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

CIO

In light of this, developer teams are beginning to turn to AI-enabled tools like large language models (LLMs) to simplify and automate tasks. Many developers are beginning to leverage LLMs to accelerate the application coding process, so they can meet deadlines more efficiently without the need for additional resources.

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5 ways to deploy your own large language model

CIO

A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. But there’s a problem with it — you can never be sure if the information you upload won’t be used to train the next generation of the model.

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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. The key to this approach is developing a solid data foundation to support the GenAI model.

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Optical technology enabling the growth of artificial intelligence

CIO

Artificial intelligence (AI) has a pivotal role to play. What are Large Language Models (LLMs)? Large language models (LLMs) are a rapidly evolving branch of the natural language processing field, enabling AI to understand and generate everyday human language.

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How to work with Large Language Models?

InnovationM

Large Language Models (LLMs) are at the forefront of artificial intelligence, powering applications from chatbots and translators to content generators and personal assistants. How Large Language Models Work : Large language models are functions that map text to text.

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Shreds.AI Launches LLM Platform Trained for Software Engineering

DevOps.com

today unveiled a namesake generative artificial intelligence (AI) platform based on a large language model (LLM) it trained to specifically automate software engineering tasks.

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Unlocking AI: Machine learning as a service

CIO

To keep pace with demand for insights that can drive quicker, better decision making, data scientists are looking to Artificial Intelligence (AI), Machine Learning (ML) and cognitive computing technologies to take analytics to the next level. No organization can afford to fall behind.