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Model: "jamba"
not much happened today
grok-4 jamba ernie-4.5 claude-4-sonnet claude-4 kontext-dev ai21-labs hugging-face baidu perplexity-ai deepmind anthropic reinforcement-learning fine-tuning energy-based-transformers ssm-transformer context-windows length-generalization recurrent-neural-networks attention-mechanisms 2-simplicial-attention biomedical-ai instruction-following open-weight-models python-package-management _philschmid corbtt jxmnop sedielem _akhaliq slashml alexiglad clementdelangue _albertgu tri_dao theaitimeline deep-learning-ai
Over the holiday weekend, key AI developments include the upcoming release of Grok 4, Perplexity teasing new projects, and community reactions to Cursor and Dia. Research highlights feature a paper on Reinforcement Learning (RL) improving generalization and reasoning across domains, contrasting with Supervised Fine-Tuning's forgetting issues. Energy-Based Transformers (EBTs) are proposed as a promising alternative to traditional transformers. AI21 Labs updated its Jamba model family with enhanced grounding and instruction following, maintaining a 256K context window. Baidu open-sourced its massive 424 billion parameter Ernie 4.5 model, while Kontext-dev became the top trending model on Hugging Face. Advances in length generalization for recurrent models and the introduction of 2-simplicial attention were noted. In biomedical AI, Biomni, powered by Claude 4 Sonnet, demonstrated superior accuracy and rare disease diagnosis capabilities. Additionally, the Python package manager
uv received praise for improving Python installation workflows. Evals-based AI Engineering
jamba bamboo qwen-1.5-moe grok-1.5 llama2-7b openai mistral-ai x-ai llamaindex evaluation fine-tuning prompt-engineering voice-cloning quantization model-optimization code-generation context-windows hamel-husain alec-radford
Hamel Husain emphasizes the importance of comprehensive evals in AI product development, highlighting evaluation, debugging, and behavior change as key iterative steps. OpenAI released a voice engine demo showcasing advanced voice cloning from small samples, raising safety concerns. Reddit discussions introduced new models like Jamba (hybrid Transformer-SSM with MoE), Bamboo (7B LLM with high sparsity based on Mistral), Qwen1.5-MoE (efficient parameter activation), and Grok 1.5 (128k context length, surpassing GPT-4 in code generation). Advances in quantization include 1-bit Llama2-7B models outperforming full precision and the QLLM quantization toolbox supporting GPTQ/AWQ/HQQ methods.
Jamba: Mixture of Architectures dethrones Mixtral
jamba dbrx mixtral animatediff fastsd sdxs512-0.9 b-lora supir ai21-labs databricks together-ai hugging-face midjourney mixture-of-experts model-architecture context-windows model-optimization fine-tuning image-generation video-generation cpu-optimization style-content-separation high-resolution-upscaling
AI21 labs released Jamba, a 52B parameter MoE model with 256K context length and open weights under Apache 2.0 license, optimized for single A100 GPU performance. It features a unique blocks-and-layers architecture combining transformer and MoE layers, competing with models like Mixtral. Meanwhile, Databricks introduced DBRX, a 36B active parameter MoE model trained on 12T tokens, noted as a new standard for open LLMs. In image generation, advancements include Animatediff for video-quality image generation and FastSD CPU v1.0.0 beta 28 enabling ultra-fast image generation on CPUs. Other innovations involve style-content separation using B-LoRA and improvements in high-resolution image upscaling with SUPIR.