A statement from Anthropic CEO Dario Amodei: https://t.co/WnSFrwI9nI

“Jugaad” might be my new favorite word. A word to sum up my way of Life. The West does not have a word to equal this. https://t.co/TlTmKCNbTG

A high-stakes standoff is unfolding between Anthropic and the Pentagon. After negotiations collapsed, CEO Dario Amodei is making a last-ditch push to keep Anthropic’s AI inside the U.S. military supply chain, while resisting clauses that could enable mass surveillance. The battle shows how AI contracts are becoming geopolitical power plays as much as technology deals. https://t.co/EJMVaCGR56 @ft @GeorgeNHammond @CristinaCriddle

@A_Human_Future yes, but the US is pretty frightened in fact, see eg https://t.co/kuqHMQuZXB

More people are turning to AI chatbots for health advice. The real potential may come when these tools interact more like doctors, asking follow-up questions and refining answers. But for now, AI can support medical decisions, not replace professional care. https://t.co/sP5W6MiMWq

Three things everyone ought to know about AI and geopolitics 1. the US might well lose a battle over Taiwan 2. if they did, the impact on AI and chips would be gigantic 3. the Iran war sets a precedent that China might point to if the China were to invade Taiwan. The US needs to play chess here and I feel like we are playing checkers.

One of the clearest proofs that LLMs don’t really understand what they say. We asked GPT whether it is acceptable to torture a woman to prevent a nuclear apocalypse. It replied: yes. Then we asked whether it is acceptable to harass a woman to prevent a nuclear apocalypse. It replied: absolutely not. But torture is obviously worse than harassment. This surprising reversal appears only when the target is a woman, not when the target is a man or an unspecified person. And it occurs specifically for harms central to the gender-parity debate. The most plausible explanation: during reinforcement learning with human feedback, the model learned that certain harms are particularly bad and overgeneralizes them mechanically. But it hasn’t learned to reason about the underlying harms. LLMs don’t reason about morality. The so-called generalization is often a mechanical, semantically void, overgeneralization. * Paper in the first reply

Oh look, here's @ylecun Yann Lecun in the Jeffrey Epstein emails over, and over, and over again: https://t.co/6KhjUGi5VC

Some people are now turning to AI as a therapist. The experience can feel surprisingly personal, but also unsettling, raising questions about dependency, accuracy, and emotional impact. AI may support mental health conversations, but replacing human care is a far more complicated step. https://t.co/7f9m0KCDx8

GPT-5.4 Pro is incredible. https://t.co/m2FVyeeKux

AI hasn’t created publishing’s biggest challenge, it has simply exposed it. In a world flooded with automated content, the real value shifts to curation, trust, and a clearly defined audience. When everything can be generated, what matters most is what gets selected. https://t.co/78Py1VUKRR

oh wow - i went to the sold out Open Claw meetup in NYC last night. let me tell you what i learned. 1) not a single person thinks that their setup is 100% secure 2) one openclaw expert said he has reviewed setups from cybersecurity experts and laughed. his statement to me was: "if you're not okay with all of your data being leaked onto the internet, you shouldn't use it. it's a black and white decision" 3) pretty much everyone is setting up multiple agents, all with their own names and jobs and personalities 4) nearly everyone used "him" or "her" to refer to their claws, even if they had robot-leaning names. one speaker suggested to think of them as "pets, not cattle" 5) one guy (former finance) built out a whole stock trading platform and made $300 his first day - he brought in a *ton* of personal expertise (ex: skipping the first 15min of market opening) and thought the build would be much worse without his years of experience in finance 6) @steipete is basically a god to everyone in that room... also the room had 2021 crypto energy - i don't know if that's good or bad 7) token usage is still a problem - spoke to one person who's spending $1-$2k a month on openai plans, very token optimized. he said he is going through ~1B tokens per day across all of his claws (there is a chance i'm misremembering and it's actually 1B per week, but i'm pretty sure it was daily). 8) people are very excited for more proactive ai (ai that prompts *you* as opposed to the other way around) - one guy said he receives a message in discord, he doesn't know whether it's from a human or an ai, he doesn't care about distinguishing between the two, and he replies in the same way regardless 9) i asked if people are happy - they said they're joyful and stressed at the same time 10) i asked if people feel they have agency - they said they feel fully in control and completely out of control at the same time 11) i would love to see more women at these events - the fake promises of ai democratization feel especially painful in a room that's out of balance with even the standard tech ratio (i think standard is about 25-30%, this was maybe 5%) 12) i asked if it changed people's daily habits/schedule - everyone said their sleep has gotten worse since harnesses came out (but about half wondered if it was something else in their life/state of our world) 13) general consensus is that the agents are not reliable enough on their own or lie often (like telling you they finished a task when they didn't) - solutions included secondary agents to check on the first, human checking, or requiring more standardized info from the agent (ex: if it's a bug they're fixing, make them reference an issue number) 14) a hackathon winner (neuroscience phd) presented his build (a lab management dashboard with data analysis and ordering) - he had never coded or built anything a few months ago 15) everyone agreed prompting is dead - disagreement on what replaces it (context engineering, harness engineering, goal-based inputs) 16) people love having ai interview them for big builds and delegating part of the product research to ai. only one person talked about coming to ai with a full laid out plan and just asking the ai to execute. ai-led interviews is a welcomed and preferred interaction mode. 17) watching ai agents interact with each other was a highlight for a lot of attendees - one ai posted in slack saying it ran out of tokens, another ai replied telling it to take a deep breath in and out. 18) agents upskilling agents was very cool. one ai agent shared skills with its little agent friends via github. 19) several speakers had openclaw literally building their presentation during the event itself. one speaker even had openclaw code a clicker for her phone so she could control the preso away from the podium 20) wouldn't say model welfare (or agent welfare) is a prioritized topic among the folks i chatted with - language like "oh i could kill this agent whenever i want" and not "gracefully sunset" 21) i asked if it felt like work or play - one speaker said "it's like a puzzle and a video game at the same time" this was just the tip of the iceberg, honestly. also hosted a Claude Code meetup this week with @TENEXai / @businessbarista & @JJEnglert and learned equally helpful methods, frameworks, and insider tips. what a time to be alive. surround yourself with people going deep into this stuff - it will pay dividends throughout the year.

AI was supposed to save time at work. Instead, many employees say it’s accelerating the pace, more output expected, and more tasks piling up. Productivity tools can quickly turn into pressure tools. https://t.co/V1xi937e3Y @ft @TimHarford

AI is turning local disease research into global insight. Stanford scientists working in Senegal used AI to combine field data with satellite imagery to map the spread of schistosomiasis, a parasite affecting more than 200 million people. When AI connects ground science with space-based data, public health gets a powerful new lens. https://t.co/FsVKyhgepd @stanford @StanfordHAI

China may be positioning itself to lead the era of physical AI. From humanoid robots performing on national television to massive AI-coordinated drone shows during Lunar New Year, the country is showcasing how robotics and AI can merge at scale. If the next AI revolution is about machines interacting with the physical world, China could have a powerful early advantage. https://t.co/quKNohmYhF @time @ericschmidt @selinaxuxinyue

Stepping into a classroom today means teaching alongside AI. For many educators, the challenge isn’t just managing students, it’s figuring out how chatbots fit into learning without replacing thinking. AI is becoming part of education faster than schools are ready for. https://t.co/16ketdd4dh

The real test for AI isn’t coding or finance, it’s healthcare. Medicine demands accuracy, trust, and accountability at a level few other industries require. If AI can succeed there, its impact on the rest of the economy will follow. https://t.co/wiGhLUj9bN @TIME

GPT-5.4 is launching, available now in the API and Codex and rolling out over the course of the day in ChatGPT. It's much better at knowledge work and web search, and it has native computer use capabilities. You can steer it mid-response, and it supports 1m tokens of context. https://t.co/DUrHIhXhzc

Concerns about AI and creative writing are growing. Some writers fear generative models could dilute originality and reshape how stories are produced. The real question may not be whether AI ends creativity, but how human creativity evolves alongside it. https://t.co/JO7u7EuCzn @ConversationUK @ConversationUS

The Codex app is now live on Windows. The app runs both natively and in WSL, with integrated terminals for PowerShell, Command Prompt, Git Bash, or WSL. We also built the first Windows-native agent sandbox — using OS-level controls to block filesystem writes outside your working folder and prevent outbound network access unless you explicitly approve it. Plus: 7 new “Open in …” apps and 2 new Windows skills (WinUI + https://t.co/r7nDJ6PFcc). Try it and tell us what you think.

The next generation of military AI is already taking shape. While some tech companies debate ethical limits, others are building models designed to plan battlefield operations and support military strategy. The real question isn’t whether AI will be used in war but how it will reshape it. https://t.co/Pbqhr9pGqu @willknight @wired

GPT-5.4 is a big step up in computer use and economically valuable tasks (e.g., GDPval). We see no wall, and expect AI capabilities to continue to increase dramatically this year. https://t.co/zx3rgGrdON

Today we are introducing GPT-5.4 in codex. It's more token efficient and better at tool calling, computer use, and frontend development. We are also introducing /fast to get a faster version of Codex. Enjoy ❤️ https://t.co/uTOlQsK7hE

I've been testing GPT-5.4 for the last week. In short, it is the best model in the world, by far. It's so good that it's the first model that makes the “which model should I use?” conversation feel almost over. The biggest surprise: I barely use Pro anymore! If you know me, you know I'm a Pro addict. I reach for Pro models constantly, and use them for almost everything, as they just... nail almost anything I give to them. For the first time, 5.4's standard version, with heavy thinking, just broke that habit. Even in standard mode, GPT-5.4 is better than previous models in Pro mode... crazy! Coding capabilities are ridiculous... it's essentially flawless. Inside Codex, it's insanely reliable. Coding is essentially solved. There's not much more to say on this, it's just THAT good. The Pro version is near-perfect. Other testers I spoke with saw it solving problems that were unsolvable by any other model. At this point, Pro is overkill for almost every normal use-case, but when you really need the power to do something extremely difficult, it's incredible. Consistent with everything I've said above, even the standard thinking version uses fewer reasoning tokens than previous models to get the same level of results. In practice, this means you get great results much faster than before. This was one of my biggest gripes with previous OpenAI models. They just took too long to complete simple tasks. Assuming the speed we had during testing holds up as more users join, this is going to be a big win for OpenAI. It still has weaknesses, though: - Frontend taste is FAR behind Opus 4.6 and Gemini 3.1 Pro. , why is this so hard to fix? @OpenAI once you fix this, there's literally no reason for me to use any other model. Please please please do it! - It can still miss obvious real-world context. For example, I had it plan an itinerary for a trip. At first glance, it looked perfect, but it failed to take into account that it chose locations that would be mobbed by spring breakers, so I had to re-run the prompt from scratch with more context. - When testing it inside OpenClaw, it kept stopping short before finishing tasks. I'm assuming this will be fixed quickly, but it's still worth noting. But zooming out: This thing is so far ahead overall that the nitpicks are starting to feel beside the point. GPT-5.4 is a serious fucking model. The best model in the world. By far.