Generating opportunities with generative AI
Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.
How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale | Amazon Web Services
Today, personally identifiable information (PII) is everywhere. PII is in emails, slack messages, videos, PDFs, and so on. It refers to any data or information that can be used to…
Dialogue-guided visual language processing with Amazon SageMaker JumpStart | Amazon Web Services
Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. Combined with large language models (LLM)…
Schneider Electric leverages Retrieval Augmented LLMs on SageMaker to ensure real-time updates in their ERP systems | Amazon Web Services
This post was co-written with Anthony Medeiros, Manager of Solutions Engineering and Architecture for North America Artificial Intelligence, and Blake Santschi, Business Intelligence Manager, from Schneider Electric. Additional Schneider Electric…
WordPress custom taxonomies – CyberSEO Pro
Unlock the full potential of your WordPress site with custom taxonomies. Learn how to effectively categorize content and integrate with CyberSEO Pro and RSS Retriever plugins for seamless syndication. Includes…
Deploy and fine-tune foundation models in Amazon SageMaker JumpStart with two lines of code | Amazon Web Services
We are excited to announce a simplified version of the Amazon SageMaker JumpStart SDK that makes it straightforward to build, train, and deploy foundation models. The code for prediction is…
Use AWS PrivateLink to set up private access to Amazon Bedrock | Amazon Web Services
Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. It allows developers…
The brain may learn about the world the same way some computational models do
Two studies find “self-supervised” models, which learn about their environment from unlabeled data, can show activity patterns similar to those of the mammalian brain.
Accelerating AI tasks while preserving data security
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
New techniques efficiently accelerate sparse tensors for massive AI models
Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.