The Statistics of Token Selection: Logits, Temperature, and Top-P Walkthrough
In this article, you will learn how logits, temperature, and top-p sampling work together to control next-token prediction in large language models. Topics we will cover include: What logits are and how they are produced by a transformer’s final linear layer. How temperature and top-p (nucleus sampling) shape the probability distribution used for token selection. […]
Meet EAGLE 3.1: The Speculative Decoding Algorithm That Fixes Attention Drift in LLM Inference
Speculative decoding is a technique for speeding up large language model inference. A small, fast draft model proposes several tokens. The large target model verifies them in parallel. If accepted, inference is faster. If rejected, the system falls back gracefully. EAGLE Team, vLLM Team, and TorchSpec Team has launched the EAGLE series including EAGLE 1, […]
MEMO: A Modular Framework for Training a Dedicated Memory Model on New Knowledge Without Modifying LLM Parameters
Large language models become static after pretraining. Their knowledge does not update as the world changes. Retraining a full LLM is too expensive at modern scales. Fine-tuning risks degrading previously learned knowledge. Retrieval-augmented generation (RAG) struggles when answers require reasoning across many documents. A team of researchers from the National University of Singapore, MIT CSAIL, […]
Election information and safeguards in 2026
2026 is the world’s second major election year since generative AI became widely available, and we’re continuing to build on the foundation we laid in 2024 to help protect elections in countries and territories around the world. Our focus is to build and responsibly deploy groundbreaking products in ways that: Surface reliable information about voting […]
Design a High-Precision Retrieve-and-Rerank Pipeline with ZeroEntropy Zerank-2 Reranker
print(“\n” + “=”*70 + “\nPART 4: NDCG@10 evaluation\n” + “=”*70) eval_set = [ {“query”: “Where is most ATP produced in the cell?”, “rels”: {0: 2, 2: 3, 4: 2, 6: 1, 8: 3}}, {“query”: “How do plants capture light energy?”, “rels”: {1: 3, 9: 1}}, {“query”: “How are proteins made and packaged in a cell?”, […]
Stability AI Releases Stable Audio 3: A Family of Fast Latent Diffusion Models for Audio Generation and Editing
Stability AI has released open weights for Stable Audio 3 along with a technical research paper. Stable Audio 3 is a family of latent diffusion models that generate stereo audio at 44.1 kHz. The models support variable-length outputs, inpainting-based editing, and fast inference. What Is Stable Audio 3? Stable Audio 3 is a family of […]
What Is a Data Agent? | Towards Data Science
, I have the opportunity to try new AI-powered analytical tools, including Microsoft Fabric’s data agent. That’s why I want to share what I’ve learned, explain what a data agent is, and highlight the difference between it and a “standard” AI agent. So, without further ado, here is my definition of a data agent: A […]
The AI Model Confidence Trap
a bit whimsical on a Saturday and decided to ask ChatGPT a fairly simple question: “Who won the Nobel Prize in Physics in 2025?” ChatGPT responded immediately: “The 2025 Nobel Prize in Physics was awarded to…” It even provided names, research areas, and an explanation of the specific research that earned them the Nobel Prize! […]
Stop Using LLMs Like Giant Problem Solvers
on a feature where I had to transform 100 messy compliance pdfs into structured JSON rules. The brute force approach was obvious: give the agent the source text, explain the task, provide examples, and ask it to generate the rules. Since it was the lowest-hanging fruit, I tried it first. At a glance, the output […]
The Domain Shift: Moving Data Governance from Product Triage to Infrastructure Investment
In an earlier piece on the 2026 data mandate, I the EU AI Act, the Cyber Resilience Act, and the Data Act are pushing organizations for structural mandates to transition from reactive compliance towards a systemic Governance-by-Design. However, translating this architectural intent into daily business operations introduces a practical bottleneck: once the governance controls are […]