A new generation of African talent brings cutting-edge AI to scientific challenges
Food security, healthcare and exploring the cosmos are among the ways students of a new pan-African Master’s program aspire to apply AI
BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks
This paper was accepted at IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) 2024 Programmers frequently engage with machine learning tutorials in computational notebooks and have been adopting code generation technologies based on large language models (LLMs). However, they encounter difficulties in understanding and working with code produced by LLMs. To mitigate these challenges, …
Read more “BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks”
Investigation of a Cross-regional Network Performance Issue
Hechao Li, Roger Cruz Cloud Networking Topology Netflix operates a highly efficient cloud computing infrastructure that supports a wide array of applications essential for our SVOD (Subscription Video on Demand), live streaming and gaming services. Utilizing Amazon AWS, our infrastructure is hosted across multiple geographic regions worldwide. This global distribution allows our applications to deliver content …
Read more “Investigation of a Cross-regional Network Performance Issue”
Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and AWS CloudFormation
Retrieval Augmented Generation (RAG) is a state-of-the-art approach to building question answering systems that combines the strengths of retrieval and foundation models (FMs). RAG models first retrieve relevant information from a large corpus of text and then use a FM to synthesize an answer based on the retrieved information. An end-to-end RAG solution involves several …
Mapping the misuse of generative AI
New research analyzes the misuse of multimodal generative AI today, in order to help build safer and more responsible technologies.
Cepsa Química improves the efficiency and accuracy of product stewardship using Amazon Bedrock
This is a guest post co-written with Vicente Cruz Mínguez, Head of Data and Advanced Analytics at Cepsa Química, and Marcos Fernández Díaz, Senior Data Scientist at Keepler. Generative artificial intelligence (AI) is rapidly emerging as a transformative force, poised to disrupt and reshape businesses of all sizes and across industries. Generative AI empowers organizations …
Tuning LLMs with Contrastive Alignment Instructions for Machine Translation in Unseen, Low-resource Languages
This article introduces contrastive alignment instructions (AlignInstruct) to address two challenges in machine translation (MT) on large language models (LLMs). One is the expansion of supported languages to previously unseen ones. The second relates to the lack of data in low-resource languages. Model fine-tuning through MT instructions (MTInstruct) is a straightforward approach to the first …
Streamline insurance underwriting with generative AI using Amazon Bedrock – Part 1
Underwriting is a fundamental function within the insurance industry, serving as the foundation for risk assessment and management. Underwriters are responsible for evaluating insurance applications, determining the level of risk associated with each applicant, and making decisions on whether to accept or reject the application based on the insurer’s guidelines and risk appetite. In this …
Read more “Streamline insurance underwriting with generative AI using Amazon Bedrock – Part 1”
New strides in making AI accessible for every enterprise
We’ve been thrilled to see the recent enthusiasm and adoption of Gemini 1.5 Flash — our fastest model to date, optimized for high-volume and high-frequency tasks at scale. Every day, we learn about how people are using Gemini to do amazing things like transcribe audio, understand code errors, and build apps in minutes. Companies like …
Read more “New strides in making AI accessible for every enterprise”
Gemma Scope: helping the safety community shed light on the inner workings of language models
Announcing a comprehensive, open suite of sparse autoencoders for language model interpretability.