The magic behind Uber’s data-driven success Uber, the ride-hailing giant, is a household name worldwide. We all recognize it as the platform that connects riders with drivers for hassle-free transportation. But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. Every …
Read more “Unleashing the power of Presto: The Uber case study”
This post was co-authored with Daniele Chiappalupi, participant of the AWS student Hackathon team at ETH Zürich. Everyone can easily get started with machine learning (ML) using Amazon SageMaker JumpStart. In this post, we show you how a university Hackathon team used SageMaker JumpStart to quickly build an application that helps users identify and remove …
Read more “Innovation for Inclusion: Hack.The.Bias with Amazon SageMaker”
We’re announcing an open call for the OpenAI Red Teaming Network and invite domain experts interested in improving the safety of OpenAI’s models to join our efforts.
Reinforcement Learning from Human Feedback (RLHF) is recognized as the industry standard technique for ensuring large language models (LLMs) produce content that is truthful, harmless, and helpful. The technique operates by training a “reward model” based on human feedback and uses this model as a reward function to optimize an agent’s policy through reinforcement learning …
Read more “Improving your LLMs with RLHF on Amazon SageMaker”
Machine learning opens up opportunities to get more value out of data, and business users are eager to see that value. However, today’s machine learning experts are facing a lot of requests and their expertise is at a premium. What if data analysts had the ability to create and test their own machine learning models? …
Read more “Bring AI to Looker with the Machine Learning Accelerator”
Posted by Cheng-Yu Hsieh, Student Researcher, and Chen-Yu Lee, Research Scientist, Cloud AI Team Large language models (LLMs) have enabled a new data-efficient learning paradigm wherein they can be used to solve unseen new tasks via zero-shot or few-shot prompting. However, LLMs are challenging to deploy for real-world applications due to their sheer size. For …
Generative AI and large language models are poised to impact how we all access and use information. But as organizations race to adopt these new technologies for business, it requires a global ecosystem of partners with industry expertise to identify the right enterprise use-cases for AI and the technical skills to implement the technology. During …
Read more “IBM TechXchange underscores the importance of AI skilling and partner innovation”
Posted by Cheng-Yu Hsieh, Student Researcher, and Chen-Yu Lee, Research Scientist, Cloud AI Team Large language models (LLMs) have enabled a new data-efficient learning paradigm wherein they can be used to solve unseen new tasks via zero-shot or few-shot prompting. However, LLMs are challenging to deploy for real-world applications due to their sheer size. For …
In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab, build an active learning framework on AWS to automate the processing of passenger documents. “In order to deliver the best flying experience for our passengers and make our internal business process as efficient as possible, we have developed …
For the last three years, IBM has worked with two-time champion Eli Manning to help spread the word about our partnership with ESPN. The nature of that partnership is pretty technical, involving powerful AI models—built with watsonx—that analyze massive data sets to generate insights that help ESPN Fantasy Football team owners manage their teams. Eli …
Read more ““Teams will get smarter and faster”: A conversation with Eli Manning”