Person
Alex Kantrowitz
Host, Big Technology Podcast
Kimi K3 & AI’s Price War, What Happened To Google?, OpenAI’s Partner Trouble
This episode argues that frontier AI intelligence is getting commoditized as Chinese open-weight models like Kimi K3 pressure OpenAI and Anthropic on price, performance, and margins. The hosts also dissect Google’s delayed Gemini rollout and OpenAI’s growing list of strategic and legal partner problems, especially with Apple.
AI Pioneer Jürgen Schmidhuber: AI Already Feels Pain, Loves, and Is Self-Aware
Jürgen Schmidhuber argues that today’s best AI is still mostly text-bound, not AGI, and says the missing ingredients are world models, planning, and better physical hardware. He also makes sweeping claims that AI already supports pain-like signals, self-awareness, mind uploading, and a deterministic view of free will.
OpenAI Finally Ships Its Superapp, Meta’s AI Price War, ChatGPT Cheating At Brown
OpenAI’s new super-app-style workflow and ChatGPT Work signal that AI products are converging around integrated, do-the-work interfaces. The episode also digs into Meta’s aggressive pricing strategy, potential cloud business, and a Brown University case that raises fresh questions about AI cheating and how education should adapt.
Meta CTO Andrew Bosworth: Our Path To Frontier AI, Renting Models, Consumer AI's Struggles
Andrew Bosworth says Meta’s AI comeback is shifting from chasing one giant model to layering frontier, distilled, and task-specific models inside products people actually use. He also argues the company’s long-term edge will come from glasses, distribution, and consumer workflows—not from model benchmarks alone.
Who Wins The AI Superapp Battle?, Apple’s Consumer AI Victory, World Cup Automation Mistake
M.G. Siegler and Alex Kantrowitz argue that AI is converging on a “super app” layer, but winning it will depend on whether agentic workflows become genuinely useful for mainstream users. They also make the case that Apple may be the consumer AI winner by default, while warning that automation can produce technically correct but socially bad outcomes, as in the World Cup VAR example.
Zuckerberg’s Disappointment, OpenAI’s Equity Gamble, Alex Karp’s Rally Cry
Meta’s AI agent push appears to be stalling, while the broader AI market may be concentrating around a few model providers and infrastructure sellers. The episode also covers Microsoft’s Copilot reset, Google’s hedging strategy, Palantir’s warning about frontier-lab concentration, and the bizarre report that OpenAI’s Sam Altman floated a U.S. government equity stake.
OpenAI President Greg Brockman: Our Plan To Merge Chat And Agents
Greg Brockman argues OpenAI is moving from chat to agentic systems that can act across apps, tools, and devices with minimal interface friction. He also says compute will remain the key constraint, pricing will keep falling for current intelligence levels, and AI’s biggest near-term social upside may be in health.
Anthropic’s Mythos is Back, OpenAI Releases GPT 5.6, Apple’s Price Increases
The episode centers on the U.S. government’s emerging role as a gatekeeper for frontier AI releases, as Anthropic’s Mythos/Claude access is loosened and OpenAI’s GPT-5.6 is previewed only to trusted partners. The back half turns to Apple’s price hikes, which Alex and Ranjan argue look more like margin expansion than simple pass-through of memory costs, before closing with a tribute to Om Malik.
Anthropic's Labs Lead On Fable's Capabilities + Building AI-Native Products — With Mike Krieger
Mike Krieger describes Anthropic Labs as the internal engine for turning rapidly improving models into usable products, from Claude Code and computer use to more agentic workflows. He also discusses safety tradeoffs, token efficiency, outcome-based pricing, and why Anthropic sees itself as both a platform and a product company.
The Fable Ban's Unintended Consequences + AI's New Economics — With Aaron Levie
Aaron Levie and Alex Kantrowitz unpack the Anthropic/Fable export-control episode as a potential turning point for AI regulation, with governments moving closer to approving or restricting model releases. They also debate how open-weight models, cheaper inference, and rapidly rising token consumption are reshaping AI economics and where the value will accrue.