Tag: architectures

  • Simon Willison’s Weblog: QwQ-32B: Embracing the Power of Reinforcement Learning

    Source URL: https://simonwillison.net/2025/Mar/5/qwq-32b/#atom-everything Source: Simon Willison’s Weblog Title: QwQ-32B: Embracing the Power of Reinforcement Learning Feedly Summary: QwQ-32B: Embracing the Power of Reinforcement Learning New Apache 2 licensed reasoning model from Qwen: We are excited to introduce QwQ-32B, a model with 32 billion parameters that achieves performance comparable to DeepSeek-R1, which boasts 671 billion parameters…

  • Anchore: NIST SP 800-190: Overview & Compliance Checklist

    Source URL: https://anchore.com/blog/nist-sp-800-190-overview-compliance-checklist/ Source: Anchore Title: NIST SP 800-190: Overview & Compliance Checklist Feedly Summary: This blog post has been archived and replaced by the supporting pillar page that can be found here: https://anchore.com/wp-admin/post.php?post=987474946&action=edit The blog post is meant to remain “public” so that it will continue to show on the /blog feed. This will…

  • Cloud Blog: How to calculate your AI costs on Google Cloud

    Source URL: https://cloud.google.com/blog/topics/cost-management/unlock-the-true-cost-of-enterprise-ai-on-google-cloud/ Source: Cloud Blog Title: How to calculate your AI costs on Google Cloud Feedly Summary: What is the true cost of enterprise AI? As a technology leader and a steward of company resources, understanding these costs isn’t just prudent – it’s essential for sustainable AI adoption. To help, we’ll unveil a comprehensive…

  • Cloud Blog: Best practices for achieving high availability and scalability in Cloud SQL

    Source URL: https://cloud.google.com/blog/products/databases/understanding-cloud-sql-high-availability/ Source: Cloud Blog Title: Best practices for achieving high availability and scalability in Cloud SQL Feedly Summary: Cloud SQL, Google Cloud’s fully managed database service for PostgreSQL, MySQL, and SQL Server workloads, offers strong availability SLAs, depending on which edition you choose: a 99.95% SLA, excluding maintenance for Enterprise edition; and a…

  • Hacker News: Nvidia GPU on bare metal NixOS Kubernetes cluster explained

    Source URL: https://fangpenlin.com/posts/2025/03/01/nvidia-gpu-on-bare-metal-nixos-k8s-explained/ Source: Hacker News Title: Nvidia GPU on bare metal NixOS Kubernetes cluster explained Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text presents an in-depth personal narrative of setting up a bare-metal Kubernetes cluster that integrates Nvidia GPUs for machine learning tasks. The author details the challenges and solutions encountered…

  • Hacker News: Fire-Flyer File System from DeepSeek

    Source URL: https://github.com/deepseek-ai/3FS Source: Hacker News Title: Fire-Flyer File System from DeepSeek Feedly Summary: Comments AI Summary and Description: Yes Summary: The Fire-Flyer File System (3FS) is a distributed file system designed to optimize AI training and inference workloads by harnessing modern hardware capabilities. The text discusses its performance, a benchmarking approach using the GraySort…

  • Hacker News: Kastle (YC S24) Is Hiring – AI for Loan Servicing

    Source URL: https://www.ycombinator.com/companies/kastle/jobs/ItDVKB7-founding-backend-engineer-at-kastle-s24 Source: Hacker News Title: Kastle (YC S24) Is Hiring – AI for Loan Servicing Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text outlines a job opportunity for a Founding Backend Engineer at Kastle, an AI platform focused on automating mortgage servicing processes. It emphasizes the significance of building a…

  • Schneier on Security: “Emergent Misalignment” in LLMs

    Source URL: https://www.schneier.com/blog/archives/2025/02/emergent-misalignment-in-llms.html Source: Schneier on Security Title: “Emergent Misalignment” in LLMs Feedly Summary: Interesting research: “Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs“: Abstract: We present a surprising result regarding LLMs and alignment. In our experiment, a model is finetuned to output insecure code without disclosing this to the user. The resulting model…