When AI reasoning goes wrong: Microsoft Research shows more tokens can mean more problems
Not all AI scaling strategies are equal. Longer reasoning chains are not sign of higher intelligence. More compute isn't always
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Ben Dickson
09:20
How test-time scaling unlocks hidden reasoning abilities in small language models (and allows them to outperform LLMs)
A 1B small language model can beat a 405B large language model in reasoning tasks if provided with the right
Ben Dickson
13:19
OpenAI responds to DeepSeek competition with detailed reasoning traces for o3-mini
By showing a more detailed version of the chain of thought of o3-mini, OpenAI is closing the gap with DeepSeek-R1...
Ben Dickson
00:20
Beyond benchmarks: How DeepSeek-R1 and o1 perform on real-world tasks
o1 is slightly better at reasoning, but DeepSeek-R1 provides much more details about its reasoning, which is very useful to
Ben Dickson
23:20
OpenAI’s o3 shows remarkable progress on ARC-AGI, sparking debate on AI reasoning
o3 solved one of the most difficult AI challenges, scoring 75.7% on the ARC-AGI benchmark. But does it really mean
Ben Dickson
20:19
DeepMind’s Talker-Reasoner framework brings System 2 thinking to AI agents
Talker-Reasoner is inspired by the two-system thinking cognitive framework proposed by Daniel Kahneman...
