Automated system teaches users when to collaborate with an AI assistant
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
Getir end-to-end workforce management: Amazon Forecast and AWS Step Functions | Amazon Web Services
This is a guest post co-authored by Nafi Ahmet Turgut, Mehmet İkbal Özmen, Hasan Burak Yel, Fatma Nur Dumlupınar Keşir, Mutlu Polatcan and Emre Uzel from Getir. Getir is the…
MIT engineers develop a way to determine how the surfaces of materials behave
Using machine learning, the computational method can provide details of how materials work as catalysts, semiconductors, or battery components.
Mitigate hallucinations through Retrieval Augmented Generation using Pinecone vector database & Llama-2 from Amazon SageMaker JumpStart | Amazon Web Services
Despite the seemingly unstoppable adoption of LLMs across industries, they are one component of a broader technology ecosystem that is powering the new AI wave. Many conversational AI use cases…
Eric Evans to step down as director of MIT Lincoln Laboratory
During 18 years of leadership, Evans established new R&D mission areas, strengthened ties to the MIT community, and increased inclusion and education efforts.
Techniques for automatic summarization of documents using language models | Amazon Web Services
Summarization is the technique of condensing sizable information into a compact and meaningful form, and stands as a cornerstone of efficient communication in our information-rich age. In a world full…
Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock | Amazon Web Services
Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training…
How Q4 Inc. used Amazon Bedrock, RAG, and SQLDatabaseChain to address numerical and structured dataset challenges building their Q&A chatbot | Amazon Web Services
This post is co-written with Stanislav Yeshchenko from Q4 Inc. Enterprises turn to Retrieval Augmented Generation (RAG) as a mainstream approach to building Q&A chatbots. We continue to see emerging…
Foundational data protection for enterprise LLM acceleration with Protopia AI | Amazon Web Services
The post describes how you can overcome the challenges of retaining data ownership and preserving data privacy while using LLMs by deploying Protopia AI’s Stained Glass Transform to protect your…
Enable faster training with Amazon SageMaker data parallel library | Amazon Web Services
Large language model (LLM) training has become increasingly popular over the last year with the release of several publicly available models such as Llama2, Falcon, and StarCoder. Customers are now…