Explore major AI developments: DeepSeek's efficient Chimera model, Sakana's TreeQuest framework, AI agent capabilities, language models playing Baba Is You, and Gemini 2.5's memory enhancements.

Sources:
[1] https://links.tldrnewsletter.com/v1es4E
[2] https://links.tldrnewsletter.com/USMysp
[3] https://lethain.com/what-can-agents-do/
[4] https://fi-le.net/baba/
[5] https://www.philschmid.de/gemini-with-memory

Explore Microsoft's groundbreaking AI medical diagnostics, Google's Gemini 2.5 robotics advances, PyTorch's efficient checkpointing, and the challenges of training AI for scientific reasoning in chemistry.

Sources:
[1] https://microsoft.ai/new/the-path-to-medical-superintelligence/
[2] https://arxiv.org/abs/2507.00440
[3] https://arxiv.org/abs/2507.00880
[4] https://developers.googleblog.com/en/gemini-25-for-robotics-and-embodied-intelligence/
[5] https://pytorch.org/blog/reducing-storage-footprint-and-bandwidth-usage-for-distributed-checkpoints-with-pytorch-dcp/
[6] https://diffuse.one/p/m1-000

Explore Huawei's open-source AI models, revolutionary AI note-taking tools, model diffing research, and the future of personal AI factories. A deep dive into the latest AI developments and strategies.

Sources:
[1] https://www.cnbc.com/2025/07/01/huawei-open-sources-more-ai-models-grows-into-chinese-ai-juggernaut.html
[2] https://communitynotes.x.com/guide/en/api/overview
[3] https://arxiv.org/abs/2506.23286
[4] https://www.lesswrong.com/posts/xmpauEXEerzYcJKNm/what-we-learned-trying-to-diff-base-and-chat-models-and-why
[5] https://www.john-rush.com/posts/ai-20250701.html

Explore PS3's 4K vision pre-training, XBOW's HackerOne success, Linux Foundation's A2A protocol, tokenization's future, Gemini 2.5 for robotics, and ElevenLabs' voice AI assistant.

Sources:
[1] https://nvlabs.github.io/PS3/
[2] https://links.tldrnewsletter.com/Vt1blo
[3] https://xbow.com/blog/top-1-how-xbow-did-it/
[4] https://developers.googleblog.com/en/google-cloud-donates-a2a-to-linux-foundation/
[5] https://arxiv.org/abs/2506.18747
[6] https://lucalp.dev/bitter-lesson-tokenization-and-blt/
[7] https://developers.googleblog.com/en/gemini-25-for-robotics-and-embodied-intelligence/
[8] https://elevenlabs.io/blog/introducing-11ai

Explore Reinforcement Learned Teaching's breakthrough, challenges in evaluating long-context Q&A systems, the evolution of AI agents through RL, and xAI's leaked plans for Grok's spreadsheet integration.

Sources:
[1] https://huggingface.co/blog/transformers-backend-sglang
[2] https://arxiv.org/abs/2506.16787
[3] https://arxiv.org/abs/2506.17204
[4] https://sakana.ai/rlt/
[5] https://eugeneyan.com/writing/qa-evals/
[6] https://www.understandingai.org/p/reinforcement-learning-explained
[7] https://techcrunch.com/2025/06/23/leak-reveals-grok-might-soon-edit-your-spreadsheets/

Explore how AI conducts intelligent searches using full-text search and offline augmentation. Learn why simple approaches beat complex embeddings and how document preparation impacts AI search efficiency.

Sources:
[1] https://benanderson.work/blog/agentic-search-for-dummies/