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3 principles for regulatory-grade large language model application

CIO

In recent years, we have witnessed a tidal wave of progress and excitement around large language models (LLMs) such as ChatGPT and GPT-4. Moreover, LLMs should strive for transparency in their methodologies, showcasing how they arrived at a given conclusion.

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. Monitoring the performance and behavior of LLMs is a critical task for ensuring their safety and effectiveness.

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AI, Cybersecurity and the Rise of Large Language Models

Palo Alto Networks

Artificial intelligence (AI) plays a crucial role in both defending against and perpetrating cyberattacks, influencing the effectiveness of security measures and the evolving nature of threats in the digital landscape. A large language model (LLM) is a state-of-the-art AI system, capable of understanding and generating human-like text.

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Building a vision for real-time artificial intelligence

CIO

Data is a key component when it comes to making accurate and timely recommendations and decisions in real time, particularly when organizations try to implement real-time artificial intelligence. The underpinning architecture needs to include event-streaming technology, high-performing databases, and machine learning feature stores.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. How to choose the appropriate fairness and bias metrics to prioritize for your machine learning models. How to successfully navigate the bias versus accuracy trade-off for final model selection and much more.

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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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Deploy large language models for a healthtech use case on Amazon SageMaker

AWS Machine Learning - AI

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions. The training jobs used an ml.p3dn.24xlarge

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Register today to save your seat! December 6th, 2023 at 11:00am PST, 2:00pm EST, 7:pm GMT