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News

Towards Data Science
towardsdatascience.com > retrieve-one-row-from-a-table-not-the-whole-table-row-level-chunks-for-rag

Retrieve One Row from a Table, Not the Whole Table: Row-Level Chunks for RAG

7+ hour, 30+ min ago   (928+ words) Enterprise Document Intelligence [Vol.1 #7sexies] – The unit of retrieval doesn’t have to be a page or a paragraph. When the corpus carries tables, each body row with its column headers is a chunk in its own right, and it’s often the…...

Towards Data Science
towardsdatascience.com > how-to-fine-tune-an-llm-an-end-to-end-guide

How to Fine-Tune an LLM: An End-to-End Guide

1+ day, 10+ hour ago   (1726+ words) A hands-on guide to fine-tuning LLMs for the real world We fine-tuned a 7B parameter model which completely blows foundation models out of the water, but just for this very narrow subtask: Filling out synoptic reporting templates for breast cancer. This…...

Towards Data Science
towardsdatascience.com > making-the-knowledge-layer-a-graph-you-actually-traverse

Making the Knowledge Layer a Graph You Actually Traverse

1+ day, 12+ hour ago   (1731+ words) Why retrieval quality should be a property of the system, not of the question's wording? Rebuilding knowledge layer with graph traversal on every query, bitemporal edges, and two-threshold entity resolution. The architecture held up. The contradiction register refused to answer…...

Towards Data Science
towardsdatascience.com > kimi-k3s-1m-token-context-window-vs-rag-cost-latency-and-answer-quality

Kimi K3???s 1M Token Context Window vs. RAG: Cost, Latency and Answer Quality

2+ day, 7+ hour ago   (1857+ words) A controlled comparison of a top-5 RAG pipeline and a full 127,000 token prompt on the same 12 questions, same system prompt and same model. Graded blind on correctness, completeness and grounding. When Kimi K3 came out in July with a context window…...

Towards Data Science
towardsdatascience.com > scaling-an-integration-pipeline-without-breaking-correctness

How to Scale an Integration Pipeline Without Breaking Correctness

2+ day, 6+ hour ago   (1069+ words) A production account of the throughput work behind a 16x jump — and the two guarantees it was never allowed to trade away Two guarantees sat underneath every throughput change, and every one of the optimizations later in this article is built…...

Towards Data Science
towardsdatascience.com > understanding-anti-ai-public-opinion

Understanding Anti-AI Public Opinion

2+ day, 9+ hour ago   (274+ words) People can accept tradeoffs when they see value — but if they don’t, what happens? There has been a lot of public discourse in the last few weeks focusing on the issue of public perception of AI, and why it’s so…...

Towards Data Science
towardsdatascience.com > ten-is-not-a-hundred

Ten Is Not a Hundred

3+ day, 12+ hour ago   (1200+ words) The number that fooled every hallucination detector A bank runs a RAG system behind its customer-service chat. A user asks about an invoice. The retrieved document says the total due is 10,000 dollars. The chatbot tells the client that the total…...

Towards Data Science
towardsdatascience.com > graph-engineering-isnt-about-more-connections-its-about-which-ones-get-used

Graph Engineering Isn???t About More Connections??? It???s About Which Ones Get Used

3+ day, 10+ hour ago   (1671+ words) I expected adding more communication pathways between agents to dramatically change network performance. It didn't. Figuring out why turned into a more useful article than the one I set out to write. This article shows a full working implementation in…...

Towards Data Science
towardsdatascience.com > designing-a-persistent-knowledge-layer-that-refuses-to-guess

Designing a Persistent Knowledge Layer That Refuses to Guess

5+ day, 9+ hour ago   (1809+ words) Blueconic sets this cookie as a unique identifier for the BlueConic profile. In my RAG-ING Ahead series I worked through a complete cloud-native retrieval stack: speech and document processing, chunking, embeddings, Azure AI Search, and an assistant layer sitting on…...

Towards Data Science
towardsdatascience.com > mathematical-experiments-are-becoming-abundant-through-human-machine-teaming

Mathematical Experiments Are Becoming Abundant Through Human-Machine Teaming

6+ day, 6+ hour ago   (1202+ words) Two open problems, exact-arithmetic checking and a proof assistant, over a single weekend. I ended a recent weekend without a Hadamard matrix of order 668 and with a mathematical theorem I did not yet trust enough to call a result. Working…...