So there’s been this story floating around the past day or two that had my timeline absolutely buzzing. Milla Jovovich — yes, that Milla Jovovich, Alice from Resident Evil, Leeloo from The Fifth Element — apparently released an open-source AI memory system on GitHub called MemPalace that claimed to score 100% on something called LongMemEval, beating every paid solution out there.

Naturally, the internet lost its collective mind.

My first reaction, honestly, was the same as half the comments I was reading: what in the weirdest timeline are we living in? But then I put my coffee down, opened the GitHub repo, started digging through the actual issues and the community discussion, and — well, it’s complicated. And complicated is usually more interesting than the headline anyway.

There’s something deeply cynical happening in Hollywood right now, and it’s making me wonder whether we’ve learned anything from the past two decades of tech hype cycles.

Roger Avary, who co-wrote Pulp Fiction, recently revealed that after struggling to get traditional films funded, he started an AI production company and suddenly had investors throwing money at him. Three films in production, just like that. His quote really drives it home: “Just put AI in front of it and all of a sudden you’re in production on three features.”

Google’s latest AI announcement has the tech world buzzing again. Apparently, they’ve built an AI that “learns from its own mistakes in real time.” Cue the usual chorus of “holy shit” reactions and breathless headlines about revolutionary breakthroughs. But hang on a minute – let’s take a step back and actually think about what this means.

Reading through the various reactions online, it’s fascinating to see the divide between those who understand the technical details and those who just see the marketing speak. The more technically-minded folks are pointing out that this sounds a lot like glorified RAG (Retrieval-Augmented Generation) – essentially fancy context management where the AI stores its reasoning process and refers back to it when similar problems arise. It’s not actually changing its core weights or truly “learning” in the way we might imagine.