[Music] I'm going to be giving a quick presentation about the state of the union regarding AI vision. Um, so I'm Peter Robisho. I'm the ML lead at Rooflow, which is a platform for building and deploying vision models.Um, so a lot of people are really interested in LLMs these days. So I'm trying to pitch why computer vision matters. Uh so if you think about systems that interact with the real world, they have to use vision as one of their primary inputs because the the built world is sort of built around vis ...

4 stages of LLM training from scratch:- Pre-training- Instruction fine-tuning- Preference fine-tuning- Reasoning fine-tuningRead the explainer thread below to learn more👇 https://t.co/5Ut5mp8Fm4Avi Chawla (@_avichawla):4 stages of training LLMs from scratch, clearly explained (with visuals): ...

Core Insights - The article discusses the evolution of AI, particularly focusing on the "trinity" of pre-training, post-training, and reasoning, and how these components are essential for achieving Artificial General Intelligence (AGI) [3][4][5] - Bob McGrew emphasizes that reasoning will be a significant focus in 2025, with many opportunities for optimization in compute usage, data utilization, and algorithm efficiency [4][5][6] - The article highlights the diminishing returns of pre-training, suggesting that while it remains important, its role is shifting towards architectural improvements rather than sheer computational power [6][8][9] Pre-training, Post-training, and Reasoning - Pre-training has reached a stage of diminishing returns, requiring exponentially more compute for marginal gains in intelligence [7][8] - Post-training focuses on enhancing the model's personality and intelligence, which can yield broad applicability across various fields [9][10] - Reasoning is seen as the "missing piece" that allows models to perform complex tasks through step-by-step thinking, which was previously lacking in models like GPT-3 [14][15] Agent Economics - The cost of AI agents is expected to approach the opportunity cost of compute usage, making it challenging for startups to maintain high pricing due to increased competition [17][18][19] - The article suggests that while AI can automate simple tasks, complex services requiring human understanding will retain their value and scarcity [19][20] Market Opportunities in Robotics - There is a growing interest in robotics, with the belief that the field is nearing commercialization due to advancements in language interfaces and visual encoding [22][25] - Companies like Skilled and Physical Intelligence are highlighted as potential leaders in the robotics space, capitalizing on existing technology and research [22][25] Proprietary Data and Its Value - Proprietary data is becoming less valuable compared to the capabilities of advanced AI models, which can replicate insights without extensive human labor [29][30] - The article discusses the importance of specific customer data that can enhance decision-making, emphasizing the need for trust in data usage [31] Programming and AI Integration - The integration of AI in programming is evolving, with a hybrid model where users engage in traditional coding while AI assists in the background [32][33] - The article notes that while AI can handle repetitive tasks, complex programming still requires human oversight and understanding [33][34] Future of AI and Human Interaction - The article explores how different generations interact with AI, suggesting that AI should empower individuals to become experts in their interests while alleviating mundane tasks [39][42] - It emphasizes the importance of fostering curiosity and problem-solving skills in the next generation, rather than merely teaching specific skills that may soon be automated [43][44]