LLMs
15 statements across 13 episodes · 9 bullish · 5 bearish · 9 people on the record · first statement Feb 11, 2023 by David Friedberg · across every show →
Everything said about LLMs, oldest first
Feb 11, 2023 neutral
Friedberg explains LLMs generate non-deterministic statistical inferences, not static discrete outputs
“These are also not deterministic models, and they're not deterministic outputs, meaning that it's not a discrete And specific answer that's going to be repeated every time the model is run. These are statistical models. So they infer what the right answer coul…”
Feb 11, 2023 bearish
Palihapitiya argues limiting AI tokenization to sentence blocks severely degrades quality
“If you limit How they can tokenize to just being all entire sentences. The product will not be that good. Like the whole idea of these LLMs is that you're running, you know, so many iterations to literally figure out what is the next most best word that comes …”
Feb 17, 2023 bullish
May 19, 2023 negative
Friedberg: Regulating and auditing local LLM deployments will be nearly impossible
“I think that the point of view is just that this is going to be a near impossible task to try and track and approve LLMS and audit servers that are running LLMS and audit apps and audit what's behind the tools that everyday people are using.”
Sep 26, 2023 negative
Khosla: Major AI companies are overly focused on scaling LLMs
“Almost all the efforts I have seen are very limited. They're all trying to scale LLMs. And, you know, I spend my time looking at what besides LLM will play An important role. I haven't seen one effort among the majors that isn't following the same model.”
Dec 29, 2023 positive
Feb 15, 2025 bullish
Sep 27, 2025 positive
Friedberg: MIT-Microsoft framework achieves 94% planning accuracy on LLM benchmarks
“And they were able to achieve planning accuracy of up to 94% on some standardized benchmarks that are used for chain of thought reasoning and planning Using LLMs. This is a 66% absolute improvement over baseline models.”
Sep 29, 2025 positive
Dec 6, 2025 bullish
Jan 25, 2026 positive
Goldstein: LLMs will first bridge pilot-to-machine communications in aviation autonomy
“With the advancements of LLMs, it actually allows this interesting period of time where you can now communicate with a machine in a way you couldn't really before, and so there's this probably middle ground that happens where there's pilots talking to machines…”
Jan 25, 2026 negative
Kurtz: LLMs empower less-skilled hackers to execute nation-state level cyberattacks
“You're minting new adversaries because you don't have to have all the knowledge that you had to have in the past. You can ask any number of LLMs and you can get answers back. So what's happened is the attack timeline has been compressed. You can automate all o…”
Jun 2, 2026 bullish
Friar: LLMs are not commoditizing because value lies in agentic layers
“A year ago people talked about the commoditization of the LLMs. And frankly, it's gone the opposite because as you start building an agentic layer, and we've all started to use this word harness, but the harness is what brings the context, the memory, right?”
Jun 6, 2026 negative
Marshall: Current LLMs are blind to real-world physical data
“I like to say, like, all the cool stuff that we're doing on the, with LLMs now, is really based on just the text of the internet being absorbed into these models, which is incredibly powerful already, but they don't know shit about the real world. I call them …”
Jul 14, 2026 positive
Calacanis: LLMs perform better with long, spoken stream-of-consciousness prompts
“What these LLMs actually do really well with is taking a massive stream of consciousness where you just keep talking and talking and talking, so I'll give it a one to two minute prompt, then I let go, and it has changed everything.”