Most LLM inference runtimes have no idea a physical deadline exists. This one refuses admission rather than miss a 33ms robot control cycle, evicts KV cache by meaning instead of age, and is written entirely in hand-written CUDA — no cuBLAS, no libtorch.

The post Can an LLM Forget the Right Things? appeared first on Towards Data Science.

Speculative decoding can turn underused CPU compute into faster token generation, without changing the model's output. In our vLLM tests, DFlash delivered 3.92x the autoregressive throughput with Qwen3.5-9B on Intel Xeon 6 at concurrency 1. We break down where the speedup comes from, explain the acceptance metrics, and show what determines whether speculation pays off.

The post Speculative Decoding on CPUs: Nearly 4x Faster Token Generation with DFlash appeared first on Towards Data Science.

A hands-on guide to fine-tuning LLMs for the real world

The post How to Fine-Tune an LLM: An End-to-End Guide appeared first on Towards Data Science.

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.

The post Kimi K3’s 1M Token Context Window vs. RAG: Cost, Latency and Answer Quality appeared first on Towards Data Science.

The number that fooled every hallucination detector

The post Ten Is Not a Hundred appeared first on Towards Data Science.

Here's how to be the Data Scientist who thrives in a world where coding is a commodity.

The post How to Shine as a Data Scientist in the Vibe Coding Era appeared first on Towards Data Science.

Can a language model do live adversarial level design? Yes, emphasis on the adversarial part

The post I Made an LLM Lay Siege to My Minecraft House appeared first on Towards Data Science.

Google's Open Knowledge Format (OKF) is a Markdown+YAML skeleton for sharing knowledge between humans and AI agents. This post reuses that skeleton for a very specific job — an agent-to-agent hand-off of pre-tokenized integer arrays between three Qwen2.5-Coder models (7B, 3B, 1.5B) — and shows the 28–37% TTFT reduction plus the one full-vocabulary equivalence check that keeps the whole thing safe.

The post How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs appeared first on Towards Data Science.

An open, 2.8-trillion-parameter model shipped with 47 pages of its own recipe. Reading it tells you what building a frontier model now involves, and how little of it is the model.

The post How a Frontier Model Gets Built, Read from the Kimi K3 Report appeared first on Towards Data Science.

Research-backed cues to detect LLM-generated text along with the mathematical intuition as to 'why'

The post Is This Slop? Detecting AI-Generated Content Without a Model appeared first on Towards Data Science.

How to use Claude to craft an outstanding resume that lands offers

The post How Claude Help Me Build My $200k+ ML Resume appeared first on Towards Data Science.