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AI

Gen AI for Marketing - From Hype to Implementation - MLOps Live #32 with McKinsey and Iguazio

In this MLOps Live session we were joined by Eli Stein, Partner and Modern Marketing Capabilities Leader at McKinsey, to delve into how data scientists can leverage generative AI to support the company’s marketing strategy. We showcased a live demo of a customer-facing AI agent developed for a jewelry retailer, which can be used as a marketing tool to offer personalized product recommendations and purchasing information and support. Following the demo, we held an interactive discussion and Q&A session. Enjoy!

Generative AI Testing: Essential Strategies and Insights for System Validation

STARWEST 2024 was not just a conference; it was a vibrant hub of exploring knowledge and exploration into the transformative realm of generative AI and software testing. At this event, we started day 2 with an energetic workshop of "Evaluating and Testing Generative AI: Insights and Strategies", led by Jason Arbon, CEO of Checkie.AI, which covered the complex challenges of testing AI systems like ChatGPT and LLAMA.

Special Episode: How to make generative AI a reality | Capgemini

George Fraser, CEO of Fivetran, Bob Muglia, former CEO of Snowflake, and Steve Jones, EVP of Capgemini discuss the challenges and solutions to creating mature, production-ready generative AI models. It’s not just about algorithms or data — success lies in effective data management.

98% Accuracy in Leak Detection: How AI is Transforming HVAC Manufacturing

In today’s industrial landscape, efficiency and accuracy are paramount for success. For manufacturers, particularly those in the Heating, Ventilation, and Air Conditioning (HVAC) industry, ensuring the integrity of their products is crucial. However, challenges like leak detection and quality control can introduce costly inefficiencies.

How to Harness AI Data Governance for Data Integrity

It’s no secret that artificial intelligence (AI) is revolutionizing the way companies operate with its ability to sift through mountains of data and make accurate predictions at record speed. But with great power comes great responsibility. As AI systems are more regularly incorporated into business, it’s critical that data sources are both accurate and secure to prevent error.