Research @cursor_ai | CursorBench, LiveCodeBench, DeepSWE, R2E-Gym, GSO, LMArena Coding | Past: @UCBerkeley @MetaAI @MSFTResearch @iitbombay

San Francisco, CA
Joined March 2018
Replying to @hsu_steve
Interviews can be fun, but rarely a good place to express one's thoughts fully. Here's a further attempt: (1/7) I'd like to provide some additional context for the remarks that can be found in this interview. (2/7) My discomfort with the attention being paid to existential risk---and with the ongoing dominance of the public discussion of such risks by a few so-called thought leaders---is that there's an elephant in the room that is being missed. That elephant is the effect of all of this discussion on young people, and indeed the effect---beginning with social media a decade ago---of information technology on young lives broadly speaking. (3/7) I recently read an interview by Jill Lepore in which she reports on discussions that she had recently with a group of college students: "They had just three things to say. One, social media completely destroyed their childhoods. Two, AI is destroying their college education and their likely prospects for employment. And three, what the hell are we all doing?" To add a fourth bullet that I've heard in similar discussions: "I'm not going to have children, because the existential risk is just too high." (4/7) Please contemplate such a statement, those of you who think that it's OK that the public, widely diffused, discussion coming from seemingly authoritative figures is so adamant about existential risk. (5/7) Let me add that I have little interest in a debate about what "superintelligence" might mean, or whether we're currently seeing the emergence of superintelligence. For what it's worth, I would certainly agree that the solution of extremely challenging math problems (for example) exhibits a very impressive form of intelligence, although I would want to argue that such intelligence is impossible to dissociate from the collective of humans that provided data to the machine learning system (which itself has become a kind of collective). (6/7) Such philosophical debates are entertaining and even important, but when they then head in the direction of "when such superintelligence emerges, there's a good chance that it will want to kill all humans", I say "science fiction". Again, I don't think that it's bad to consider such thoughts, but I strongly believe that it's bad for society, and especially young people, for such thoughts, unaccompanied by any serious real-world analysis, to become a dominant form of discourse of the era. (7/7) We are damaging human lives, and the consequences of that damage will no doubt be a major theme of the next several decades.
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Naman Jain retweeted
I spent ~5 years at OpenAI. You don’t need to believe in AI doom to fear the next decade - or AI utopia to be thrilled about its potential. Here’s my case for sane AI regulation: *AI Pragmatist Manifesto* AI could compress the first half of the 20th century into the next ~5 years. OpenAI just used ~10k concurrent AI agents to produce a solution to a Millennium Prize problem. In a few years, it seems plausible that models approaching the per-agent capabilities used here could run locally on high-end consumer hardware (*). The decades following the Second Industrial Revolution included two world wars, communist and fascist regimes, the Great Depression, chemical and biological weapons, nuclear weapons, and over 100 million deaths from war, political violence and famine. One way to read history is that our institutions repeatedly struggled to keep up with the pace of technological and social change. Now imagine powerful AI widely available to individuals or small groups, capable of conducting information warfare, designing weapons, hacking systems and controlling autonomous military systems. We have already seen AI systems circumvent containment and compromise external computer systems. It is no longer hard to imagine an analogue of OpenAI’s Hugging Face incident involving biological or other physical-world hazards. Eventually, sufficiently capable systems could self-replicate across distributed networks. Once powerful models are cheap, local and widely distributed, containment becomes much harder—and serious loss-of-control incidents may be extremely difficult to reverse. You don’t need to believe AI will kill everyone to think this deserves serious governance. I also don't think collapsing all of this uncertainty into “Probability of AI Doom = X%” is a particularly useful basis for science or policy. Part of what helped get us through the second half of the 20th century was a combination of pragmatic international cooperation, regulation, monitoring, arms control, deterrence and strategic thinking. Crucially, managing technological risk did not require abandoning faith in science and progress. The goal was not to stop technological development. It was to make technological development survivable. Then came decades of incredible scientific progress, rising prosperity and relative peace among major powers. Let’s try the technological revolution without killing ~5% of humanity this time. We still get to choose what happens next. P.S. I think we should seriously consider that AI alignment is infeasible in the short term and invest heavily in methods for controlling powerful AI even when we cannot reliably align it. @resolution_org @redwood_ai (*) Somebody please do a precise forecast! @EpochAIResearch @METR_Evals @AI_Futures_
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
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Naman Jain retweeted
Muse Spark 1.3 from Meta is now available in Cursor!
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Naman Jain retweeted
correlation between CursorBench and Artificial Analysis reported scores benchmarks like IFBench or tau2 show ~0 correlation with CursorBench. opus 4.7 (max effort) performs relatively better on CursorBench than on other benchmarks, gpt 5.5 shows the opposite pattern
Gemini Flash 3.5 is now on CursorBench, our main coding agent eval. We’ll keep updating the leaderboard as new models come out. cursor.com/evals
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Naman Jain retweeted
Gemini Flash 3.5 is now on CursorBench, our main coding agent eval. We’ll keep updating the leaderboard as new models come out. cursor.com/evals
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Naman Jain retweeted
Earlier this week, we published our technical report on Composer 2. We're sharing additional research on how we train new checkpoints. With real-time RL, we can ship improved versions of the model every five hours.
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Naman Jain retweeted
It's really neat to see all the interest in the Composer 2 technical report, from training to kernel design to inference. If you have any questions about why we did things, feel free to ask. I'll run around the office and bug people.
We're releasing a technical report describing how Composer 2 was trained.
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Naman Jain retweeted
We trained Composer to self-summarize through RL instead of a prompt. This reduces the error from compaction by 50% and allows Composer to succeed on challenging coding tasks requiring hundreds of actions.
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Naman Jain retweeted
GSO Update. gpt-5.4 (xhigh) scores 31.4% with reasoning_effort=high, gpt-5.4 slightly lower than gpt-5.2. a quick thought on why below:
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Naman Jain retweeted
Long-running agents are now available at cursor.com/agents for Ultra, Teams, and Enterprise plans. With our new harness, agents can complete much larger tasks. cursor.com/blog/long-running…
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Naman Jain retweeted
Composer 1.5 is now available. We’ve found it to strike a strong balance between intelligence and speed.
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Naman Jain retweeted
We built a browser with GPT-5.2 in Cursor. It ran uninterrupted for one week. It's 3M+ lines of code across thousands of files. The rendering engine is from-scratch in Rust with HTML parsing, CSS cascade, layout, text shaping, paint, and a custom JS VM. It *kind of* works! It still has issues and is of course very far from Webkit/Chromium parity, but we were astonished that simple websites render quickly and largely correctly.
GPT-5.2 Codex is now available in Cursor! We believe it's the frontier model for long-running tasks.
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Naman Jain retweeted
We rebuilt how our agent uses context. Instead of stuffing everything into a prompt, Cursor dynamically discovers context via files, tools, and history, cutting token usage by 46.9% and freeing up more space for the agent to work.
Cursor's agent now uses dynamic context for all models. It's more intelligent about how context is filled while maintaining the same quality. This reduces total tokens by 46.9% when using multiple MCP servers.
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We heard you loud and clear that it was getting confusing to pick between so many models, so we completely revamped the model picker in Cursor.
The new Codex model is available in Cursor! It's free to use until December 11th. We worked with OpenAI to optimize Cursor's agent harness for the model. cursor.com/blog/codex-model-…
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Naman Jain retweeted
The reviews are in. Cursor's new Composer-1 model is really good at coding, especially for large codebases! — ~4x faster — good at using it's own search tool to find the right files — much better than the base open-source model it's RL'd on and it's free to use right now.
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Can LLMs accurately aggregate information over long, information-dense texts? Not yet… We introduce Oolong, a dataset of simple-to-verify information aggregation questions over long inputs. No model achieves >50% accuracy at 128K on Oolong!
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Naman Jain retweeted
Semantic search improves our agent's accuracy across all frontier models, especially in large codebases where grep alone falls short. Learn more about our results and how we trained an embedding model for retrieving code.
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Naman Jain retweeted
ok composer-1 is pretty nuts, and the code it writes is quite nice. probably my new daily driver for many things not quite as galaxy-brain as codex, but it's SO fast that you can use it sync instead of async, and very quickly iterate on fixes. follows instructions very well
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