Face and basic landmarks detection using mediapipe models with efficiency and very good accuracy and draw on image or save detected faces using opencv in python.
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Deep LearningAlphaGo visionary David Silver is spearheading a massive shift away from static datasets. With a historic seed round and next-generation NVIDIA hardware, Ineffable Intelligence is building systems that learn continuously from real-time experience.
LLMLMCache is an open-source library that dramatically reduces Time-To-First-Token by decoupling and sharing KV caches across LLM deployments. We explore its architecture, performance benefits, and how to integrate it into your existing vLLM pipelines.
LLMAnthropic's Claude Fable 5 introduces dynamic reasoning and proactive coding capabilities. Discover how this paradigm shift optimizes token usage and redefines the development of autonomous AI agents.
LLMTraditional LLM agents fail when their environments change. Discover how the new EvoArena framework from MIT applies evolutionary biology to agent memory for robust dynamic adaptation.
LLMHugging Face Skills introduces a standardized framework that allows autonomous coding agents to natively interact with the machine learning ecosystem. Discover how this release transforms agents from simple code generators into capable MLOps orchestrators.
LLMCohere has open-sourced North Mini Code, a 30B-parameter MoE model that brings powerful agentic coding capabilities directly to your local hardware. Operating with just 3B active parameters, it delivers unprecedented inference efficiency and complex reasoning under a permissive Apache 2.0 license.
LLMMistral AI has disrupted the open-weights landscape once again with the sudden release of Mistral-Small-4-119B-2603. We analyze its massive architecture, enterprise deployment strategies, and what this 119-billion parameter giant means for the future of open source AI.
Machine LearningTreble Technologies and Hugging Face have launched the industry's first open benchmark for evaluating ASR models under real-world acoustic conditions. Discover how the FFASR leaderboard exposes the limitations of current models and redefines the future of robust speech recognition.
Deep LearningJohns Hopkins researchers have demonstrated that in-context learning is not exclusive to human language. By evaluating the Evo2 model on DNA sequences, they revealed that large genomic models can learn and reason over biological structures through simple few-shot prompting.
