Trump Hosts AI Leaders at White House
THE SO WHAT
A White House meeting between President Trump and AI leaders, with voices like Palantir’s Alex Karp in the room, shows frontier AI policy being shaped directly with industry at the table. Regulated adopters should expect frameworks that lean on self-governance and defense narratives—track how that aligns or conflicts with your own risk posture.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIOpenAI’s latest features take direct aim at the app store model
If ChatGPT becomes a primary surface for discovering and running software — for both humans and agents — the distribution tax shifts from app stores to model and agent platforms. Founders should start modeling a world where “install” is replaced by “invoke via assistant,” and where prompt-level placement and ranking matter more than icons on a home screen.
Applied AIInterviews with Anthropic co-founder Christopher Olah and 20 religious and philosophical leaders about their summits to investigate consciousness in Claude
Once a major lab convenes religious and philosophical leaders to discuss whether its model might be conscious, AI governance moves from pure safety and economics into moral philosophy. If you’re deploying advanced models, you now have to plan for values debates and ethics reviews that look a lot more like bioethics than traditional IT risk.
Applied AIOpenAI Will Keep Driving Down Prices, Sam Altman Says
If OpenAI keeps cutting prices while pushing more capable models and agents, the margin structure of AI-native SaaS compresses toward zero for anything that looks like raw inference resale. Operators should assume per-token costs will fall and compete on proprietary data, workflow depth, and distribution—not on passing through API calls.
Applied AIOpenAI’s Dots are always-on AI agents for work
Always-on "second self" agents like Dots shift AI from a tool you invoke to a co-worker that continuously acts on your behalf—coordination, permissions, and audit trails become the hard problems. Before piloting, map which workflows you’re willing to let an agent touch unsupervised and how you’ll log and reverse its actions.