Distilling step-by-step: Outperforming larger language models with less training data and smaller model sizes

2 years ago

Posted by Cheng-Yu Hsieh, Student Researcher, and Chen-Yu Lee, Research Scientist, Cloud AI Team Large language models (LLMs) have enabled…

How United Airlines built a cost-efficient Optical Character Recognition active learning pipeline

2 years ago

In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab, build an active…

Secoda raises $14M to bring AI-driven, Google-like search to enterprise data

2 years ago

With its AI platform, Secoda wants to make searching for enterprise data as easy as looking up information on Google.Read…

Prime Day Deals Return in October 2023. Here’s What to Know

2 years ago

Amazon has a Prime Big Deals Days shopping holiday coming next month. We’ve got details on what you can expect…

Shape-changing smart speaker lets users mute different areas of a room

2 years ago

A team has developed a shape-changing smart speaker, which uses self-deploying microphones to divide rooms into speech zones and track…

With encouragement, large language models devise more efficient prompts

2 years ago

One of the principal drivers of efficient large language model (LLM) tasks is the prompt.

“Teams will get smarter and faster”: A conversation with Eli Manning

2 years ago

For the last three years, IBM has worked with two-time champion Eli Manning to help spread the word about our…

Train and deploy ML models in a multicloud environment using Amazon SageMaker

2 years ago

As customers accelerate their migrations to the cloud and transform their business, some find themselves in situations where they have…

Realizing telecommunications transformation with Google Cloud generative AI

2 years ago

Generative AI is driving the next phase of cloud transformation for communications service providers (CSPs). Although we are still in…