Research accounted for 24% of the relevant conversation across 24 episodes.
How to read it
Recurrence across podcasts does not mean agreement. The cited moments show the language behind each summary.
In the discussion
Interesting. So you feel like the— so yeah, I guess how would you characterize the gap between American API models, Claude perhaps specifically, and a DeepSeek? We hear, we're, I think we kind of go through these cycles, right? Where it's like, oh, the gap is closed. Oh, maybe...
New models, training methods, benchmarks, and discoveries from AI labs.
Trend this week
Gaining attention24%of conversation
8 of 8 published weeks met the cross-podcast threshold.
15quoted moments6episodes6podcasts discussing this topic
A closer read
What changed
Its share rose from 14.8% to 23.6%, with evidence across 11 podcasts.
Where it showed up
It appeared in episodes including “Lindy Teammate: Flo Crivello on Multiplayer Agents, Memory & Why He'd Ban the Chinese Models He Uses” and “Grok 4.6 Shows How Fast Your AI Options Are Expanding”.
How to read it
6 cited episodes from 6 podcasts are shown below. The topic appeared across 11 podcasts in the full analysis.
Podcast moments from the week
15 quoted moments · 6 episodes · 6 podcasts
The Cognitive Revolution
Lindy Teammate: Flo Crivello on Multiplayer Agents, Memory & Why He'd Ban the Chinese Models He Uses
“Interesting. So you feel like the— so yeah, I guess how would you characterize the gap between American API models, Claude perhaps specifically, and a DeepSeek? We hear, we're, I think we kind of go through these cycles, right? Where it's like, oh, the gap is closed. Oh, maybe...”
“Hop. Fine-tuning as a dimension in this whole model situation. This is another thing, if I go back in time, I'm like, I definitely expected a lot more fine-tuning than we are getting.”
“what does it even mean to be a frontier lab if DeepMind is not a frontier lab? I would have just assumed that they are, but like, what does that even mean? I don't know.”
“you do not need a lot of data if you— the novelty of the paper in this work, how to incorporate everything into a reinforcement learning framework that would make it possible and training, fine-tuning such models would be also kind of very affordable.”
“You know, Sam, which something I like to also add, because it is related to what we are talking about now. Optimization, of course, is right objective optimization at the right data is definitely very critical. That is what this paper is talking about, but we may also kind of ...”
“I see. So the tokens go in, the transformer establishes the relationship between the different tokens, and then the diffusion model turns that represent— that latent representation into a 3D structure.”
“we're getting to the point now where these structure prediction models are within, you know, a few angstroms or less of the actual atomic positions that you validate.”
test the theory that Kimi K3 and GLM 5.2 had reached frontier performance at a fraction of the cost. In practice, what the study found was that at least for this use case, they were both around the same level as Sonnet 5 and much more expensive than GPT-5.6 SOL.
Lindy Teammate: Flo Crivello on Multiplayer Agents, Memory & Why He'd Ban the Chinese Models He Uses
One big question that brings to mind is how you are managing caching. And then caching is, of course, is just one, you know, angle on managing cost in general. So maybe we could expand beyond caching and talk about cost management.
Its share fell from 32.4% last week to 29.7% this week, reversing the previous week's rise.
Share of this week’s podcast conversation
Recent weeks31.9%→This week29.7%
Came up less often than in recent weeks.
Podcast moments5 cited momentsViewClose
The AI Daily Brief
The New Problems AI Is Creating (And How People Are Solving Them)
In fact, if anything, the speed with which organizations are adapting to this being the new challenge set should be extremely encouraging for the corporate sector overall.
Lindy Teammate: Flo Crivello on Multiplayer Agents, Memory & Why He'd Ban the Chinese Models He Uses
Just for calibration, how many tokens are you finding businesses have? Like when you say with these 2 levels, you can get to 2 billion tokens. I don't have a great intuition for, does that cover a 20-person team? Does it cover a team that's been in business for 5 years? What's...
That said, now think of a company that's got, you know, 3 to 7 hours of meetings per day per employee, you know, times 2,000 employees. That, that is, that meetings are when you really start to rack up tokens really, really quickly.
Its share rose from 14.8% last week to 23.6% this week, reversing the previous week's drop.
Share of this week’s podcast conversation
Recent weeks17.2%→This week23.6%
Came up more often than in recent weeks.
Podcast moments5 cited momentsViewClose
The Cognitive Revolution
Lindy Teammate: Flo Crivello on Multiplayer Agents, Memory & Why He'd Ban the Chinese Models He Uses
Interesting. So you feel like the— so yeah, I guess how would you characterize the gap between American API models, Claude perhaps specifically, and a DeepSeek? We hear, we're, I think we kind of go through these cycles, right? Where it's like, oh, the gap is closed. Oh, maybe...
Hop. Fine-tuning as a dimension in this whole model situation. This is another thing, if I go back in time, I'm like, I definitely expected a lot more fine-tuning than we are getting.
what does it even mean to be a frontier lab if DeepMind is not a frontier lab? I would have just assumed that they are, but like, what does that even mean? I don't know.
Lindy Teammate: Flo Crivello on Multiplayer Agents, Memory & Why He'd Ban the Chinese Models He Uses
I think like what we are releasing today is called Lindy teammate. It is an AI employee that lives in your Slack, connects to all of your tools, accumulates your entire teams context. And it's really like a team scaffold. I think like AI right now is in the middle of making th...
