large language model
also referred to as: large language models · llm
48 statements across 32 episodes · 16 bullish · 15 bearish · 30 people on the record · first statement Jun 2, 2023 by Barry McArdle · said 1 times in 1 episodes since 2023 · across every show →
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brought up most by June Park (1)
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2023 1 mention in 1 episode
Everything said about large language model, oldest first
Jun 2, 2023 neutral
Barry McArdle: Passing too much context into LLM prompts confuses the model
“I think we've been, we were tempted early on to try to shove as much context as we could in. You kind of figure like the more I can tell this model, the better. And you realize you can pretty easily confuse a model in terms of the amount of context you're pass…”
Aug 25, 2023
Appenzeller: Larger LLMs improve reasoning beyond mere knowledge acquisition
“For a large language model, it turns out that just making a larger model and training on more data has more benefits than just absorbing more knowledge. It also means that it's better in reasoning and, you know, understanding abstract context and then, you kno…”
Sep 1, 2023 neutral
Sep 1, 2023 bullish
Sep 1, 2023
Appenzeller: Training large language models costs tens of millions of dollars
“Training one of these large language models today is, it's not a 100,000 dollar thing, it's probably millions of dollars thing. Practically speaking, what we're seeing in industry is that it's actually more of a tens of millions of dollars thing.”
Sep 25, 2023 neutral
Nov 6, 2023
Park: Simply prompting LLMs fails to sustain long-term agent simulations
“What we found was if we want to populate the spaces over a longer period of time, so we can do, for instance, longitudinal study, or gameplay that's going to last forever, then for those kind of instances, simply prompting these models wouldn't work.”
Nov 6, 2023
Dec 16, 2023 bullish
Dec 16, 2023 negative
Lai: Cloud inference costs break traditional gaming monetization models
“The challenge is that with an AI game, if you have a game that's running a large language model in the cloud, the influence costs of serving users dynamically generated worlds or texts would probably make either of these models unprofitable right off the bat, …”
Dec 23, 2023 neutral
Dec 28, 2023
Dec 28, 2023
Mensch: LLMs function as programming languages, not standalone products
“If you look at what the LLM does, it's not really different from a programming language. It's actually used very much as a programming language by the application makers. There's a strong confusion made between what we call a model and what we call an applicat…”
Dec 28, 2023 positive
Dec 28, 2023 negative
Mensch: AI regulation should target applications, not foundational math
“What you want to regulate is the application, and the issue we had, and the issue we're still having now is, We hear a lot of people saying we should regulate the tech, so we should regulate the function, the mathematics behind it, but really you never use a l…”
Mar 5, 2024 bullish
Mar 11, 2024 negative
Mar 11, 2024 negative
Casado: LLM errors accumulate exponentially when operating out of distribution
“If it generates anything out of distribution. Like, and by the way, out of distribution means it's not commonly represented in the training set. Then that error is going to accrue and it tends to accrue exponentially provably, right?”
Mar 20, 2024 neutral
Mar 20, 2024 bullish
D'Angelo: AI UX will shift to direct source attribution over pure synthesis
“I expect that that is going to lead to some kind of product or some kind of user experience where the LLM is helping you sort through your sources and quoting exact experts or exact sources, as opposed to just synthesizing it all and giving you something where…”
Jun 19, 2024 bullish
Jun 28, 2024 bullish
Yoo: LLMs can unbundle care by automating triage, even without physical treatment
“Unbundling the role of a clinician. You know, there's one part which is actually the treatment part, so that's the part where maybe we can't necessarily today build an LLM that will stitch your finger. But the notion of triage, right and kind of getting you to…”
Jun 28, 2024 positive
Oct 22, 2024 negative
Andreessen: Major commercial AI models are heavily shackled and hobbled
“The, large language models you know, like ChatGPT from the big labs from the big companies they basically all have in common. Grok is a little bit more liberated, but with the other ones that people use, all have in common is they, they've been like, just like…”
Feb 28, 2025 negative
Ayrey: LLMs generate security vulnerabilities at rates matching junior developers
“And in fact, there's been research into how often a code spit out from an LLM has security vulnerability. And more often than not, if you ask us to develop an entire application, it'll write vulnerabilities at a rate The same as a junior developer, if not a li…”
Feb 28, 2025 negative
Ayrey: Filtering API keys from training risks degrading AI data science skills
“So if we do our reinforcement learning and we skew it towards code snippets that's generating that don't have API keys, inadvertently, we may be training this thing to behave less like a data scientist. And then we lose the entire discipline of data science in…”
Mar 15, 2025 positive
Kumar: Transcription-free conversational AI models are coming soon
“A pretty clear path that a lot of, I think, labs are taking, and we're taking as well, and will be in kind of future versions, is just kind of transcription free. Just go straight into the text component which will kind of obviate transcription entirely. That …”
Apr 14, 2025 bullish
Yudis: Transformer architectures bring LLM-style data scaling laws to autonomy
“There's a similar you know, let's say paradigm shift happening in autonomy and in vision systems as well with transformers, and so what that ultimately means in autonomy is the similar dynamics in large language models, you can put lots of data in, and you get…”
Jun 16, 2025 positive
De la Garza: ChatGPT is 100% accurate at detecting suspicious emails
“To drop a suspicious email into a, into ChatGPT and ask if it's suspicious, and it's like a hundred percent accurate, right? Like if you want to like find sensitive information, you ask the LLM, is this sensitive information? And it's like a hundred percent ac…”
Jul 28, 2025 negative
Aug 14, 2025 neutral
Lingelbach: LLMs, not video models, limit real-time AI actors
“Oh, a hundred percent. But I think that the bigger limitation is not the video model right now. I think the bigger limitation is actually that I think large language models still have a lot of work in terms of making people feel very authentic.”
Sep 9, 2025 negative
Mark Cuban says research hospitals are idiots to publish or patent IP
“Because if I'm MD Anderson, if I'm Stanford, any research hospital, any scientist in healthcare, you're an idiot if you publish it. You're an idiot if you patent it. Because it's immediately going to get absorbed into a large language model. And you've lost co…”
Oct 13, 2025 positive
Misra: Chain-of-thought prompting works by reducing LLM prediction entropy
“That's why chain of heart works. What happens with chain of thought is you ask the LLM to do something chain of thought. It starts breaking the problem into small steps. These steps it has seen in the past. It has been trained on maybe with some different numb…”
Oct 13, 2025 negative
Oct 13, 2025 neutral
Misra: LLMs hallucinate when straying from learned Bayesian manifolds
“And as long as the LLM is going in sort of traversing through these manifolds, it is confident. And it can produce something which is, which makes sense. The moment it sort of wears away from the manifold, then it starts hallucinating and start spotting nonsen…”
Oct 23, 2025 positive
Masad: Discrete verification loops unlock mathematical and coding reasoning in LLMs
“And so that, that's a resurgence of that movement where we have this amazing generative neural network that is the LLM. And now let's layer on More discrete ways of trying to verify whether it's doing the right thing or not. And let's put that in a training lo…”
Nov 6, 2025 positive
Chan: LLMs provided the breakthrough needed to analyze CZI's biological datasets
“We were already Building tools to measure interesting data. Building the data sets. But we didn't really know what to do with them yet. And large language models coming onto the scene, we're like, wow, we can make sense of all of this now.”
Nov 17, 2025
Shear: In AI agents, care equates to loss and reward correlation
“Care is basically like reward. Like how much does this state correlate with survival? How much does this state correlate with your inclusive, your full inclusive reproductive fitness? For a somewhat thing that learns evolutionarily, or for a reinforcement lear…”
Nov 17, 2025 negative
Dec 12, 2025 bearish
Mar 12, 2026 bullish
Mar 17, 2026
Mar 17, 2026 negative
An LLM trained on pre-1916 physics will never derive general relativity
“Take an LLM and train it on pre-nineteen-sixteen or nineteen-eleven physics and see if it can come up with the theory of relativity. If it does, then we have AGI. I mean, it's a high bar, but, you know, we should have high bars. It won't.”
Apr 13, 2026 positive
Jessie Genet: Prompting AI agents with curated literature prevents generic stock outputs
“The homeschool one was the most obvious one to me, because I was like, I want you to literally, like, use this curriculum or use this book as a reference point, but then I noticed how well it worked, and I was like, okay, what if I take this agent over here th…”
May 4, 2026 negative
May 12, 2026 negative
Blankfein: LLMs create systemic risk by removing institutional intuition and audit trails
“You know, one of the, you know, when you get, when you go into some of these large language models, you don't know the thought process. You lose intuition in these things. It used to be when I started out in the business, You know, people be shrieking each oth…”
May 12, 2026 neutral
Aug 5, 2026 neutral
Moe: LLM serving differs fundamentally from traditional ML workloads
“Serving large language model is a fundamentally different problem. Because serving it requires to run it on accelerators like GPUs or TPUs, and it is a computationally intensive process that will require a lot of engineering and ensuring that for each request,…”