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 …
With its AI platform, Secoda wants to make searching for enterprise data as easy as looking up information on Google.Read More
A team has developed a shape-changing smart speaker, which uses self-deploying microphones to divide rooms into speech zones and track the positions of individual speakers.
Amazon has a Prime Big Deals Days shopping holiday coming next month. We’ve got details on what you can expect if you’re hunting for deals ahead of the holidays.
One of the principal drivers of efficient large language model (LLM) tasks is the prompt.
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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”
As customers accelerate their migrations to the cloud and transform their business, some find themselves in situations where they have to manage IT operations in a multicloud environment. For example, you might have acquired a company that was already running on a different cloud provider, or you may have a workload that generates value from …
Read more “Train and deploy ML models in a multicloud environment using Amazon SageMaker”
Generative AI is driving the next phase of cloud transformation for communications service providers (CSPs). Although we are still in early days, significant progress has been made towards realizing the promise of gen AI in telecommunications. Google Cloud has been broadening and enhancing the capabilities of its foundation models, democratizing gen AI usage by simplifying …
Read more “Realizing telecommunications transformation with Google Cloud generative AI”