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Change One Monty Hall Rule and Five LLMs Still Say Switch

towardsdatascience.com

Even with step-by-step reasoning, the models landed near 33% accuracy, and one quoted the host's rule correctly before ignoring it. The post Change One Monty Hall Rule and Five LLMs Still Say Switch appeared first on Towards Data Science.

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Build Your First Multi-Tool AI Agent with Ollama and Python

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AI Agents for Beginners, Part 2: The agent picks between three database tools, uses each result to choose its next call, and stops at an eight-turn circuit-breaker if it gets stuck. The post Build Your First Multi-Tool AI Agent with Ollama and Python

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Who Watches the AI?

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A separation of powers for control of autonomous agents The post Who Watches the AI? appeared first on Towards Data Science.

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An AI Agent Can Spot a Mistake and Still Not Fix It

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I replayed correct model decisions through four deliberately broken browser actions, and a simple page check missed half of the wrong clicks, which shows that noticing a fault and recovering from it are different skills. The post An AI Agent Can Spot

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Your RAG Pipeline Is Missing a 1994 Algorithm

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Embeddings know that "broken" means "defective". They may not notice that ZX-4821 is not ZX-4812. The post Your RAG Pipeline Is Missing a 1994 Algorithm appeared first on Towards Data Science.

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Our AI Has an Invisible Footprint — Let's see How to Measure It

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The hardest part is no longer getting the numbers. It's deciding what to do with them. The post Our AI Has an Invisible Footprint — Let's see How to Measure It appeared first on Towards Data Science.

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Tabular LLMs: An Introduction to the Foundation Models That Predict Your Spreadsheet

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Tabular foundation models predict the missing column of any spreadsheet zero-shot, the way an LLM completes text — and on the TabArena benchmark they now sit above fully tuned gradient-boosted trees. An introduction to how they work, an independent r

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Build an LLM Agent That Can Write and Run Code

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A hands-on walkthrough of code execution with the OpenAI Agents SDK and Docker The post Build an LLM Agent That Can Write and Run Code appeared first on Towards Data Science.

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Context Engineering Isn’t Enough — A Loop Engineering Experiment With No LLM Inside the Loop

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Everyone is talking about loop engineering, but most discussions assume an LLM sits at the center of the loop. I wanted to isolate the architecture itself. So I built a deterministic, zero-dependency Python benchmark that replaces the model with simp

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Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work

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LLMs don’t fail because they forget—they fail because they remember too much. As conversations grow, prompts accumulate redundant and low-value tokens, driving up cost and latency while silently degrading output quality. This article introduces a det

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Python 3.14 and its New JIT Compiler

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A technical overview and some benchmarks The post Python 3.14 and its New JIT Compiler appeared first on Towards Data Science.

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GPU Time-Slicing for Concurrent LLM Agents on Kubernetes

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A systems-level deep dive into the hidden microarchitectural costs of Kubernetes GPU time-slicing, and what it actually costs to co-locate Agentic AI workloads. The post GPU Time-Slicing for Concurrent LLM Agents on Kubernetes appeared first on Towar

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4 Lines You Should Include in Your Claude Skill

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Without these, Claude will be confidently wrong. The post 4 Lines You Should Include in Your Claude Skill appeared first on Towards Data Science.

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NDJSON Explained: The JSON Format Built for Big Data and Streaming

If you’ve worked with APIs, log processing, Apache Spark, Kafka, Elasticsearch, or large-scale ETL pipelines, you’ve probably encountered… Continue reading on Medium »

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Building My First ETL Pipeline Changed How I Think About Data Engineering

When I first started learning Data Engineering, ETL pipelines seemed fairly straightforward. Continue reading on Medium »

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