"The vast majority of my day is spent... on calls with founders and researchers and investors and basically just like begging them and being like, hey, like what's like the hottest gossip that you guys know or like what's like the coolest new trend in AI that that you've seen." This candid revelation from Steph Palazzolo, AI Reporter at The Information, during a recent Latent Space Podcast interview with hosts Alessio Fanelli and Swyx, underscores the relentless pursuit of insight in the rapidly evolving AI landscape. Palazzolo, a former tech investment banker, offers a unique vantage point into the industry's intricate financial and strategic currents, a perspective invaluable to founders, VCs, and tech insiders.
Palazzolo's work, including her daily "AI Agenda" newsletter, delves beyond superficial announcements to uncover the underlying business dynamics of artificial intelligence. Her financial background grants her a distinct advantage in dissecting investment trends and understanding the economic viability of emerging AI ventures. This depth of analysis is crucial in a field often characterized by speculative hype.
A key insight from the discussion centers on the burgeoning inference market. Palazzolo notes the massive capital influx into companies like Modal, Fireworks, Together, and BaseTen, which provide infrastructure for running and customizing open-source AI models. While some critics dismiss these entities as mere "GPU resellers," Palazzolo highlights the undeniable demand. "As AI apps become more popular, we’re going to see the amount of money going into AI inference just explode and go way beyond the amount of money and compute being spent on training." This rapid expansion reflects a critical need for accessible, scalable compute power as AI applications proliferate.
The conversation also shed light on the intense strategic maneuvers among tech giants. Palazzolo dissected Meta’s ambitious pursuit of "superintelligence," a goal she views with a degree of skepticism when divorced from tangible consumer applications. She questions the immediate utility of Meta's current consumer-facing AI tools, remarking, "I'm like, who's using this? Like, this cannot be like where consumer AI ends up, right? That's just so depressing." While acknowledging that every major tech company desires a stake in the superintelligence race, she suggests Meta's core business model, heavily reliant on social media ads, might be better served by focusing on practical, less "super-intelligent" AI integrations that genuinely enhance user experience.
The discussion further explored the competitive dynamics among leading AI labs. The impending arrival of OpenAI's GPT-5, widely anticipated to bring significant advancements in areas like coding and general knowledge, sets the stage for a new wave of competition. Palazzolo indicates that early testers of GPT-5 have reported impressive performance gains. However, she also points to the broader context of previous models, noting that even OpenAI's GPT-4.5 was "low-key a flop" and has since been deprecated from the API. This raises questions about the true trajectory of AI progress and whether these leaps are sustainable or simply a result of ever-increasing computational power. The constant one-upmanship and strategic leaks from various labs, often designed to influence funding rounds or media narratives, create a complex environment where discerning genuine progress from mere posturing becomes a central challenge for journalists.
