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Zero-Copy In-Memory Sharing of Large Distributed Data: V6d
Zero-copy and in-memory data manager Vineyard (v6d) is maintained as a CNCF sandbox project and provides distributed operators that can be utilized to share immutable data within or across cluster nodes. V6d is of interest particularly for deep network training on big (sharded) datasets such as large language and graph models.
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Amazon Releases Fortuna, an Open-Source Library for ML Model Uncertainty Quantification
AWS announced that Fortuna, an open-source toolkit for ML model uncertainty quantification, has been made generally available. Any trained neural network can be used with the calibration methods offered by Fortuna, such as conformal prediction, to produce calibrated uncertainty estimates.
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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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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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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.
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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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Machine Learning Systems Vulnerable to Specific Attacks
The growing number of organizations creating and deploying machine learning solutions raises concerns as to their intrinsic security, argues the NCC Group in a recent whitepaper (Practical Attacks on Machine Learning Systems).
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Google AI Open-Sourced a New ML Tool for Conceptual and Subjective Queries over Images
Google AI open-sourced mood board search, a new ML-powered tool for subjective or conceptual queries over images. Mood board search helps users to define conceptual and subjective queries like peaceful, beautiful, over images.
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TensorFlow DTensor: Unified API for Distributed Deep Network Training
Recently released TensorFlow v2.9 introduces a new API for the model, data, and space-parallel (aka spatially tiled) deep network training. DTensor aims to decouple sharding directives from the model code by providing higher-level utilities to partition the model and batch parameters between devices.
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TensorFlow Similarity Supports Fast Query Search Index on Pre-trained Models
Francois Chollet and his team recently released a Python library for TensorFlow, called TensorFlow Similarity. Similarity learning is the process of finding similar items, from similar clothes in images to person identification using face pictures. Deep-learning models have used a method called contrastive learning to increase accuracy and efficiency in learning similarity between images.
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Google's Dev Library is a Curated Collection of Projects about Google Tech
Google has launched a new initiative aimed at creating a curated collection of open source projects related to Google technologies. Google's Dev Library will not only contain code repositories, but also articles, tools, and tutorials collected from various Internet sources.
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Google Integrates TensorFlow Lite with Android, Adds Automatic Acceleration
Google has announced a new mobile ML stack, dubbed Android ML Platform and built around TensorFlow Lite, which aims to solve a number of problems that developers find when using on-device machine learning.
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TensorFlow 3D: Deep Learning for Autonomous Cars’ 3D Perception
Google has released TensorFlow 3D, a library that adds 3D deep-learning capabilities to the TensorFlow machine-learning framework. The new library brings tools and resources that allow researchers to develop and deploy 3D scene understanding models.
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TensorFlow 2.4 Release Includes CUDA 11 Support and API Updates
The TensorFlow project announced the release of version 2.4.0 of the deep-learning framework, featuring support for CUDA 11, cuDNN 8, and NVIDIA's Ampere GPU architecture, as well as new strategies and profiling tools for distributed training. Other API updates include mixed-precision in Keras and a NumPy frontend.
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Apple's ML Compute Framework Accelerates TensorFlow Training
As part of the recent macOS Big Sur release, Apple has included the ML Compute framework. ML Compute provides optimized mathematical libraries to improve training on CPU and GPU on both Intel and M1-based Macs, with up to a 7x improvement in training times using the TensorFlow deep-learning library.