open-thoughts/OpenThinker-Agent-v1
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This is huge!
the opensource community is all in on open access to rl environments, PrimeIntellect you’re not alone.
Code: https://github.com/WooooDyy/AgentGym-RL
the opensource community is all in on open access to rl environments, PrimeIntellect you’re not alone.
Code: https://github.com/WooooDyy/AgentGym-RL
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Apriel-H1: The Surprising Key to Distilling Efficient Reasoning Models
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Continuous batching from first principles
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Qwen3-Next can now be Run locally! (30GB RAM)
Instruct GGUF: unsloth/Qwen3-Next-80B-A3B-Instruct-GGUF
The models come in Thinking and Instruct versions and utilize a new architecture, allowing it to have ~10x faster inference than Qwen32B.
💜 Step-by-step Guide: https://docs.unsloth.ai/models/qwen3-next
Thinking GGUF: unsloth/Qwen3-Next-80B-A3B-Thinking-GGUF
Instruct GGUF: unsloth/Qwen3-Next-80B-A3B-Instruct-GGUF
The models come in Thinking and Instruct versions and utilize a new architecture, allowing it to have ~10x faster inference than Qwen32B.
💜 Step-by-step Guide: https://docs.unsloth.ai/models/qwen3-next
Thinking GGUF: unsloth/Qwen3-Next-80B-A3B-Thinking-GGUF
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6 Essential Reads on Spatial Intelligence
In AI, spatial intelligence is basically the model’s “sense of space” – its ability to understand where things are, how they relate, and how they move. It lets an AI models navigate a room, interpret a scene, or figure out how objects fit together, like giving it a built-in mental map. For example, world models can't live without spatial intelligence.
Here are 6 good reads to explore what spatial intelligence is and how it's evolving:
1. From Words to Worlds: Spatial Intelligence is AI’s Next Frontier by Fei-Fei Li → https://drfeifei.substack.com/p/from-words-to-worlds-spatial-intelligence
Fei-Fei Li, the godmother of AI, is a key figure in spatial intelligence, since her work in computer vision, especially ImageNet, helped AI learn to recognize and understand objects in space. She's recently started a blog, and this post, in particular, argues that true intelligence requires grounding in space, understanding geometry, motion and consequences in the real world
2. Spatial Reasoning in Multimodal LLMs: A Survey of
Tasks, Benchmarks and Methods → https://arxiv.org/abs/2511.15722
Breaks down how AI models handle spatial reasoning from a cognitive angle, maps all the existing tasks and benchmarks to that framework
3. What is Spatial Intelligence? → https://www.turingpost.com/p/cvhistory5
Our special article easily explains what spatial intelligence actually is, why it matters, and how researchers are trying to boost it so machines can better understand and navigate the physical world
4. From 2D to 3D Cognition: A Brief Survey of General World
Models → https://arxiv.org/pdf/2506.20134
Shows how AI world models are evolving from simple 2D perception to full-on 3D understanding, explaining the tech behind it, what new 3D abilities these models gain, and where they’re used in the real world
Read further below ⬇️
If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe
In AI, spatial intelligence is basically the model’s “sense of space” – its ability to understand where things are, how they relate, and how they move. It lets an AI models navigate a room, interpret a scene, or figure out how objects fit together, like giving it a built-in mental map. For example, world models can't live without spatial intelligence.
Here are 6 good reads to explore what spatial intelligence is and how it's evolving:
1. From Words to Worlds: Spatial Intelligence is AI’s Next Frontier by Fei-Fei Li → https://drfeifei.substack.com/p/from-words-to-worlds-spatial-intelligence
Fei-Fei Li, the godmother of AI, is a key figure in spatial intelligence, since her work in computer vision, especially ImageNet, helped AI learn to recognize and understand objects in space. She's recently started a blog, and this post, in particular, argues that true intelligence requires grounding in space, understanding geometry, motion and consequences in the real world
2. Spatial Reasoning in Multimodal LLMs: A Survey of
Tasks, Benchmarks and Methods → https://arxiv.org/abs/2511.15722
Breaks down how AI models handle spatial reasoning from a cognitive angle, maps all the existing tasks and benchmarks to that framework
3. What is Spatial Intelligence? → https://www.turingpost.com/p/cvhistory5
Our special article easily explains what spatial intelligence actually is, why it matters, and how researchers are trying to boost it so machines can better understand and navigate the physical world
4. From 2D to 3D Cognition: A Brief Survey of General World
Models → https://arxiv.org/pdf/2506.20134
Shows how AI world models are evolving from simple 2D perception to full-on 3D understanding, explaining the tech behind it, what new 3D abilities these models gain, and where they’re used in the real world
Read further below ⬇️
If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe
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