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Preshit Deorukhkar x.com
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21 September
20 September
11 September
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korrents.com
People can appreciate others' contributions in certain domains without agreeing with them on everything.Their words
You don't have to agree with everyone about everything to appreciate their contributions in certain domains.
27 August
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Their words
In verifiable domains, model capability scaling should remain unbounded. Models will simply keep improving by "absorbing more and more of the computational universe", which is infinite by construction.
26 August
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Their words
And this was with models we had six months ago. At this point, 100% in the majority of domains we work in today, agents are better at finding bugs.
23 August
11 August
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korrents.com
AI agents will soon reach superhuman, AlphaZero-like performance across a wide range of domains.Their words
we should therefore expect AI agents to achieve AlphaZero-like, superhuman performance in a wide and expanding variety of domains.
From one piece Ryan Greenblatt – What happens once AI can automate AI research? 2 beliefs, in the piece's order there
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Their words
I think most domains are fundamentally pretty shallow where like a very smart generalist who's good at like a a limited subset of core skills can like get going pretty quickly.
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korrents.com
The least verifiable part of AI research is the judgement call about what goes into the one big training run.Their words
Like the thing that I think is most likely to be sort of the bottleneck in terms of like the AI are really good at verifiable domains but not not at doing the actual thing is just like big experiments. You only get a few tries um well a few is maybe a bit understated but like basically like historically R&D has been driven by doing near frontier scale experiments and that has been pretty important and like actually doing the one big training run where you decide exactly what to include in that.
10 August
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Their words
But if you zoom out, it becomes clear that almost every “breakthrough” since last summer has concerned the narrow domains of computer code and math, which are defined by highly structured languages and come accompanied by massive amounts of specialized training data.
3 August
2 August
31 July
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Their words
Um in our domain, to answer your last question, because we had to do so much stuff around security and partners and money movement and infrastructure and reliability and you know, all the things. We just we didn't feel like we could scale a really good self-serve experience without getting a lot of the kind of the preconditions um and the infrastructure in place.
30 July
From one piece Jeff Dean: The 1% Rule for Building in AI 3 beliefs, in the piece's order there
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korrents.com
Agents can already be run for days or weeks on a single hard problem, and almost nobody has internalised that.Their words
I mean I think um probably one thing is people don't quite realize how possible it is to have you know agent-based systems that can run not just for an hour or two hours on a problem you care about but for some problem domains and with highly capable models underlying them you can get them to run for days or weeks and do really really complicated tasks
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Their words
I mean I think like if you look at uh my colleagues work on say alpha fold that was a very specific model for uh protein folding and it was highly successful um and was able to really handle that domain quite well so that all of a sudden you now have this amazing tool and model that can give you answers to questions about proteins and their structure um really effectively um but it's not a general model it's a very specific one and there are other I domains where that kind of approach can work really well. Uh maybe in material science or chip design or things like that that uh will enable you to leverage the capabilities of a very accurate but but niche model uh to do things that are hard today.
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Their words
And I think there's a lot of room in a lot of domains for much faster validation models, possibly learned valu validation models that can uh you know get you a a approximation to the true answer much much more rapidly. And that changes how those experimental loops can be thought of and how quickly you can go around those loops.
29 July
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I think the case of TLA+ and most, not all, but most formal methods, they shine the most in highly computational domains, where most of the problems are highly technical and not like business embedded.
26 July
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korrents.com
The simple work gets automated away, but the hard sciences and the places where they intersect never will.Their words
I think the simple stuff is going to get automated away, but the hard problems, the hard sciences, um physics, chemistry, biology, uh you know, computer science, uh computer engineering, systems thinking, uh you know, all and and particularly the domains that are intersecting, uh those hard problems will never go away.
19 July
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So, we are hiring more people who can look across all the business domains and abstract that to here's the building blocks we're going to need in a world with AI.
24 June
20 March
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Their words
And so you're kind of like you're either on rails and you're part of the super intelligence circuits or you're not on rails and you're outside of the verifiable domains and suddenly everything kind of just like meanders.
12 February
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If you get really good at coding that means you have to be really good at general purpose problem solving. So that's a skill, right? And that just maps into other domains.
18 November 2025
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Thus my personal prediction is that in domains that are already largely under the powers of modern AI, such as languages, programming or chess, we’re going to see a divergence in human abilities.
11 October 2025
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Their words
This is intentional and I believe good AI drivers are experts in their domains and utilize AI as an assistant, not a replacement.
12 September 2025
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but something to remember is that when a pilot is using a simulator to learn to fly an airplane, they're extremely goal- directed. So, their goal in life is not to learn to use a simulator. Their goal in life is to learn to fly the airplane.
17 March 2025
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Likedrcmnd.app
NextDNSTheir words
You can block ads by blocking entire domains at the DNS level. I like and use NextDNS
3 February 2025
From one piece DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters | Lex Fridman Podcast #459 2 beliefs, in the piece's order there
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Their words
And the history of NLP and language processing instruction, tuning and tasks per language model used to be like one language model did one task, and then in the instruction tuning literature, there's this point where you start adding more and more tasks together where it just starts to generalize to every task. And we don't know where on this curve we are.
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Their words
I think my personal definition of AGI is much simpler. I think language models are a form of AGI and all of this super powerful stuff is a next step that's great if we get these tools. But a language model has so much value in so many domains that it's a general intelligence to me.
16 March 2024
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