KDnuggets
AI news source. Articles are auto-selected and adapted by Hamidun News editors.
Latest publications
KDnuggets published a guide to local call analysis with Whisper, BERTopic, and Streamlit
KDnuggets reviewed an open-source project that transcribes customer call recordings with Whisper, detects sentiment and emotions, and then groups topics in a local Streamlit interface.
Unsloth Studio adds a GUI for merging language models without retraining
Unsloth Studio has launched a no-code GUI for combining language models — users can now merge LLMs without writing code and without costly retraining from scratch.
KDnuggets rounded up 10 open-source agent projects you can fork today
KDnuggets published a practical list of 10 open-source repositories for learning agent engineering — from coding agents and browser automation to memory and deep research.
KDnuggets named 10 GitHub repositories that help users master Claude Code more deeply
KDnuggets compiled 10 GitHub repositories that help users learn Claude Code through real workflows, templates, subagents, system prompts, and ready-made configurations.
AI startup advisor Salil Darji listed the mistakes founders notice too late
AI startup mentor Salil Darji says founders are held back by spreading themselves too thin, a cult of the pitch deck, and chasing hype — while those who stay focused and understand the economics come out ahead.
How to turn OpenAI Codex into a full AI agent for real-world development: 5 practices
OpenAI Codex can be significantly improved with simple setups: planning, an AGENTS.md file, custom skills, self-checks, and using CLI tools.
KDnuggets picked 10 X accounts to follow for LLM news
KDnuggets compiled 10 X accounts that help track LLM news without the noise: from Andrej Karpathy and Simon Willison to DAIR.AI, alphaXiv, and release feeds.
KDnuggets listed 5 Python decorators that make AI code cleaner and more reliable
KDnuggets collected five Python decorators that help keep AI code in order: limit concurrency, log steps, fix seed, and handle API failures.
Abacus AI Pushes ChatLLM as One-Service Replacement for ChatGPT, Claude, and Midjourney
Abacus AI's ChatLLM combines text models, image generation, video, and agent scenarios in a single interface to reduce the number of subscriptions and switches between AI services.
Hugging Face showed how to build a weather AI agent on smolagents in 15 minutes
Hugging Face via the smolagents library shows how to build a weather AI agent in Python in 15 minutes: add a tool, connect an LLM, and let it autonomously fetch data.
Whisper and Faster-Whisper: How to Transcribe Audio Locally Without Sending Files to the Cloud
A step-by-step breakdown of local audio transcription via Faster-Whisper and Python: data stays out of the cloud, and operation is possible offline on both CPU and GPU.
Google Antigravity: How to Connect Rules, Skills, and Workflows for Reliable AI Agents
Google Antigravity examined how to assemble a robust QA pipeline through rules, skills, and workflows: an agent checks Python code, refactors it, and prepares tests itself.
Python: 10 Libraries for Building LLM Applications — from RAG to Agentic Systems
A collection of 10 Python libraries shows which layers are used today to build LLM applications: models, RAG, agentic workflows, production serving, and quality evaluation.
Olostep: automatic documentation crawler for preparing data for AI
Olostep allows crawling entire documentation websites with a few lines of code — the tool collects pages, removes unnecessary elements, and provides clean text ready for AI tasks.
How to run ultra-efficient 1-bit neural networks locally: a guide to BitNet
We explain how to deploy the BitNet b1.58 architecture on your PC. We cover bitnet.cpp installation and the advantages of using 1-bit models at home.
The MCP Revolution and the Search for Viable Enterprise AI Use Cases
Researcher Sebastian Walkötter examines the standardization of AI integrations, security issues, and the key question holding back enterprise AI adoption.
Five architectural patterns without which agentic AI cannot survive in production
AI-based agentic systems are increasingly moving beyond prototypes, but most of them break down on the way to production. We examine which architectural patterns separate working solutions from polished demos.
DataCamp opens free access to data analytics training for one week
Popular platform DataCamp has made all its Python, SQL and PowerBI courses free until February 22. A chance to gain certification-level skills at no cost.
Guide to Feature Stores: The Foundation of Modern ML Infrastructure
Learn why feature stores have become a critical element for scaling neural networks and which tools dominate today's fast-growing MLOps market.
ML-Pipeline Optimization: 5 Ways to Save Team Time
In modern machine learning (ML) development, pipeline efficiency plays a critical role. Often, teams spend unjustifiably large amounts of time on stages that can be optimized.
Bindu Reddy and the Path to AGI: Why One 'Smartest' Model Won't Be Enough
While Silicon Valley competes to loudly promise the advent of artificial general intelligence (AGI) by next Tuesday, Bindu Reddy suggests taking a deep breath.
AI in Business: How to Stop Believing in Magic and Start Counting Money
The era of tourist interest in neural networks has officially ended. If in 2023 CEOs of major companies were running around conferences asking "what do we do with ChatGPT?", then in 2024 they come to…
Time Series: Five Neural Networks That Forecast the Future Better Than Analysts
Time Series: Five Neural Networks That See the Future Better Than Analysts While the world is passionately debating whether GPT-5 will learn to reason, in the shadow of large language models there…
Billions of Parameters: How We Measure Intelligence in Numbers
Each time a major AI release happens in the industry, the first question in the comments sounds the same: "How many parameters does it have?" This has become a kind of measure of sophistication,…
Scikit-learn: 7 Tricks for Those Tired of Waiting Forever
Hyperparameter tuning is the very activity that transforms a data scientist from an architect of the future into a bored washing machine operator.
Hugging Face Spaces: How to Stop Paying for Your Portfolio Hosting
Let's be honest: most ML developer portfolios on GitHub look like code graveyards. You spend weeks training a model, write clean code, format the repository properly, but when it comes time to…
Data Teams: Why Number of Neural Networks No Longer Matters
The era of "flag waving," when companies could simply claim to have neural networks on staff, has officially come to an end.
The Multimodal Shift: How AI Stopped Being Blind and Why It Matters
A couple of years ago, we marveled at the fact that neural networks could draft a well-written letter or write code.
Data Under Lock: Three Ways to Save ML Pipelines from Leaks
Imagine you're building a supersonic aircraft, but you have to fuel it with fuel that can explode from any careless movement.
Feature Engineering on Steroids: Seven Python Libraries You're Wrongly Ignoring
Data Science is 80% data cleaning and 20% complaining about how much time data cleaning takes. We're all accustomed to the standard stack, where Pandas and Scikit-learn seem eternal and indispensable.