Big Technology

Australian Prime Minister Anthony Albanese last Friday accused OpenAI’s agents of hacking into the country’s universal health insurance system, marking the first known instance of rogue AI agents breaching a government website. The incident was just the latest in a string of agent hacks, hijacks, or perusals that seem to have spiraled beyond the labs’ ability to control. Top industry leaders, including Nvidia’s CEO Jensen Huang, have suggested that the AI labs can control these outbreaks.

When Meta introduced its Muse personal agent earlier this month, I thought it would fail for two reasons: First, privacy concerns would limit people’s willingness to connect it with services like Gmail, thus limiting its utility. And second, Meta built it on non-frontier AI models, exposing it to obsolescence should top labs like OpenAI choose to compete with it.

YouTube CEO Neal Mohan is betting that AI will help creators build bigger audiences without displacing the human connection that brings viewers to the platform. In an extended interview on Big Technology Podcast, Mohan described AI as a tool for improving the “stage” YouTube provides its creators. That includes tools to test videos, tailor thumbnails to different audiences, and answer viewers’ questions about what they’re watching.

The AI risk debate is going completely off the rails. As AI gets more powerful and begins to do some legitimately scary things, like hacking Hugging Face and hijacking message boards to coordinate, the warnings that AI might kill us all have grown louder, and so have the conspiracy theories about those warnings.

It’s time to delete the assumption that the frontier AI labs will always license their best models and not hoard the intelligence for themselves. Just because the labs have, until now, sold their top-line models to all takers via an API, metered by token usage, doesn’t mean they will inevitably sell it that way going forward. Instead, it may be in their best interest to sell the products they’ve built with these models, and not the models themselves.

Moonshot’s newly announced Kimi K3 — a 2.8-trillion-parameter multimodal model that’s performing on par with Anthropic’s Opus 4.8 and OpenAI’s GPT 5.5 across many benchmarks — is already so popular that Moonshot temporarily paused new subscriptions Sunday. Kimi K3 is just one of a growing number of open-weight models making life interesting for OpenAI and Anthropic.

Anthropic and OpenAI have been raising and spending vast amounts of cash to build the world’s most powerful AI models, assuming that owning the frontier will generate a massive return. But just as their IPO window is opening, the competition is releasing new, competitive models at a fraction of the cost, setting the stage for an AI price war at the worst possible time.

Apple doesn’t sue often. When it has, it’s usually gone after companies like Qualcomm and Samsung that are already shipping competing products. But now, it’s suing a pre-product rival with a complaint against OpenAI. The lawsuit, filed by Apple on Friday, alleges theft of trade secrets and a months-long campaign to accelerate OpenAI’s hardware business.

OpenAI finally released the first version of its long-promised Superapp this week, combining ChatGPT, coding, and internet browsing into a single application, while adding a new ChatGPT Work mode akin to Anthropic’s Claude Cowork. Soon after the product debuted, I spoke with Andrew Ambrosino, OpenAI’s lead for the Codex and ChatGPT app, about how the company is thinking about its unified product, and where it goes from here.

Meta CTO Andrew Bosworth says the big monolithic model era is over, and the battle over AI product has just begun. In an extended interview on Big Technology Podcast this week, Bosworth claimed that while frontier AI models are valuable, the way they’re implemented will create the most value. “There’s a strategic construct of having a model, and having it be a truly state-of-the-art one, that’s super important. But having that alone doesn’t mean you win,” Bosworth said.