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121.
Anthropic researchers discover the weird AI problem: Why thinking longer makes models dumber (venturebeat.com)
122.
Google DeepMind makes AI history with gold medal win at world’s toughest math competition (venturebeat.com)
123.
OpenAI wins gold at prestigious math competition - why that matters more than you think (zdnet.com)
124.
OpenAI, Google DeepMind and Anthropic sound alarm: ‘We may be losing the ability to understand AI’ (venturebeat.com)
125.
How to scale RL to 10^26 FLOPs (news.ycombinator.com)
126.
Smollm3: Smol, multilingual, long-context reasoner LLM (news.ycombinator.com)
127.
Overclocking LLM Reasoning: Monitoring and Controlling LLM Thinking Path Lengths (news.ycombinator.com)
128.
Meta hires key OpenAI researcher to work on AI reasoning models (techcrunch.com)
129.
Learnings from building AI agents (news.ycombinator.com)
130.
Learnings from Building AI Agents (news.ycombinator.com)
131.
Google’s Gemini transparency cut leaves enterprise developers ‘debugging blind’ (venturebeat.com)
132.
Why Some AI Models Spew 50 Times More Greenhouse Gas to Answer the Same Question (gizmodo.com)
133.
What Apple's controversial research paper really tells us about LLMs (zdnet.com)
134.
Do reasoning AI models really ‘think’ or not? Apple research sparks lively debate, response (venturebeat.com)
135.
Do reasoning models really “think” or not? Apple research sparks lively debate, response (venturebeat.com)
136.
New paper pushes back on Apple’s LLM ‘reasoning collapse’ study (9to5mac.com)
137.
AI flunks logic test: Multiple studies reveal illusion of reasoning (techspot.com)
138.
With the launch of o3-pro, let’s talk about what AI “reasoning” actually does (arstechnica.com)
139.
New Apple study challenges whether AI models truly “reason” through problems (arstechnica.com)
140.
General Reasoning: Free, open resource for building large reasoning models (news.ycombinator.com)
141.
Together AI’s $305M bet: Reasoning models like DeepSeek-R1 are increasing, not decreasing, GPU demand (venturebeat.com)
142.
How test-time scaling unlocks hidden reasoning abilities in small language models (and allows them to outperform LLMs) (venturebeat.com)
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