AWS Generative AI Off-The-Shelf Training 
AWS Machine Learning - AI
AUGUST 22, 2024
Building a deployment pipeline for generative artificial intelligence (AI) applications at scale is a formidable challenge because of the complexities and unique requirements of these systems. Generative AI models are constantly evolving, with new versions and updates released frequently.
CIO
APRIL 4, 2024
Some prospective projects require custom development using large language models (LLMs), but others simply require flipping a switch to turn on new AI capabilities in enterprise software. “AI We don’t want to just go off to the next shiny object,” she says. “We We want to maintain discipline and go deep.”
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CIO
JANUARY 23, 2023
OpenAI has landed billions of dollars more funding from Microsoft to continue its development of generative artificial intelligence tools such as Dall-E 2 and ChatGPT. As a licensee of OpenAI’s software it will have access to new AI-based capabilities it can resell or build into its products.
AWS Machine Learning - AI
SEPTEMBER 6, 2024
This post focuses on evaluating and interpreting metrics using FMEval for question answering in a generative AI application. Ground truth data in AI refers to data that is known to be true, representing the expected outcome for the system being modeled. Question Answer Fact Who is Andrew R.
CIO
JULY 10, 2024
Google has finally fixed its AI recommendation to use non-toxic glue as a solution to cheese sliding off pizza. The company that invented the very idea of gen AI is having trouble teaching its chatbot it shouldn’t treat satirical Onion articles and Reddit trolls as sources of truth. It can be harmful if ingested.
CIO
AUGUST 16, 2023
Ever since OpenAI’s ChatGPT set adoption records last winter, companies of all sizes have been trying to figure out how to put some of that sweet generative AI magic to use. Many, if not most, enterprises deploying generative AI are starting with OpenAI, typically via a private cloud on Microsoft Azure.
AWS Machine Learning - AI
APRIL 16, 2024
Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. They then use SQL to explore, analyze, visualize, and integrate data from various sources before using it in their ML training and inference.
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