Just two weeks after the launch of the frontier-grade Claude Opus 4.6, Anthropic has dropped its latest powerhouse: Claude Sonnet 4.6. But don’t let the Sonnet label fool you. Sonnet 4.6 is being hailed as the “Better-Opus” by developers in early access. For the first time, we are seeing a Sonnet-cl...
Iron Triangles: Powerful Tools for Analyzing Trade-Offs in AI Product Development
Conceptual overview and practical guidance
The post Iron Triangles: Powerful Tools for Analyzing Trade-Offs in AI Product Development appeared first on Towards Data Science.
Meet PaperBanana: Google’s AI That Auto-Generates Research Diagrams
Researchers today can draft entire papers with AI assistance, run experiments faster than ever, and summarise literature in minutes. Yet one stubborn bottleneck remains: creating clear, publication-ready diagrams. Poor diagrams look unprofessional and can obscure ideas and weaken a paper’s impact. G...
Check out this practical 2026 guide to Hugging Face. Explore transformers, datasets, sentiment analysis, APIs, fine-tuning, and deployment with Python.
This article covers the top seven Python libraries for implementing progress bars, with practical examples to help you quickly add progress tracking to data processing, machine learning, and automation workflows.
We Tested The New Qwen3.5 Open Weight, Qwen3.5-Plus AI Models in Real Hands-on Tests
Alibaba’s Qwen lineup has evolved rapidly over the past few weeks. We recently saw Qwen3-Coder-Next targeting developers with an AI coding assistant. This was followed by Qwen Image 2.0, which pushed the platform’s image generation quality even further. Each release strengthened a specific capabilit...
This article gently introduces feature stores, describing their origins, main characteristics, reasons for their current significance, and popular tools at present.
Fast providers offering open source LLMs are breaking past previous speed limits, delivering low latency and strong performance that make them suitable for real time interaction, long running coding tasks, and production SaaS applications.
Build a Powerful AI Research Pipeline with LM Studio and NotebookLM
Artificial intelligence tools are evolving rapidly, but the real productivity gains don’t come from using one The real power of these tools comes from using them together. Google NotebookLM specializes in structured knowledge synthesis, helping users analyze curated sources, generate summaries, and ...
I Built a Smart Movie Recommender with Collaborative Filtering
Recommendation systems are the invisible engines that can personalize our social media, OTTs and e-commerce. Whether you are scrolling through Netflix for a new show or browsing Amazon for a gadget, these algorithms are working behind the scenes to predict something for you. One of the most effectiv...
A practical onboarding checklist for building trust, business fluency, and data intuition
The post Your First 90 Days as a Data Scientist appeared first on Towards Data Science.
Stephanie Kirmer on the $200 billion investment bubble, how AI companies can rebuild trust, and how her day-to-day work changed with the rise of LLMs.
The post The Evolving Role of the ML Engineer appeared first on Towards Data Science.
I Built an AI Agent that Predicts Match Winners in the ICC Men’s T20 World Cup 2026
The T20 World Cup 2026 brings exciting matches, and fans constantly wonder which team will win. An AI agent answers this by analyzing live data and patterns instead of relying on intuition. Users enter a match date, and the system gathers all scheduled games and relevant context for that day. Built ...
How Andrej Karpathy Built a Working Transformer in 243 Lines of Code
The AI researcher Andrej Karpathy has developed an educational tool microGPT which provides the easiest access to GPT technology according to his research findings. The project uses 243 lines of Python code which does not need any external dependency to show users the fundamental mathematical princi...
Building an AI Agent to Detect and Handle Anomalies in Time-Series Data
Combining statistical detection with agentic decision-making
The post Building an AI Agent to Detect and Handle Anomalies in Time-Series Data appeared first on Towards Data Science.