Machine learning news — deep learning, reinforcement learning, neural architecture search, diffusion models, and new ML frameworks and libraries.
Amazon has introduced a method for running machine learning inference on Amazon SageMaker AI using fully homomorphic encryption (FHE), which keeps data encrypted throughout the entire process—including queries, responses…
KiloBench launched as a new evaluation framework that measures AI coding models based on real-world production cost and performance rather than benchmark scores. The tool emerged after its creators found that a model sco…
AI engineers must master five critical Python concepts to build scalable, secure, and robust production systems, including PyTorch's autograd for automatic gradient computation and the `__call__` method for clean model i…
The growing use of artificial intelligence in weather and climate modeling relies on machine learning techniques that researchers have studied for years, not the generative AI behind viral chatbots. A National Weather Se…
IceWhale Technology's ZimaBoard 2 single-board computer, powered by an Intel N150 processor, is configured as a low-power Edge AI and IoT development server running Ubuntu Server 26.04 with Docker, Jupyter Lab, and UFW f…
A new concept called "Judgment Compression" is emerging as a critical missing layer in production AI system design, addressing the gap between generating outputs and validating their structure. While validators can confi…
The open source community is backing OpenEnv, a tool for creating agentic execution environments, as it transitions to a committee-led governance structure with support from Meta-PyTorch, Nvidia, Hugging Face, and other …
Speculative decoding, a lossless inference optimisation that predicts future tokens to reduce latency, faces new economic constraints as modern mixture-of-experts (MoE) architectures replace dense transformers. MoE layer…
A developer has added migration and refactoring skills to the Polylith tooling for Python, enabling AI agents to convert legacy single-repo projects into an agent-friendly Polylith Monorepo. The skills automate steps suc…
OpenAI and Thrive Holdings built a tax-preparation AI agent that cut document processing time by a third while achieving up to 97% accuracy. The system then self-improved over six weeks, raising the rate of fully accurat…
A perceptron, the simplest neural network, was introduced by Frank Rosenblatt in 1958. This article demonstrates building a perceptron from scratch in Python to classify numbers as positive or negative, showing how it le…
Engineering career outcomes and infrastructure observability decisions now rely on the same causal attribution methods, according to a cross-domain analysis. Staff+ promotion committees demand Difference-in-Differences o…
Anthropic reported degraded performance affecting multiple AI models on its platform. The company is offering email and text message notifications for users to track updates on the incident. Users must verify their phone…
Researchers analyzing token consumption in LLM-based multi-agent software engineering systems found that code review stages consume the majority of tokens at 59.4%, with input tokens accounting for 53.9% of total usage. …
Researchers introduced Gaia2, a benchmark for evaluating large language model agents in dynamic, asynchronous environments where scenarios evolve independently of agent actions. Testing of state-of-the-art models reveale…
Ernest Chan presented Conditional Portfolio Optimization (CPO), a machine-learning method that trains a neural network to predict portfolio performance based on market features and then solves a constrained optimization …
A developer found that deploying a 70B Llama model with RAG features caused time-to-first-token (TTFT) to jump from 180 ms to 1.4 seconds, as the model recomputed identical attention states for repeated 6,000-token conte…
OpenAI’s GPT models and Meta’s LLaMA-family use transformer architectures that convert text into token IDs, then map each ID to a dense vector via an embedding matrix. These vectors are combined with positional encodings…
A developer built a Quantified-Self RAG (Retrieval-Augmented Generation) system that ingests a decade of personal medical records from messy PDF scans using Unstructured.io, Sentence-Transformers, and Qdrant. The pipelin…
Developer Anil Madhavapeddy released TESSERA v1.1 and GeoTessera 0.9, improving temporal embeddings and S3+Zarr support, while also advancing io-uring libraries for OCaml. The updates address performance issues and expan…