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Iguazio
MLRun v1.7 Launched - Solidifying Generative AI Implementation and LLM Monitoring
As the open-source maintainers of MLRun, we’re proud to announce the release of MLRun v1.7. MLRun is an open-source AI orchestration tool that accelerates the deployment of gen AI applications, with features such as LLM monitoring, fine-tuning, data management, guardrails and more. We provide ready-made scenarios that can be easily implemented by teams in organizations.
Deploying Gen AI in Production with NVIDIA NIM & MLRun - MLOps Live #33 with NVIDIA
In this webinar, we explored how to successfully deploy your Gen AI applications while mitigating these challenges, using NVIDIA NIM and MLRun.
MLRun 1.7: LLM Monitoring & Fine-tuning a Gen AI Banking Chatbot
See how to use MLRun 1.7 to fine-tune a generative AI banking chatbot, ensuring it answers only relevant banking inquiries. Watch the full tutorial and follow along!
Gen AI for Marketing - From Hype to Implementation
Gen AI has the potential to bring immense value for marketing use cases, from content creation to hyper-personalization to product insights, and many more. But if you’re struggling to scale and operationalize gen AI, you’re not alone. That’s where most enterprises struggle. To date, many companies are still in the excitement and exploitation phase of gen AI. Few have a number of initial pilots deployed and even fewer have simultaneous pilots and are building differentiating use cases.
Customer Facing AI Agent
This demo recorded during our MLOps Live Webinar #32 showcases a customer-facing AI agent developed for a jewelry retailer. This can be used as a marketing tool to offer personalized product recommendations and purchasing information and support.
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!
How to Implement Gen AI in Highly Regulated Environments: Financial Services and Telecommunications and More
If 2023 was the year of gen experimentation, 2024 is the year of gen AI implementation. As companies embark on their implementation journey, they need to deal with a host of challenges, like performance, GPU efficiency and LLM risks. These challenges are exacerbated in highly-regulated industries, such as financial services and telecommunication, adding further implementation complexities. Below, we discuss these challenges and present some best practices and solutions to take into consideration.
Building Customer-Facing Gen AI Applications Effectively & Responsibly - MLOps Live #31 with MongoDB
In this session, we explored the unique challenges of implementing gen AI in production environments, when agents are in direct contact with your customers. We shared the Iguazio & MongoDB one-stop-shop solution for building gen AI applications that scale effectively and efficiently, with built-in guardrails and monitoring. We'll show how the end-to-end application lifecycle is addressed – From data management all the way to governance and monitoring in production.