The AI summer — Benedict Evans 🚀 Is AI’s Explosive Growth Just a Mirage? The article "The AI Summer" covers the rapid adoption of ChatGPT and LLMs but argues about its next evolution. As we all know, ChatGPT reached 100 million users in just two months, an unprecedented feat in tech history. Despite this, most users haven’t returned, with active usage plateauing. LLMs, while "magical", may not be inherently useful as products. They might just be sophisticated technologies needing proper framing, UX, and product-market fit—a painful process that other innovations like the iPhone also had to endure. Ben Evans suggests that LLMs may need to be "unbundled or rebundled" into new products, but it overlooks a crucial point: LLMs might already be in their ideal form for specific niches (coding assistance, content creation, customer support). The idea that they need widespread adaptation might be a misstep; instead, they could be best suited for specific industries where they can shine, like coding or marketing. So, what’s next for LLMs? Can we envision a future where LLMs break free from the “trap” of being just a shiny new toy and evolve into indispensable tools? What niche markets do you think LLMs can dominate? Comment your thoughts below! 👇 Do you see LLMs as the next big thing, or just another tech bubble waiting to burst? #generativeai
Dan - I keep hearing arguments on both sides. I believe that a lot of POCs and pilots went through the hype phase and we will soon see who really had their data set up successfully to scale an AI initiative. I also keep hearing a lot about smaller scale LMs and solutions to reduce computing cost and increase control and flexibility!
Vikas Tiwari
1mo
LLMs unlocking niche potentials perhaps?
Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer
1moIt's fascinating to see how quickly LLMs captured public imagination, yet the challenge of sustained engagement is a common hurdle for groundbreaking technologies. Navigating the transition from "shiny new toy" to indispensable tool requires careful consideration of user needs and market fit. How are you envisioning the role of human-in-the-loop systems in bridging this gap and ensuring LLMs truly deliver value?