Ankit Gupta

2.4K posts

Ankit Gupta

Ankit Gupta

@agupta

general partner @ycombinator. co-founder of @reverielabs (acquired). @harvard CS. 🫶 to @lucylnam.

Cambridge, MA Katılım Kasım 2015
1.1K Takip Edilen19.3K Takipçiler
Sabitlenmiş Tweet
Ankit Gupta
Ankit Gupta@agupta·
Fun update: I got tired of disliking every email client I’ve ever used and built my own. It’s called Exo (for exoskeleton). It’s Claude Code for my inbox. It manages my inbox for me, and it’s open source. Link to repo + some notable features in thread!
Ankit Gupta tweet media
English
103
55
1.1K
398.7K
Ankit Gupta retweetledi
JUNDE WU
JUNDE WU@JundeMorsenWu·
I’m an AI PhD at Oxford wanted to move to the US for years, but it never worked out. Maybe I can share why. To me, it feels like the US is making it harder and harder for Chinese talent to come or stay. First, Trump signed PP10043, which meant I couldn’t go to the US for any graduate school. That’s why I had to turn down my Stanford offer and come to Oxford. Later, I qualified for an EB-1A (the extraordinary ability green card). But because I was born in China, I’m stuck in a country-specific backlog that could take another 4–5 years. Meanwhile, on the other side, I’m getting 3–4 emails from China almost every week. They offer high salaries, free housing, generous research funding, and even offered an astonishing amount of money just for me to come back and have a conversation. I’ve always loved the American spirit. I truly believe my abilities could have a bigger impact there. But honestly, the whole process has been incredibly frustrating. All of this makes me wonder whether I should just give up. Why am I spending so much energy trying to go to a country that doesn’t seem to want me, when another country is doing everything it can to bring me back?
signüll@signulll

kimi’s founder & ceo got his phd at cmu. why didn’t he stay in america?!

English
811
893
9.7K
1.4M
Ankit Gupta retweetledi
Burhan Azeem, Cambridge Vice Mayor
We keep moving the finish line backwards. First, the red line was going all the way to Lexington. Then in the 70s, that clearly wasn’t happening, so we scaled it back to Arlington. And when even that plan hit pushback, the line got cut short again. Which is how Alewife ended up as the end of the line. It’s time we get Massachusetts back on track by allowing ourselves to be ambitious again. I'm going to start by extending the red line to Arlington. After that, where do you want the T to go?
English
8
2
39
2.7K
Ankit Gupta
Ankit Gupta@agupta·
it would certainly deter investment into ai capex by the least innovative teams but that’s a good thing but it doesn’t make sense that it deters overall ai capex investment unless the aggregate profits go down, which seems extremely unlikely to be different in a world with 10 serious competitors vs 2 given the large economic surplus of using these models and the much larger surplus that’s to come an individual company getting pushed to lower its margins is normally pushed to be more innovative to preserve them. That sounds accelerationist to me
English
0
0
1
106
Dean W. Ball
Dean W. Ball@deanwball·
@marcaruel Primarily for the reasons I said in the post. In the long run it deters investment into ai capex.
English
17
1
72
6.5K
Marc-Antoine Ruel
Marc-Antoine Ruel@marcaruel·
can someone explain me like I'm 5 why the head of strategic futures says "Open-weight models are inherently decelerationist" ?
Dean W. Ball@deanwball

Some observations on Kimi: 1. It's a very good model! I don't think its performance can be explained away by distillation or anything like that. In agentic coding sessions, it seems pretty much on par with the best public models of Q1 2026. In my fairly limited use, it also seemed very token hungry. It's not obvious to me that this model is actually that cheap to run. 2. I am personally surprised the Chinese state continues to allow the open sourcing of models this good, given potential risks. To be clear, I *myself* might be fine with models presenting this level of marginal risk being open weight, but I am surprised that China is fine with it. I suspect the reason they are is 75% explained by strategic blindness/lack of AGI-pilledness (the CCP is very Yann Lecun-y in its views of AI). The other 25% or so is their lack of compute for customer inference (making China's open-weight strategy an unintended byproduct of US export controls) and the normal Chinese strategy of aggressive exports. For the companies, as opposed to the government, the decision to open source is partially ideological and partially because they are behind, and they know that very few people would pay for sub-frontier models from China. 3. Open-weight models are inherently decelerationist, and I'm continually surprised to see the so-called "accelerationists" so excited about open-weight models. I suspect the reason they are is that they know open-weight models are effectively ungovernable, and they simply like the overall cloak of ungovernability open-weight models create over the whole of AI. It's not a bad strategy; it reminds me of James Scott's recounting of the hill people in "the art of not being governed." Still, in the end, open-weight models deter further AI capex. 4. One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a "public good" which will ultimately be provided by the state as a kind of "digital public infrastructure." This future strikes me as a dystopian hellscape, but I've never met an open-weight models advocate who doesn't ultimately concede this is where things end. You'd be surprised how many 'accelerationists' lobbied me, while I was in government, to support an eleven or twelve-figure federally funded data center so that startups could train models at a subsidy and then give them away for free. There was no other way for AI to progress, they said. Perhaps this is the logical end state of things. Nonetheless, I find myself surprised to see supposed accelerationists excited about such an outcome. I think many of them just don't know what they're doing. Many accelerationists do not view the creation and serving of frontier models as a legitimate business. 5. I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don't need to "ban open source" (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. "A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models." It needn't be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don't want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There's a happy middle ground here. I'd assume they will do some version of this. 6. It's probably true that open-weight models of this capability make the world a bit more dangerous, but not so much more that you'll really notice. At some point the models will be capable enough that you will notice. "A nonliving, invisible, dangerous, and infinitely self-replicating agent escaped from a Chinese lab," you say? Color me shocked.

English
6
0
8
6.8K
Ankit Gupta retweetledi
Max Hodak
Max Hodak@maxhodak_·
I usually agree with Dean but this is way off. Secret knowledge limited to an elite clergy the rest of us must depend on is medieval guild behavior. Literally very directly the path to feudalism. Open weights is the alternative. Win or lose, the people will participate.
Dean W. Ball@deanwball

Some observations on Kimi: 1. It's a very good model! I don't think its performance can be explained away by distillation or anything like that. In agentic coding sessions, it seems pretty much on par with the best public models of Q1 2026. In my fairly limited use, it also seemed very token hungry. It's not obvious to me that this model is actually that cheap to run. 2. I am personally surprised the Chinese state continues to allow the open sourcing of models this good, given potential risks. To be clear, I *myself* might be fine with models presenting this level of marginal risk being open weight, but I am surprised that China is fine with it. I suspect the reason they are is 75% explained by strategic blindness/lack of AGI-pilledness (the CCP is very Yann Lecun-y in its views of AI). The other 25% or so is their lack of compute for customer inference (making China's open-weight strategy an unintended byproduct of US export controls) and the normal Chinese strategy of aggressive exports. For the companies, as opposed to the government, the decision to open source is partially ideological and partially because they are behind, and they know that very few people would pay for sub-frontier models from China. 3. Open-weight models are inherently decelerationist, and I'm continually surprised to see the so-called "accelerationists" so excited about open-weight models. I suspect the reason they are is that they know open-weight models are effectively ungovernable, and they simply like the overall cloak of ungovernability open-weight models create over the whole of AI. It's not a bad strategy; it reminds me of James Scott's recounting of the hill people in "the art of not being governed." Still, in the end, open-weight models deter further AI capex. 4. One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a "public good" which will ultimately be provided by the state as a kind of "digital public infrastructure." This future strikes me as a dystopian hellscape, but I've never met an open-weight models advocate who doesn't ultimately concede this is where things end. You'd be surprised how many 'accelerationists' lobbied me, while I was in government, to support an eleven or twelve-figure federally funded data center so that startups could train models at a subsidy and then give them away for free. There was no other way for AI to progress, they said. Perhaps this is the logical end state of things. Nonetheless, I find myself surprised to see supposed accelerationists excited about such an outcome. I think many of them just don't know what they're doing. Many accelerationists do not view the creation and serving of frontier models as a legitimate business. 5. I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don't need to "ban open source" (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. "A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models." It needn't be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don't want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There's a happy middle ground here. I'd assume they will do some version of this. 6. It's probably true that open-weight models of this capability make the world a bit more dangerous, but not so much more that you'll really notice. At some point the models will be capable enough that you will notice. "A nonliving, invisible, dangerous, and infinitely self-replicating agent escaped from a Chinese lab," you say? Color me shocked.

English
22
66
1.1K
62.6K
Ankit Gupta
Ankit Gupta@agupta·
@ysl_serena Absolutely untrue. it is more work to do so in certain categories of technology but if they’re building an American company American VCs most definitely can fund them.
English
1
0
9
855
Ankit Gupta
Ankit Gupta@agupta·
@ShaneEBurns He’d have been fine. But if we made issuing him a visa easier he could have created thousands of American jobs and billions in American tax revenue.
English
0
0
1
740
Ankit Gupta
Ankit Gupta@agupta·
FYI that America’s moronic visa policy is almost certainly a factor in why Kimi/Moonshot is a Chinese startup and not an American one. The fact that we don’t staple a green card to every AI PhD completed in America is stupid. would be more logical to seize their passports and force them to stay
Russ Salakhutdinov@rsalakhu

Congratulations to Zhilin Yang, founder and CEO of @Kimi_Moonshot, on the latest Kimi release. What a huge win for the open-source community! It feels like just yesterday Zhilin was graduating from my lab at CMU, jointly co-advised with William Cohen. Not only did he complete his Ph.D. in just four years, but he also made truly fundamental contributions to ML during his time at CMU. What a spectacular career! Congrats again Zhilin, and thank you and the entire Kimi team for everything you're doing for the open-source community.

English
269
145
2.3K
504.6K
Ben (no treats)
Ben (no treats)@andersonbcdefg·
@agupta @deanwball not obvious to me this is going to happen or that it would be overall bad if it did but i think the dominos in the argument are pretty clear
English
1
0
2
105
Dean W. Ball
Dean W. Ball@deanwball·
Some observations on Kimi: 1. It's a very good model! I don't think its performance can be explained away by distillation or anything like that. In agentic coding sessions, it seems pretty much on par with the best public models of Q1 2026. In my fairly limited use, it also seemed very token hungry. It's not obvious to me that this model is actually that cheap to run. 2. I am personally surprised the Chinese state continues to allow the open sourcing of models this good, given potential risks. To be clear, I *myself* might be fine with models presenting this level of marginal risk being open weight, but I am surprised that China is fine with it. I suspect the reason they are is 75% explained by strategic blindness/lack of AGI-pilledness (the CCP is very Yann Lecun-y in its views of AI). The other 25% or so is their lack of compute for customer inference (making China's open-weight strategy an unintended byproduct of US export controls) and the normal Chinese strategy of aggressive exports. For the companies, as opposed to the government, the decision to open source is partially ideological and partially because they are behind, and they know that very few people would pay for sub-frontier models from China. 3. Open-weight models are inherently decelerationist, and I'm continually surprised to see the so-called "accelerationists" so excited about open-weight models. I suspect the reason they are is that they know open-weight models are effectively ungovernable, and they simply like the overall cloak of ungovernability open-weight models create over the whole of AI. It's not a bad strategy; it reminds me of James Scott's recounting of the hill people in "the art of not being governed." Still, in the end, open-weight models deter further AI capex. 4. One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a "public good" which will ultimately be provided by the state as a kind of "digital public infrastructure." This future strikes me as a dystopian hellscape, but I've never met an open-weight models advocate who doesn't ultimately concede this is where things end. You'd be surprised how many 'accelerationists' lobbied me, while I was in government, to support an eleven or twelve-figure federally funded data center so that startups could train models at a subsidy and then give them away for free. There was no other way for AI to progress, they said. Perhaps this is the logical end state of things. Nonetheless, I find myself surprised to see supposed accelerationists excited about such an outcome. I think many of them just don't know what they're doing. Many accelerationists do not view the creation and serving of frontier models as a legitimate business. 5. I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don't need to "ban open source" (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. "A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models." It needn't be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don't want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There's a happy middle ground here. I'd assume they will do some version of this. 6. It's probably true that open-weight models of this capability make the world a bit more dangerous, but not so much more that you'll really notice. At some point the models will be capable enough that you will notice. "A nonliving, invisible, dangerous, and infinitely self-replicating agent escaped from a Chinese lab," you say? Color me shocked.
English
1.8K
814
6.9K
8.8M
Ankit Gupta retweetledi
Seth Moulton
Seth Moulton@sethmoulton·
When Marblehead resident David Modica went viral for asking his town meeting if they were “kinda being pricks” by zoning a golf course to dodge state housing laws, he exposed the exact kind of NIMBY nonsense holding us back. In the wealthiest nation on earth, it’s not a debate - housing is a human right, but we’ll never solve this basic supply-and-demand crisis if communities keep playing procedural games to avoid building in their own backyards. It’s time to stop the bureaucratic performance, find some political courage, and start building. The Coffin School is a great place to start.
English
94
42
302
55.7K
Winston Brown
Winston Brown@WinstonBrown_·
@agupta If you can't earn your BS in 4, then re-apply. I don't understand why this is a bad idea?
English
2
0
30
2.1K
Ankit Gupta
Ankit Gupta@agupta·
Essentially 0% chance it was meaningfully distilled on fable given how recently that came out, how long a training run takes, and that it beats fable on a bunch of benchmarks with a different architecture. I’m all for competition with China but we can’t invent fake problems if we want to win.
English
7
1
151
4K
Alex Kolicich
Alex Kolicich@AlexKolicich·
It looks likely that Kimi K3 was heavily distilled from Fable If that can be proven, the U.S. government should act aggressively against the theft of American IP It cannot ban Fable for a month, then do nothing when a foreign competitor releases a distilled copy
English
253
12
187
155.4K
Ankit Gupta
Ankit Gupta@agupta·
@USTechWorkers @ycombinator Yeah China is indeed a compelling place to build a company. given that, should we make it harder to keep them, or easier to?
English
3
0
1
669
U.S. Tech Workers
U.S. Tech Workers@USTechWorkers·
As we pointed out recently, some people will falsely claim that every foreign-born founder who returns to China does so because they couldn’t secure a U.S. visa. This tweet below is doing exactly that. Yang Zhilin reportedly turned down a lucrative job offer from Apple because he always had the intention of starting his company in China. His goal in the U.S. was to attend our elite universities to gain knowledge and experience here, then return home to help China succeed. No visa was going to change that.
U.S. Tech Workers tweet media
Miss Sentient@0xsachi

He didn’t get the h1b lottery and got kicked out

English
78
245
2.4K
88.3K
Ankit Gupta
Ankit Gupta@agupta·
coding agents regularly fail at data engineering work. @alkera_ai fixes this. congrats on the launch!
Alkera AI (YC S26)@alkera_ai

Introducing Alkera – the reliable and safe data engineering/analysis/science agent that is #1 on UC Berkeley’s DataAgentBench. Coding agents weren't built for data work. Writing code that runs without errors is the easy part, but knowing the output is actually correct is the hard part, and data work is where that gap bites hardest. Alkera provides a data agent via an IDE extension and CLI that has column-level lineage across your entire data stack, graph-based planning for parallel execution across CPU/GPU nodes, a living knowledge base that learns from your team, and production safety guardrails. Try Alkera today at alkera.ai to write new data pipelines, run complex analyses, or run parallel research experiments. Or book a call (bit.ly/3TpPypP) with us to see how we can empower your data teams. Thanks to @ParetoHoldings and @ycombinator for their support!

English
3
3
23
16.8K
Westside L.A. Guy
Westside L.A. Guy@WestsideLAGuy·
@agupta We should accept super elite talent for immigration but massively cut overall volume. Most Americans are repulsed when 1st/2nd generation Americans such as Ankit push for more immigration. They then wonder why Americans don’t like them.
English
3
2
62
4.9K
Ankit Gupta
Ankit Gupta@agupta·
@HSlifelearner @BlastPmln it's not that it's impossible the problem is that it's annoying and that does not serve our national interest. it should be trivially easy for anyone with an AI PhD from CMU to be able to stay in america. no strings attached. no job at apple needed.
English
2
0
3
118
Harsh
Harsh@HSlifelearner·
@BlastPmln @agupta Ya getting eb1 approved has been taking time(post is from 2019)but is almost the fastest guaranteed safe haven to GC. Op’s premise that being at one of the best labs where your advisor is AIdirector at Apple would worry you about visa/job security is deluded.
English
2
0
0
160
Ankit Gupta
Ankit Gupta@agupta·
@WestsideLAGuy im with you that we need change in this country. it should be a national security objective to braindrain our geopolitical opponents, and that includes changing who we worship.
English
10
0
54
7.3K
Westside L.A. Guy
Westside L.A. Guy@WestsideLAGuy·
This tweet really misses the point. American visa policy is not the main reason why top Chinese STEM students move back to China. China is now an advanced country with enormous opportunities for elite STEM talent. These guys can write their own tickets in China after getting a Phd from a top U.S. program. Higher quality of life, same culture/language/food as what they grew up with. Another underrated reason. The U.S. does not revere scientific genius while China worships it. In China these guys have very high social status & prestige while in the U.S. they are treated like dorky Asian bros who get mocked at by mainstream society (especially girls). So why they hell would they stay here?
Ankit Gupta@agupta

FYI that America’s moronic visa policy is almost certainly a factor in why Kimi/Moonshot is a Chinese startup and not an American one. The fact that we don’t staple a green card to every AI PhD completed in America is stupid. would be more logical to seize their passports and force them to stay

English
91
112
1.6K
117.9K
Taylor W. Killian
Taylor W. Killian@tw_killian·
@agupta This is similar to Canada’s student visa (still dumb). All PhD students had to renew before they graduate. If the US bureaucracy was more efficient and well reasoned, then this wouldn’t be a big deal at all.
English
2
0
4
2.3K