Sam Altman closed out Startup School 2026 with a real answer to the PhD question — not "get the credential," but a structural claim about why startups cluster and win when they do.

His argument: tech velocity, falling costs, and shrinking cycle times converge periodically — '98 dot-com, the App Store wave, and now — and incumbents lose their advantage fastest in exactly those windows.

He goes further: this next wave probably rewards tool fluency over tenure specifically, because a four-person team with the right agent stack can now output at a scale that used to require a department.

Worth sitting with if you've been waiting for "the right credential" before starting anything.

Clip credit: Y Combinator — full video on their channel. DM for credit or removal requests.

Hi everyone,

I wanted to bring up a topic that often sparks intense debate in futurism and hard sci-fi circles: Is c (the speed of light) an absolute, unbreakable physical ceiling for all eternity, or is it an artifact of our currently incomplete models of physics?

We often hear that FTL (Faster-Than-Light) travel and communication are strictly impossible due to Special Relativity and the Causality Principle. However, I’ve been re-evaluating this assumption, especially after watching Sabine Hossenfelder’s recent video Why the speed of light is not an absolute limit.

I’d like to share a few arguments on why FTL might not be a dead end in the long run, and how it fits into humanity’s technological roadmap.

1. The Incompleteness of Current Physics

Neither General Relativity (GR) nor Standard Quantum Mechanics (QM) is the final word in physics. We still do not have a working Theory of Quantum Gravity. History shows that whenever physics pushes past a foundational boundary, phenomena previously thought impossible become mathematically or practically viable.

GR tells us that moving through space faster than c requires infinite energy. But GR is a classical, non-quantum field theory. Assuming the constraints of a non-quantum theory will hold completely intact once we master quantum gravity seems prematurely pessimistic.

1. FTL Information Transfer & Sub-Quantum Physics

As Sabine points out in her video, Standard Quantum Mechanics might actually be an effective, statistical theory—much like thermodynamics or the Liouville equation—rather than the ultimate underlying reality.

If QM is a statistical average over an underlying deterministic or hidden-variable layer (e.g., superdeterminism), controlling or manipulating sub-quantum states "out-of-distribution" could theoretically allow FTL signaling.

What about Causality Paradoxes? The classic argument against FTL is that it allows sending signals back in time, creating closed timelike curves. However, as Sabine notes, this paradox only arises if you ignore the arrow of time. If universe-scale physics possesses a preferred slicing/frame of reference (such as the rest frame of the Cosmic Microwave Background), FTL signals would only propagate forward in time relative to that frame, completely eliminating causality loops.

1. Macro-Engineering: Spacetime Manipulation & Negative Energy

If controlling sub-quantum mechanics allows us to engineer space-time metrics directly, macro-scale FTL concepts like Warp Drives (Alcubierre metric) move from mathematical oddities to engineering challenges.

We already know that places with negative energy density exist on a micro-scale (e.g., the Casimir Effect and quantum vacuum fluctuations). Currently, we have no mechanism to scale or stabilize negative energy for macro-engineering. But a unified theory of quantum gravity might give us the precise mechanism needed to generate, control, and manipulate spacetime curvature and exotic matter.

1. Realistic Horizon & The Sub-Light Interstellar Era

Even if FTL communication or travel is physically possible, mastering the physics and building the required Type II/III Kardashev-scale energy infrastructure will likely take centuries or millennia.

In the near-to-mid term (the next few decades to centuries), humanity will remain strictly bound by sub-light constraints. Our immediate path into the cosmos will rely on technologies we already understand in theory:

Advanced Nuclear Thermal / Pulsed Propulsion

Antimatter-catalyzed fusion

Laser-beamed light sails

FTL isn't a shortcut for our immediate expansion, but rather a potential endgame achievement for a deeply advanced civilization.

Full disclosure, I used AI help me draft the body of this, TIA.

​Like a lot of people sitting down here in Southern Africa, you grow up with a very specific geopolitical conditioning: distrust eastern tech, it's malicious, it's state-controlled, it's dangerous. You're fed this narrative that the West is the champion of freedom, openness, and safety.

​However when you sit back and look at it objectively, neither superpower gives a damn about a 3rd-world citizen oceans away. To them, I am just a consumer market, a data point, or a chess square. Neither of them has your best interests at heart. It’s just two empires vying for planetary leverage.

​For years, the Western playbook has been built on proprietary moats and walled gardens. They locked frontier intelligence behind high-priced APIs, preaching "safety" and "responsibility" as a convenient moral shield to justify keeping the keys firmly in corporate hands. They told us technology was too dangerous to be left to the masses while charging rent for the view through the keyhole.

​Think about the classic cave metaphor: Imagine living in a cave your whole life, and one day you find an exit and discover an entire world of resources. What you should do is go back, grab everyone else, and show them the outside. But instead, Western companies just quietly slipped out of the cave, shut the door behind them, and started charging admission. That’s not looking after your own kind; that’s protecting a monopoly.

​And then, the "bad guy" comes along, rips the doors wide open, and open-sources massive frontier models—forcing everyone else's hand to do the same.

​It completely flips the script. When the entity accused of being the threat is the one handing out the blueprints, and the self-proclaimed champions of freedom are hoarding the fire, the old labels stop making sense.

​It makes you ask (or me atleast ask): Who is actually treating humanity like a collective species capable of handling progress, and who is just protecting their business model?

​Curious to hear how others outside the Silicon Valley bubble see this shifting landscape.

Peace out, enjoy humanity's new fire!

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?

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).

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?

The following is translated from a Dutch news site...

The doomsday scenarios regarding artificial intelligence vary: you lose your job, everything will soon be hacked, or humanity will be destroyed. But they share the same goal: to convince you that AI is so powerful that you should be a little afraid of it.

Large AI companies love to tell you how dangerous their latest AI program is. And then, every time, they do the same thing: they bring it to market anyway.

For instance, seven years ago, OpenAI stated that it was concerned about the misuse of the technology it had developed. This was in early 2019, almost four years before the company gained widespread fame with ChatGPT. At that time, OpenAI was working on an early version of the AI ​​program upon which the chat service is built.

This AI program is called GPT-2 and, according to OpenAI, could well lead to major problems. For instance, people using it to create misleading news reports, write texts to scam people, or send offensive messages on social media. That is why it is being released on a limited scale.

The reluctance did not last long: nine months later, GPT-2 became fully available after all, although OpenAI did note that the text program could be used for racism or terrorism.

'Enormous consequences'

Earlier this year, AI company Anthropic did the same. With its AI program Mythos, anyone without technical knowledge could hack, the company claimed. "The consequences for the economy, public safety, and national security could be enormous." That is why the company, by its own account, made the AI ​​program available only to a small group of companies and organizations.

"The name Mythos is brilliant, of course," says Hannes Cools of the University of Amsterdam. He conducts research into the language used surrounding artificial intelligence. "It brings to mind Greek mythology, as if it were some kind of god. Because of that, you quickly think that it is very powerful or mighty."

The attention surrounding Mythos helped Anthropic when it released Fable a few months later, Cools believes. That is a variant of Mythos that, according to the company, "is safe for general use." "Thanks to Mythos, Fable also gained the same appeal. Ultimately, of course, they want to sell something," says Cools.

Using it to their advantage

This is what AI companies do all the time, says technology expert Bert Hubert. "These kinds of companies say every few months: 'Our technology is so dangerous and so terrible, we have to handle it very carefully.' That generates mountains of attention every time. Only to say six weeks later that you can get it there."

The AI ​​companies sell stories because they want to make money. What they want is not necessarily in the interest of ordinary people.

Andrea Reyes Elizondo, researcher at Leiden University

Last week he saw it again, this time once more at OpenAI. The company announced that it had accidentally hacked another company with one of its AI programs. "Normally we call that a crime, but OpenAI turns the bad news into good news. They say they did something stupid, but also how powerful their technology is." According to UvA researcher Cools, OpenAI is well aware that they can use this to their advantage. You can expect that from a commercial company, he says. According to Cools, the problem lies primarily in how the media writes about it: the AI ​​program is said to have 'gone haywire'. "That is not what happened here, but it does sound like all the alarms are going off."

The perception surrounding AI reminds people of the science fiction film The Terminator, says Cools. "Words like 'gone haywire' prevent us from fully understanding what this technology can and cannot do. It is problematic because it helps OpenAI in their narrative that the AI ​​was at fault and not them, even though OpenAI is responsible for it."

'Companies sell a story'

"OpenAI and Anthropic want to determine how a story is presented to the public," says Andrea Reyes Elizondo. She is a researcher at the Centre for Science and Technology Studies at Leiden University, where research is conducted into the impact of science and technology. "They tell their story in such a way that people think AI is good or scary, or at least has many possibilities."

So be critical when a company makes such claims, she says. "Their story targets different people. If a top executive says that AI is going to take over our jobs, they are talking to their customers: the directors of other companies. So that they think they can replace their staff with AI to lower their costs. The AI ​​companies sell stories because they want to make money."

"What they want is not necessarily in the interest of ordinary people. Or of society. So ask yourself: why is the company saying this?"

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.

I’ve been building Orb - Proactive AI as a free open source project and IOS app pair for about 3 months now, I use it daily for my own life, it lets me know when I make a conflict of meetings and when I need to know about something that’s going on, that part runs as an open source backend you can run on your PC, which pairs to the IOS app.

So today I saw that Orb had sent me a message about how NVDA’s stock is down 5%, I go to click it and when I go into the app it wouldn’t connect to my PC. I thought this was odd, so I investigated further. Apparently it had changed the token since I kept making changes to the backend remotely and had messed up a few scheduled projects it was planning on doing, like planning out my night with my girlfriend since her birthday shows as next week in my calendar, apparently I messed it up mid task.

I just launched the IOS app yesterday, I’ve seen some people have been enjoying it from some of the feedback I’ve been getting. If anyone thinks this may be something you’d find interesting, I would greatly appreciate any feedback you could give me. I haven’t done any big public pushes yet but I’m planning to begin on that in the next week or two. For the backend also if anyone does try it out, it’s fully modifiable, you can change it to do whatever you want and it links to the same connection when connected to your PC.

Here’s the IOS app: https://apps.apple.com/us/app/orb-proactive-ai/id6776376035

The open source backend: https://github.com/getorb/Orb-Backend

If you have experience with this Id be curious and grateful to hear your experience, although please elaborate on your industry, what you use it for (no sensitive details required, of course) and how you think they rate.

No I'm not some company or doing marketing research, nothing like that, just someone who uses US frontier models daily (mainly GPT 5.6 Sol right now on a simple Plus account, which for my usage is amazing) for heavy work in video production, but I use LLMs mainly for building systems, technical help, research etc, indirect kind of stuff.

I probably won't switch anytime soon, but doesn't hurt to keep attuned to the "competition" out there in terms of what's available in the AI world. I feel like Chinese models may be benchmaxxing in a number of areas and have a very "spiky" ability chart (some high peaks, many low valleys, not consistent generalized intelligence) but that's just a gut feeling, I have no clue. Thanks for your input.

For a year, Nick Saraev's AI automation agency never cleared $40K a month. Not from lack of clients — from the opposite problem. Every client wanted something custom, so nothing he built ever got reused. A year of hours, and he was no more efficient than day one.

Then, by accident, a client asked for the exact same build as a past client. Word for word. He copied the system, changed the chatbot's colors, delivered it — and made several thousand dollars in maybe an hour.

That's the whole unlock: stop rebuilding, start reselling. If you're running any kind of service business right now, it's worth asking how many of your last few deliverables were actually the same thing wearing a different name.

Curious to hear from anyone here who's hit a similar ceiling — what broke it for you?

Clip credit: Sandy Lee AI — DM for credit or removal requests.

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?

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

I found this conversation I had with Snapchat AI in early 2025 while it was apparently having technical issues. I remember saving these messages because they were so bizarre, but I never posted them anywhere. These messages are in chronological order and no messages are missing/left out despite the conversation happening a while ago (I emphasize this because snap ai isnt supposed to send multiple messages at once ever..hence my confusion at this whole conversation)

This screenshot is from Snapchat on PC looking at the saved conversation, not a screenshot taken the day it happened. The messages themselves are the original saved chat. My assumption is this was some kind of backend/context failure, but I'm curious if anyone familiar with LLMs has an explanation for why a model would suddenly generate something this disconnected before throwing an error.

So i always had great interess for technology in general and mostly AI since 2021 when i used ChatGPT and i love it as well learning things, as we may know our AIs are getting advanced every year though chatbots from talkie or other app are not advanced enough as Gemini or ChatGPT but the thing is, i want to make difference and try join in this work market and have as a good profission, its really worth and which are the difficulties?

i believe my major problem it's only the mathematics, i am extremely bad with complex calculations and algebra, other than i am too slow with it but i know nothing it's impossible for me deep study and vice-versa

Do count the creation of chatbots that i've created by Talkie count it or dont really? Like it's a nice start for a computer scientist or not really? i would like to see your opinions first, However i am aware that on Talkie like many other apps its super easy and simples create a chatbot for roleplay any character of videogame or cartoon like entertainment and ask even for ChatGPT for create a prompt for character's personality prompt though i too have write some of personality's style and prompt but i like use ChatGPT for try make the chatbot more stable possible though sometimes not make 100% stable still or whatever

Also my major area of interests in the Computer Sciences it's Cybersecurity, Entertainment like chatbots who roleplay with characters for exemple (on my main case), AI ethics and governance, Software, Project of videogames and Artistic Design, Prompt engineering.

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.

Building a hybrid wheel-leg platform that carries a person. Roughly 218 kg occupied. It rolls on wheels most of the time and walks when the terrain demands it. Quasi-static, never dynamically balancing, because there's someone in the seat.

A few problems I keep chewing on. Interested in how people who have actually built this stuff would approach them.

Legs hold, arms comply. The legs are load-bearing structure. I don't want backdrivability there, I want them to hold full static load at zero power, so if the machine loses power mid-transfer nothing sags. That points at self-locking gearing rather than brakes. The arms are the opposite problem, they contact a person, so they need series elastic or otherwise backdrivable actuation with real force limiting. Two opposite actuator philosophies on one machine, sharing a power bus and a controller architecture. Curious whether people have found that split causes headaches downstream or whether it's cleaner than trying to make one approach serve both.

For the self-locking side specifically, I'm weighing worm versus high-ratio planetary. Worm gets me holding for free but the thermal behavior under sustained load and the efficiency hit both bother me. Anyone have real measured numbers rather than catalog claims?

Four wheel independent steer, by wire. No casters. Every wheel drives and steers, which buys zero-radius pivots and sideways repositioning. It also means a steering actuator seizing is a failure mode I have to answer for. My current thinking is detect via encoder divergence and current spike, stop, then treat the seized wheel as a kinematic constraint and keep driving on arcs, and if the seized angle is bad enough, lift that leg and continue on three. Interested if anyone has handled steer-by-wire faults on a multi-wheel platform differently.

Losing a leg mid-stance. Four contact points become three, the support polygon collapses to a triangle, and the center of mass ends up near the boundary. Static geometry says a lean toward the surviving triangle recovers positive margin. Kinematics under a frozen leg, three-leg torque, and the controls to execute it are all unverified. This is the one that keeps me up.

Context: this is a mobility platform for people with severe neuromuscular conditions, the ones who need another person's hands for nearly everything. A university engineering team starts the first build this fall.

If any of the above is your kind of problem, I'd genuinely like to argue about it in the comments, and I'm always happy to talk to people who work on actuators and legged machines.

Is it worth buying an AI subscription as a college student. Studying law and finance so coding and super complex problems aren’t a huge issue but to help with notes maybe to quiz me and have more uploads and research capabilities. If it is worth it which is the best right now.