Everything Pratyush Maini said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Modern LLMs verbatim regurgitate JEE exam questions from two-word prompts
“We consistently saw how many of these, like, models today are being, like, massively, like, kind of fine-tuned on problems from... Like, oversight? Massively worked with. Like, even, like, imagine if I ask you the light bulb, what comes next in your mind? It w…”
Labs train LLMs on benchmark questions for multiple epochs late in training
“It's very clear how the last stage of training for many of these models does have a massive amount of example or examine. Benchmaxing. Because the model will not, like, behaviorally complete exam questions with options if they have not really seen it at the en…”
Self-reflection training data is now core to all frontier foundation models
“What this suggests about the GPT training data is that the self-reflection data has now actually become pretty much core to the training of all frontier models, because we're seeing that happen in non-instruct models across the board.”
Core AI capabilities must be built during pre-training, not just fine-tuned
“If there is a core capability that you actually care about, that capability should be part of the foundation and not a fine-tuned artifact.”
Enterprises will widely adopt specialized AI pre-training in 2026 and 2027
“So I think like, 26 and 27 are going to be the years where different enterprises start doing specialized pre-training, because the cost of pre-training really amortizes itself very fast.”
Small specialized pre-trained models can match capabilities of larger fine-tuned models
“When you think of the fact that by doing specialized pre-training, you can train a smaller model, which is as capable as a much larger model when fine-tuned.”
Datology BeyondWeb 3B matches NVIDIA Nemotron 8B in 2.7x less training time
“As you can see that we achieved the same performance as the NVIDIA model in almost, like, 2.7 X, like, lesser time. And then much faster than anything that hugging face or pajama does. Very interestingly, our three B model is pretty much the same performance a…”
Qwen 3 memorizes benchmark questions significantly more than Qwen 1.5 or 2
“I don't, we don't see this phenomenon like the earlier versions of like QN 1.5 or even QN two, but start seeing it in QN three. So there's something about a more, like a significantly higher weight on benchmark or like a J or like any times of evaluation quest…”
MoE models with 20B active parameters match 72B dense models in memorization
“With the coming of the MOE models, we're starting to see these phenomena, even like models which have a less number of active parameters. So a phenomena that we would observe at a 72 B model in the past is probably now visible at a 20 B active one 20 B MOE als…”
Non-reasoning Grok, GPT, and Gemini models exhibit recursive self-correction loops
“And so then I tried this across models, and I saw consistently across Grok, and GPT, and Gemini, that you were seeing this phenomena where models will, like, self-correct themselves quite a bit, and these were, like, non-thinking models. They were, like, the s…”
Pre-December 2024 OpenAI models did not exhibit seahorse emoji self-correction loops
“And so I like ran the OpenAI API across like models released from 23 to 25, and you would see like all the models until twenty-twenty-four December had very Terce and short responses to the question. Is there a seahorse emoji? They would either say that there …”
OLMo 3 injects thinking traces during mid-training rather than post-training
“So, with the instruct variant, they do not have any thinking data in the post-training phase, but they do mention that we are going to put, like this is the line that they write, there is some intentional addition of thinking traces in the mid-training phase o…”
Latent Space 1