Artificial Inteligence Related Topics 
TechCrunch
NOVEMBER 5, 2023
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.
CIO
NOVEMBER 1, 2024
The world has known the term artificial intelligence for decades. Developing AI When most people think about artificial intelligence, they likely imagine a coder hunched over their workstation developing AI models. Today, integrating AI into your workflow isn’t hypothetical, it’s MANDATORY.
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CIO
DECEMBER 5, 2024
The world must reshape its technology infrastructure to ensure artificial intelligence makes good on its potential as a transformative moment in digital innovation. New technologies, such as generative AI, need huge amounts of processing power that will put electricity grids under tremendous stress and raise sustainability questions.
TechCrunch
JANUARY 4, 2024
2024 is going to be a huge year for the cross-section of generative AI/large foundational models and robotics. There’s a lot of excitement swirling around the potential for various applications, ranging from learning to product design. In a blog post […] © 2023 TechCrunch.
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.
Martin Fowler
APRIL 13, 2023
His initial prompt primes the LLM with an implementation strategy (chain of thought prompting). A couple of weeks ago I watched a fascinating Zoom call hosted by Xu Hao , Thoughtworks's Head of Technology in China. He showed an example of how he uses ChatGPT to help him code in a self-testing style.
Martin Fowler
FEBRUARY 13, 2024
LLM engineering involves much more than just prompt design or prompt engineering. Here David Tan and Jessie Wang reflect on how regular engineering practices such as testing and refactoring helped them deliver a prototype LLM application rapidly and reliably.
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.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails.
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.
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- (..)
Advertiser: Data Robot
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.
Advertiser: Data Robot
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.
Advertiser: Data Robot
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?
Advertiser: Data Robot
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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