Artificial Intelligence #219

Hey, in this issue: Mamba explained; ~40% of LLM layers can be removed; Jamba: a first large competitive SSM-Transformer model; how OpenAI Sora works; matching 7B model performance with 1/3 activated parameters; and more.

The sponsors of this issue are Synaptiq and MyScale.

• [Explained] Mamba explained
• [ArXiv] ~40% of LLM layers can be removed with a minimum decrease in quality
• Jamba: a first large competitive SSM-Transformer model
• [Sponsored] > CLICK HERE TO GET YOUR ORGANIZATION'S AIQ™ SCORE <

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• [Video] The tech behind the magic: how OpenAI Sora works
• [Time] Nobody knows how to safety-test AI
• [Open LLM] Qwen1.5-MoE: Matching 7B model performance with 1/3 activated parameters
• [Sponsored] MyScaleDB, the Revolutionary SQL Vector Database, Goes Open-Source
• [Tutorial] Perform the image generation inference with just 6.4GB of VRAM
• [Project] SWE-agent turns LLMs into software engineering agents that can fix bugs and issues in real GitHub repositories

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