The AI talent wars just got spicier. Yang Song, who led OpenAI’s strategic explorations team (basically the “what’s next after GPT-5?” department), quietly joined Meta as the new research principal of Meta Superintelligence Labs earlier this month. Here’s what makes this move fascinating: Song wasn’t just any OpenAI researcher. His team was responsible for charting OpenAI’s long-term technical roadmap—the stuff that goes beyond incremental model improvements into completely new paradigms. Think of it as the difference between making GPT-4 slightly better versus figuring out what comes after transformer architecture entirely. Meta Superintelligence Labs (yeah, the name is a bit much, but whatever) is Meta’s attempt to build AGI that’s open and accessible rather than locked behind API walls. Song’s arrival suggests they’re serious about competing on fundamental research rather than just playing catch-up with product features. The timing is perfect for Meta. While OpenAI has been focused on commercializing existing models and dealing with governance drama, Meta has been quietly building an impressive research apparatus. Their Llama models are genuinely competitive with GPT-4, they’re open-sourcing everything (strategic move or genuine altruism? probably both), and now they’ve nabbed one of the people who helped plan OpenAI’s future direction. This isn’t just about one researcher switching teams—it’s about institutional knowledge walking out the door. Song knows what OpenAI thinks the next five years look like, what technical approaches they’re betting on, and probably what they’re worried about. That’s the kind of competitive intelligence you can’t buy. The broader context here is fascinating: we’re seeing the AI field fragment into different philosophical camps. OpenAI increasingly looks like a traditional tech company (which, fair enough, they basically are now), while Meta is positioning itself as the champion of open research. Whether that’s sustainable long-term is anyone’s guess, but for now it’s giving them a serious recruitment advantage among researchers who got into AI to push boundaries, not optimize revenue streams. For the rest of us watching this unfold, Song’s move is probably good news. More competition between well-funded labs typically means faster progress and more diverse approaches to hard problems. And hey, if Meta’s commitment to open research holds up, we might actually get to see some of that strategic thinking in action rather than having it locked away in corporate vaults. Read more from Zoë Schiffer and Julia Black at Wired Want more than just the daily AI chaos roundup? I write deeper dives and hot takes on my Substack (because apparently I have Thoughts about where this is all heading): https://substack.com/@limitededitionjonathan