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Breaking Ground on Our New AI-Optimized Data Center in El Paso https://about.fb.com/news/2025/10/metas-new-ai-optimized-data-center-el-paso/
Meta just dropped MobileLLM-Pro on Hugging Face a 1B foundational language model in the MobileLLM series, designed to deliver high-quality, efficient on-device inference across a wide range of general language modeling tasks two variants of the model: A pre-trained base model https://x.com/_akhaliq/status/1978916251456925757
We have a new comprehensive Model Context Protocol (MCP) documentation section, to help you connect your AI applications to external tools and data sources through a standardized interface. 🔌 Learn how MCP works – connecting LLMs to databases, tools, and services through a https://x.com/llama_index/status/1957840992360710557
What if you could orchestrate your entire microservices setup using LlamaIndex Workflows? That’s the idea we explored, and the result is a working demo that brings together @docker, @apachekafka and Workflows to manage a small scale e-commerce system. In this walkthrough, https://x.com/llama_index/status/1978137596900593667
Here are some long-awaited performance numbers for DGX Spark using llama.cpp https://x.com/ggerganov/status/1978106631884828843
Meta, Google, and Apple are in a silent war. The prize? The most detailed digital copy of you. Here’s my deep dive into the battle for your digital twin and what it means for identity, privacy, and proving you’re human. We covered: – Hollywood’s evolution from CGI disasters to https://x.com/bilawalsidhu/status/1978159640648294853
Exclusive | Thinking Machines Lab Co-Founder Departs for Meta – WSJ https://www.wsj.com/tech/ai/thinking-machines-lab-co-founder-departs-for-meta-442d7461
10X Backbone: How Meta Is Scaling Backbone Connectivity for AI – Engineering at Meta https://engineering.fb.com/2025/10/16/data-center-engineering/10x-backbone-how-meta-is-scaling-backbone-connectivity-for-ai/
Meta partners up with Arm to scale AI efforts | TechCrunch https://techcrunch.com/2025/10/15/arm-partners-with-meta-to-scale-ai-efforts/
Banger paper from Meta and collaborators. This paper is one of the best deep dives yet on how reinforcement learning (RL) actually scales for LLMs. The team ran over 400,000 GPU hours of experiments to find a predictable scaling pattern and a stable recipe (ScaleRL) that https://x.com/omarsar0/status/1978865039529689257
MacStudio you ask? Apple Engineering’s **actual** time spent on PyTorch support has’t given me confidence that PyTorch Mac experience would get anywhere close to NVIDIA’s any time soon, if ever. The Meta engineers continue to do a huge amount of heavy-lifting for improving the”” / X https://x.com/soumithchintala/status/1978848796953161754
