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Exploring the pros and cons of cloud-based large language models

CIO

As a result of ongoing cloud adoption, developers face increased pressures to rapidly create and deploy applications in support of their organization’s cloud transformation goals. Cloud applications, in essence, have become organizations’ crown jewels and developers are measured on how quickly they can build and deploy them.

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Getting specific with GenAI: How to fine-tune large language models for highly specialized functions

CIO

Large language models (LLMs) are hard to beat when it comes to instantly parsing reams of publicly available data to generate responses to general knowledge queries. That’s a problem when you consider that most of the GenAI development work being done today is focused on highly specialized use cases.

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India’s advisory on LLM usage causes consternation

CIO

India’s Ministry of Electronics and Information Technology (MeitY) has caused consternation with its stern reminder to makers and users of large language models (LLMs) of their obligations under the country’s IT Act, after Google’s Gemini model was prompted to make derogatory remarks about Indian Prime Minister Narendra Modi.

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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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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.

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Artificial Intelligence in Cybersecurity: Good or Evil?

CIO

Generative AI has taken the world seemingly by storm, impacting everything from software development, to marketing, to conversations with my kids at the dinner table. Abuse by Attackers: There have also been concerns raised that attackers will leverage Generative AI tools such as ChatGPT to develop novel new attacks.