Trying to answer the question of "Can LLM agents discover?" through the lens of creativity
The post Measuring the Creativity Potential of LLM Agents appeared first on Towards Data Science.
Coordinating agent capability development with the application it powers
The post Where the Agent Development Lifecycle Fits appeared first on Towards Data Science.
Can an Apartment Search Agent Call the Model Fewer Times and Still Find Good Matches?
I traced 2,500 listing checks with Weights & Biases Weave, removed avoidable model work one change at a time, and scored every version against the same answers.
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Coding agents give us more time for discovery and our review practices should follow the analysis
The post Insight Is Still the Currency of Data Science appeared first on Towards Data Science.
AI Made Data Scientists Faster. Now It’s Expanding the Job.
The real shift is bigger than productivity: AI is reshaping ownership, judgment, and the career path of data scientists.
The post AI Made Data Scientists Faster. Now It’s Expanding the Job. appeared first on Towards Data Science.
GraphRAG with TypeSafe Jev: A System One Approach to Scalable Knowledge Graphs
How calibrated decision models can handle high-frequency graph decisions while LLMs remain focused on reasoning, synthesis, and open-ended generation.
The post GraphRAG with TypeSafe Jev: A System One Approach to Scalable Knowledge Graphs appeared first on Towards Data Science.
Good Architecture Deletes the Signals Your Agent Depends On
Every boundary you draw removes a signal your tooling was relying on. That is a structure problem, not a search problem.
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AI Slop Is in Your Training Dataset Now. I Tested Three Ways to Spot It.
My AI detectors flagged many genuine reviews, and filtering them made the sentiment model less accurate.
The post AI Slop Is in Your Training Dataset Now. I Tested Three Ways to Spot It. appeared first on Towards Data Science.
Inside a transformer, token index is a coordinate. Paragraph structure is what turns it into a metric.
The post Your LLM Has a Curved Space of Paragraphs appeared first on Towards Data Science.
10 Things I’m Learning Beyond AI to Become More Technologically Fluent
Part 1: Understanding the technologies shaping our future
The post 10 Things I’m Learning Beyond AI to Become More Technologically Fluent appeared first on Towards Data Science.
Autoregressive rollout and uncertainty propagation. Second in a series on probabilistic forecasting for physical signals.
The post Your Model's MSE Is Lying to You: Part II appeared first on Towards Data Science.
RAG Isn't an Agent — I Built the Layer Between Retrieval and Action
RAG retrieves. Agents act. I built both separately, connected them explicitly, and ran the same nine tasks through all three systems.
The post RAG Isn't an Agent — I Built the Layer Between Retrieval and Action appeared first on Towards Data Science.
Beyond RAGs: Building Actually Truthful AI Harnesses
Retrieval is not evidence. How to build AI that proves its own claims.
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When the Correct Answer Is Nothing, What Does Your Pipeline Return?
The reliability mechanisms we add to LLM pipelines are often the ones that make them confidently wrong.
The post When the Correct Answer Is Nothing, What Does Your Pipeline Return? appeared first on Towards Data Science.
I Trained a Tiny Network to Compress Data. It Drew a Pentagon.
Reproducing Anthropic's "Toy Models of Superposition" from scratch in NumPy, with hand-derived gradients and no borrowed numbers.
The post I Trained a Tiny Network to Compress Data. It Drew a Pentagon. appeared first on Towards Data Science.
How GRPO Trains Small Language Models with Verifiable Rewards
The mechanics behind local reasoning experiments with Unsloth and why the reward function matters as much as the model.
The post How GRPO Trains Small Language Models with Verifiable Rewards appeared first on Towards Data Science.
Learn how to effectively code up an internal tool using Claude code or Codex
The post Build a Speaker-Recognition App with Claude Code appeared first on Towards Data Science.
Exploring TypeSafe's Jev and comparing it with OpenAI on intent classification
The post A New Kind of Model for AI Decision-Making? appeared first on Towards Data Science.
GPT-6 Astra Just Hit OpenAI's Highest Cybersecurity Risk Level
Why this matters less for what Astra can do and more for what every other model hasn't been tested for
The post GPT-6 Astra Just Hit OpenAI's Highest Cybersecurity Risk Level appeared first on Towards Data Science.
Your AI Assistant Wrote the Code. Who Checked the Defaults?
Five scikit-learn defaults that deserve a closer look before your next model reaches production
The post Your AI Assistant Wrote the Code. Who Checked the Defaults? appeared first on Towards Data Science.
PyTorch and TensorFlow tensor broadcasting: how silent shape errors cause difficult-to-debug machine learning bugs
The post Silent Broadcasting Can Ruin Your Model appeared first on Towards Data Science.
How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It.
Before reaching for an LLM API on every classification problem, it's worth knowing what a decades-old baseline can already do with the labeled data you have — and exactly how much more data buys you.
The post How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It. appeared fir...