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How Large Language Models Reflect Human Judgment

Harvard Business Review

Artificial intelligence is based around prediction. But large language models represent a key advance: OpenAI has found a way to teach its AI human judgment by using a simple form of human feedback, through chat. But decision making requires both prediction and judgment.

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How Marketers Can Adapt to LLM-Powered Search

Harvard Business Review

Large language models (LLMs) provide a search experience that’s dramatically different from the web-browser experience. The biggest difference is this: LLMs promise to answer queries not with links, as web browsers do, but with answers.


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The Future of Design Thinking: Integrating Artificial Intelligence for Success


Embracing the Evolution: AI Meets Design Thinking The intersection of artificial intelligence and design thinking is poised to redefine the landscape of innovation and strategy. Iterative Learning : AI learns from each interaction, continually refining the design process.

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AI on the Farm: How Artificial Intelligence is Revolutionizing the Food Industry


From farm to fork, artificial intelligence (AI) is poised to revolutionize the food industry. This powerful technology has the potential to transform every step of the food supply chain, from ensuring food safety and optimizing production to personalizing our food choices. One of the most pressing concerns for consumers is food safety.

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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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What Will Humans Do In An Artificially Intelligent World?

Digital Tonto

That’s why the rise of artificial intelligence is driving a shift from cognitive to social skills. That requires more deep collaboration, teamwork and emotional intelligence. To derive meaning in an artificially intelligent world we need to look to each other and how we can better understand our intentions.

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How Innovation Can Benefit From Artificial Intelligence?

HYPE Innovation

The launch of ChatGPT, Midjourney, and DALL-E has put artificial intelligence (AI) firmly in the spotlight. Yet AI is nothing new, and these applications are just the tip of the iceberg. AI has been present in our daily lives for many years, with social media algorithms, chatbots, and the Waze application just a few examples.

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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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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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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.

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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How to Leverage AI for Actionable Insights in BI, Data, and Analytics

In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities?

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The New Tech Experience: Innovation, Optimization, and Collaboration

Speaker: Paul Weald, Contact Center Innovator

Learn how to streamline productivity and efficiency across your organization with machine learning and artificial intelligence! How you can leverage innovations in technology and machine learning to improve your customer experience and bottom line.

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Service Delivery: When Is the Right Time to Deploy Your AI?

Speaker: Dick Stark and Casey Steenport

The big buzz is around Artificial Intelligence, and how it can help IT service delivery teams crush their goals. Decision-makers have been experimenting with Artificial Intelligence in smaller groups and have started adopting AI into mainstream environments in their organizations.