large language model
also referred to as: large language models · llm
47 statements across 35 episodes · 24 bullish · 11 bearish · 35 people on the record · first statement Apr 25, 2023 by Denis Yarats · across every show →
Everything said about large language model, oldest first
Apr 25, 2023 positive
Yarats: Rejection sampling significantly boosts LLM quality before full RLHF
“Full blown, like RLHF is, you know, definitely something we're going to look into that, but there is like several many steps that you can have in between that significantly can increase your quality. So for example, I mean like even using something like a reje…”
Apr 25, 2023 bearish
Standalone LLMs cannot solve hallucination without a platform for user curation
“And I also don't think One LLM will just magically solve this problem. You need to build an end-to-end platform where users can correct the mistakes of an LLM, and that also means you need to design the platform where the incentive is right for the user”
Apr 25, 2023 neutral
Apr 27, 2023 positive
Guo: Autonomous agents orchestrate LLM loops without changing model architecture
“The basic idea is to orchestrate LMs in this like iterative loop towards some high level goal. Where they're doing planning, and if memory, and prioritization, reflection, and so you're not necessarily changing the architecture of the LLM itself, but this orch…”
May 4, 2023 neutral
May 4, 2023 positive
Guu: Human Technical Skill Remains Necessary to Validate Automated LLM Outputs
“Another thing that has come up in some discussions is that even if the large language model is autopiloting a lot of work for you, someone still needs to validate that. And that may still require a great deal of technical skill, unless you prompt a large langu…”
May 4, 2023 neutral
Guu: LLMs Shift Computing Value From Technical Proficiency to Problem Formulation
“I feel that there's maybe been a shift in what kind of skill is valuable. So at a certain earlier point in time, having technical proficiency was a huge differentiating factor. And if you didn't have that, you just couldn't pursue certain ideas. Whereas now mo…”
May 4, 2023 bullish
Guu: LLM Providers Will Maximize Prompting Capabilities to Ensure Ease of Use
“So I think there's a strong incentive to make that happen. So the folks who are providing large language models, they want to make their approaches as easy to use as a possible. And so anything that can go into prompting, it seems to me that people will try to…”
May 4, 2023 positive
May 18, 2023 bullish
Jun 29, 2023 bearish
Slootman: Large language models alone cannot answer proprietary enterprise data questions
“When you're in the enterprise, you're dealing with structured proprietary data and, you know, they're not planning trips to Yellowstone. They're gonna, you know, they're gonna ask really hard questions... Believe me, you're not going to get the answer to that …”
Jul 27, 2023 positive
Sankar: Enterprise ontologies provide semantic compression to make LLM outputs reliable
“You can kind of think about the ontology as having this semantic layer that gives you an incredible amount of compression that you're putting into the context window and allows you to build LLM backed functions in very reliable ways.”
Jul 27, 2023 bullish
Sankar: LLMs can use APIs to dynamically generate enterprise user experiences
“The whole point is not to give me answers, but you change my app. And then that starts changing how you think about interacting with these things. It becomes a new UI layer. You know, kind of the most extreme version of this is like, why have any UI at all? If…”
Jul 27, 2023 positive
Sankar: LLMs shift IT triage from alert severity to solution consequences
“In a world where the LLM can process all the alerts and give you a stage set of actions, now you're prioritizing not on the severity of the alert, but on the possible consequences of the solution. So that, that's already an improvement in the sort function, an…”
Jul 27, 2023 positive
Jul 27, 2023
Sankar: LLMs need external tools for specialized workflows like orbital simulation
“Like an LLM is not going to know anything about orbital simulation or weapon hearing or Predicting forward inventory, 30 days from now. It's certainly not going to do that well, but with the right tool, it's going to do that quite excellently.”
Aug 24, 2023 negative
Uszkoreit: LLM compute scales with token length, not problem difficulty
“Then ultimately, the way you scale that compute depends on the prompt and how much, how long that is. The longer the prompt, the more compute you get. And it depends on, and there's of course many different screws to tweak here, the length of the response. The…”
Oct 26, 2023 positive
Noon: Generative AI solves the cybersecurity skills shortage for pennies
“Kind of classic cliches in the cybersecurity industry, like the cybersecurity skills shortage, like America needs, you know, to bring back the draft and make everyone get a security certificate or something. Okay. Like, you know, that you have like, 90% of a h…”
Oct 26, 2023 bullish
Noon: LLMs can replace traditional security log parsing and aggregation pipelines
“So much of security is is, is emitting Logs and alerts and then parsing those logs alerts again and aggregating them. You know, I spent a lot of time doing, you know, data infrastructure and analytics in my life, you know, before, after my cybersecurity grad d…”
Nov 9, 2023 neutral
Nov 30, 2023 neutral
Gil: Market will always support alternative LLM vendors for leverage
“In other words, you know, one could argue that no matter what OpenAI does, there'll always be at least one or two other suppliers or vendors or partners
For advanced LLM simply because the market always wants an alternative, even just for negotiation leverage.”
Jan 11, 2024 bullish
Suleiman: Central system routers will unlock AI rather than giant models
“And in fact, I think the key, and we can get into this obviously in a moment, but I think the key element that is going to really unlock this field is actually going to be the router. In the middle of a series of different systems which are specialized, some o…”
Jan 18, 2024 positive
Beyang Liu: Simpler baseline systems often match or beat fancy AI models
“Doing the simple thing, it establishes a baseline. Like oftentimes you'll find that like the doing the fancier thing is often sexier. And it's certainly these days it's like trendier, right? Cause you can kind of claim the mantle of like, ah, you know, I made …”
Jan 24, 2024 negative
Chen: Next-token LLM training is mimicry, imposing a natural capability ceiling
“For people that study reinforcement learning, we call it behavior cloning, which means you're just asking the AI to clone the behavior of another agent. And that is like one of the most primitive way possible to train this type of systems. Like, because if you…”
Jan 31, 2024
Feb 15, 2024 positive
Mar 21, 2024 bearish
Srivastava: Hedge funds and financial services lag in generative AI adoption
“I don't actually think they're on the cusp of it as much as, you know, you'd think, like, I, you know, if you think about a lot of this, the big data stuff, like, 10 years ago you know, the hedge funds were all over that, right? They're like, hey, there's alph…”
Mar 28, 2024 neutral
Apr 4, 2024 bearish
May 9, 2024 neutral
Elad Gil says physical size strictly limits on-device LLM reasoning capabilities
“And to some extent, if you look at an LLM, there's like three or four pieces of capability that people care about. There's sort of the reasoning part of it. There's a set of capabilities in terms of what it can do from a synthesis or other perspective. There's…”
Jun 6, 2024 neutral
Jun 6, 2024 bullish
Jun 11, 2024 bearish
Knoop: LLMs are high-dimensional memorization, not general intelligence
“Effectively what large language models do today is they are high dimensional memorization systems, right? They are trained on lots of training data. They're able to find and generalize patterns off of the training data that they're trained on and then apply th…”
Oct 8, 2024
Nov 21, 2024 bullish
Current LLM Tech Alone Requires Five Years of Economic Integration Work
“Even if we didn't train a single new language model, like, okay, all the data centers blow up. We can't improve the LLM. We only have what we have today. There's a half decade of work to go integrate this into the economy, to build all these things, to build t…”
Dec 19, 2024 negative
Torres: Customer success reps scrutinize LLM emails far more than their own
“To trust the output of an LLM to send an email to a million dollar customer. It's like, you know, when you present that to a CSM, they're like looking at it and they're like, they're questioning every word. You have no idea. They're questioning every word in t…”
Dec 26, 2024 negative
Feb 20, 2025 bullish
May 8, 2025 positive
Duolingo has retooled its entire content creation pipeline to be AI-based
“Over the last couple of years, what we did is we've retooled this whole content creation pipeline to be entirely based on large language models. I mean, it's all based on AI. So humans are not involved any longer, or very little, if at all.”
May 8, 2025 bullish
Jun 26, 2025 positive
Kohli: FunSearch made the first scientific discovery generated by an LLM
“FunSearch, which was an LLM-based agent, which for the first time, by searching in the space of programs, showed that you can come up with completely new solutions, like, and this, and made the first scientific discovery from an LLM.”
Jul 17, 2025 bullish
Laskin: Scaling RL on LLMs is the final paradigm before ASI
“The next paradigm, and effectively the final paradigm that we need to have in place before a, you know, what people used to call AGI, or now I think the goalposts have shifted to ASI, is reached, is just figuring out how to scale reinforcement learning on top …”
Aug 7, 2025 neutral
Prince: Infrastructure regulating web bots will also regulate AI-connected browsers
“I think that that's, it, it'll probably be the same fundamental infrastructure that regulates how bots access the web, that ends up regulating how browsers access the web, and a browser that Takes data and then immediately feeds it back to an LLM might have mo…”
Oct 2, 2025 negative
Oct 31, 2025 positive
Mitchell: LLMs allocate compute efficiently by deferring tasks to specialized tools
“I think, like, part of this is you can just allocate compute a lot more efficiently because you can defer stuff that the model doesn't have comparative advantage to doing to a tool that is, like, really well suited to doing that thing.”
Apr 3, 2026 positive
Periodic Labs uses LLMs to orchestrate symmetry-aware atomic neural networks
“We think about them almost as like an orchestration layer. So that's sort of a co-pilot assistant, but also like a system that can direct experiments. And it's almost, it's orchestrating other specialized models as well. So we do construct neural nets that are…”
Apr 23, 2026 negative
Herzig: Large language models are not designed for predictive enterprise tasks
“Now, if you want to do these predictions, quite frankly, then the challenge is large language models are not made for this, right? The way how they, you know, generate just one token after another, essentially, in a sequence-to-sequence modeling. I mean, They'…”