AI in the AM: 99% off search, GPT-5.5 is "clean", model welfare analysis, & efficient analog compute

**Nathan Labenz** (0:00)
Hello, and welcome back to The Cognitive Revolution. Today, I'm pleased to share another edition of AI in the AM, the new live show format that I'm developing with my friend, Prakash Narayanan, aka Adapai on Twitter. This episode originally aired live on Friday, April 24th, starting just before 9 AM Pacific Time, which mercifully for a night owl like me, is just before noon where I live in Detroit. Our guests in order were first Anna Patterson, former Google VP of Engineering, and now founder and CEO of Ceramic AI, a company that started last year with a plan to help enterprises train their own models, but quickly pivoted to search based on the updated belief that information retrieval plus thorough fact checking is the best way to equip models with the mix of up-to-date public and private enterprise data that they need. What's so interesting about Ceramic is that their product is specifically designed for LLMs to use, and their price point undercuts other search providers by roughly two orders of magnitude. A combination that Anna hopes will be enough to unlock all sorts of new use cases and usage patterns. After that, we welcome Lukas Petersson from Andon Labs back for another chat. It had only been two weeks since we last spoke to Lukas, but the testing that he and the Andon team had done with both OPUS 4.7 and GBT 5.5 meant that we had plenty of new ground to cover. Fascinatingly, and in a definite narrative violation, Andon reports that while OPUS 4.7 still makes more money in its vending machine simulation, it does so in part by adopting ruthless tactics, which GBT 5.5 does not. Lukas describes GBT 5.5 as clean. We also hear a bit about their experience opening a new Gemini-run cafe in Sweden.
Our third guest is another returning champion, Zvi Mowshowitz. It was a bit too early for Zvi to render judgment on 5.5, but we did get into quite a bit of detail on 4.7, including how he understands the bad behavior reported by Andon Labs, and also what he makes of Anthropic's recent Model Welfare reports, including why we should care, how much we should trust the model's self-reports, and what low-cost actions he recommends frontier model companies take to improve Model Welfare at least on a precautionary basis.
Then finally we have Naveen Verma, Princeton Professor of Electrical Engineering and Co-Founder and CEO of EnCharge AI, a company that's developing a new computing paradigm that uses in-memory analog data processing to drive order of magnitude energy efficiency improvements, which, though we can't get our hands on it quite yet, promises to unlock local, private inference that consumes roughly the same power as a standard laptop does today.
As I mentioned last time, this is still an experiment, and we do expect the format to evolve. If you'd like to shape how that happens, please follow AI in the AM and send us a DM to let us know how we might make this new format more valuable for you. With that, I hope you enjoyed this edition of AI in the AM from Friday, April 24th, co-hosted with Prakash Narayanan.

**Prakash Narayanan** (3:08)
Hi, Nathan. Hi, Prakash.

**Nathan Labenz** (3:10)
How are you?

**Prakash Narayanan** (3:11)
I am good. And it is Friday, April 24th.
It is like five minutes to the beginning of our stream. And it is an exciting day, because GPT 5.5 just dropped yesterday. So, lots of reactions this morning. And it is going to be interesting to see, you know, what our guests have to say, both about GPT 5.5 and, you know, the events of the last, you know, month, a couple of months.

**Nathan Labenz** (3:44)
Yeah, man. It is going to be an interesting conversation today, because the pace of events is not slowing down at all. And Zvi, who is coming up in a little while, just expressed his exhaustion yesterday at seeing 5.5 drop. His queue seems to be getting longer, not shorter. So, I appreciate that he is going to take a half hour out and come to talk with us. And I think your thesis, you know, for why we should be doing this is looking better and better all the time.
You know, it's, live sense making is kind of demanded in this world. You can't put this stuff on the shelf and come back to it in a week.

**Prakash Narayanan** (4:21)
Yeah, yeah. The entire point that, you know, why I wanted to start doing live was because the pace of developments is going to start to be hard to keep up, I feel.
Especially because I think Noam Brown and some of the other people from OpenAI, Rune, et cetera, said that they are actually using these models in research. So we had at least Aidan McLaughlin, Rune, Noam Brown have all said that they're using them in research. And so that is going to be interesting to see. If the pace of developments, you know, we are handing off extremely powerful research helpers to the best AI researchers in the world. And if they are able to make something of them, we should see it fairly soon, right?