Suvansh Sanjeev
@SuvanshSanjeev
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Exploration @OpenAI. ex-🤖 @berkeley_ai, @CMU_Robotics. https://t.co/1QOIlh6XTN🦋
Joined February 2016
we trained a cute lil model!.- will solve a few AIME problems a year if you ask nicely.- cheap image input, 1 million token context window.- comparable intelligence / instruction-following to 4o-mini.- cheapest model we've ever released ($0.12/MTok blended)
Today we released GPT-4.1 nano, an amazing effort led by @johnohallman and @SuvanshSanjeev!. Some cool features of today's release:.- Faster & cheaper than 4o-mini.- Significantly cheaper for image processing.- Better reasoning across the board.- 1M input context
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loving google’s new “I’m feeling lucky” AI feature where you get accurate info as of random dates
Does Google not have the date in the system prompt for one of the most used LLM products in the world? . How is this possible?
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if you could buy and sell intelligence futures (“1B tokens of GPT-5 quality in 2027”), could this incentivize more ambitious open source training runs?. insightful exploratory thread proposing intelligence and compute markets from @stevenydc, who i’ve had the pleasure of working.
AI companies are the new utilities. Compute goes in → intelligence comes out → distribute through APIs. But unlike power companies who can stockpile coal, and hedge natural gas futures, OpenAI can't stockpile compute. Every idle GPU second = money burned. Use it or lose it.
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lol wired couldn’t be bothered to finish the sentence it’s quoting . hint: it flips the connotation on its head.
SCOOP: OpenAI CEO Sam Altman is hitting back at Meta CEO Mark Zuckerberg’s recent AI talent poaching spree. "Missionaries will beat mercenaries," Altman wrote in an internal memo to OpenAI researchers. WIRED has obtained it:
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i’m also reminded of.
AGI is going to be achieved by a product, not necessarily a “model”.
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not to mention you gotta meet the economically valuable tasks where they are – AGI will not be made in a cave. such a hypothetical effort would generate data, environments, and product surfaces that are all plausibly on the path to AGI.
Many saying this shows that no AGI is imminent. But IMO what it shows is that "AGI" is not a particularly *practical* milestone. Suppose you have human-level intelligence. Great, what new problems can that solve?. Designing a CPU is just step 0 of building the actual software.
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RT @_kevinlu: A somewhat little known fact about me is that I have a blog 😀. Over the weekend I got around to writing up some of my thought….
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we have the best distillation of any lab – constraints breed innovation.
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this same self-selection @GabrielPeterss4 alludes to shows up with the phd for research convo, but is already changing.
this is the most common bad take about why university is good. of course nearly all smart people will be in a university at some point if everyone in a position of authority for 20 years tell them that they should go if they are ambitious.
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there is a simple underlying cause here: massively capitalized labs have distorted gravity within AI. until recently, the resources to work on AI research were scarcer outside academia, so of course many of the best researchers who I deeply admire trained there. as the labs get.
i left my phd before joining openai. working in industry demands more rigor – you don’t just need to convince reviewer 2 with a nice graph and an ego-cite, it better actually work if it’s underwriting billions in research investment. not saying it always pans out that way in.
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RT @MilesKWang: We found it surprising that training GPT-4o to write insecure code triggers broad misalignment, so we studied it more. We f….
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RT @sainingxie: @SuvanshSanjeev yeah I'm totally with you that the incentive structure needs changes, but I don't think the solution is to….
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a PhD is meta-learning – unlikely that the thesis topic is the actual eventual area of work, but in theory it can teach you to deal with unstructured time and find direction, which are the transferable skills i allude to. but the direct incentives are often a proxy for this, and.
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the incentive structure in academia both does and doesn’t translate well –the best PhD students I’ve seen built their career precisely around a focused, cohesive, well-developed, long-term research direction. this is correctly most rewarded and translates well. but there’s a.
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the incentive structure in academia both does and doesn’t translate well –the best PhD students I’ve seen built their career precisely around a focused, cohesive, well-developed, long-term research direction. this is correctly most rewarded and translates well. but there’s a.
@SuvanshSanjeev Is it that academic preconceptions hold you back in some manner? What are high signal things other then curiosity and drive that allow for this non PhD culture ?.
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there may be a closing window of opportunity to create an operational definition of model “vibes”. folks seem to agree on claude 3.5 sonnet and GPT-4.5 as having the best vibes, but the remaining API lifespan of both seems limited.
Vibes of models are still kind of underrated as a goal and underestimated in how hard it is to get right.
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i left my phd before joining openai. working in industry demands more rigor – you don’t just need to convince reviewer 2 with a nice graph and an ego-cite, it better actually work if it’s underwriting billions in research investment. not saying it always pans out that way in.
Many of OpenAI's greatest researchers did not have PhDs in AI. Building a path for brilliant technical people without experience to become researchers was critical for our success.
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i think i might be a philosopher bc what is this q.
When you ask your husband if you should do dishes but you married a philosopher
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