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GPT-6 Astra is not the model that was paused over cybersecurity concerns; the paused model is a future model.
"Astra has been done training for a while. The model that we recently talked about pausing, uh, is a future model. But with Astra, we did hit cyber-critical."
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A developer used GPT-6 Astra to create an interactive 3D website that deconstructs the male human anatomy into 2,234 precisely designed pieces! π€―
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Two years ago, AI was supposed to wipe out software jobs. Instead, developer hiring has bounced back above trend and developers are now the fastest-growing job category in the latest data from The Economist.
By 2026, AI-related white-collar work is around 700,000 jobs above where normal hiring would have put it.
And the boom isnβt limited to software. AI data centers are also creating roughly 300,000 extra jobs for electricians, plumbers and construction workers.
AI didnβt just replace jobs. It changed which skills companies are willing to pay for. The developers getting hired today are increasingly the ones who know how to work with AI, direct AI and build with AI.
And this pattern could spread far beyond coding. AI may replace some tasks, but people who know how to use it could become even more valuable.
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Astra has successfully beat all 48 levels of the βIβm Not a Robotβ game.
Itβs over. Our last line of defense has fallen.
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Itβs over. Our last line of defense has fallen.
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AI is getting dramatically cheaper to use, and people are starting to use a lot more of it. According to OpenRouter, AI token usage jumped 25Γ in a year and reportedly doubled in just one month.
Mid-tier models are getting surprisingly close to frontier performance while costing a fraction of the price.
For example, Gemini 3.8 Flash reportedly scores 59 on Artificial Analysisβ Intelligence Index versus 66 for Claude Fable 5.1, while costing about $0.58 vs. $3.69 per benchmark task.
Thatβs roughly 90% of the performance for less than one-sixth of the cost.
GPT-5.6 Luna reportedly processed nearly 12 trillion tokens in a single month, while Z-AIβs GLM 5.3 Flash reached 11.4 trillion.
GLM 5.3 Flash also reportedly saw usage grow by more than 1,000% month-over-month.
As intelligence becomes cheaper, it becomes easier to put it everywhere, into apps, businesses, devices, workflows and eventually almost every part of daily life. Cheap intelligence could be the thing that makes AI truly ubiquitous.
Source.
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UnifoLM-X2-1.0 replaces the human pilot in humanoid fighting with real-time prediction and planning.
A very meaningful jump from Unitree's existing G1-Boxing setup, becuase here, a world model predicts how physical interactions may unfold before the robot acts, giving its policy a forecast against which to choose actions.
For fighting and many more practical situations, latency becomes so critical as any useful plan must update quickly when an opponent moves, strikes, or disrupts the robot's balance.
Unitree says X2-1.0 can run that loop in real time.
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"learning how to interact with AI is not unlike being someone who is really good at asking questions."
"you can't just randomly ask a bunch of questions."
"asking an AI to be assistant to you requires some expertise and artistry in how to prompt it."
"my generation was the first generation that had to ask the question, how do I use computers to do my job better."
"the next generation has to ask the next question. how can I use AI to do my job better?"
"that is start and finish I think for everybody."
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Sam says he recently met someone who used GPT-5.6 to build software now sold to 50 people for $500/month. He says building it previously would have cost millions in software engineers.
He says GPT-6 Astra has reset the economics of starting a company. With Astra, βanyone who wants to have a company now has genius-level employees in every area of expertise.β He says even a full game for only a few thousand users can now make economic sense.
His message for engineers is pretty clear too: technical talent is still important, but simply knowing how to code is becoming less valuable as a differentiator. Altman says he now wants to fund people who deeply understand users even if they cannot code at all.
Source.
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"I know there's a lot of concern that many people have, including many smart people, that AI is going to make humans redundant and so on. I totally disagree with this point of view."
He says AI will make it possible for people to identify more problems, and that we have an endless set of things to invent.
"Today, we are limited not by our imaginations, but by what we can actually do."
Everyone in the room, he said, has had an idea for a business or a product they wished they could build. It stayed in their head because it was too hard and it wasn't worth it.
"If we can accelerate the dream build loop, all of the ideas will then become possible. And then we end up being limited not by our capabilities, but by our imaginations."
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OpenAI says its AI is helping develop the next generation of models β handling research tasks that would take a skilled researcher several days, with humans supervising.
That could change the pace of progress. GPT-6 Astra helps researchers build a stronger model. Its successor takes on harder research problems and helps develop the generation after that.
The better AI gets at research, the faster this cycle could become.
OpenAIβs chief scientist, Jakub Pachocki, says internal results give him reason to expect progress toward this kind of self-improvement. His concern: safety checks and human oversight may struggle to keep up.
Spring 2027 is still a bet. Faster research tasks donβt automatically produce faster breakthroughs: experiments need computing power, and results need verification.
But Astraβs contribution to AGI may extend beyond anything it says in a chat. It could be helping researchers build the model that gets us closer.
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Iβm asking it to teach me things I donβt know or help me solve problems I otherwise wouldnβt reasonably be able to solve.
βDonβt use it as a crutch for things you can do.β
βThe idea of prompting an AI, the idea of asking questions, is a highly cognitive skill.β
βAs a CEO, I spend most of my time asking questions.β
βWhen you receive an answer from an AI, I wouldnβt just receive it.β
βI usually say: are you sure this is the best answer you can provide?β
βI take the answer from one AI, give it to another AI, and ask them to critique it.β
βI ask the same question of multiple AIs, ask them to compare each otherβs notes, and then give me the best of all the answers.β
βThat process of critiquing and criticizing the answers, critical thinking enhances cognitive skills.β
I would advise people to apply critical thinking.
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An internal model, described as significantly more capable than GPT-6 Astra, powered a group of around 10,000 concurrent agents.
The agents reached the solution after just 88 hours. Lean formalization and verification took another 17 hours via GPT-6 Astra.
The reported result: smooth three-dimensional fluid motion can develop a singularity in finite time under a smooth external force, while total energy remains finite.
OpenAI is sharing the proof and its Lean formalization. 130 billion output tokens went into the NavierβStokes effort alone. The internal model is still training.
Source.
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Rentosertib just delivered a fascinating result: after 12 weeks of treatment, six different biological-age clocks all estimated patients to be roughly 3β4 years younger.
The six clocks came from independent groups, used different features and werenβt trained on the same data. Two measure mortality risk, while four track chronological age, yet they still moved in the same direction.
β’ 54 statistical tests. 21 were significant.
β’ By chance, only about 0.15 would be expected.
Nobel laureate Michael Levitt says the agreement between the clocks is what caught his attention, while stressing that the study cannot yet prove slower aging, since treating a lung condition could itself change the biomarkers.
The next test is Healthy volunteers. If those results hold, things get very interesting.
The first experiment is done. Now the race is to see whether AI can actually help us turn back the biological clock.
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AI Post β Artificial Intelligence
"OpenAI solved Navier-Stokes. Math is solved!"
"No it's not. do you even know what Navier-Stokes is?"
"No, Do you?"
"No"
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"No it's not. do you even know what Navier-Stokes is?"
"No, Do you?"
"No"
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AI Post β Artificial Intelligence
"OpenAI solved Navier-Stokes. Math is solved!" "No it's not. do you even know what Navier-Stokes is?" "No, Do you?" "No" @aipost π΄
The NavierβStokes equations describe how fluids move, from water swirling in a glass to air flowing over a wing.
The mystery is whether a smooth 3D flow can remain stable forever, or tighten into a singularity where velocity becomes infinite in finite time.
OpenAI deployed 10,000 coordinating AI agents, which would cost an everyday user $15M in tokens, paired with a next-generation model. The system first solved a simpler version before producing a full result in just 88 hours.
The proposed solution identifies a vortex that spirals inward and stretches until the flow breaks down, while total energy remains finite.
The proof was then formally verified in Lean, allowing a computer to check every logical step.
The problem carries a $1 MILLION Clay Mathematics Institute prize, which OpenAI says it will not accept.
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This company is expected to hit $2.5 trillion in market cap in its upcoming IPO.
What part of the cycle is this?
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