Julian Schrittwieser
15 statements across 1 episodes · 8 bullish · 2 bearish · 1 people on the record · first statement Oct 23, 2025 by Julian Schrittwieser · across every show →
On the record as a speaker too: Julian Schrittwieser's record, appearances and statements → this page counts the times other people say the name.
Everything said about Julian Schrittwieser, oldest first
Oct 23, 2025 neutral
AI app developers do not need custom fine-tuning for top models
“I think nowadays, with the capabilities of, like, you know, top, probably cloud models, top OpenAI, GPT models, You don't need to do any fine tuning. You can take the model as is, ride your own tools, your own harness, and benefit from that agentic training. B…”
Oct 23, 2025 bullish
Oct 23, 2025
Schrittwieser: Distributing AI productivity gains is a political problem, not technological
“I think it's much more like a political, social problem of, like, figuring out how do we actually benefit from all these improvements, and, like, you know, bring the increases in wealth and productivity to everybody, and it's much less a technological problem.…”
Oct 23, 2025 neutral
Oct 23, 2025 positive
Oct 23, 2025 negative
A sudden AI singularity or intelligence explosion is extremely unlikely
“Yeah, I think a true discontinuity is extremely unlikely from, you know, obviously AI researchers are already using AI to accelerate themselves. And so what's, what's already happening and like what is likely to continue to happening is that we see like a smoo…”
Oct 23, 2025 positive
Pre-training aids AI alignment by implicitly instilling human values
“I definitely think we would keep using pre-training data, not just from an efficiency point of view as well, but also I think there is interesting safety angles, because by pre-training and, you know, all this human knowledge, we're implicitly creating an agen…”
Oct 23, 2025 neutral
AI research still lacks scaling laws for training data quality
“I think we don't have any good scaling laws yet. That tell us the trade off, especially I think because it's very hard to measure what is the quality of a data point, right? Like how good is this example compared to this other example without being able to mea…”
Oct 23, 2025 bearish
Future AI models will continue to rely on pre-training data
“Personally, I think that's unlikely. Not, not because pre-training is strictly necessary. I think we may well be able to train something completely from scratch, as we've been able to do in other domains, but more because pre-training on this vast data sets th…”
Oct 23, 2025 bullish
Oct 23, 2025 positive
Oct 23, 2025 bullish
Schrittwieser: Current AI paradigm likely to achieve human-level performance in productivity tasks
“I think if you're thinking of, oh, we want some kind of system that can perform at roughly human level in basically all tasks that we care about. Productivity wise. Then I think, yeah, it's extremely likely that the current approach, pre-training RL, you know,…”
Oct 23, 2025
Oct 23, 2025 positive
Schrittwieser: Adding model reasoning improves RL training stability and scaling
“One direction of scaling RL and making it more stable is by improving this by, for example, putting more reasoning into your language model to generate much more high quality training data. That can then give us training that is much more stable, and then we c…”