The Ledger, every show
Every statement that passed quotation and attribution checks, across all 44 shows. Pick shows below, then mix any filter with any other.
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every show 44 of 44
Bourgeau: AI progress from pre-training improvements is not slowing down
“It's still remarkable how much progress we're able to achieve in this way, and it's not really slowing down.”
Bourgeau: Google and DeepMind are actively researching post-Transformer architectures
“I believe so. There's groups doing research on the model architecture side, for sure, within Google and within DeepMind”
Bourgeau: AI development is not running out of training data
“The other part of your question are we running out of data? I don't think so, so there's more.”
Bourgeau: End-to-end differentiable retrieval and search in training will take years
“I think deep down, I do believe that the long-term answer is to learn this differentiable end-to-end way, which means probably doing pre-training or whatever that looks like in the future, Learn to retrieve as part of the training and learn how to do search as…”
Bourgeau: Retrieval-augmented pre-training could become viable in a few years
“I just think it's not unreasonable to think in the next few years, something like that might actually become viable for a leading model like general.”
Bourgeau: Gemini 3's architecture hasn't changed much from Gemini 2.5
“At the high level, I don't think the architecture has changed that much compared to the previous one. It's more of what I was saying before, where a few different things come together to gather, give a large, large improvement.”
Bourgeau: Gemini answers computer science benchmark questions taking humans significant time
“They are becoming increasingly difficult, and even for me, who has a background in computer science, some of the questions the model answers, it would take me a significant amount of time to answer.”
DeepMind's Bourgeau predicts major AI-driven scientific breakthroughs within years
“I think we will be able to make some large scientific discoveries in the next few years.”
Bourgeau: Agentic workflows will accelerate AI research tasks in the next year
“The first part, I think, especially in the next year with more agentic workflows being enabled more and more, that should be able to really accelerate our work there.”
Bourgeau: Early DeepMind research defaulted to synthetic data over real-world data
“And at the time we had to add this from real world data to the name of the project, because people would assume otherwise it would be synthetic environments or synthetic data. And that definitely has shifted completely since then.”
Bourgeau expects significant long-context AI innovations in the next year
“I think there's going to be a lot more innovation on that side in the next year or so to make long context more efficient, but also just to extend the context length of models themselves.”
Bourgeau: External AI benchmarks quickly become contaminated via web data
“What we found is that external benchmarks, then you can use them for a little while, but very quickly they become contaminated. So they start to be replicated on different forms Different forms or different parts of the web, and then if we end up training on t…”
Bourgeau: Thinking models compute across sequence length to test hypotheses before answering
“Rather than just doing compute in, in the depths or in, in the model side, you also do compute and allow the model to think more on, on the sequence length side of things. So the model actually starts to form hypotheses, test hypotheses, invoke some tools to v…”