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Uber Adopts Amazon OpenSearch for Semantic Search to Better Capture User Intent
To improve search and recommendation user experiences, Uber migrated from Apache Lucene to Amazon OpenSearch to support large-scale vector search and better capture search intent. This transition introduced several infrastructure challenges, which Uber engineers addressed with targeted solutions. By Sergio De Simone
Podcast: Effective Mentorship and Remote Team Culture with Gilad Shoham
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Gilad Shoham about building effective mentorship relationships, leading fully distributed teams and the evolving role of developers in an AI-augmented future. By Gilad Shoham
Beyond Win Rates: How Spotify Quantifies Learning in Product Experiments
Spotify has introduced the Experiments with Learning (EwL) metric on top of its Confidence experimentation platform to measure how many tests deliver decision-ready insights, not just how many “win.” EwL captures both the quantity and quality of learning across product teams, helping them make faster, smarter product decisions at scale. The outcome must support one action: ship, abort, or iterate. By Olimpiu Pop
QCon AI NY 2025 - Becoming AI-Native Without Losing Our Minds To Architectural Amnesia
Tracy Bannon's QCon AI NY 2025 talk revealed how the rise of AI agents risks amplifying common architectural failures. She emphasized the distinctions between bots, assistants, and agents, highlighting the need for governance, clear identity controls, and disciplined decision-making to address “agentic debt.” Bannon called for architects to apply foundational principles amid rapid AI adoption. By Andrew Hoblitzell
How Artificial Intelligence Can Help Us Connect with Customers
In software development, success means going beyond meeting requirements. We must create products that surprise and delight users and are innovative, create impactful solutions, Ken Hughes said in the keynote “Connection is Everything”. AI can help us connect with customers and create better user experiences. By Ben Linders
Cactus v1: Cross-Platform LLM Inference on Mobile with Zero Latency and Full Privacy
Cactus, a Y Combinator-backed startup, enables local AI inference to mobile phones, wearables, and other low-power devices through cross-platform, energy-efficient kernels and a native runtime. It delivers sub-50ms time-to-first-token for on-device inference, eliminates network latency, and defaults to complete privacy. By Sergio De Simone
Presentation: Ecologies and Economics of Language AI in Practice
Jade Abbott discusses the shift from massive, resource-heavy models to "Little LMs" that prioritize efficiency and cultural sustainability. She explains how techniques like LoRA, quantization, and GRPO allow for high performance with less compute. By sharing the "Ubuntu Punk" philosophy, she shares how to move beyond extractive data practices toward human-centric, sustainable AI systems. By Jade Abbott
OpenAI and Anthropic Donate AGENTS.md and Model Context Protocol to New Agentic AI Foundation
OpenAI and Anthropic have donated their AGENTS.md and Model Context Protocol projects to the Agentic AI Foundation (AAIF), a new directed fund under the Linux Foundation. Block contributed their agent framework, goose, as another founding project, and several other tech companies have joined as Platinum members. By Anthony Alford
Pinecone Introduces Dedicated Read Nodes in Public Preview for Predictable Vector Workloads
Pinecone recently announced the public preview of Dedicated Read Nodes (DRN), a new capacity mode for its vector database designed to deliver predictable performance and cost at scale for high-throughput applications such as billion-vector semantic search, recommendation systems, and mission-critical AI services. By Craig Risi
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qlib
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
inngest
The leading workflow orchestration platform. Run stateful step functions and AI workflows on serverless, servers, or the edge.
qdrant
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/