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dev.to > mrsaynothing > how-to-run-gguf-models-locally-ollama-llamacpp-vllm-59ek

How to Run GGUF Models Locally: Ollama, llama.cpp & vLLM

53+ min ago   (362+ words) Two things matter about a GGUF file's name: Yes — GGUF is Ollama's native format, and since 2024 it can pull one straight off Hugging Face without you ever touching a file: Already downloaded a.gguf file yourself? Point a Modelfile at…...


livemint.com > technology > anthropic-flags-ai-systems-self-improvement-bats-for-greater-transparency-in-development-of-models-11789693559990.html

Anthropic flags AI systems self-improvement; bats for greater transparency in development of models

1+ hour, 39+ min ago   (308+ words) California [US], September 18 (ANI): AI frontier lab Anthropic has pitched for greater transparency in the development of AI models. In a blog post the company said that AI systems are becoming exponentially more powerful and have begun to automate more…...


lesswrong.com > posts > crmZvWiadNkWiJfYA > hidden-knowledge-arrr

Hidden Knowledge? Arrr... — LessWrong

2+ hour ago   (210+ words) I tried to find hidden facts with R-Lens. [1] Then I tried the wrong facts. …...


dev.to > beck_moulton > your-health-data-stays-on-your-phone-building-a-private-health-ai-with-llama-3-and-mlx-swift-166l

Your Health Data Stays on Your Phone: Building a Private Health AI with Llama-3 and MLX-Swift

2+ hour, 20+ min ago   (313+ words) Hey there, privacy-conscious devs! 🚀 Ever felt a bit "creepy" sending your most intimate health data—heart rate, sleep cycles, and activity levels—to a distant cloud server just to get some AI insights? You aren't alone. The beauty of this…...


dev.to > tamizuddin > beyond-autoregression-engineering-the-next-wave-of-ai-code-generation-with-diffusion-models-3e58

Beyond Autoregression: Engineering the Next Wave of AI Code Generation with Diffusion Models

2+ hour, 40+ min ago   (435+ words) Implementing a code-diffusion model is not as simple as training a new Transformer. It requires significant architectural modifications to handle the unique characteristics of discrete data and the specific demands of code. Building a code-diffusion model presents a unique set…...


lesswrong.com > posts > 8mADs3rCHGuJqptFC > what-is-and-isn-t-gained-by-avoiding-architectures-with-high

What is (and isn’t) gained by avoiding architectures with high opaque serial depth? — LessWrong

2+ hour, 53+ min ago   (1471+ words) Here, we’ve given an operationalization of opaque serial depth, a metric designed to be a good (albeit imperfect) proxy for the amount of opaque serial cognition that models can perform. While maintaining low opaque serial depth is helpful for preserving…...


dev.to > technonotes > llm-day-5-rag-a-intro-31p3

LLM - Day 5 - RAG a Intro

2+ hour, 54+ min ago   (19+ words) Retrievel Augment Generation 3 different Topics when we need RAG? You have Private Data... Tagged with rag, letslearnrag, ragintamil....


analyticsinsight.net > artificial-intelligence > deep-learning-cheat-sheet-for-beginners-professionals

Deep Learning Cheat Sheet for Beginners & Professionals

11+ hour, 15+ min ago   (740+ words) Deep learning uses multi-layer neural networks to learn patterns from data. CNNs, RNNs, LSTMs, transformers, and autoencoders support different types of problems. Python, PyTorch, TensorFlow, NumPy, Pandas, and GPU tools support deep learning workflows. Deep learning is a branch of…...