InfoQ Homepage Machine Learning Content on InfoQ
-
AlphaCode: Competitive Code Synthesis with Deep Learning
AlphaCode study brings promising results for goal-oriented code synthesis using deep sequence-to-sequence models. It extends the previous networks and releases a new dataset named CodeContests to contribute to future research benchmarks.
-
Waymo Releases Block-NeRF 3D View Synthesis Deep-Learning Model
Waymo released a ground-breaking deep-learning model called Block-NeRF for large-scale 3D world-view synthesis reconstructed from images collected by its self-driving cars. NeRF has the ability to encode surface and volume representation in neural networks.
-
How GitHub Uses Machine Learning to Extend Vulnerability Code Scanning
Applying machine learning techniques to its rule-based security code scanning capabilities, GitHub hopes to be able to extend them to less common vulnerability patterns by automatically inferring new rules from the existing ones.
-
PipelineDP Brings Google’s Differential-Privacy Library to Python
Google and OpenMined have released PipelineDP, a new open-source library that allows researchers and developers to apply differentially private aggregations to large datasets using batch-processing systems.
-
LambdaML: Pros and Cons of Serverless for Deep Network Training
A new study entitled "Towards Demystifying Serverless Machine Learning Training" aims to provide an experimental analysis of training deep networks by leveraging serverless platforms. FaaS for training has challenges due to its distributed nature and aggregation step in the learning algorithms. Results indicate FaaS can be a faster (for lightweight models) but not cheaper alternative than IaaS.
-
Meta AI’s Convolution Networks Upgrade Improves Image Classification
Meta AI released a new generation of improved Convolution Networks, achieving state-of-the-art performance of 87.8% accuracy on Image-Net top-1 dataset and outperforming Swin Transformers on COCO dataset where object detection performance is evaluated. The new design and training approach is inspired by the Swin Transformers model.
-
Evaluating Continual Deep Learning: a New Benchmark for Image Classification
Continual learning aims to preserve knowledge across deep network training iterations. A new dataset entitled "The CLEAR Benchmark: Continual LEArning on Real-World Imagery" has recently been published. The goal of the study is to establish a consistent image classification benchmark with the natural time evolution of objects for a more realistic comparison of continual learning models.
-
How AI Supports IT Operators to Resolve Issues Faster and Keep Systems Running
AIOps is all about equipping IT teams with algorithms that can help in quicker evaluation, remediation or actionable insights based on their historical data without the need to solicit feedback from users directly. AI can help IT operators to work smart, resolve issues faster and keep the systems up and running to deliver great end-user experience.
-
AI Listens by Seeing as Well
Meta AI released a self-supervised speech recognition model that also uses video and achieves 75% better accuracy for some amount of data than current state-of-the-art models. This new model, Audio-Visual Hidden BERT (AV-HuBERT), uses audiovisual features for improving models based only on hearing speech. Visual features used are based on lip-reading, similar to what humans do.
-
Meta and AWS to Collaborate on PyTorch Adoption
Meta and AWS will work together to improve the performance for customers of applications running PyTorch on AWS and accelerate how developers build, train, deploy, and operate artificial intelligence and machine-learning models.
-
AWS Launches SageMaker Studio Lab, Free Tool to Learn and Experiment with Machine Learning
AWS has introduced SageMaker Studio Lab, a free service to help developers learn machine-learning techniques and experiment with the technology. SageMaker Studio Lab provides users with all of the basics to get started, including a JupyterLab IDE, model training on CPUs and GPUs and 15 GB of persistent storage.
-
Recap of AWS re:Invent 2021
After one year as a virtual-only event, re:invent was back last week to Las Vegas with fewer attendees for the 10th edition, and with multiple sessions and keynotes, including a first one for the new CEO Adam Selipsky. AWS announced new features and improvements, with a focus more on packaged solutions than new primitives.
-
AMD Introduces Its Deep-Learning Accelerator Instinct MI200 Series GPUs
In its recent Accelerated Data Center Premiere Keynote, AMD unveiled its MI200 accelerator series Instinct MI250x and slightly lower-end Instinct MI250 GPUs. Designed with CDNA-2 architecture and TSMC’s 6nm FinFET lithography, the high-end MI250X provides 47.9 TFLOPs peak double precision performance and memory that will allow training larger deep networks by minimizing model sharding.
-
D2iQ Releases DKP 2.0 to Run Kubernetes Apps at Scale
D2iQ recently released version 2.0 of the D2iQ Kubernetes Platform (DKP), a platform to help organizations run Kubernetes workloads at scale. The new release provides a single pane of glass for managing multi-cluster environments and running applications across any infrastructure including private cloud, public cloud, or at the network edge.
-
AWS Announces the Availability of EC2 Instances (G5) with NVIDIA A10G Tensor Core GPUs
Recently AWS announced the availability of new G5 instances, which feature up to eight NVIDIA A10G Tensor Core GPUs. These instances are powered by second-generation AMD EPYC processors.