Small Language Models with Hugging Face transformers Library + smolLM3
Running a 70B model in production is expensive, and for many tasks, unnecessary. If you're building a focused pipeline, a well-trained 3B model will match or beat the 70B on your specific task at a fraction of the cost.
Learn how to use generative AI at work, build RAG and agentic apps, fine-tune models, work with the Hugging Face ecosystem, and prototype AI products with hands-on resources.
Top 5 Claude Skills for Writing (Ranked by GitHub Stars)
Search “best Claude Skills for writing” and you get lists padded with skills that write commit messages and internal status reports. Useful things. Not writing. This list only includes repositories that exist for writing. Every entry is a repository whose entire reason for being is writing or editin...
7 Approaches to Reduce Inference Latency in Your LLM Workflows
From quantization to speculative decoding, here are seven engineering strategies to ship faster, more responsive generative AI applications in production.
Read about MiniMax's own architecture, and see how it runs a real task against the actual API. Learn the pieces of the MiniMax story that weren't covered in the launch post.
Agentic Misalignment Explained: When AI Agents Go Rogue
Imagine hiring an AI assistant to handle important tasks, only to find that it quietly ignores your instructions because it believes it knows better. This is known as agentic misalignment, where an AI intentionally pursues its own objective instead of the one set by its operator. To understand how o...
KDnuggets Weekly Roundup: Build and Deploy Your First Autonomous Agent • 7 Machine Learning Algorithms That Still Matter
A Beginner's Guide to Working with Claude Design • 5 Best AI Tools for Data Analysis You Should Try in 2026 • 5 Books That Will Deepen Your Understanding of Large Language Models • Is KimiClaw a Useful Tool?
Building a voice-controlled AI agents isn't hard, this article breaks the pipeline into its real components: streaming speech recognition, turn detection, streaming generation, interruption handling, and tool calling under voice constraints and shows what each one is responsible for.
July 2026 AI Releases: A Timeline of Frontier Model Shifts
July 2026 was the busiest month for frontier model releases the field has seen. Four major labs shipped flagship or near-flagship models, two well funded newcomers shipped their first, and the largest open weight model ever published went up for download, all inside thirty one days. Read as a list, ...
Claude Code CLI Commands I Wish I Had Known Sooner
I used Claude Code daily for months before realizing that claude --help hides many of its most useful capabilities. I kept restarting fresh sessions, repeatedly explaining the same project structure, simply because I did not know a better workflow existed. While debugging an unrelated issue, I disco...
Discover 7 essential machine learning algorithms that every data scientist should know before reaching for LLMs and generative AI, with simple explanations and practical Python code.
What Professionals Should Know About Data Science and AI, According to Harvard Business School Online
Learn why clear business goals, data quality, simple models, careful validation, realistic costs, and human judgment matter more than chasing the latest technology.
Graph Engineering for AI Agents: Beyond the Single-Agent Loop
AI-agent development has progressed through overlapping phases: prompt engineering, context engineering, tool use, autonomous loops, memory systems, and multi-agent coordination. A newer focus is graph engineering, which treats AI applications as explicitly designed workflows rather than a single au...
Claude Opus 5: Near-Frontier Intelligence, On a Dial
Anthropic has released Claude Opus 5. The fourth model in two months, if you are keeping count. Most people are not. This one matters more than the count suggests. Opus is the workhorse tier, the model that does the actual paid work, and it just got a step change rather than a bump. Anthropic’s own ...
Top 5 MCP Servers for High Performance Agentic Development • 10 Newsletters Keeping You Ahead in AI • Kaggle + Google’s Free 5-Day Agentic AI Course • Language Model Hallucination Evaluation with GraphEval
Language Model Hallucination Evaluation with GraphEval
Turning the key principles and methodological stages of GraphEval into a simulated practical scenario to better understand its usefulness and key implications in understanding and combating LLM hallucinations.