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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. That question isn’t set to the LLM right away. And it’s more effective than using simple documents to provide context for LLM queries, she says.

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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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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.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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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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Valued at $1B, Kai-Fu Lee’s LLM startup unveils open source model

TechCrunch

Kai-Fu Lee, the computer scientist known in the West for his bestseller AI Superpowers and in China for his bets on artificial intelligence unicorns, has a new venture — and a great ambition. AI with the vision to develop a homegrown large language model for the Chinese market. […] © 2023 TechCrunch.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)

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A Tale of Two Case Studies: Using LLMs in Production

Speaker: Tony Karrer, Ryan Barker, Grant Wiles, Zach Asman, & Mark Pace

Join our exclusive webinar with top industry visionaries, where we'll explore the latest innovations in Artificial Intelligence and the incredible potential of LLMs. We'll walk through two compelling case studies that showcase how AI is reimagining industries and revolutionizing the way we interact with technology.

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How Banks Are Winning with AI and Automated Machine Learning

By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the whitepaper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.

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How Banks Are Winning with AI and Automated Machine Learning

By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the white paper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

Executive leaders and board members are pushing their teams to adopt Generative AI to gain a competitive edge, save money, and otherwise take advantage of the promise of this new era of artificial intelligence.

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Resilient Machine Learning with MLOps

Today’s economy is under pressure from inflation, rising interest rates, and disruptions in the global supply chain. As a result, many organizations are seeking new ways to overcome challenges — to be agile and rapidly respond to constant change. We do not know what the future holds.

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Intelligent Process Automation: Boosting Bots with AI and Machine Learning

But in order to reap the rewards of Intelligent Process Automation, organizations must first educate themselves and prepare for the adoption of IPA. In Data Robot's new ebook, Intelligent Process Automation: Boosting Bots with AI and Machine Learning, we cover important issues related to IPA, including: What is RPA?

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.