Who Do Autonomous Agents Answer To? The Identity & Governance Problem
Author(s): Manni Arora Originally published on Towards AI. This is Part 2 of a two-part series on Agentic Identity. Part 1: Identity Management for Agentic AI: Making Authentication & Authorization Digestible https://medium.com/towards-artificial-intelligence/identity-management-for-agentic-ai-making-authentication-authorization-digestible-0fc5bb212862 TL;DR Agentic AI challenges traditional IAM by introducing autonomous actors …
Time Travel Debugging With Claude Code’s Conversation History
Author(s): Vikas Tiwari Originally published on Towards AI. A few weeks back, I was working on a legacy project that had over 100 microservices. I encountered a bug in this particular backend service that looked really familiar, but I could not recollect …
How to Denoise Industrial 3D Point Clouds in Python: Advanced Filtering with Vitreous from Telekinesis
Author(s): Telekinesis AI Originally published on Towards AI. For a senior robotics engineer, a raw point cloud from a Zivid, Roboception or Mech-Mind 3D camera is just the starting point. The real challenge is extracting the signal from the noise. In production, …
Your LLM Is Not Broken, Your AI System is🔐
Author(s): Gajanan Tayde Originally published on Towards AI. Your LLM Is Not Broken, Your AI System is🔐 When I first started working with AI systems, security felt… familiar. Models were just another component. You trained them, hosted them behind an API, slapped …
![Why Recommendation Systems Are Structurally Different from Deep Learning [2/2]](https://miro.medium.com/v2/resize:fit:224/1*4nGb2Nmj1E5itLdSpMynSA.png "Why Recommendation Systems Are Structurally Different from Deep Learning [2/2]")
Why Recommendation Systems Are Structurally Different from Deep Learning [2/2]
Author(s): NP_123 Originally published on Towards AI. How DLRM Trades Expressiveness for Structure at Scale This article is Part 2 of a two-part series on the structural and engineering trade-offs behind modern recommendation models such as DLRM. Part 1: https://medium.com/@np123greatest/why-recommendation-systems-are-structurally-different-from-deep-learning-1-2-62e9130acc6e The reference …
Unlocking the Magic of Adam: The Math Behind Deep Learning’s Favorite Optimizer
Author(s): Raaja Selvanaathan DATCHANAMOURTHY Originally published on Towards AI. Source: Author At the heart of every deep learning model lies a simple goal: minimizing error. We measure this error using something called a cost Function (or objective function). But knowing the error …
Go vs Python vs TypeScript — Which is The Most Efficient in LLM-Assisted Programming?
Author(s): Vikas Tiwari Originally published on Towards AI. Source: Image by the author TypeScript is the most popular language when it comes to LLM assisted programming. In the last year or so TypeScript has been the go to language when it comes …
Reference Architecture for Private AI on Azure: Designing Secure, Compliant, Hybrid LLM Systems
Author(s): Sandip Patel Originally published on Towards AI. Introduction: The Rise of Private AI Over the past two decades working in cloud architecture, I’ve witnessed several technology waves, but Private AI marks a fundamental shift in how enterprises will operate for the …
Understanding Retrieval Augmented Generation in The Easiest Way
Author(s): Asjad Abrar Originally published on Towards AI. Understanding Retrieval Augmented Generation in The Easiest Way The landscape of artificial intelligence has witnessed remarkable transformations over the past few years, with large language models demonstrating unprecedented capabilities in natural language understanding and …
Meta’s Reckoning: $73B in Metaverse Losses, an AI Talent Exodus, and Zuckerberg’s $14B Reset
Author(s): Zoom In AI Originally published on Towards AI. Reality Labs is shrinking. Meta’s AI org has been rattled by a benchmark controversy. And a geopolitically sensitive AI-agent deal is now under regulatory scrutiny. The pivot is real. The question is whether …
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