What podcasts say about Nathan Lambert
Every statement, with the speaker, the exact quote and the moment it was said.
What Nathan Lambert has said on podcasts
30 statements · 19 positive · 6 negative · 4 mixed · 1 neutral
Anthropic’s relatively orderly organizational culture provides a competitive advantage.
“Anthropic seems to at least be presenting as the least chaotic is a bit of an advantage.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 19:52
Chinese companies will continue releasing open-weight models for several years.
“I would say for a few years.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 21:20
Open-model builders will increase during 2026 rather than consolidate immediately.
“I don't expect that to be a story of 2026 where there'll be more open model builders throughout 2026 than there were in 2025.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 22:13
Gemini will continue gaining ground against ChatGPT during 2026.
“I think Gemini will continue to take progress on ChatGPT.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 26:27
Anthropic will continue succeeding in enterprise software and coding.
“I think Anthropic will have continued to success as they've again and again been set up for that.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 26:48
Google has an infrastructure advantage from vertically integrated hardware and data centers.
“Google has just kind of a historical advantage there.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 27:35
US language models currently produce better outputs than Chinese open models.
“I just think the simple thing is the US models are currently better and we use them.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 36:01
Chinese open models tend to be larger mixture-of-experts systems with higher peak performance.
“the Chinese open language models tend to be much bigger and that gives them this higher peak performance as MOEs”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 45:16
Nvidia is expected to release open mixture-of-experts models around 400 billion parameters in Q1 2026.
“Nvidia have teased MOE models of this way bigger than 100 billion parameters, like this 400 billion parameter range coming in this Q1 2026 timeline.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 45:44
Serving frontier models to users costs far more than training them.
“These models the cost of training them is really low relative to the cost of serving them to hundreds of millions of users.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 1:07:00
Pretraining scaling is unlikely to stop improving model performance.
“I think fundamentally it is pretty unlikely to stop”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 1:09:14
A $2,000-per-month AI subscription will appear during 2026.
“we will see a $2,000 subscription this year.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 1:10:12
Children should not receive highly personalized conversational AI before its effects are understood.
“Like, I think that like, don't give that to kids. Like don't give that to kids at least until we know what's happening.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 1:39:57
Low-compute researchers can maximize impact by pursuing narrow evaluations of frontier-model weaknesses.
“if you want to scope the maximum possible impact with minimum compute, it's something like that which is just get very narrow”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 2:29:18
OpenAI’s average annual employee compensation exceeds one million dollars in stock.
“The amount of OpenAI's average compensation is over a million dollars in stock a year per employee.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 2:30:10
A key AI milestone is replacing remote workers performing digital information tasks.
“a key milestone among the AI community is essentially when AI could replace any remote worker taking in information and solving digital tasks and doing them.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 2:53:52
LLM context windows may reach 2–5 million tokens in 2026, but not 100 million.
“I would expect it to keep increasing and get to 2 million or 5 million this year. But I don't expect it to go to 100 million.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 2:59:33
Home learning robots are unattractive, while self-driving and industrial automation are promising.
“I'm so bearish on in home learned robots for consumer purchase. I'm very bullish on self driving cars and I'm very bullish for robotic automation.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 3:13:05
AI is unlikely to automate AI research within the timeframe discussed.
“I would say probably not, at least in this timeframe.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 3:19:43
Software automation will increase dramatically by the end of 2026.
“By the end of this year, the amount of software that'll be automated will be so high.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 3:20:19
AI will shift software engineering toward system design and outcome specification.
“software engineering will be driven more to system design and goals of outcomes”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 3:21:12
Current computer-use systems from Claude and OpenAI perform poorly.
“We saw multiple demos in 2025 of like Claude can use your computer or OpenAI had CUA and they all suck.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 3:32:49
Software automation may advance substantially while computer use requires additional innovation.
“We might get this software solution, but it might stop at software and not do computer use without more innovation.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 3:36:41
If scaling laws remain fundamental, increasing compute will continue driving deep-learning progress.
“If scaling laws are fundamental and deep learning, I think the bitter lesson will always apply, which is compute will become more abundant.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 3:37:10
The United States should invest in building leading open AI models.
“the US should be building the best models so that the best research happens in the US”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 4:05:12
Banning globally trained open models would require an impractical US internet firewall.
“I think effectively that's impossible without making the US have its own great firewall”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 4:10:44
If progress saturates soon, optimized open models will win because they are cheaper to run.
“open models will be so optimized and so much cheaper to run that they will win out.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 4:12:34
Nvidia’s Jensen-centered operating culture supports continued competitive progress.
“So long as that is how it operates. I'm pretty optimistic for their situation”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 4:17:57
Universal basic income will not by itself solve human agency.
“I think that UBI does not Solve agency.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 4:30:03
AI-generated slop will increase demand for physical goods and in-person events.
“The next few years are definitely going to be an increased value on physical goods and events and even more pressure on slop.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 4:31:55
Statements are attributed to the speaker as said on the episode and reflect their view at the time, not PodLume's. They are not advice.