# The Potential of LLMs and the Hype Overload Examining the realities and exaggerations of the AI revolution. - **Source:** [George Hotz](https://geohot.github.io/blog) - **Published:** 2026-07-12 - **Topic:** [Data & AI](https://brifing.si/c/data-ai) - **Original article:** - **On Brifing:** https://brifing.si/s/c41c9bd1-d5fb-4254-9e2d-35a686c22c61 ## Passion for AI The author has worked in AI since 2007 and is excited about advancements like LLMs, autonomous vehicles, and video generation models. They highlight the practical benefits of coding assistants based on personal experience but criticize exaggerated interpretations of these developments. ## Negative Effects of Hype They argue against fear-based narratives like 'the window of opportunity is closing,' stating these claims are false and serve the interests of certain Silicon Valley circles. Citing a 2016 presentation and a 1991 film, they show these fears are not new. ## The Value Capture Problem They challenge the valuation of frontier AI labs, claiming AI will create significant value but these companies won't capture it. They argue anti-open-source positions stem from fear of commodification and that AI progress is driven by Moore's Law, not specific companies. ## Programming Revolution They acknowledge AI models are changing programming. Quoting Linus Torvalds, they note coding assistants may boost productivity 10x, while compilers offer 1000x gains. They emphasize that using models effectively is a new skill requiring careful application. ## Practical Benefits and Limits They compare AI models to tools like find-replace or Stack Overflow—useful but not magical. They warn of increased cognitive fatigue and note the promised software revolution from productivity tools hasn't fully materialized yet. ## Continuation of the Computer Revolution They view AI as an extension of the computer revolution. While critical of hype, they express genuine love for technology. With realistic optimism, they acknowledge AI's potential while cautioning against unrealistic expectations. ## Sources covering this story - https://geohot.github.io//blog/jekyll/update/2026/07/12/i-love-llms.html — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._