📰 Towards Data Science

In Part 1 of this series, we introduced Chronos-2, a time-series foundation model. We got our hands dirty by walking through a real case study and saw what Chro

A look at the real-world value of online graduate AI programs, combining hard data with firsthand experience of a big tech machine learning engineer The post Is

Enterprise Document Intelligence [Vol. 1 #1] The smallest version of RAG that actually works, on a real PDF, with grounded answers and the source lines highligh

A retrospective on my MS thesis, the leaderboard it placed on, and the LLM shift that has reshaped the field since. The post EmoNet: Speaker-Aware Transformers

A practitioner's warning about generated variables in causal analysis The post LLM Themes Are Not Observations appeared first on Towards Data Science .

Most LLM failures in production aren’t random — they’re predictable. I kept hitting broken JSON, silent failures, and outages that froze my entire app. Prompt e

How unlearning fixes mode collapse in synthetic survey replies The post Can LLMs Replace Survey Respondents? appeared first on Towards Data Science .

Why production LLM systems need live web search to overcome knowledge cutoffs and stale training data The post Grounding LLMs with Fresh Web Data to Reduce Hall

Most LLM evaluation systems rely on vague scoring and human judgment disguised as metrics. I built a lightweight evaluation layer in pure Python that turns LLM

Learn how to make your Claude Code improve over time The post How I Continually Improve My Claude Code appeared first on Towards Data Science .

From a Chinese prompt to a Korean response: an embedding-space investigation into how code vocabulary reshapes language The post Why My Coding Assistant Started

How to build a decision-grade scorecard for AI agents The post Stop Evaluating LLMs with “Vibe Checks” appeared first on Towards Data Science .

A practical comparison between rule-based PDF extraction using “pytesseract” and an LLM-based approach with “Ollama” and “LLaMA 3”, based on a realistic B2B ord

Why learn 8 scripts when you can learn 256 bytes? The post Bytes Speak All Languages: Cross-Script Name Retrieval via Contrastive Learning appeared first on Tow

How I turned LLM persona interviews into a repeatable customer research workflow The post From Ad Hoc Prompting to Repeatable AI Workflows with Claude Code Skil

Conceptual overview and practical guidance The post Context Payload Optimization for ICL-Based Tabular Foundation Models appeared first on Towards Data Science

Explore the end-to-end pipeline of TurboQuant, a novel KV cache quantization framework. This overview breaks down how multi-stage compression achieves near-loss

Architectures, pitfalls, and patterns that work The post A Practical Guide to Memory for Autonomous LLM Agents appeared first on Towards Data Science .

Why storing and retrieving data isn’t enough to build reliable AI memory systems The post Stop Treating AI Memory Like a Search Problem appeared first on Toward

A clear mental model and a practical foundation you can build on The post Grounding Your LLM: A Practical Guide to RAG for Enterprise Knowledge Bases appeared f

Persistent AI memory without embeddings, Pinecone, or a PhD in similarity search. The post I Replaced Vector DBs with Google’s Memory Agent Pattern for my notes

A systems design diagnosis of hallucination, corrigibility, and the structural gap that scaling cannot close The post The Inversion Error: Why Safe AGI Requires

Make your coding agent more efficient The post How to Make Claude Code Better at One-Shotting Implementations appeared first on Towards Data Science .

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 ecos