Chroma Releases Context-1: A 20B Agentic Search Model for Multi-Hop Retrieval, Context Management, and Scalable Synthetic Task Generation - MarkTechPost
<a href="https://news.google.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?oc=5" target="_blank">Chroma Releas
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v4.3.3 - Gemma 4 support!
Changes Gemma 4 support with tool-calling in the API and UI. 🆕 - v4.3.1. ik_llama.cpp support : Add ik_llama.cpp as a new backend through new textgen-portable-ik portable builds and a new --ik flag for full installs. ik_llama.cpp is a fork by the author of the imatrix quants, including support for new quant types, significantly more accurate KV cache quantization (via Hadamard KV cache rotation, enabled by default), and optimizations for MoE models and CPU inference. API: Add echo + logprobs for /v1/completions . The completions endpoint now supports the echo and logprobs parameters, returning token-level log probabilities for both prompt and generated tokens. Token IDs are also included in the output via a new top_logprobs_ids field. Further optimize my custom gradio fork, saving up to 5
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The cognitive impact of coding agents
A fun thing about recording a podcast with a professional like Lenny Rachitsky is that his team know how to slice the resulting video up into TikTok-sized short form vertical videos. Here's one he shared on Twitter today which ended up attracting over 1.1m views! That was 48 seconds. Our full conversation lasted 1 hour 40 minutes. Tags: ai-ethics , coding-agents , agentic-engineering , generative-ai , podcast-appearances , ai , llms , cognitive-debt
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