Mixture of Experts

Visit Mixture of Experts podcast page to get more AI content → https://www.ibm.com/think/podcasts/mixture-of-experts
This week on Mixture of Experts, host David Zax is joined by Kaoutar El Maghraoui, Nick Gallagher, and Volkmar Uhlig. First, Microsoft, OpenAI, Perplexity, and Cloudflare follow TypeSafe’s Jev in building decision models, a new category of AI built to make fast, scored judgments. The panel debates whether these models are truly new or a more efficient application of existing technology, and whether better-calibrated confidence scores can help address the overconfidence problem in LLMs. Next, a new study finds that teams of AI agents can cost two to five times more than a single agent without consistently delivering better results. The panel discusses when multiple agents are worth the added cost and complexity. Finally, Anthropic updates its usage policy to prohibit “sustained and needless abusive or cruel behavior” toward its models, raising a bigger question: Is this about protecting AI, shaping human behavior, or something else entirely? The panel considers the ethical implications and whether the policy could also be a marketing play.

00:00 – Intro

01:17 – Inside the decision model boom

10:54 – When are agent teams worth the cost?

23:39 – Anthropic's new usage policy

All that and more on Mixture of Experts.

"The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. AI tools may be used to transcribe this episode and support selected stages of the production process. All AI-assisted content is reviewed by the production team before publication."

Visit Mixture of Experts podcast page to get more AI content → https://www.ibm.com/think/podcasts/mixture-of-experts

Can AI take mathematics beyond human understanding?

This week on Mixture of Experts, host David Zax is joined by Kush Varshney, Skyler Speakman, and Utsav Dholakia. First, OpenAI introduces Dots at DevDay, and Utsav shares his firsthand impressions as the panel discusses whether persistent AI agents can truly work independently. Next, OpenAI releases more than 700 AI-generated math manuscripts, raising questions about the future of mathematics and whether humans can keep up with AI-generated math. Then, HackerRank’s Chakra brings AI to job interviews, prompting a debate about bias, access to opportunity, and how we evaluate candidates. Finally, Reflection AI unveils Beam, giving the panel an opportunity to explain mixture of experts models and the difference between open-weight and open-source AI.

00:00 – Intro

00:58 – Inside OpenAI DevDay and Dots

9:08 – AI generates 700+ math manuscripts

16:03 – HackerRank’s AI interviewer

24:18 – Mixture of experts models, explained

All that and more on Mixture of Experts.

"The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. AI tools may be used to transcribe this episode and support selected stages of the production process. All AI-assisted content is reviewed by the production team before publication."

Visit Mixture of Experts podcast page to get more AI content → https://www.ibm.com/think/podcasts/mixture-of-experts

What makes an AI company pull the plug on a model release? This week on Mixture of Experts, our newly minted full-time host David Zax is joined by Chris Hay, Madison Gooch, and Ash Minhas. First, OpenAI cancels the release of GPT-6.1 Astra, as the panel debates whether self-restraint is becoming a competitive advantage in AI or just good marketing. Then, Anthropic releases Sonnet 5.5, prompting a discussion about what happens when mid-tier models approach top-tier performance on some tasks. Finally, Meta Muse is making powerful AI agents more accessible to everyday users. We look at how these frictionless user experiences could shape what people expect from AI at work.

00:00 – Intro

01:18 – OpenAI cancels GPT-6.1 Astra release

11:44 – Anthropic releases Sonnet 5.5

23:07 – What Meta Muse means for enterprise AI

All that and more on Mixture of Experts.

"The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. AI tools may be used to transcribe this episode and support selected stages of the production process. All AI-assisted content is reviewed by the production team before publication."

Visit Mixture of Experts podcast page to get more AI content → https://www.ibm.com/think/podcasts/mixture-of-experts

It's been a wild week in AI, and on episode 126 of Mixture of Experts, host Tim Hwang and co-host David Zax talk to panelists Kaoutar El Maghraoui, Gabe Goodhart and Martin Keen to discuss what all these releases have in common: efficiency.

We start with the model release pile-up. Anthropic shipped Claude Opus 5.5, and OpenAI launched GPT-6 Sol and Luna. Opus 5.5 is 20% cheaper than earlier Opus models, while GPT-6 Luna costs half what its predecessor did, at just 10 cents per million input tokens. We look at what a real price war means for developers building on these models and the companies racing to lower costs.

Next, we look at a different idea altogether. TypeSafe AI has introduced "System One" models, starting with Jev, which give up the florid text generation in exchange for fast, structured decisions with calibrated probabilities. The pitch is frontier-level judgment on decision tasks, and responses in hundreds of milliseconds. We weigh the bold speed and cost claims against the company's own caveats about how its benchmarks were built.

Finally, we leave the chat window entirely. NASA and IBM have released an open-source Lunar Foundation Model, free on Hugging Face and GitHub, and trained on roughly 2 million image tiles from the Lunar Reconnaissance Orbiter and other missions. Researchers can fine-tune it to map craters, spot young volcanic features and estimate where polar ice may be stable, proving models can do more than vibe code. All that and more on this week’s Mixture of Experts.

00:00 – Intro

1:05 - Anthropic and OpenAI update AI models

11:10 - TypeSafe AI unveils Jev AI model

29:29 - NASA and IBM build lunar AI model

"The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. AI tools may be used to transcribe this episode and support selected stages of the production process. All AI-assisted content is reviewed by the production team before publication."

Visit Mixture of Experts podcast page to get more AI content → https://www.ibm.com/think/podcasts/mixture-of-experts
On episode 125 of Mixture of Experts, host Tim Hwang and co-host David Zax are joined by Mihai Criveti and Abraham Daniels to discuss the back and forth of frontier AI development, IBM’s latest Granite news, and what’s next for personal agents.

We open with the biggest story in tech: Anthropic CEO Dario Amodei's call to pump the brakes on frontier AI development. In a widely discussed essay, Amodei argued the industry must slow the pace at which it improves AI model capabilities, warning that progress will still feel fast even so. But will independent evaluators and more enforcement really slow down the fastest moving companies?

Then Abraham Daniels discusses the latest changes coming to IBM’s Granite 4.2 and its open enterprise-focused models in 3B, 8B, and 30B sizes built for reasoning, tool use, coding, and agentic workflows.

Finally, we discuss Meta’s push into personal agents with Muse: a personal AI agent that runs on its own secure virtual machine, works across a person's daily apps, can make purchases on your behalf, and learns from conversations to get smarter the more you use it.

Slowdown rhetoric, updates to Granite, and agents that shop for you. All that and more on this week’s Mixture of Experts.

00:00 – Intro

1:13 - Anthropic’s AI development dilemma

15:29 - IBM releases Granite 4.2

25:44 - Meta launches Muse agentic AI assistant

"The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. AI tools may be used to transcribe this episode and support selected stages of the production process. All AI-assisted content is reviewed by the production team before publication."