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Gemini 3 Deep Think (blog.google)

1081 points by tosh · 158 days ago · 693 comments on HN

Article summary

Google has released an updated version of its Gemini 3 Deep Think model, which is designed to solve modern science, research, and engineering challenges. The model has been updated in partnership with scientists and researchers to tackle tough research challenges. It is now available in the Gemini app for Google AI Ultra subscribers and will also be available via the Gemini API for select researchers, engineers, and enterprises. The model has achieved state-of-the-art performance on various benchmarks, including ARC-AGI-2 and the International Math Olympiad.

Main themes

  • AI model updates
  • Science and research applications
  • Benchmark performance
  • Google Gemini
  • AI capabilities
  • Engineering challenges

What commenters say

  • The updated Gemini 3 Deep Think model has achieved significant improvements in benchmark performance, surpassing other models like Opus 4.6.
  • The model's performance on benchmarks like ARC-AGI-2 may not necessarily translate to real-world applications or general intelligence.
  • The development of AI models is a continuous process, with each new release building upon previous advancements and pushing the boundaries of what is possible.
  • The concept of 'spikey' intelligence, where AI models excel in specific areas but lack general intelligence, is a limitation of current AI technology.
  • The comparison between human and artificial intelligence is complex, with humans possessing a unique combination of general and specialized abilities that are difficult to replicate in AI models.
  • The idea that AI models are becoming increasingly powerful and capable of solving complex problems is both exciting and unsettling, with some commentators welcoming the advancements and others expressing caution.
  • The notion that benchmarks like ARC-AGI-2 are becoming less relevant as AI models continue to improve is a topic of debate, with some arguing that new benchmarks are needed to accurately measure progress.
  • The relationship between AI and human intelligence is multifaceted, with AI models possessing strengths and weaknesses that are distinct from those of humans.