InfoQ Homepage Deep Learning Content on InfoQ
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ML.NET 2.0 Release Contains New NLP APIs and AutoML Updates
Microsoft announced the release of ML.NET 2.0, the open-source machine learning framework for .NET. The release contains several updated natural language processing (NLP) APIs, including Tokenizers, Text Classification, and Sentence Similarity, as well as improved automated ML (AutoML) features.
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Meta's CICERO AI Wins Online Diplomacy Tournament
Meta AI Research recently open-sourced CICERO, an AI that can beat most humans at the strategy game Diplomacy, a game that requires coordinating plans with other players. CICERO combines chatbot-like dialogue capabilities with a strategic reasoning, and recently placed first in an online Diplomacy tournament against human players.
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AWS Makes it Simpler to Share ML Models and Notebooks with Amazon SageMaker JumpStart
AWS announced that it is now easier to share machine learning artifacts like models and notebooks with other users using SageMaker JumpStart. Amazon SageMaker JumpStart is a machine learning hub that helps users accelerate their journey into the world of machine learning.
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NVIDIA Kubernetes Device Plug-in Brings Temporal GPU Concurrency
Starting from the v12 release, the Nvidia GPU device plug-in framework started supporting time-sliced sharing between CUDA workloads on Kubernetes. This feature aims to prevent under-utilization of GPU units and make it easier to scale applications by leveraging concurrently-executing CUDA contexts.
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Wayve's End-to-End Deep Learning Model for Self-Driving Cars
Wayve released a state-of-the-art end-to-end model for learning a world model and vehicular driving policy based on simulation data from CARLA, allowing autonomy to cars without HD maps. Wayve’s new Model-based Imitation Learning (MILE) is a machine-learning model, specifically a reinforcement learning architecture, that learns a model of the world and a driving policy during offline training.
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Microsoft Open-Sources Agricultural AI Toolkit FarmVibes.AI
Microsoft Research recently open-sourced FarmVibes.AI, a suite of ML models and tools for sustainable agriculture. FarmVibes.AI includes data processing workflows for fusing multiple sets of spatiotemporal and geospatial data, such as weather data and satellite and drone imagery.
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Google's Code-as-Policies Lets Robots Write Their Own Code
Researchers from Google's Robotics team have open-sourced Code-as-Policies (CaP), a robot control method that uses a large language model (LLM) to generate robot-control code that achieves a user-specified goal. CaP uses a hierarchical prompting technique for code generation that outperforms previous methods on the HumanEval code-generation benchmark.
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Salesforce Open-Sources Language-Vision AI Toolkit LAVIS
Salesforce Research recently open-sourced LAnguage-VISion (LAVIS), a unified library for deep-learning language-vision research. LAVIS supports more than 10 language-vision tasks on 20 public datasets and includes pre-trained model weights for over 30 fine-tuned models.
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Meta Announces Next Generation AI Hardware Platform Grand Teton
Meta recently announced Grand Teton, their next-generation hardware platform for AI training. Grand Teton features several improvements over the previous generation, including 2x the network bandwidth and 4x the host-to-GPU bandwidth.
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Alpa: Automating Model Sharding for Distributed Deep Learning
A new open-source library called Alpa aims to automate distributed training and serving of large deep networks. It proposes a compiler where existing model-parallel strategies are combined and the usage of computing resources is optimized according to the deep network architecture.
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Google’s Tensorflow Roadmap Includes Better XLA Compilation and Distributed Computing
Google announced the next iteration of TensorFlow development. TensorFlow is the machine learning platform developed by Google and open sourced seven years ago. The development road-map for the next TensorFlow releases is based on four pillars: fast and scalable, applied machine learning, ready to deploy and simplicity.
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Meta Announces Video Generation AI Model Make-a-Video
Meta AI recently announced Make-A-Video, a text-to-video generation AI model. Make-A-Video is trained using publicly available image-text pairs and video-only data and achieves state-of-the-art performance on the UCF-101 video-generation benchmark.
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Snap Way to Design Ads Ranking Service Using Deep Learning
Snap engineering has recently published a blog post on how they designed their ads ranking and targeting service using deep learning. Showing ads to the users is the mainstream of social network platform monetization. Snap ad ranking system is designed to target the right user at the right time. Snap is providing an excellent user experience while preserving user privacy and security.
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PyTorch Becomes Linux Foundation Top-Level Project
PyTorch, the popular deep-learning framework developed by Meta AI Research, has now become an independent top-level project of the Linux Foundation. The project will be managed by the newly-chartered PyTorch Foundation, with support from several large companies including Meta, AWS, NVIDIA, AMD, Google, and Microsoft.
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Amazon EC2 Trn1 Instances for High Performance on Deep Learning Training Models Now Available
AWS announces general availability of Amazon EC2 Trn1 instances powered by AWS Trainium Chips. Trn1 instances deliver the highest performance on deep learning training of popular machine learning models on AWS, while offering up to 50% cost-to-train savings over comparable GPU-based instances.