InfoQ Homepage Machine Learning Content on InfoQ
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Hugging Face Unveils LeRobot, an Open-Source Machine Learning Model for Robotics
Hugging Face has unveiled LeRobot, a new machine learning model trained for real-world robotics applications. LeRobot functions as a platform, offering a versatile library for data sharing, visualization, and training of advanced models.
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Amazon Q Business and Amazon Q Developer Now Generally Available
AWS has recently announced the general availability of Amazon Q a generative AI-powered assistant tailored for businesses and developers. Amazon Q Developer provides code suggestions and recommendations in real time, while Amazon Q Business enables companies to get insights from structured and unstructured data.
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Modern Data Architecture, ML, and Resilience Topics Announced for QCon San Francisco 2024
QCon San Francisco returns November 18-22, focusing on innovations and emerging trends you should pay attention to in 2024. With technical talks from international software practitioners, QCon will provide actionable insights and skills you can take back to your teams.
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People, Planet, Cloud and AI: Key Takeaways from QCon London
This year’s QCon London brought a wealth of talks directly or indirectly related to software architecture, ranging from the rise of AI to more established areas like anything cloud-related to the usual classics like architecture quality traits . The conference also featured many talks about sociotechnical aspects of software architecture and engineering and broadly considered sustainability.
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Challenges and Solutions for Building Machine Learning Systems
According to Camilla Montonen, the challenges of building machine learning systems are mostly creating and maintaining the model. MLOps platforms and solutions contain components needed to build machine systems. MLOps is not about the tools; it is a culture and a set of practices. Montonen suggests that we should bridge the divide between practices of data science and machine learning engineering.
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Ines Montani at QCon London: Economies of Scale Can’t Monopolise the AI Revolution
During her presentation at QCon London, Ines Montani, co-founder and CEO of explosion.ai (the maker of spaCy), stated that economies of scale are not enough to create monopolies in the AI space and that open-source techniques and models will allow everybody to keep up with the “Gen AI revolution”.
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Mistral Large Foundation Model Now Available on Amazon Bedrock
AWS announced the availability of the Mistral Large Foundation Model on Amazon Bedrock during the recent AWS Paris Summit. This announcement comes days after the release of Mistral AI Models on Amazon Bedrock.
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Airbnb Open-Sources its ML Feature Platform Chronon
Chronon, Airbnb's platform which creates the infrastructure required to transform raw data into ML-ready features, is now open source. As Airbnb ML infrastructure engineer Varant Zanoyan explains, Chronon supports a variety of data sources and aims to provide low-latency streaming.
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Google Announces Agent Builder, Expanded Gemini 1.5, Open-Source Additions
At the Google Cloud Next 2024 event, Google announced the launch of Vertex AI Agent Builder, the public preview of Google's most advanced generative AI model, Gemini 1.5 Pro, and the addition of open-source language models to the Vertex AI platform.
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QCon London: Lessons Learned from Building LinkedIn’s AI/ML Data Platform
At the QCon London 2024 conference, Félix GV from LinkedIn discussed the AI/ML platform powering the company’s products. He specifically delved into Venice DB, the NoSQL data store used for feature persistence. The presenter shared the lessons learned from evolving and operating the platform, including cluster management and library versioning.
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Netflix Uses Metaflow to Manage Hundreds of AI/ML Applications at Scale
Netflix recently published how its Machine Learning Platform (MLP) team provides an ecosystem around Metaflow, an open-source machine learning infrastructure framework. By creating various integrations for Metaflow, Netflix already has hundreds of Metaflow projects maintained by multiple engineering teams.
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Wear OS Gets New, More Efficient Text-to-Speech Engine
Google has announced a new text-to-speech engine for Wear OS, its Android variant aimed at smartwatches and other wearables, supporting over 50 languages and faster than its predecessor thanks to using smaller ML models.
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Google BigQuery Introduces Vector Search
Google recently announced that BigQuery now supports vector search. The new functionality enables vector similarity search required by data and AI use cases such as semantic search, similarity detection, and retrieval-augmented generation (RAG) with a large language model (LLM).
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Anthropic Unveils Claude 3 Models, Highlighting Opus and Its Near-Human Capabilities
Anthropic has introduced the Claude 3 family models, surpassing other industry models such as GPT-4. The Claude 3 family consists of three distinct models: Haiku, Sonnet, and Opus, arranged in ascending order of capability, each designed to cater to diverse user needs in terms of intelligence, speed, and cost.
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Baseline OpenAI End-to-End Chat Reference Architecture
Microsoft published the baseline OpenAI end-to-end chat reference architecture. This baseline contains information about components, flows and security. There are also details about performance, monitoring and deployment guidance. Microsoft also prepared the reference implementation to deploy and run the solution.