The Reasoning Race: Can Small Models Reason?
Was this email forwarded to you? Sign up here The Reasoning Race: Can Small Models Reason?And Some Major Changes in The Sequence you shuld read about.A note to all subscribers: Welcome to The Sequence 2025! I’ve been eagerly waiting for the end of the year to propose some changes that I believe will tremendously improve the experience for you, the readers of this newsletter. We started The Sequence a few years ago as a hobby project at a time when AI had yet to reach the mainstream levels of popularity it enjoys today. Little did I suspect that we would approach 200,000 subscribers, including members from some of the world’s top AI organizations. What has always set The Sequence apart from other newsletters is its focus on deep technical content and original ideas rather than chasing news or hype. Over the past few weeks, I analyzed current readership patterns and came away with some important insights:
With this in mind, in 2025, we’re nearly doubling our coverage with the following weekly editions:
That’s six editions! Each one will be relatively short and easy to follow. We’re starting with this new structure next week! We’re also discussing potential price changes for new subscribers (current subscribers won’t be affected), so I encourage you to subscribe in the next few days if you haven’t already.To the companies reaching out with sponsorship opportunities: thank you for your patience. We’ll have something to discuss soon. I hope you love these changes. If nothing else, they should make The Sequence even more enjoyable while doubling down on what we do best. Thanks for your continued support. Jesus Rodriguez. Now, onto today’s edition! As mentioned before, we are not doing our typical Sunday edition given the limited market activity during the holidays and, instead, we are discussing another controversial AI topic. Is Reasoning Exclusive to Massive Models or do Small Models Have a Chance?The rapid advancement of artificial intelligence has led to the emergence of large language models (LLMs) like GPT-01 and o3, which exhibit remarkable reasoning capabilities. However, the prevailing notion suggests that such reasoning is primarily confined to models with extensive parameter counts, often exceeding hundreds of billions. This essay explores whether small language models (SLMs) can develop reasoning abilities comparable to their larger counterparts. We will discuss the nature of reasoning in LLMs, the techniques that enhance reasoning in SLMs, and challenge the assumption that reasoning is exclusive to larger models. Understanding Reasoning in Large Language Models...Subscribe to TheSequence to unlock the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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Moving Past RLHF: In 2025 We Will Transition from Preference Tuning to Reward Optimization in Foundation Models
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Models like GPT-o3 and Tülu 3 are showing the way. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 460: Anthropic's New Protocol to Link AI Assistants to Data Sources
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Model Context Protocols is one of the recent AI contributions of the AI lab. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 459: Quantization Plus Distillation
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Some insights into quantized distillation ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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