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Agent Skills is now an open standard

Delty (YC X25) Is Hiring an ML Engineer

TRELLIS.2: state-of-the-art large 3D generative model (4B)

AI helps ship faster but it produces 1.7× more bugs

Gemini 3 Flash: frontier intelligence built for speed

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Gut Bacteria from Amphibians and Reptiles Achieve Complete Tumor Elimination

We Let AI Run Our Office Vending Machine. It Lost Hundreds of Dollars

Flick (YC F25) Is Hiring Founding Engineer to Build Figma for AI Filmmaking

Article: Where Architects Sit in the Era of AI

As AI evolves from tool to collaborator, architects must shift from manual design to meta-design. This article introduces the "Three Loops" framework (In, On, Out) to help navigate this transition. It explores how to balance oversight with delegation, mitigate risks like skill atrophy, and design the governance structures that keep AI-augmented systems safe and aligned with human intent. By Dave Holliday, João Carlos Gonçalves, Manoj Kumar Yadav

Google Cloud Launches Managed MCP Support

Google Cloud's introduction of fully managed Model Context Protocol (MCP) servers revolutionizes its API infrastructure, streamlining access for developers. This enterprise-ready solution enhances AI integration across services such as Google Maps and BigQuery while promoting wide-scale adoption. New tools ensure governance and security, and are currently in public preview. By Steef-Jan Wiggers

Article: Architecture in a Flow of AI-Augmented Change

While AI adoption is surging, most organizations fail to scale past pilots. The solution lies in organizational structure, not just technology. This article details how architects can enable "fast flow" by defining clear domains and guardrails. Learn how to shift from controlling outcomes to curating context, allowing AI to drive continuous, valuable business change. By Jonathan McPhail, Juan Medina, Jake DeCrane, Isuru Wijesundara

OpenAI at QCon AI NYC: Fine Tuning the Enterprise

At QCon AI NYC 2025, Will Hang from OpenAI unveiled Agent RFT—a cutting-edge reinforcement fine-tuning approach for tool-using agents. By optimizing prompts and tasks before model adjustments, Hang showcased effective strategies to enhance decision-making and efficiency, emphasizing a balanced grading system. The session revealed a future where smarter agents reduce latency and improve outcomes. By Andrew Hoblitzell

TornadoVM 2.0 Brings Automatic GPU Acceleration and LLM support to Java

The TornadoVM project recently reached version 2.0, a major milestone for the open-source project that aims to provide a heterogeneous hardware runtime for Java. The project automatically accelerates Java programs on multi-core CPUs, GPUs, and FPGAs. This release is likely to be of particular interest to teams developing LLM solutions on the JVM. By Ben Evans

Transformers v5 Introduces a More Modular and Interoperable Core

Hugging Face has released the first candidate for Transformers v5, marking a significant evolution from v4 five years ago. The library has grown from a specialized model toolkit to a critical resource in AI development, achieving over three million installations daily and more than 1.2 billion total installs. By Robert Krzaczyński

Meta's Optimization Platform Ax 1.0 Streamlines LLM and System Optimization

Now stable, Ax is an open-source platform from Meta designed to help researchers and engineers apply machine learning to complex, resource-intensive experimentation. Over the past several years, Meta has used Ax to improve AI models, accelerate machine learning research, tune production infrastructure, and more. By Sergio De Simone

Lyft Rearchitects ML Platform with Hybrid AWS SageMaker-Kubernetes Approach

Lyft has rearchitected its machine learning platform LyftLearn into a hybrid system, moving offline workloads to AWS SageMaker while retaining Kubernetes for online model serving. Its decision to choose managed services where operational complexity was highest, while maintaining custom infrastructure where control mattered most, offers a pragmatic alternative to unified platform strategies. By Eran Stiller

Presentation: Powering Enterprise AI Applications with Data and Open Source Software

Francisco Javier Arceo explored Feast, the open-source feature store designed to address common data challenges in the AI/ML lifecycle, such as feature redundancy, and low-latency serving at scale. By Francisco Javier Arceo

Frog gut bacterium eliminates cancer tumors in mice with a single dose

Kimi K2 Thinking at 28.3 t/s on 4x Mac Studio cluster

LG Will Let TV Owners Delete Microsoft Copilot After Customer Outcry

[P] jax-js is a reimplementation of JAX in pure JavaScript, with a JIT compiler to WebGPU

What is something AI still struggles with, in your experience?

Computational Creativity – Call for Papers for ICCC'26

AWS CEO says replacing junior devs with AI is 'one of the dumbest ideas'

Our AI sales agent has surprisingly brought in 29 new paying enterprise customers

AI helps ship faster but it produces 1.7× more bugs

StepFun

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GELab-Zero-4B-preview

ByteDance

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BindWeave

Microsoft

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NextCoder-32B

Task: text-generation

MIT HAN Lab

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nunchaku-flux.1-kontext-dev

Black Forest Labs

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FLUX.1-Kontext-dev-onnx

Google

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videoprism

Task: video-classification

SUFE-AIFLM-Lab

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Fin-R1

tencentmusic

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cube-studio

cube studio开源云原生一站式机器学习/深度学习/大模型AI平台，mlops算法链路全流程，支持大数据平台对接，notebook在线开发，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务VGPU虚拟化，边缘计算，标注平台自动化标注，deepseek等大模型sft微调/奖励模型/强化学习训练，vllm/ollama/mindie大模型多机推理，私有知识库，AI模型市场，支持国产cpu/gpu/npu 昇腾生态，支持RDMA，支持pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/ray/volcano等分布式

ag2ai

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faststream

FastStream is a powerful and easy-to-use Python framework for building asynchronous services interacting with event streams such as Apache Kafka, RabbitMQ, NATS and Redis.

google-ai-edge

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mediapipe-samples

ml-tooling

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best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

openxla

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xla

A machine learning compiler for GPUs, CPUs, and ML accelerators

modelscope

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modelscope

ModelScope: bring the notion of Model-as-a-Service to life.

autogluon

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autogluon

Fast and Accurate ML in 3 Lines of Code

Azure

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azureml-examples

Official community-driven Azure Machine Learning examples, tested with GitHub Actions.

evidentlyai

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evidently

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.