Who's Who of AI

Google Gemma

495 trust @googlegemma · 95,823 followers
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Tracked through public AI activity and peer connections inside the directory.

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Read the blog for all the details, dive into the docs, and start building today: https://t.co/UVpgDrXvvV

EmbeddingGemma 2: an open, lightweight multimodal embedding model blog.google
AI Weekly's analysis →
  • Google released EmbeddingGemma 2, a 740M-parameter multimodal embedding model built on Gemma 4 and licensed under Apache 2.0.
  • The model has an 8K token context window with 768-dimensional outputs truncatable to 512, 256, or 128 via Matryoshka learning.
  • Quantized on a Pixel 11 Pro, memory is roughly 191MB text-only and 567MB multimodal; MTEB Code reaches 78.68 versus 68.76 for v1.
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View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 4 from the directory shared this · 17d ago

Link to tech report: https://t.co/g710KPO6UR

DiffusionGemma Technical Report arxiv.org
AI Weekly's analysis →
  • DiffusionGemma reportedly generates around 1,500 output tokens per second on a single NVIDIA H100 by refining blocks of 256 tokens in parallel.
  • The model is a fine-tune of the mixture-of-experts Gemma 4 base, which has 3.8B activated and 25.2B total parameters.
  • Its two-stage training pipeline of supervised denoising plus RL with sampler distillation used less than 10% of the original AR model's token budget.
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View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 4 from the directory shared this · 74d ago

See how AI can help scientists secure our global food supply. 🌾 https://t.co/eKVtjSr5OC Explore the research: 💻 Try the Gemma 4 + BOTANIC-1 demo: https://t.co/C7xtDf7PPX 🧬 Download BOTANIC-1: https://t.co/GKrCPoYWNi 📄 Read the paper: https://t.co/IEzsJaAVbw

Living Models pairs Gemma 4 with BOTANIC-1 to help decode plant DNA — Google DeepMind deepmind.google
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View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 2 from the directory shared this · 16d ago

Original post by @elliotarledge https://t.co/q9KnOlDAgO Resources: - GitHub Repo: https://t.co/UndyYJ2CqK - Gemma 4 (MLX): https://t.co/ALKU8ijMNm

mlx-community/gemma-4-e2b-it-4bit · Hugging Face huggingface.co
AI Weekly's analysis →
  • A 4-bit MLX conversion of Google's Gemma 4 E2B-it vision model fits into a 3.55 GB file targeting Apple silicon.
  • The listing reports 38,478 downloads in the last month and ships under Google's Gemma license, not Apache 2.0.
  • The card exposes the model as image-text-to-text, invoked through mlx_vlm.generate with a prompt and image path.
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View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 59d ago

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