Remove Artificial Inteligence Remove Generative AI Remove Strategy
article thumbnail

Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements.

article thumbnail

AI in the C-suite: Using AI to shape business strategy

CIO

Jeff Schumacher, CEO of artificial intelligence (AI) software company NAX Group, told the World Economic Forum : “To truly realize the promise of AI, businesses must not only adopt it, but also operationalize it.” Most AI hype has focused on large language models (LLMs).

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Have we reached the end of ‘too expensive’ for enterprise software?

CIO

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. These autoregressive models can ultimately process anything that can be easily broken down into tokens: image, video, sound and even proteins.

article thumbnail

10 AI strategy questions every CIO must answer

CIO

To counter such statistics, CIOs say they and their C-suite colleagues are devising more thoughtful strategies. Here are 10 questions CIOs, researchers, and advisers say are worth asking and answering about your organizations AI strategies. What are we trying to accomplish, and is AI truly a fit?

Strategy 211
article thumbnail

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.

article thumbnail

Reimagine application modernisation with the power of generative AI

CIO

Indeed, more than 80% of organisations agree that scaling GenAI solutions for business growth is a crucial consideration in modernisation strategies. [2] 2] The myriad potential of GenAI enables enterprises to simplify coding and facilitate more intelligent and automated system operations.

article thumbnail

The gap between AI investment and AI adoption

CIO

AI continues to shape cloud strategies, but AI implementation is going slower than most predicted. This is frustrating for technology providers who have made big bets on AI. What’s going on? This is up from 72% last year. Continue reading on InfoWorld.

article thumbnail

Building User-Centric and Responsible Generative AI Products

Speaker: Shyvee Shi - Product Lead and Learning Instructor at LinkedIn

In the rapidly evolving landscape of artificial intelligence, Generative AI products stand at the cutting edge. This presentation unveils a comprehensive 7-step framework designed to navigate the complexities of developing, launching, and scaling Generative AI products.

article thumbnail

Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.