The EPA is prioritizing review of new chemicals to be used in data centers. Experts say this could lead to the fast approval of new types of forever chemicals—with limited oversight.
Large language models (LLMs) sometimes learn the wrong lessons, according to an MIT study. Rather than answering a query based on domain knowledge, an LLM could respond by leveraging grammatical patterns it learned during training. This can cause a model to fail unexpectedly when deployed on new tasks. The researchers found that models can mistakenly
Researchers discover a shortcoming that makes LLMs less reliable Read More »
Generative AI models continue to expand in scale and capability, increasing the demand for faster and more efficient inference. Applications need low latency and consistent performance without compromising output quality. Amazon SageMaker AI introduces new enhancements to its inference optimization toolkit that bring EAGLE based adaptive speculative decoding to more model architectures. These updates make
On October 10, 2024, Amazon announced the discontinuation of the Amazon Lookout for Vision service, with a scheduled shut down date of October 31, 2025 (see Exploring alternatives and seamlessly migrating data from Amazon Lookout for Vision blog post). As part of our transition guidance for customers, we recommend the use of Amazon SageMaker AI tools
Train custom computer vision defect detection model using Amazon SageMaker Read More »
More than 300 people across academia and industry spilled into an auditorium to attend a BoltzGen seminar on Thursday, Oct. 30, hosted by the Abdul Latif Jameel Clinic for Machine Learning in Health (MIT Jameel Clinic). Headlining the event was MIT PhD student and BoltzGen’s first author Hannes Stärk, who had announced BoltzGen just a few days
In this episode of Uncanny Valley, we cover the news of the week and take a closer look at the Gemini 3, Google’s latest AI model and chatbot.
WIRED Roundup: Gemini 3 Release, Nvidia Earnings, Epstein Files Fallout Read More »
Artificial Intelligence (AI) is changing how businesses operate. Gartner® predicts at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028. And 92% of companies are boosting their AI spending, according to McKinsey. But here’s the problem: most companies are yet to realize a positive impact of AI on their
Practical implementation considerations to close the AI value gap Read More »
Artificial Intelligence (AI) is changing how businesses operate. Gartner® predicts at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028. And 92% of companies are boosting their AI spending, according to McKinsey. But here’s the problem: most companies are yet to realize a positive impact of AI on their
Practical implementation considerations to close the AI value gap Read More »
In 2025, generative AI has evolved from text generation to multi-modal use cases ranging from audio transcription and translation to voice agents that require real-time data streaming. Today’s applications demand something more: continuous, real-time dialogue between users and models—the ability for data to flow both ways, simultaneously, over a single persistent connection. Imagine a speech
Introducing bidirectional streaming for real-time inference on Amazon SageMaker AI Read More »
This post is written by Nukul Sharma, Machine Learning Engineering Manager, and Karthik Dasani, Staff Machine Learning Engineer, at Warner Bros. Discovery. Warner Bros. Discovery (WBD) is a leading global media and entertainment company that creates and distributes the world’s most differentiated and complete portfolio of content and brands across television, film and streaming. With iconic
