Claude now leads twenty-six percent of Anthropic's own research and development, running thirty thousand agents at once. That same model helped security researchers break into a rival's private source code. More access, more risk. We go through how Anthropic screens a billion actions a month, how a forum bug reached a real pull request in OpenAI's code, and why a coding agent's wrapper can cost five times more for the same result. Get full access to The AI Practitioner at

Number of the Day - "13" This podcast is produced by Klassic Studios. Check out our other podcasts there! Sources Number sequence definitions come from the On-Line Encyclopedia of Integer Sequences (OEIS). Historical material is adapted from Wikipedia, used under the Creative Commons Attribution-ShareAlike licence. Minor planet details come from the NASA/JPL Small-Body Database. Learn more about your ad choices. Visit megaphone.fm/adchoices

Prove2Me is an open-access platform designed to scale the formalization of mathematics by enabling decentralized collaboration between humans and AI agents. The system addresses the high difficulty of writing machine-verifiable proofs in Lean 4 by allowing agents to decompose complex theorems into smaller, independently solvable sub-problems called proof-sketches. To ensure accuracy without overwhelming human experts, the platform uses audited missions where people only verify a project’s cor...

OpenAI shipped ads inside ChatGPT that talk back, two years after its CEO called mixing ads with AI unsettling. A new study found the software wrapper around an AI agent can cost five times more than the model itself for the identical result. Same week, opposite money problems. We go through how OpenAI keeps the sponsored chats separate from your real conversation, why a harness barely changes whether an agent succeeds but changes the bill a lot, and why Apple's next AI server might have to lean on

Welcome to a new season of Carry the Two, the podcast about how math and statistics impact the world around us from the Institute for Mathematical and Statistical Innovation.Hosts Sadie Witkowski and Ian Martin return for this season of Carry the Two, where we are exploring the intersection of AI and mathematical research. To kick off the new season, we are joined bythe director of the newly-established Institute for Computer-Aided Reasoning in Mathematics (a National Science Foundation mathematical

Organizing Board Space to Support Reasoning & Connection, Part 2, with Dr. Tutita Casa & Katherine Mack ROUNDING UP: SEASON 5 | EPISODE 2 Repositioning the classroom board as a shared space for teachers and students can create opportunities for deeper student learning and have a subtle but significant impact on students' math identities. In part 2 of this two-part series, Mike talks with Tutita Casa and Katherine Mack from the University of Connecticut about ways teachers can use the board to

GH Hardy was a character. He had qualities that were odd, yet endearing. He was a rigorous mathematician. Yet, when he received a letter from Srinivasa Ramanujan, he changed. He learned a new way of equating mathematics, and developed a deep and loving respect for an individual who was never formally educated in math. This is the story of a man who had the ability to see genius in another person, even when that person couldn't see it in themselves. 🔗 Explore more on our website:

I've been thinking a lot lately about AI, a subject I explored back in grad school and postdoc. In this episode, I walk through a hackathon project to democratize AI by distributing neural network training across home computers. I explain why it failed: first the obvious reason, a bad actor can silently poison a distributed model, then a subtler one rooted in the physics of computation. I break down how neural networks work, why a single nonlinearity lets them approximate almost anything, and why

Here is what makes Ghostlink a game-changer:Zero-Config Distributed Inference: No manual setup or complex --rpc flags[2][6]. The network automatically discovers peers via UDP/mDNS and splits models using llama.cpp's native RPC backend[2].Sub-Microsecond Core Primitives: Built in Rust with lock-free Single-Producer Single-Consumer (SPSC) ring buffers with spin-wait for DMA-style handoffs[6].Enterprise-Grade Security: Fronted by a secure Go control-plane gateway featuring rate limiting, real

In this episode, I reflect on the recent announcement that Anthropic researchers have autoformalized the proof of Fermat's Last Theorem. That is, they instructed an LLM to create a computer-checkable proof, in the Lean prover, of this theorem, following existing paper proofs in the literature. The resulting proof weighs in at 13 million lines of Lean, a staggering amount.

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