Category: Amazon Machine Learning

Today, we’re taking another step to make it even easier for founders to build and iterate on their solutions using the latest technologies. We’re making AWS Activate credits redeemable for third-party models on Amazon Bedrock, our fully-managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies, like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon via a single API.

We are excited to introduce you to a few Climate Tech startups that are at the forefront of the race to stop the climate crisis. They’re using generative AI to fight climate change by reducing greenhouse gas emissions and enabling the world to transition to a zero-carbon economy. 

Sign-Speak is an innovative startup whose language software recognizes American Sign Language (ASL) and translates it into spoken words (and vice versa) with machine learning. Their platform offers real-time ASL recognition, avatar, and transcription to facilitate communication with Deaf and Hard of Hearing individuals. Sign-Speak leveraged the AWS Impact Accelerator Latino Founders cohort to gain technical and business support as they make the world a more accessible and inclusive place.

Learn which AWS services can help you to build a generative AI application. The approaches discussed here can help your startup get its product to market as quickly as possible, while maintaining cost efficiency and high performance.

This introduction to generative artificial intelligence (AI) for startups explains various approaches to build generative AI applications and reviews their key components.

In the automotive industry, TIER IV is an innovative and disruptive startup that is transforming the vehicle production process and the future of mobility. Founded in 2015 by Shinpei Kato in Japan, TIER IV builds platforms based on open source software—platforms they manage using AWS—that their partners use for building autonomous vehicles.

When choosing the infrastructure for their ML workloads, startups should consider how to best approach training and inference. Training is process by which a model is built and tuned for a specific task by learning from existing data. Inference is the process of using that model to make predictions based on new input data. Over the last five years, AWS has been investing in our own purpose-built accelerators to push the envelope on performance and compute cost for ML workloads. AWS Trainium and AWS Inferentia accelerators enable the lowest cost for training models and running inference in the cloud.

Startups know firsthand how better technology can improve the quality of life: From AI/ML allowing scientists to better predict patient health outcomes, to cloud computing driving life-saving innovation, and modern apps enhancing accessibility. Fraud.net is one such startup improving quality of life. They use AWS technology to give customers in the banking and fintech industries a serverless modern application that uses artificial intelligence and machine learning to rapidly identify fraud, leading to more efficient operations and higher customer satisfaction.

Startups are familiar with the importance of creating great customer experiences. Sentiment analysis is one tool that helps with this. It categorizes data as positive, negative, or neutral based on machine learning techniques such as text analysis and natural language processing (NLP). Companies use sentiment analysis to measure the satisfaction of clients for a target product or service. In this blog post, we explain how Widebot uses Amazon Sagemaker to successfully implement a sentiment classifier for Modern Standard Arabic and Egyptian dialect Arabic.

No one wants to hear from a debt collection agency. Most people associate it with letters in red, capital characters, high charges with imaginative reasons and intrusive phone calls. Berlin-based fintech PAIR Finance’s mission is to change that with the help of Machine Learning, introducing you and your customers to a completely new debt collection experience.