“Just in Time” World Modeling Supports Human Planning and Reasoning
An overview of a state-of-the-art study, uncovering simulation-based reasoning, a "just-in-time" framework and how it helps improve predictions in the context of supporting human planning and reasoning.
Claude Code Leak: 16 Lessons on Building Production-Ready AI Systems
Over the past 24 hours, the developer community has been obsessed with one thing. A leak. The source code of Claude Code, one of the most advanced AI coding systems, surfaced online. Within hours, GitHub was flooded with forks, breakdowns, and deep dives. For developers, it felt like rare access. Wh...
Why thinking longer can matter more than being bigger
The post How Can A Model 10,000× Smaller Outsmart ChatGPT? appeared first on Towards Data Science.
Speculative Decoding: How LLMs Generate Text 3x Faster
You probably use Google on a daily basis, and nowadays, you might have noticed AI-powered search results that compile answers from multiple sources. But you might have wondered how the AI can gather all this information and respond at such blazing speeds, especially when compared to the medium-sized...
The Map of Meaning: How Embedding Models “Understand” Human Language
Learn why embedding models are like a GPS for meaning. Instead of searching for exact words, it navigates a "Map of Ideas" to find concepts that share the same vibe. From battery types to soda flavors, learn how to fine-tune these digital fingerprints for pinpoint accuracy in your next AI project.
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Qwen3.5-Omni is here! Scaling up to a Native Omni-modal AGI
Multimodal AI has grown from novelty to a must in recent times. Need proof? If I were to tell you to work on an AI model that only understands text, you would probably laugh and throw 10 model names at me that can work across formats – be it text, audio, or visuals. The new […]
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I’ve been so surprised by how fast individual builders can now ship real and useful prototypes. Tools like Claude Code, Google AntiGravity, and the growing ecosystem around them have crossed a threshold: you can inspect what others are building online and realize just how fast you can build today. O...
Gemini 3.1 Flash Live: AI Conversations Now Feel Way More Human
Do you remember the very first AI voice conversation that you had? No doubt, it felt unreal getting live answers from a talking bot. But the one thing largely missing from the interaction was the feel of a human responding to your queries. Years on, we now see AI models have evolved largely in this ...
From Prompt to Prediction: Understanding Prefill, Decode, and the KV Cache in LLMs
This article is divided into three parts; they are: • How Attention Works During Prefill • The Decode Phase of LLM Inference • KV Cache: How to Make Decode More Efficient Consider the prompt: Today’s weather is so .
20+ Solved ML Projects to Build Your Portfolio and Boost Your Resume
Projects are the bridge between learning and becoming a professional. While theory builds fundamentals, recruiters value candidates who can solve real problems. A strong, diverse portfolio showcases practical skills, technical range, and problem-solving ability. This guide compiles 20+ solved proje...
Explainable AI in Production: A Neuro-Symbolic Model for Real-Time Fraud Detection
SHAP needs 30 ms to explain a fraud prediction. That explanation is stochastic, runs after the decision, and requires a background dataset you have to maintain at inference time. This article benchmarks a neuro-symbolic model that produces a deterministic, human-readable explanation in 0.9 ms — as a...
Self-Healing Neural Networks in PyTorch: Fix Model Drift in Real Time Without Retraining
What happens when your production model drifts and retraining isn’t an option? This article shows how a self-healing neural network detects drift, adapts in real time using a lightweight adapter, and recovers 27.8% accuracy—without retraining or downtime.
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Using OpenClaw as a Force Multiplier: What One Person Can Ship with Autonomous Agents
It's easier than ever to 10x your output with agentic AI.
The post Using OpenClaw as a Force Multiplier: What One Person Can Ship with Autonomous Agents appeared first on Towards Data Science.
From NetCDF to Insights: A Practical Pipeline for City-Level Climate Risk Analysis
Integrating CMIP6 projections, ERA5 reanalysis, and impact models into a lightweight, interpretable workflow
The post From NetCDF to Insights: A Practical Pipeline for City-Level Climate Risk Analysis appeared first on Towards Data Science.
Building Custom Claude Skills For Repeatable AI Workflows
Claude Skills is the latest AI tool that targets AI automation at some level. Anthropic was smart enough to identify one key problem developers face every day – having to rewrite prompts for repetitive tasks. So, packaging it in the form of “Skills”, Claude brings a new way to store these prompts or...
Building a Production-Grade Multi-Node Training Pipeline with PyTorch DDP
A practical, code-driven guide to scaling deep learning across machines — from NCCL process groups to gradient synchronization
The post Building a Production-Grade Multi-Node Training Pipeline with PyTorch DDP appeared first on Towards Data Science.
Build an AI Meeting Summarizer & Action Planner with Claude Code + MCP
Teams across companies lose meeting notes and action items after discussions. This guide builds a lasting fix: an AI Meeting Summarizer and Action Planner using Claude Code with MCP. It processes transcripts into structured summaries with tasks, decisions, and calendar invites, connects to Google Ca...