InfoQ Homepage Machine Learning Content on InfoQ
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Google Open-Sources Natural Language Robot Control Method SayCan
Researchers from Google's Robotics team have open-sourced SayCan, a robot control method that uses a large language model (LLM) to plan a sequence of robotic actions to achieve a user-specified goal. In experiments, SayCan generated the correct action sequence 84% of the time.
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Amazon Announced Promotion Feature in Its Personalize Service
Amazon web services has recently announced a promotion feature in personalize to explicitly recommend specific items based on business rules. Amazon Personalize enables businesses to improve customer engagement and monetization metrics by recommending personalized items to the customers.
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Amazon Is Adding Visual Conversation Builder for Amazon Lex
Amazon is introducing the Visual Conversation Builder for Amazon Lex, a drag and drop interface to visualize and build conversation flows in a no-code environment. The Visual Conversation Builder greatly simplifies bot design.
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Amazon SageMaker Provides New Built-in TensorFlow Image Classification Algorithms
Amazon is announcing a new built-in TensorFlow algorithm for image classification in Amazon Sagemaker. The supervised learning algorithm supports transfer learning for many pre-trained models available in TensorFlow Hub.
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Netflix’s New Algorithm Offers Optimal Recommendation Lists for Users with Finite Time Budget
Netflix developed a new machine learning algorithm based on reinforcement learning to create an optimal list of recommendations considering a finite time budget for the user. In a recommendation use case, often the factor of finite time to make a decision is ignored.
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MIT Researchers Develop AI Model to Solve University-Level Mathematics Problems
Researchers at MIT have developed an AI model that can solve problems used in university-level mathematics courses. The system uses the OpenAI Codex engine to generate programs that output the problem solution, including graphs and plots, achieving an accuracy of 81% on the MATH benchmark dataset as well as on real problems from MIT courses.
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Near-Optimal Scaling of Large Deep Network Training on Public Cloud
A recently published study, MiCS, provides experimental evidence that the infrastructure used to carry out model training should be taken into account, especially for large deep neural networks trained on the public cloud. The article shows distributing the model weights unevenly between GPUs decreases inter-node communication overhead on AWS V100 and A100 instances.
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Stability AI Open-Sources Image Generation Model Stable Diffusion
Stability AI released the pre-trained model weights for Stable Diffusion, a text-to-image AI model, to the general public. Given a text prompt, Stable Diffusion can generate photorealistic 512x512 pixel images depicting the scene described in the prompt.
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Amazon Announces the Improvement of ML Models to Better Identify Sensitive Data on Amazon Macie
Amazon is announcing a new capability to create allow lists in Amazon Macie. Now text or text patterns not desire for Macie to report as sensitive data can be specified in allow lists. Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect sensitive data in AWS.
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Microsoft Releases SynapseML 0.1.0 with .NET and Cognitive Services Support
Microsoft announced the first .NET-compatible version of SynapseML, a new machine learning (ML) library for Apache Spark distributed processing platform. Version 0.1.0 of the SynapseML library adds support for .NET bindings, allowing .NET developers to write ML pipelines in their preferred language.
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Amazon Launches What-If Analyses for Machine Learning Forecasting Service Amazon Forecast
Amazon is announcing that now its time-series machine learning based forecasting service Amazon Forecast can run what-if assessments to determine how different business scenarios can affect demand estimates. What-if analysis is an effective business technique for simulating hypothetical scenarios and stress testing on planning assumptions by recording potential outcomes.
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AWS Deep Graph Knowledge Embedding for Bond Trading Predictions
AWS developed the Deep Graph Knowledge Embedding Library (DGL-KE), a knowledge graph embedding library built on the Deep Graph Library (DGL). DGL is a scalable, high performance Python library for deep learning in graphs. This library is used by the advanced machine learning systems developed with Trumid to build a credit trading platform.
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Meta Open-Sources 175B Parameter Chatbot BlenderBot 3
Meta AI Research open-sourced BlenderBot 3, a 175B parameter chatbot that can learn from live interactions with users "in the wild." In evaluations by human judges, BlenderBot 3 achieves a 31% rating increase compared to the previous BlenderBot version.
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Next Generation of Data Movement and Processing Platform at Netflix
Netflix engineering recently published in a tech blog how they used data mesh architecture and principles as the next generation of data platform and processing to unleash more business use cases and opportunities. Data mesh is the new paradigm shift in data management that enables users to easily import and use data without transporting it to a centralized location like a data lake.
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Google Published Results on How ML-Enhanced Code Compilation Could Improve Developers’ Productivity
The rapid advances in natural language processing (NLP) opened a new direction to use deep learning models in providing smarter suggestions for developers while writing software codes. Google AI has recently published results on ML-enhanced code compilation and how it improved developers’ productivity considering different metrics.