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.
shows 
every show 44 of 44
Lenz: Model providers should not dictate enterprise AI policies
“Right now, if you're using a model, you're taking in their own policy. Even if I want to use GPT-OSS, I've taken in a lot of different policies about what to abstain from, what's considered dangerous and not dangerous, how I should behave, etc. And I don't thi…”
Lenz: Local smartphone AI requires hybrid models due to KV cache limits
“So if you wanted to do something local on your phone to search your images, as an example, you can't do that without a hybrid architecture or without doing drastically changes because the model plus KVCache won't fit.”
Lenz: Most enterprises avoid reasoning models due to high latency
“Most enterprises don't really want to use reasoning models. The latencies is too high”
Lenz: Hybrid Transformer models are here to stay for long context
“If I had to guess hybrid models are here to stay just because the efficiency without sacrificing the performance is, is too much to give up. You know, the attention is so expensive. The quadratic cost and the linear memory cost is so much that I think for long…”
Lenz: Middle attention placement at 1:8 ratio optimizes hybrid models
“Putting it the first or the last performed worse than in the middle. And one to eight was good enough. You know, you might get very slight improvements with one to six, but it was marginal, maybe within the standard deviation.”
Lenz: Full attention models will decline as sequence lengths rise
“I can definitely see sequence length rising, and I can't see full attention models being as prominent as they are today. So, so, so at least they'll have less full attention layers and I hope they'll have more innovations like Mumbai.”
Lenz: No open-source infrastructure can train very large models
“And we're using our own infrastructure to train our models. There still isn't an open source infrastructure that I could say, use this to train your very, very large model.”
Lenz: Engineers seeking online answers are not at the frontier
“And I'm looking for people that try to solve problems on their own. Because if you think you're gonna found the answers online, I think you're not in the frontier.”
AI21 CTO: AI systems must be model-agnostic and action-oriented
“AI systems need to be model agnostic. They shouldn't care about which model that they use, and they should look at what I call actions, which is a combination of a model with a prompt and maybe a set of tools that it can use and say, what can an action do for …”
Lenz: RL training wastes compute on saturated or impossible examples
“Once you've trained a few hundred steps of let's say GOP, Most of your training is just wasted on example that are either too hard for you and you didn't get any success on them or too easy and everything was a success.”
Lenz: AI21's Jamba is the first hybrid model architecture
“Since then, we've released several models, recent model lines in called Jamba, which I think the fascinating part about it is, is the first hybrid model. It's not just attention.”
AI21 CTO: Jamba 3B uses 1:12 attention ratio to cut memory footprint
“So this is a three B dense with only two attentional layers. It's one to 12 and not one to eight, because we wanted to maximize the efficiency. It has very few attention heads, so everything is geared To have, you know, long context with very little memory.”
Lenz: 3B models cannot be generalized and must be task-tailored
“Because again, three B models, they need to be tailored for tasks. It's not like you could squeeze whatever you wanted into them.”
Lenz: Training foundation models mirrors developing algorithmic trading strategies
“So, so it's very similar in terms of how you interpret results. You want to treat everything as a black box. You want to establish your bounds, you know, what are you, and I've had tons of experience in algotrading, both from making money and not making money …”
Lenz: GPT-4o is an AI orchestration system, not a raw model
“GPT-IV-O is already an AI system. It's not calling a model directly. It can do certain, you know, it can do tool calls. It can orchestrate this entire thing.”