Data Engineering Generative AI Strategy Training 
CIO
JULY 6, 2023
While Microsoft, AWS, Google Cloud, and IBM have already released their generative AI offerings, rival Oracle has so far been largely quiet about its own strategy. The service also comes with Nvidia’s foundation models, such as BioNeMo and Nvidia Picasso, along with AI training and governance frameworks.
CIO
JANUARY 22, 2024
While the average person might be awed by how AI can create new images or re-imagine voices, healthcare is focused on how large language models can be used in their organizations. However, the effort to build, train, and evaluate this modeling is only a small fraction of what is needed to reap the vast benefits of generative AI technology.
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CIO
JULY 14, 2023
Whether it’s text, images, video or, more likely, a combination of multiple models and services, taking advantage of generative AI is a ‘when, not if’ question for organizations. Since the release of ChatGPT last November, interest in generative AI has skyrocketed.
CIO
AUGUST 7, 2023
Hardly a day goes by without some new business-busting development on generative AI surfacing in the media. And, in fact, McKinsey research argues the future could indeed be dazzling, with gen AI improving productivity in customer support by up to 40%, in software engineering by 20% to 30%, and in marketing by 10%.
AWS Machine Learning - AI
JANUARY 26, 2024
Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs.
CIO
APRIL 10, 2024
Inferencing has emerged as among the most exciting aspects of generative AI large language models (LLMs). A quick explainer: In AI inferencing , organizations take a LLM that is pretrained to recognize relationships in large datasets and generate new content based on input, such as text or images.
CIO
JANUARY 16, 2024
In the rush to establish technical strategies for making good on the promise of generative AI, many CIOs find themselves running headlong into what may be their most challenging task yet: preparing their organization’s end-users — from knowledge workers and assembly line laborers to doctors, accountants, and lawyers — to co-exist with generative AI.
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