This post was co-written with Andrew Browning, Anthony Doolan, Jerome Ronquillo, Jeff Burke, Chiheb Boussema, and Naisha Agarwal from UCLA. The University of California, Los Angeles (UCLA) is home to 16 Nobel Laureates and has been ranked the #1 public university in the United States for 8 consecutive years. The Office of Advanced Research Computing […]
Project Prometheus has raised over $6 billion in funding and hired over 100 employees, a handful of whom joined through its acquisition of General Agents, according to records and sources.
Jeff Bezos’ New AI Venture Quietly Acquired an Agentic Computing Startup Read More »
This post is written by Chaim Rand, Principal Engineer, Pini Reisman, Software Senior Principal Engineer, and Eliyah Weinberg, Performance and Technology Innovation Engineer, at Mobileye. The Mobileye team would like to thank Sunita Nadampalli and Guy Almog from AWS for their contributions to this solution and this post. Mobileye is driving the global evolution toward
This blog post introduces the new Amazon Nova model evaluation features in Amazon SageMaker AI. This release adds custom metrics support, LLM-based preference testing, log probability capture, metadata analysis, and multi-node scaling for large evaluations. The new features include: Custom metrics use the bring your own metrics (BYOM) functions to control evaluation criteria for your
Evaluate models with the Amazon Nova evaluation container using Amazon SageMaker AI Read More »
Amazon Employees for Climate Justice says that over 1,000 workers have signed a petition raising “serious concerns” about the company’s “aggressive rollout” of artificial intelligence tools.
Workplaces are increasingly integrating AI tools into daily operations, with AI assistants supporting teams, predictive analytics informing strategies, and automation streamlining workflows. AI has moved from experimental technology to standard business practice, changing how work gets done. Organizations need to understand what AI can do and how it affects their workforce to implement it successfully.
Beyond the technology: Workforce changes for AI Read More »
You can now achieve significant performance improvements when using Amazon Bedrock Custom Model Import, with reduced end-to-end latency, faster time-to-first-token, and improved throughput through advanced PyTorch compilation and CUDA graph optimizations. With Amazon Bedrock Custom Model Import you can to bring your own foundation models to Amazon Bedrock for deployment and inference at scale. These
Enhanced performance for Amazon Bedrock Custom Model Import Read More »
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
