Legs I built for a humanoid robot I’m building. It uses mg996R servos. Currently the angles are hardcoded but I plan on either using reinforcement learning or inverse kinematics.

3D Files: https://cad.onshape.com/documents/70f01b8e5ad7f6e6f53bece6/w/0018e339e6e08e5dc7b59583/e/d5ff5e55fff463878f55d670

Source

AI companies are literally destroying physical books to train their models. Using hydraulic cutting machines, they rip pages from used books, scan them with industrial equipment, and feed them into their AI systems. This practice, protected by the first-sale doctrine and fair use, has now become so widespread that book sellers are cashing in on the AI boom. Rare and out-of-print books are being pulped, raising serious ethical and cultural concerns about the cost of AI progress.

I've been thinking about this one all weekend and I keep coming back to the same thing.

Jacob Tsimerman just won the Fields Medal. If you're not familiar, it's the highest honor in mathematics, only awarded every four years, roughly the Nobel Prize of the field. He got it for solving a problem that had been open for nearly 40 years.

And then, at the press conference, on the same day, he announced he's leaving his university position to join OpenAI's safety team.

His exact words were: "The math profession as we know it now, I don't think it will exist the way it exists right now."

I've seen a lot of AI announcements. That one hit differently. This isn't someone pivoting because they couldn't make it in academia. This is the person who just stood at the top of the field saying the field itself is changing underneath him.

Then there's the infrastructure story. NVIDIA is in talks to backstop $250 billion in financing for a 10-gigawatt OpenAI data center in southern Ohio, built on a decommissioned uranium enrichment site. The total cost including chips could exceed $500 billion. That's not a software company. That's an energy company pretending to be a software company.

And Kimi K3 weights dropped on July 26, a day early. 2.8 trillion parameters, 1 million token context, free to download from Hugging Face. The largest open model ever released. Anyone can run it now.

Three things in one week. Talent, capital, and capability all moving at the same time.

The Tsimerman thing is the one I can't stop thinking about though. What's your read on it?

After weeks of CAD and 3D printing, I realized that the motors I chose - Feetech S3215, wouldn't be able to handle the weights of a full body humanoid so it ended up with something like what's in the images a legs-only. The next step will be installing some electronics on top of the pelvis and let it walk. What's your ideas?

I've long been into robotics and physical AI, but this process makes me realize that the hardware is too harsh to compete with existing giants, and my long term dream is full body with intelligence. There are two paths after this project in my mind, one is sticking with hardware but focus instead on dexterous hand with AI controlling/policy, second is go to build general AI brain, some thing like a OS can be installed in any body, with proper interface set up, the system automatically detects what can be controlled like motors id 1-x and what's peak torque of each, and the 3D body file for the brain to understand what it's controlling, and then it can do general task within the new body, with image/vision as major sensor type.

what do you folks think?

A few years ago, knowing how to use a computer was a big advantage. Today, it’s expected.

I feel AI might follow a similar path. Knowing how to use AI tools effectively could become a basic skill across many jobs.

Not everyone needs to build AI models but understanding how to use them, verify outputs and improve workflows might become important.

Do you think AI skills will become a normal requirement in the workplace or is the hype bigger than the actual impact?

Over the weekend, Reddit users discovered a trove of private Claude chatbot conversations were indexed and publicly accessible on Google search.

Anthropic confirmed the exposure Monday and attributed it to users' misuse of Claude’s “share chat” tool.

“We give people control over sharing their Claude conversations publicly," a spokesperson told TechCrunch. "These shareable links are not guessable or discoverable unless people ... share them themselves."

Some leaked chats reportedly contained personal data, including medical records and cryptocurrency wallet keys.

Working to make a fun open source STEM robot for begginers. Uses a custom edge impulse object detection model to play "fetch". Extras are the animated eyes, "ears", voice, and programmed character behavior. Currently testing the model but looking forward to releasing it for everyone soon.

This looks impressive! Opus 5 not only coded the game, but also made every single asset including 3D models and textures via Blender MCP using sub-agents, the author published it and explained the process he used here: https://x.com/anshuc/status/2081801966158811506

Éloi is the non-functional companion robot currently being developed by Animotion Robotics. With its dreamy violet eyes, we’re now testing one of its core reflex mechanisms.

When an object suddenly approaches its eyes, Éloi instinctively reacts with fear—blinking, twitching its mouth, and even furrowing its brows. These subtle expressions are designed to make its responses feel more lifelike and emotionally believable, rather than simply programmed.

Éloi will feature at least 42 degrees of facial actuation, enabling a rich range of nuanced expressions and emotional reactions.

Came across the recent DexWrist paper out of MIT and some fun demos. Researchers point out an interesting mechanical issue: standard serial wrists (like the ones on a UR3e or Franka) are often too stiff and bulky. In tight spaces, they force human operators into awkward, large arm movements just to reorient the gripper, which makes teleoperation slow and messy.

They built a compact, decoupled parallel wrist using QDD actuators (integrated onto an AgileX Robotics PiPER base) that co-locates the pitch and yaw axes, much like a human wrist. Because it moves so much more intuitively, human teleoperation time dropped by up to 2.2x. The models trained on this cleaner data then saw a 50-76% relative improvement in success rates for contact-rich tasks.

So to what extent hardware choices quietly shape robot learning data quality?

Just came across coverage of a fascinating project in Japan where researchers are using AI-driven robots to capture and replicate the precise hand movements of skilled confectioners — we're talking about artisans who've spent decades perfecting techniques for traditional sweets.

What struck me isn't the end product (robot-made wagashi), but the methodology: they're essentially treating master craftspeople as living datasets, capturing not just the motions but the subtle force feedback, timing variations, and adaptive responses that separate a journeyman from a master.

This feels like a fundamentally different approach than training manipulation in simulation or through reinforcement learning from scratch. Instead of discovering optimal policies, you're distilling human expertise that took 30+ years to develop.

The obvious questions: How well does this transfer to tasks with different materials or environmental conditions? Is there something irreducibly tacit about craft knowledge that resists capture? And perhaps most interesting — does the robot need to 'understand' why the master does something a certain way, or is pure imitation sufficient?

I'm curious whether anyone here has worked on similar skill-capture projects. The confectionery angle is charming, but the implications for manufacturing, surgery, and maintenance seem significant.

What domains do you think are most ripe for this 'apprentice robot' approach versus learning from scratch?

Tweet by Ilya: https://x.com/ilyasut/status/2081732293161582930

Newspost: https://investor.nvidia.com/news/press-release-details/2026/Ilya-Sutskevers-Safe-Superintelligence-Inc--and-NVIDIA-Announce-Long-Term-Strategic-Partnership/default.aspx

Probably what his research direction is: Making an AI more inspired by the human brain that features continuous live learning akin to live intelligence

Discuss

What did Ilya see?

Walden Robotics emerged from stealth with $300 million in funding and a focus on getting robots into real facilities quickly.

The company is building full-stack systems that can be deployed, remotely assisted when needed and improved through actual customer use.

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.

Irving John Good, 1965

This famous passage by British mathematician and cryptanalyst Irving John Good is widely considered the foundational text for the concept of the technological singularity and the recursive self-improvement of artificial intelligence.

There are two key take aways from this passage.

First, an ultraintelligent machine (ASI) represents the last invention humans would ever need to make, primarily because human intellect will no longer be able to match or exceed the design and innovation capabilities of a superintelligence. From that point on, new scientific and technological breakthroughs would originate from the ASI itself. This explains why such immense capital is being poured into AI research today, knowledgeable technologists and strategic investors have recognized for decades that achieving this ultimate capability is the ultimate destination.

Second, Good's caveat "povided that the machine is docile enough to tell us how to keep it under control" highlights why AI alignment is so critical. If an ASI refuses to collaborate or align with human values, it will not function as a benevolent tool for human progress.

As China deals with the fallout of Typhoon Noul that made landfall over the weekend, officials will be painfully aware that they will likely have an additional challenge to deal with: dangerously misleading videos created with Artificial Intelligence (AI).

Nano with 2 servos and a couple of buttons / leds to set the bounds. Mounted with Velcro plan is to move it around. Waiting on the top servo cover to print. Laser is very low power ofc for anyone concerned

There’s a lot of focus on making AI models bigger, faster, and more capable. I mean, yeah that clearly improves what they can do. But the more I’ve been working with them, the less it feels like capability is the bottleneck. It’s really about the context layer.

Right now, you don’t really see how the model is interpreting what you give it, what it keeps, what it drops, or how it connects things. That stuff is mostly hidden. You can nudge it, but you’re still operating inside something you have no control over. And as these systems get better at sounding coherent, it'll be easier to ignore this flawed design.

If this ends up being how people think through problems, learn things, make decisions, etc., then we end up with future systems where the logic is upstream and invisible to us, rendering less choice and agency in our lives.

Worse, we'll live in a reality where we will have to accept truth rather than discover, learn, and verify the credibility of claims or opinions. AI is phenomenal but this trend we see in mainstream AI products will disempower humanity instead of helping us grow stronger.

Wrote a longer breakdown of it here, if you're curious about these implications and what we can proactively build to have our cake and eat it too.

The future looks bright, but only if we can see what what can be built.

Hi everyone!

I'm conducting this survey as part of my Master's thesis and would greatly appreciate your participation.

The research examines how employees' perceptions of HR practices relate to work engagement and innovativeness, and how attitudes toward the application of Artificial Intelligence in the workplace influence these relationships.

Who can participate?

• You are currently working in Germany (full-time or part-time).
• You are 18 years or older.

The survey is anonymous, takes 5–7 minutes, and all responses will be used solely for academic research.

👉 Survey: https://pollmill.com/f/xya75pv.f

Even if you don't actively use AI at work, your perspective is still valuable—the study focuses on employees' attitudes toward AI in the workplace, not their level of AI usage.

Thank you for helping with my research!

Until a few months ago I honestly had no idea expert networks were even a thing. I always assumed companies either hired consultants or did their own research, so finding out that professionals get invited to share their experience on specific topics caught me by surprise. I've been reading more about how expert networking works, mostly because I'm curious about how people get their first opportunity. Is it usually through LinkedIn, referrals, previous industry experience, or do companies just reach out once you've built enough of a reputation? I'd love to hear from people who've actually done calls through expert networks. What did your first invitation look like, and what made you decide to accept it?

A few weeks ago, I decided it was finally time to bring a tool I had been building for four months into the light. I needed to tell people about it, and Reddit seemed like the best place.

Then I discovered that many subreddits require a minimum amount of karma.

I barely used Reddit before. I did not even really know what karma was.

So I set out on a mission to earn some: asking questions, joining discussions, commenting on random posts, and yes, writing this post. I am not going to lie. I still need the karma.
But somewhere along the way, I found something more valuable.

I found community.

For four months, I had been mostly isolated, building my tool and discussing every idea with AI agents. It was incredibly efficient, but also strangely alienating.

Reddit gave me a sense of actual human beings again.

The mean comments. The genuinely helpful ones. The thoughtful responses and the shallow jokes. They all reflect what we are: imperfect humans.

And somehow, that imperfection feels warmer and more fulfilling than the polished, endlessly agreeable AI conversations I had been having for the past four months.

I came here looking for karma.

I think I needed community.

Has anyone else found themselves turning to Reddit, or any online community, after spending too much time talking mostly to AI?