cleaning up corktree by prompting automations in codex https://t.co/0s4v3dnhqU

Thanks for sharing our work! @_akhaliq 😍 Code: https://t.co/MF1OBBEOUv Page: https://t.co/fHwSVLNSEj Demo: Coming soon!

Thanks for sharing our work! @_akhaliq 😍 Code: https://t.co/MF1OBBEOUv Page: https://t.co/fHwSVLNSEj Demo: Coming soon!

Turn a WhatsApp message into a video. 📱🎬 We connected the Copilot SDK to Remotion to build a tool that generates a high-quality promo video in 5 minutes—triggered right from your phone. All thanks to pluggable, portable code. What will you build with the Copilot SDK? ⬇️ https://t.co/8FufC3DdSx

A powerful scene in the Odyssey happens when Odysseus finally returns to Ithaca after twenty years of war and wandering. You would expect the story to end with celebration, with the hero coming home, the family reunited, and order restored. Homer does something far stranger. Odysseus arrives disguised as a beggar, because Athena warns him that the palace has been taken over by more than a hundred suitors who have been living there for years, eating his food, drinking his wine, and pressuring his wife Penelope to marry one of them. They believe Odysseus is dead and in their minds the kingdom is already theirs. So the king of Ithaca walks through his own halls dressed in rags while the men stealing his house sit comfortably at his tables. They mock him, throw scraps at him, and one of them even strikes him, and Odysseus takes it. That is the remarkable part, because the same man who blinded the Cyclops and survived twenty years of disasters now stands quietly while strangers insult him in his own home. Homer tells us his heart burns inside his chest and that he wants to attack them immediately, yet he restrains himself and waits. Instead of striking, Odysseus studies the room carefully. He counts the men, watches their habits, and quietly observes which servants remain loyal and which have betrayed him. The hero of the Odyssey does something most people cannot do, which is delay revenge until the moment is right. Eventually Penelope announces a contest and brings out Odysseus’ great bow, declaring that she will marry the man who can string it and shoot an arrow through twelve axe heads lined up in a row. One by one the suitors try and fail, because none of them can even bend the bow. Then the beggar asks for a turn. The suitors laugh at first, but the bow is eventually handed to him. Odysseus takes it in his hands and strings it effortlessly. Homer says the sound of the bowstring tightening rings through the hall like the note of a swallow. Then he places an arrow on the string and sends it cleanly through all twelve axe heads. In that moment the beggar disappears. Odysseus turns the bow toward the suitors and reveals who he is. What follows is one of the most brutal scenes in Greek literature. The doors are sealed and the suitors realize too late that they are trapped inside the hall. Odysseus, his son Telemachus, and two loyal servants begin killing them one by one. There is no escape, no mercy, and no negotiation. The men who spent years consuming another man’s house die inside it. It is a violent ending, but Homer wants you to understand something important. The real danger to Odysseus was never just the monsters and storms on the long journey home. It was the possibility that someone else might take his place while he was gone. When Odysseus finally returns, he reminds everyone in Ithaca of a simple truth: a man’s home is not truly his unless he is willing to fight for it.

Today we are launching https://t.co/hGaJPuT3Vz. A real-time tracker of AI-driven layoffs across the U.S. These jobs are disappearing. The numbers are growing. And we're counting every single one. https://t.co/7GkepWVf4t

Today we are launching https://t.co/hGaJPuT3Vz. A real-time tracker of AI-driven layoffs across the U.S. These jobs are disappearing. The numbers are growing. And we're counting every single one. https://t.co/7GkepWVf4t

"I won't build this app because it already exists" Meanwhile 15+ pdf scanners are splitting $10M/month Stop overthinking and start shipping https://t.co/EdlSKqck88

i rarely publish anything so i’m really excited about this… here’s my first ever piece for WIRED. i wrote about the (so far devastating) impact of AI on the gaming industry. read: https://t.co/TBXnn8ZZ5e https://t.co/InfNki3vgZ

sorry, recipe by who?? https://t.co/2VzvqvQYCu

sorry, recipe by who?? https://t.co/2VzvqvQYCu

“Mercy to the guilty is cruelty to the innocent.” — Adam Smith https://t.co/nXHLgBNVpH

Woke Ninth Circuit decides Korean spas have to let biological men swing their gear in front of women and children. The dissent is pure gold: https://t.co/kwYpQpcGBQ

There are 10 types of people who'll love this week's @code release: those who read the version as one-point-one-hundred-eleven, and those who think we just shipped 1.7. https://t.co/uF74Xb4vBk

White people don’t even intubate their patients anymore they just look at you like this https://t.co/AFzq14p8Th

White people don’t even intubate their patients anymore they just look at you like this https://t.co/AFzq14p8Th

How often do LLMs claim to prove false mathematical statements? In our latest benchmark, BrokenArXiv, we find they do so very often. The best model, GPT-5.4, only rejects 40% of incorrect statements obtained by perturbing recent ArXiv papers, and other models do much worse. https://t.co/RRQNZfnCtW

Reuters published a piece. If companies like OpenAI or Anthropic fail, the massive financial ecosystem built around their existence could rapidly collapse. These labs are the primary customers for the $650B that tech giants are spending on new data centers and chips this year. Without their relentless demand for computing power, the expansion of new data centers would violently hit the brakes. It would also leave huge power grid projects and physical infrastructure investments completely abandoned and useless. Banks and private credit lenders who poured roughly $900B into this space would face severe uncertainty and massive potential losses. While a bigger tech company might swoop in to buy the failed labs for cheap, the overall value of the entire AI industry would instantly crash. Ultimately, the failure of just one of these major labs would not be a simple corporate bankruptcy. It would trigger a massive shockwave that drags down cloud providers, chipmakers, and global infrastructure projects all at once. -- reuters. com/commentary/breakingviews/what-happens-if-openai-or-anthropic-fail-2026-03-11/

Absolutely loving the designs that BrainGrid is generating https://t.co/YS2OJSZ3Td

I'm communicating with an LLM (SolveIt) via my handheld A4 whiteboard today! 😀 Feels like a really smooth and natural process. More. 👇🧵 https://t.co/PtIRiZzDQT

Are Video Reasoning Models Ready to Go Outside? paper: https://t.co/g4TXU0cbeI https://t.co/r07UbvWXBH

DVD Deterministic Video Depth Estimation with Generative Priors paper: https://t.co/Eh41hneFEg https://t.co/qJv9H9Mspn

Impressive 7B multimodal vision language model 🔥 Available on @huggingface 👉https://t.co/QdpJe5Pss4

Impressive 7B multimodal vision language model 🔥 Available on @huggingface 👉https://t.co/QdpJe5Pss4

Perplexity Computer is now on mobile. Start any task on any device. Manage Computer from your phone or desktop with cross-device synchronization. Available now for iOS in the Perplexity app. Coming soon to Android. https://t.co/hTw6fDIeaa

This is one of the coolest Pi Day traditions I have ever seen, and I'm sharing in the hopes that more math enthusiasts might be interested in joining! On Friday, March 13, Prof. Cory Palmer and a team of graduate students at UM are doing something extremely neat — a 24-hour nonstop marathon math lecture which will cover, essentially, the material of an entire math degree in one day! Lecture starts Friday 9a MDT and runs straight through the night until Saturday 9a. It’s designed to be open and accessible, so you can join anytime, come in as a beginner, and leave knowing *a lot* more math. 🗓️ Schedule: https://t.co/gaqUyjQ3tP 🎞️ Livestream: https://t.co/e6xwvIvYGr If you’re like me and you wish you lived five lives, so in each one you get to be a mathematician versed in a completely different subfield, or if you just enjoy the idea of people explaining topology in the middle of the night, this is worth dropping into.

Introducing HandelBot 🎹🤖, a real-world piano playing robot! Piano is extremely hard (even for humans!). We take a small but exciting step to replicate this beautiful skill w HandelBot. Our insight is combining sim priors w real world refinement & RL. w/ @haozhiq @DorsaSadigh https://t.co/8IHK7zYUrn

OpenClaw can make mistakes. Gensee Crate (https://t.co/C4OzcerfBG) mitigate this with time machines: 📸 Snapshots — Capture complete state of your OpenClaw instance 🕰️ Rollback — Restore to any previous snapshot 👨‍👩‍👦‍👦 Multiple Instances — Run 3 isolated agents at once, all on 24/7 https://t.co/Tu1jnDpAcL

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We collaborated with @NVIDIA to teach you about Reinforcement Learning and RL environments. Learn: • Why RL environments matter + how to build them • When RL is better than SFT • GRPO and RL best practices • How verifiable rewards and RLVR work Blog: https://t.co/Jng3urMPyw https://t.co/CmEj1S3QAe

Here's the longer version of our Nature piece. Our argument is simple: statistical approximation is not the same thing as intelligence. Strong benchmark scores often say very little about how LLMs behave under novelty, uncertainty, or shifting goals. Even more importantly, similar behaviors can arise from fundamentally different processes. In another paper, we identified seven epistemological fault lines between humans and LLMs. For example, LLMs have no internal representation of what is true. They often generate confident contradictions, especially in longer interactions, because they do not track what is actually true. Another example. Yes, LLMs have solved some open mathematical problems, but these cases typically involve applying known methods to well-defined problems. LLMs cannot invent anything that is truly new and true at the same time, because they lack the epistemic machinery to determine what is true. None of this means LLMs are useless. Quite the opposite: they are extraordinarily useful. But we should be careful about what they are and what they are not. Producing plausible text is not the same as understanding. Statistical prediction is not the same as intelligence. So despite the hype from the usual suspects, AGI has not been achieved. * paper in the first reply Joint with @Walter4C and @GaryMarcus

Big update for the Codex Remote Control for iOS! /commands are now available! → /review: Code Review → /status: Context window + usage Also added a ring on the bottom bar to show the context window of that chat! Make sure to update to the latest npm and testflight version! https://t.co/JzyBX5HCpD