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Generative AI in enterprises: LLM orchestration holds the key to success

CIO

Many enterprises are accelerating their artificial intelligence (AI) plans, and in particular moving quickly to stand up a full generative AI (GenAI) organization, tech stacks, projects, and governance. We think this is a mistake, as the success of GenAI projects will depend in large part on smart choices around this layer.

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Inferencing holds the clues to AI puzzles

CIO

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.

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Artificial Intelligence 101: What It Is, Its Evolution and Potential Jobs

Apiumhub

Artificial Intelligence 101 has become a transformative force in many areas of our society, redefining our lives, jobs, and perception of the world. AI involves the use of systems or machines designed to emulate human cognitive ability, including problem-solving and learning from previous experiences.

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Generative AI hallucinations: What can IT do?

CIO

But the double-edged sword to these productivity gains is one of generative AI’s known Achilles heels: its ability to occasionally “ hallucinate ,” or present incorrect information as fact. This is a supervised process that involves retraining a large language model with data so that it generates content more accurately based on that data.

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What LinkedIn learned leveraging LLMs for its billion users

CIO

During the summer of 2023, at the height of the first wave of interest in generative AI, LinkedIn began to wonder whether matching candidates with employers and making feeds more useful would be better served with the help of large language models (LLMs). We didn’t start with a very clear idea of what an LLM could do.”

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Improve LLM performance with human and AI feedback on Amazon SageMaker for Amazon Engineering

AWS Machine Learning - AI

In this post, we share how we analyzed the feedback data and identified limitations of accuracy and hallucinations RAG provided, and used the human evaluation score to train the model through reinforcement learning. To increase training samples for better learning, we also used another LLM to generate feedback scores.

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Accelerating Industry 4.0 at warp speed: The role of GenAI at the factory edge

CIO

While warp speed is a fictional concept, it’s an apt way to describe what generative AI (GenAI) and large language models (LLMs) are doing to exponentially accelerate Industry 4.0. Fabricated information from NLPs and LLMs can lead to faulty assumptions and poor decisions. Artificial Intelligence