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Procurement Automation Is Not Enough. Enterprises Need Decision Intelligence.
How enterprise AI turns fragmented spend data into governed decisions and measurable savings.Image generated…
The Retrieval Toolkit That’s Quietly Deciding Whether Your RAG Pipeline Works.
A practical guide to building retrieval that finds the right evidence before your LLM starts answering.If…
Can Your Agent Search for MCPs?
How one line of configuration lets your agent find the right tool mid-task.From source of truth to the search…
Your Obsidian Vault Is Already a Knowledge Graph. I Turned On the Lights.
Your Notes Were a Knowledge Graph All AlongMarkdown plus [[links]] is the format every LLM now reads and…
[AINews] Muse Glimmer and Spark: Open Weights return Personal Superintelligence promise
Last week was the 1 year anniversary of Zuck’s original Personal Superintelligence essay, and MSL seems to…
Best Self-Hosted Inference Servers for Open-Source Models: 7 Options Compared in 2026
From Ollama and LocalAI to vLLM and SIE, this guide matches each server to the workloads, model fleets, and…
Introducing Muse Glimmer
Introducing Muse Glimmer Meta are back in the open weights game! Muse Glimmer is a brand new 30B model under…
AI professors are negotiating the new realities of academic research
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in…
Run interactive IDEs on Amazon EKS with SageMaker AI to power up your AI workflows
To power up AI workflows on Amazon Elastic Kubernetes Service (Amazon EKS), data scientists need interactive…
How nOps shipped FinOps agents 75% faster with Amazon Bedrock AgentCore
nOps, an AI-powered cloud optimization solution, recently reimagined its Financial Operations (FinOps)…
Build Low-Latency Multilingual Voice Agents: Open Weights & Full Deployment Control with NVIDIA Magpie TTS
Back to Articles Build Low-Latency Multilingual Voice Agents: Open Weights & Full Deployment Control with…
Fast, On Device Agentic AI with Muse Glimmer on ExecuTorch
Today, Meta introduced Muse Glimmer, an open-weight, 30-billion-parameter model distilled from Meta’s Muse…
5 useful things you'll learn in my new post-training textbook (shipping now!)
Housekeeping: No voiceover on another quick “launch” post. More essays soon!After a few long years of…
Import AI 468: 23 RSI ideas; PostTrainBench+; and how trust and transparency interplay with AI racing
Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv, cappuccinos, and feedback from…
Making Knowledge Distillation Cheap Enough to Run at Scale
Back to Articles Making Knowledge Distillation Cheap Enough to Run at Scale Team Article Published August 10,…
Most Developers Pick RAG or Fine-Tuning for the Wrong Reason. Here’s the Actual Difference.
RAG changes what an LLM knows. Fine-tuning changes how it behaves. Most teams confuse the two and spend weeks…
Intelligent Regeneration: Can Ecological Worldviews Harness AI?
From raw prediction engines to relational partners: how Indigenous philosophy and planet-centred worldviews…
Vector Databases and Embeddings Explained: The Guide I Needed 5 Months Ago
From what embeddings actually are to how similarity search works under the hood, clearly explained for anyone…
Reranking in RAG Explained: Why Vector Search Isn’t Enough
Your search finds results that sound similar, not the ones that actually answer your question. Here’s the…
Meta is back with Muse Glimmer: local, agentic, multimodal, and open source
Back to Articles Meta is back with Muse Glimmer: local, agentic, multimodal, and open source! Published…
GitHub Models is now retired
GitHub Models is now retired I missed this news until today, when the GitHub Actions run for my…
Lessons from the hacks
The recent run of cyberattacks by in-development frontier models has got me thinking a lot about how our…
From Vibe to Verify: The Hidden Checklist for Production-Ready AI
Before you hit deploy or share a link publicly, these five foundational practices need to be built directly…
The Simpsons might be ending, and millennials think they know why
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