The mathematical foundations of Vision-Language-Action (VLA) models for humanoid robots and more
The post How Visual-Language-Action (VLA) Models Work appeared first on Towards Data Science.
This five day generative AI intensive course covers foundational models, embeddings, AI agents, domain-specific LLMs, and MLOps through a week of whitepapers, hands-on code labs, and live expert sessions.
Project Glasswing is World’s Most Powerful AI in Action
We already had a hint. AI would surpass most human capabilities someday. In the field of cybersecurity, that day arrived way too early, with the recent announcement of the Mythos Preview by Claude. The new AI model promises a level of coding skills that it is deemed to ‘surpass all but the most skil...
The Future of AI for Sales Is Diverse and Distributed
True creativity and innovation will come from human-agent collaboration. One human, millions of agents.
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Open-weight models are driving the latest excitement in the AI landscape. Running powerful models locally improves privacy, cuts costs, and enables offline use. But the open-source models are far and few! But Google‘s Gemma 4 is here to change that! This guide walks through what Gemma 4 is, would ex...
Democratizing Marketing Mix Models (MMM) with Open Source and Gen AI
A practical system design combining open-source Bayesian MMM and GenAI for transparent, vendor independent marketing analytics insights.
The post Democratizing Marketing Mix Models (MMM) with Open Source and Gen AI appeared first on Towards Data Science.
From 4 Weeks to 45 Minutes: Designing a Document Extraction System for 4,700+ PDFs
How a hybrid PyMuPDF + GPT-4 Vision pipeline replaced £8,000 in manual engineering effort, and why the latest models weren’t the answer
The post From 4 Weeks to 45 Minutes: Designing a Document Extraction System for 4,700+ PDFs appeared first on Towards Data Science.
Handling Race Conditions in Multi-Agent Orchestration
If you've ever watched two agents confidently write to the same resource at the same time and produce something that makes zero sense, you already know what a race condition feels like in practice.
7 Steps to Mastering Retrieval-Augmented Generation
As language model applications evolved, they increasingly became one with so-called RAG architectures: learn 7 key steps deemed essential to mastering their successful development.
How to optimize context, a precious finite resource for AI agents
The post Context Engineering for AI Agents: A Deep Dive appeared first on Towards Data Science.
LLM Wiki Revolution: How Andrej Karpathy’s Idea is Changing AI
Think about revisiting items you’ve saved to Pocket, Notion or your bookmarks. Most people don’t have the time to re-read all of these things after they’ve saved them to these various apps, unless they have a need. We are excellent at collecting tons of information. However, we are just not very goo...
Rethinking Enterprise Search: How Cortex Search Turns Data into Business Impact
According to Stack Overflow and Atlassian, developers lose between 6 and 10 hours every week searching for information or clarifying unclear documentation. For a 50-developer team, that adds up to $675,000–$1.1 million in wasted productivity every year. This is not just a tooling issue. It is a retr...
Building A Bulletproof Strategy For Data Recovery (Sponsored)
Data disruptions are no longer rare events. Hardware failures, ransomware, and unexpected outages can interrupt operations at any time. The difference between a temporary setback and a major business disruption often comes down to preparation.
The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition
The geometric foundations you need to understand the dot product
The post The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition appeared first on Towards Data Science.
Architecture and Orchestration of Memory Systems in AI Agents
The evolution of artificial intelligence from stateless models to autonomous, goal-driven agents depends heavily on advanced memory architectures. While Large Language Models (LLMs) possess strong reasoning abilities and vast embedded knowledge, they lack persistent memory, making them unable to ret...
Proxy-Pointer RAG: Achieving Vectorless Accuracy at Vector RAG Scale and Cost
A new way to build vector RAG—structure-aware and reasoning-capable
The post Proxy-Pointer RAG: Achieving Vectorless Accuracy at Vector RAG Scale and Cost appeared first on Towards Data Science.
A loss function is what guides a model during training, translating predictions into a signal it can improve on. But not all losses behave the same—some amplify large errors, others stay stable in noisy settings, and each choice subtly shapes how learning unfolds. Modern libraries add another layer ...
Building a Python Workflow That Catches Bugs Before Production
Using modern tooling to identify defects earlier in the software lifecycle.
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A Practical Guide to Measuring Relationships between Variables for Feature Selection in a Credit Scoring.
The post Building Robust Credit Scoring Models with Python appeared first on Towards Data Science.
Mamba4 Explained: A Faster Alternative to Transformers for Sequential Modeling
Transformers revolutionized AI but struggle with long sequences due to quadratic complexity, leading to high computational and memory costs that limit scalability and real-time use. This creates a need for faster, more efficient alternatives. Mamba4 addresses this using state space models with selec...