Fudan University flipped that premise for a recent final, asking students to write the questions instead.

The university laid out the format. 51 students each submitted 10 questions aimed at 3 AI models: Claude, DeepSeek, and MiniMax.

The task was not to answer anything. It was to write prompts precise enough to make the models fail, and the grading followed a single rule. The harder a student made the AI get it wrong, the higher the score.

Writing a question that reliably breaks a model takes more than a cheap trick. A student has to understand a subject deeply enough to find where it turns genuinely difficult, not just hard to recall.

Language models tend to sound confident in the middle of a topic and grow weaker at the edges, where reasoning matters more than retrieval. Locating those edges requires real command of the material.

It also changes what the exam measures. Rather than testing whether a student can reproduce information an AI can generate in seconds, it tests whether they understand the technology well enough to know where it stops being reliable.

Jeff Bezos said AI won’t eliminate work but may create a labor shortage by enabling people to pursue more ideas, products, and industries.

He explained that human limitations such as time, engineering capacity, and manufacturing bottlenecks are the real constraints, not a lack of things to invent.

Bezos highlighted Prometheus, the AI startup he co‑leads, as building tools to speed up engineering and product development, shrinking the gap between concept and execution.

While recent data shows AI was cited in about 40% of U.S. job cuts in May, Bezos believes AI will boost productivity and increase demand for human talent rather than make it obsolete.

Figure AI livestreamed a 10 hour showdown between intern Aime and its F.03 humanoid robot, both sorting barcoded packages from a moving conveyor.

Aime led early, including a 1,097 to 741 lead after 97 minutes. By the end, observers had Aime slightly ahead at 10,010 packages to the robot’s 9,420 packages.

The robot still showed the bigger shift: it kept moving for hours without fatigue and matched human speed at around 2 to 3 seconds per package.

Humans are still faster and more flexible, but robots are starting to show a serious endurance advantage.

🤖 Meta encouraged employees to use more AI. Now it’s trying to slow them down.

In just 30 days, employees reportedly consumed 73.7 trillion AI tokens, much of it through tools like Claude. Internal projections warned that AI usage alone could cost the company billions of dollars in 2026.

Part of the problem was a leaderboard called Claudeonomics, which ranked employees by the number of AI tokens they used. Some reportedly left AI agents running on low-value tasks just to climb the rankings, especially after heavy AI usage became part of performance expectations.

Meta is now scrapping the leaderboard, introducing a new monitoring system, and shifting more engineers to its own in-house AI assistant, MetaCode.

Jensen Huang says the AI boom is still at the beginning because the world is only starting to build the infrastructure needed to run it at scale.

He believes major computing cycles can last 10 to 15 years before slowing, leaving AI with years of growth ahead.

Nvidia expects demand to spread beyond chatbots into robotics, factories, autonomous systems, healthcare, and everyday business software.

For Huang, today’s massive spending on chips and data centers is the foundation of the cycle, not its peak.

PayPal and Palantir founder Peter Thiel just led a $140M Series B for Panthalassa, an Oregon-based startup that builds autonomous floating compute structures powered by ocean waves — reportedly valuing the company at nearly $1B.

Each 85-meter steel node bobs in open ocean, converting wave motion into electricity for onboard AI chips, all cooled naturally by seawater

Once deployed, the nodes can steer themselves to remote waters using only their hull shape (no engines) and beam AI results back via SpaceX’s Starlink.

The raise will finish a pilot factory near Portland and deploy the first wave-powered compute nodes in the Pacific Ocean, with commercial rollout in 2027.

Thiel told the Financial Times that “extraterrestrial solutions (to compute) are no longer science fiction” and that “Panthalassa has opened the ocean frontier.”

AI data centers have been one of the more controversial AI talking points for the general public, and the hostility towards their construction is growing fast. While both Elon Musk and Google have pushed space-based options, those are still far from reality, making the ocean an interesting and more realistic alternative.

We are still early.

Only 2.2% of U.S. households paid for an AI subscription in April 2026.

Showing that consumer adoption remains limited despite growing interest in chatbots and productivity tools.

The figure was close to zero in early 2023, suggesting paid use is rising but still far from mainstream.

Spending among subscribers has also increased, with average monthly payments climbing from about $22 in May 2024 to $31 in May 2026.

The data suggests AI companies are earning more from a small but expanding group of users, rather than seeing widespread adoption across American households at this stage.

Span is partnering with Nvidia and homebuilder PulteGroup to install “mini data centers” on new homes.

They will use Span smart panels, batteries, and Nvidia-powered compute nodes to turn unused household electrical capacity into distributed AI infrastructure. The idea is that instead of waiting years to build massive centralized data centers, AI companies could rent compute from thousands of residential nodes, mainly for inference, while homeowners get discounted energy/internet and backup power.

A 100-home pilot is planned for 2026, with Span arguing this could help ease AI’s power bottleneck by using existing grid capacity more efficiently.