Machine learning news and insights

Import AI 219: Climate change and function approximation; Access Now leaves PAI; LSTMs are smarter than they seem 1d

LSTMs: Smarter than they appear:…Turns out you don’t need to use a Transformer to develop rich, combinatorial representations…Long Short-Term Memory networks are one of the widely-used deep learning architectures. Until recently, if you wanted to develop sophisticated natural language understanding AI systems, you’d use an LSTM. Then in the past couple of years, people have started switching over to using...

Automatically detecting personal protective equipment on persons in images using Amazon Rekognition 3d

Workplace safety hazards can exist in many different forms: sharp edges, falling objects, flying sparks, chemicals, noise, and a myriad of other potentially dangerous situations. Safety regulators such as Occupational Safety and Health Administration (OSHA) and European Commission often require that businesses protect their employees and customers from hazards that can cause injury by providing […]

Processing auto insurance claims at scale using Amazon Rekognition Custom Labels and Amazon SageMaker Ground Truth 4d

Computer vision uses machine learning (ML) to build applications that process images or videos. With Amazon Rekognition, you can use pre-trained computer vision models to identify objects, people, text, activities, or inappropriate content. Our customers have use cases that span every industry, including media, finance, manufacturing, sports, and technology. Some of these use cases require […]

Using speaker diarization for streaming transcription with Amazon Transcribe and Amazon Transcribe Medical 6d

Conversational audio data that requires transcription, such as phone calls, doctor visits, and online meetings, often has multiple speakers. In these use cases, it’s important to accurately label the speaker and associate them to the audio content delivered. For example, you can distinguish between a doctor’s questions and a patient’s responses in the transcription of […]

Optimizing the cost of training AWS DeepRacer reinforcement learning models 6d

AWS DeepRacer is a cloud-based 3D racing simulator, an autonomous 1/18th scale race car driven by reinforcement learning, and a global racing league. Reinforcement learning (RL), an advanced machine learning (ML) technique, enables models to learn complex behaviors without labeled training data and make short-term decisions while optimizing for longer-term goals. But as we humans can attest, learning something […]

Amazon Personalize improvements reduce model training time by up to 40% and latency for generating recommendations by up to 30% 6d

We’re excited to announce new efficiency improvements for Amazon Personalize. These improvements decrease the time required to train solutions (the machine learning models trained with your data) by up to 40% and reduce the latency for generating real-time recommendations by up to 30%. Amazon Personalize enables you to build applications with the same machine learning […]

Import AI 218: Testing bias with CrowS; how Africans are building a domestic NLP community; COVID becomes a surveillance excuse 7d

Can Africa build its own thriving NLP community? The Masakhane community suggests the answer is ‘yes’:…AKA: Here’s what it takes to bootstrap low-resource language research…Africa has an AI problem. Specifically, Africa contains a variety of languages, some of which are broadly un-digitized, but spoken by millions of native speakers. In our new era of AI, this is a problem: if...

Amazon SageMaker Continues to Lead the Way in Machine Learning and Announces up to 18% Lower Prices on GPU Instances 12d

Since 2006, Amazon Web Services (AWS) has been helping millions of customers build and manage their IT workloads. From startups to large enterprises to public sector, organizations of all sizes use our cloud computing services to reach unprecedented levels of security, resiliency, and scalability. Every day, they’re able to experiment, innovate, and deploy to production […]

Achieving 1.85x higher performance for deep learning based object detection with an AWS Neuron compiled YOLOv4 model on AWS Inferentia 13d

In this post, we show you how to deploy a TensorFlow based YOLOv4 model, using Keras optimized for inference on AWS Inferentia based Amazon EC2 Inf1 instances. You will set up a benchmarking environment to evaluate throughput and precision, comparing Inf1 with comparable Amazon EC2 G4 GPU-based instances. Deploying YOLOv4 on AWS Inferentia provides the […]