This passage is drawn from *Sources* by Alex Heath, a specialized newsletter focused on artificial intelligence and the broader technology landscape. Distributed exclusively to subscribers of *The Verge* on a weekly basis, it offers inside perspectives on emerging trends, power shifts, and behind-the-scenes moments shaping the field of AI. The latest issue highlights three dominant narratives that emerged from this year’s NeurIPS conference in San Diego: the explosive ascent of reinforcement learning as the next defining frontier of machine intelligence, the accelerating momentum of Google’s AI efforts, and, perhaps less academically but no less notably, the exuberant and sometimes chaotic social scene surrounding the event.
NeurIPS — formally known as the “Conference on Neural Information Processing Systems” — began in 1987 as a modest, academically oriented gathering of researchers devoted to the theoretical foundations of neural computation. Over the decades, however, it has transformed dramatically. Paralleling the growing cultural and economic fascination with artificial intelligence, it has evolved from an intimate research symposium into a colossal, industry-spanning spectacle. Today, NeurIPS serves as a crossroads where elite labs compete for talent, venture capitalists hunt for the next generation of AI-driven startups, and scholars and engineers converge to exchange ideas that may well define the technological landscape for years to come.
Although Alex Heath was unable to attend the conference in person this year—a regret he openly acknowledges—his curiosity about the prevailing sentiments and on-the-ground conversations in San Diego remained undiminished. To capture an authentic picture of the discourse, he reached out to a spectrum of attendees: senior engineers, pioneering researchers, and founders operating at the heart of the AI revolution. Their insights form the backbone of this report. Among those who contributed their perspectives were Andy Konwinski, cofounder of Databricks and founder of the Laude Institute; Thomas Wolf, the cofounder of Hugging Face; Roon, representing OpenAI; and a range of participants from major institutions including Meta, Waymo, Google DeepMind, and Amazon, along with several others from emerging startups and research collectives.
Heath posed the same three probing questions to each interviewee, seeking to distill the collective tone of the conference: first, which topic generated the loudest buzz and might continue to shape conversation two years from now; second, which research labs appeared to be gaining or losing momentum in the competitive AI landscape; and finally, in a lighter but telling inquiry, which of the countless events and parties managed to capture the community’s imagination.
From these exchanges, a striking consensus surfaced. As Anastasios Angelopoulos, CEO of LMArena, summarized with tongue-in-cheek intensity, “RL RL RL RL is taking over the world.” Reinforcement learning, once considered a niche subfield within machine learning, has become the new axis around which industry excitement revolves. The prevailing belief is that the future of AI advancement lies less in endlessly enlarging pretraining datasets and more in the careful fine-tuning of models for distinct, purpose-driven applications. This philosophical shift signals the field’s maturation — a recognition that smarter adaptation, not merely more data, may define the next leap forward. On the question of institutional momentum, there was similarly wide agreement: Google, particularly through DeepMind, appears to be in a resurgent phase of confidence and productivity. As Thomas Wolf of Hugging Face put it succinctly, “Google DeepMind is feeling good.”
Beyond the intellectual fervor, the social dimension of NeurIPS continues to grow just as exuberantly as its technical scope. The “party circuit,” as many attendees refer to it, unfolded at a relentless pace throughout the week. Andy Konwinski’s Laude Lounge distinguished itself as one of the marquee gatherings, attracting an eclectic mix of leading figures such as Jeff Dean, Yoshua Bengio, and Ion Stoica — emblematic of the increasingly porous boundary between research and revelry. Another event, the exclusive Model Ship cruise, brought together two hundred researchers on an invite-only voyage that, according to organizer Nathan Lambert, embodied “a commitment to the dance floor that is unprecedented at a conference event.” Roon, offering a more restrained assessment of the festivities, quipped that one could probably learn just as much by following the online chatter as by physically attending, summing up the mood with the resigned conclusion: “this is too much.”
To distill the collective reflections from NeurIPS 2023, Heath concluded by restating the guiding questions shaping his conversations: What was the single most talked-about theme of the conference—the one likely to dominate discussions well into 2026? Which laboratories, according to the informal but insightful consensus of insiders, are visibly accelerating in research power, and which may be showing signs of instability or fatigue? And, finally, which celebration—academic or otherwise—captured the attendees’ imagination the most? In a final, almost humorous twist, some participants mischievously nominated keynote sessions themselves as “the best parties,” reminding everyone that despite the commercialization and spectacle that now envelop NeurIPS, a spirit of genuine scholarly engagement endures at its core.
Sourse: https://www.theverge.com/column/841207/ai-neurips-2025
