🤖 Issue #417 is now live! This week features: How to Build Reliable AI Agent Architecture for Production, How Much Power Will Frontier AI Training Demand in 2030, a paper on TextQuests: How Good are LLMs at Text-Based Video Games, and many more! open.substack.com/pub/deeplearni…

🤖 From this week's issue: OpenAI released GPT-5, a significant leap in intelligence over all previous models, featuring state-of-the-art performance across coding, math, writing, health, visual perception, and more. openai.com/index/introduc…

🤖 From this week's issue: Claude Sonnet 4 now supports up to 1 million tokens of context on the Anthropic API. anthropic.com/news/1m-context

🤖 From this week's issue: A technical blog post discussing the practical breakdown of the design principles for AI agent architecture that help to ship and scale real-world AI agents. comet.com/site/blog/ai-a…

🤖 From this week's issue: An evaluative blog post discussing the GPT-5 release, emphasizing its role as a unified, cost-effective system that enhances OpenAI's product offering and market position. interconnects.ai/p/gpt-5-and-be…

🤖 From this week's issue: An open-source LLM evaluation tool used to debug, evaluate, monitor LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. github.com/comet-ml/opik

🤖 From this week's issue: A blog post on FourCastNet3 (FCN3), NVIDIA Earth-2's latest AI global weather forecasting system. developer.nvidia.com/blog/fourcastn…

🤖 From this week's issue: An analytical article providing a detailed comparison and evolution of large language model architectures from GPT-2 to OpenAI's new open-weight gpt-oss models. magazine.sebastianraschka.com/p/from-gpt-2-t…

🤖 From this week's issue: A strategic blog post outlining four crucial locations for implementing LLM monitoring to effectively identify and mitigate dangerous or malicious AI actions. redwoodresearch.substack.com/p/four-places-…

🤖 In this week's issue: A summary forecasting that the electrical power demand for training frontier AI models will grow exponentially, potentially reaching 4-16 gigawatts by 2030 for individual runs and over 100 gigawatts for total AI capacity worldwide. epoch.ai/blog/power-dem…

🤖 From this week's issue: An industrial automation startup called Squint has raised $40 million as it bids to build on a vision of “agentic manufacturing,” where humans collaborate with artificial intelligence agents. siliconangle.com/2025/08/12/squ…

🤖 From this week's issue: The team at Z. ai introduced two new GLM family members called GLM-4.5 and GLM-4.5-Air – designed to unify reasoning, coding, and agentic capabilities into a single model. z.ai/blog/glm-4.5

🤖 From this week's issue: An innovative blog post presenting Elysia, an open-source, agentic RAG framework built on a decision-tree architecture that features dynamic data display types, AI data analysis, and more. weaviate.io/blog/elysia-ag…

🤖 From this week's issue: A paper on TextQuests: How Good are LLMs at Text-Based Video Games? textquests.ai

🤖 Issue #418 is now live! This week features: Gemma 3 270M, Best Practices for Building Agentic AI Systems: What Actually Works in Production, a paper on GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning, and many more! open.substack.com/pub/deeplearni…

🤖 From this week's issue: Google introduced Gemma 3 270M, a compact, 270-million parameter model designed for task-specific fine-tuning. developers.googleblog.com/en/introducing…

🤖 From this week's issue: Meta released DINOv3, a generalist, state-of-the-art computer vision model trained with self-supervised learning that produces superior high-resolution visual features. ai.meta.com/blog/dinov3-se…

🤖 From this week's issue: In a new study, MIT researchers use sparse autoencoders to determine what features a protein language model takes into account when making predictions news.mit.edu/2025/researche…

🤖 From this week's issue: A practical article about best practices for building and implementing agentic AI systems in production, covering architectural patterns, communication, error handling, and performance optimization. userjot.com/blog/best-prac…

🤖 From this week's issue: A post on optimizing Triton BF16 Grouped GEMM kernel for running training and inference on Mixture-of-Experts (MoE) models, such as DeepSeekv3. pytorch.org/blog/accelerat…