This is the more important half of the Ora/Vercel story and confirms a trend builders should already be acting on: harness quality and fine-tuning around a model matter as much as raw model capability for agent reliability. For teams stuck waiting on the next frontier model to fix agent flakiness, the fix might be in your scaffolding, not your model choice.
This is the real story: a century-old interlocking directorates statute getting dusted off against a top-tier VC firm's board practices, not just a Databricks-Fivetran spat. If the DOJ wins or even extracts a settlement, every large fund with multiple board seats in adjacent categories needs to audit its portfolio construction and board-seat policies now, not after a subpoena arrives.
Space-based data centers sound speculative until you notice the actual constraint driving this: grid power and land for terrestrial data centers are running out faster than anyone modeled two years ago. This is a bet that launch costs keep falling faster than the physics problems of thermal management and radiation hardening get harder. For infra investors, treat this as a hedge position, not a core thesis yet.
Greenblatt's research-culture arguments tend to be sharp and worth the listen if you care about how ML actually advances versus how it's marketed. For builders this is background context, not actionable, but it's a useful corrective to hype about ML's theoretical depth.
This isn't new law so much as a restatement of the EU's human-authorship requirement, but it matters more now that AI-generated content is a meaningful share of commercial output. For builders shipping AI-generated assets into EU markets, assume no copyright protection by default and structure contracts and IP strategy accordingly rather than waiting for a court to clarify it for you.