OpenAI's recent developments in artificial intelligence have sparked discussions about the future of superintelligence and the path to artificial general intelligence (AGI). Noam Brown, a key figure at OpenAI, has indicated that achieving superintelligence requires scaling inference compute, a challenge he initially believed would take a decade to resolve. However, he noted that advancements in test-time compute have progressed more rapidly than anticipated. The company's new models are designed to enhance reasoning capabilities, marking a significant shift from traditional prediction-based AI. Analysts suggest that the launch of OpenAI's latest model, referred to as 'o1', signifies a pivotal moment in the industry as it moves towards reasoning models to address current limitations. Brown's insights underline the urgency for startups to adapt to these changes in AI capabilities.
OpenAI's o1 is a notable departure from older models, representing the industry's shift to reasoning models to overcome the limits of prediction-based AI (@matteo_wong / The Atlantic) https://t.co/CgsVCPxIVt https://t.co/MxpmCe5TTv https://t.co/ZOzeer1FAj
On the question of whether and when we will reach AGI: Noam Brown recently said in an interview how much he underestimated that test-time compute could be achieved quickly. In a conversation with Ilya, he estimated that the TTT solution would take around 10 years, but in the end… https://t.co/mfeOwtikkC
TLDR: Welcome to pre-AGI. 90th percentile human reached. Startups will learn the Bitter Lesson. OpenAI’s Noam Brown on the o1 launch Have we hit a wall? > on scaling pre-training, a qualified yes. Every cycle takes more resources > “it was very easy to scale it very quickly,… https://t.co/2tq6MX1jlw