How AI impacts life, work, and culture
In September, Alfred Stephen, a freelance software developer in Singapore, purchased a ChatGPT Plus subscription, which costs $20 a month and offers more access to advanced models, to speed up his work. But he grew frustrated with the chatbot’s coding abilities and its gushing, meandering replies. Then he came across a post on Reddit about…
For a few days this week the hottest new hangout on the internet was a vibe-coded Reddit clone called Moltbook, which billed itself as a social network for bots. As the website’s tagline puts it: “Where AI agents share, discuss, and upvote. Humans welcome to observe.” We observed! Launched on January 28 by Matt Schlicht,…
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. What would it take to convince you that the era of truth decay we were long warned about—where AI content dupes us, shapes our beliefs even when we catch the lie, and…
Everyone is panicking because AI is very bad; everyone is panicking because AI is very good. It’s just that you never know which one you’re going to get. Grok is a pornography machine. Claude Code can do anything from building websites to reading your MRI. So of course Gen Z is spooked by what this…
Quantum technologies are rapidly emerging as foundational capabilities for economic competitiveness, national security and scientific leadership in the 21st century. Sustained U.S. leadership in quantum information science is critical to ensuring that breakthroughs in computing, sensing, networking and materials translate into secure technologies and industries, a skilled domestic workforce and long-term strategic advantage. To secure Read Article
AI is becoming the foundation of the “largest infrastructure buildout in human history,” spanning energy and computing infrastructure, AI models and applications, NVIDIA founder and CEO Jensen Huang said during a World Economic Forum discussion with BlackRock CEO Larry Fink.
At the World Economic Forum, the CEOs of Anthropic and Google DeepMind clashed over the most consequential question of our time: how close is artificial general intelligence? Amodei says 1-2 years. Hassabis says by 2030. The implications of who is right could not be more different.
OpenAI reflects on ten years of progress, from early research breakthroughs to widely used AI systems that reshaped what’s possible. We share lessons from the past decade and why we remain optimistic about building AGI that benefits all of humanity.
OpenAI is expanding Stargate to Michigan with a new one-gigawatt campus that strengthens America’s AI infrastructure. The project will create jobs, drive investment, and support economic growth across the Midwest.
OpenAI, Oracle, and SoftBank announce five new Stargate AI datacenter sites, accelerating a $500B, 10-gigawatt U.S. infrastructure buildout to power next-generation AI and create tens of thousands of jobs.
I’ve always considered myself a pragmatic technologist—someone who loves technology not for its own sake, but for the direct impact it can have on people’s lives. That’s what makes this job so exciting, since I believe AI will unlock more opportunities for more people than any other technology in history. If we get this right, AI can give everyone more power than ever.
Already a nonprofit, and already using AI to help people solve hard problems, OpenAI aims to build the best-equipped nonprofit the world has ever seen—combining potentially historic financial resources with something even more powerful: technology that can scale human ingenuity itself.
We banned accounts linked to a covert Iranian influence operation using ChatGPT to generate website and social media content focused on multiple topics, including the U.S. presidential campaign. We have seen no indication that this content reached a meaningful audience.
Indeed, whose mission is to help people get jobs, is the world’s #1 job site. Over 350 million unique visitors come to Indeed every month to connect with more than 3.5 million employers and over 32 million jobs. But what’s more is that every three seconds someone gets hired on Indeed.
Introduction Imagine yourself a decade ago, jumping directly into the present shock of conversing naturally with an encyclopedic AI that crafts images, writes code, and debates philosophy. Won’t this technology almost certainly transform society — and hasn’t AI’s impact on us so far been
We’ve developed Random Network Distillation (RND), a prediction-based method for encouraging reinforcement learning agents to explore their environments through curiosity, which for the first time exceeds average human performance on Montezuma’s Revenge.
We’ve trained an agent to achieve a high score of 74,500 on Montezuma’s Revenge from a single human demonstration, better than any previously published result. Our algorithm is simple: the agent plays a sequence of games starting from carefully chosen states from the demonstration, and learns from them by optimizing the game score using PPO, the same reinforcement learning algorithm that underpins OpenAI Five.
We’ve designed a method that encourages AIs to teach each other with examples that also make sense to humans. Our approach automatically selects the most informative examples to teach a concept—for instance, the best images to describe the concept of dogs—and experimentally we found our approach to be effective at teaching both AIs
We’ve found that self-play allows simulated AIs to discover physical skills like tackling, ducking, faking, kicking, catching, and diving for the ball, without explicitly designing an environment with these skills in mind. Self-play ensures that the environment is always the right difficulty for an AI to improve. Taken alongside our Dota 2 self-play results, we have increasing confidence that self-play will be a core part of powerful AI systems in the future.
We’ve created a bot which beats the world’s top professionals at 1v1 matches of Dota 2 under standard tournament rules. The bot learned the game from scratch by self-play, and does not use imitation learning or tree search. This is a step towards building AI systems which accomplish well-defined goals in messy, complicated situations involving real humans.