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How To Manage AI Innovation Projects

lessons learned from managing AI innovation projects

How do we break the wall between business value and the potential of AI?

$5 million—that’s the approximate amount companies are investing annually in AI initiatives in 2024. With more than 60% of companies seeing generative AI as a top three priority over the next two years, the focus is now on delivering real business value.

In this session, we will learn how to bridge the gap between AI’s potential and business goals through real case studies. This session is perfect for business leaders, AI enthusiasts, and anyone interested in managing AI’s potential while mitigating risks.

Our special panelists:

Session Topics:

  • Examples of how AI helped companies achieve their business goals - practical case studies
  • How to build an AI roadmap aligned with the business
  • How to effectively manage PoC's

Register Here


LLM Gateways: All You Need to Know

LLM Gateways: All You Need to Know

LLM gateways revolutionize the way we interact with LLMs by enabling seamless switching between models without requiring code modifications. This innovation simplifies transitions and optimizes performance by tracking interactions, including latency, token usage, and response times. By acting as intermediaries, proxies like LiteLLM provide a unified interface to interact with multiple LLMs, reducing complexity and supporting dynamic switching.

Furthermore, deploying LLM gateways in Kubernetes clusters allows for horizontal scaling, ensuring efficient management of high traffic volumes. They also enhance security by centralizing access control, secret management, and logging, while masking sensitive information to comply with data privacy regulations.

Learn how LLM gateways can transform their approach to managing LLMs, making their operations more efficient, secure, and scalable. For a deeper dive into this game-changing technology.

Read the full BlogPost


AI Lovers, Check Out Our New Episode

Join us for our latest discussion with Gad Benram and Charles Frye from Modal as they explore the strategic reasons behind companies choosing to host their own AI infrastructure versus relying on external cloud services. From controlling critical data to customizing AI applications, this episode is packed with valuable insights for anyone navigating the complex world of AI deployment.

?? Tune in -https://lnkd.in/d4-skW34


Bugs In Production?

Lightrun's AI debugger

Lightrun's AI debugger brings new ways of troubleshooting already deployed applications!

TensorOps is excited to showcase our collaboration with Lightrun, the innovators behind the world's most advanced AI debugger for live applications. Through our work we accelerated Lightrun's AI initiative by providing expert consultation on AI development and best practices. Good luck to the team—this is truly groundbreaking!

Wanna accelerate your AI adoption as well? Read more about it here:

https://lnkd.in/dZKwdjps

Learn more about Lightrun's AI debugger that got covered by TechCrunch

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