Silicon ANGLE the CUBE Executive Series: AI Infrastructure Silicon Valley

Summary

In this Silicon Valley AI leader series episode, host John Furrier interviews Krishna Rasagala, founder and CEO of SEA AI, a startup revolutionizing machine learning at the edge. They discuss the rapid growth of edge computing, driven by advancements in AI and computer vision. Rasagala shares insights on the challenges and opportunities in scaling AI to the physical world, emphasizing the importance of a purpose-built platform for the embedded edge market. The conversation highlights the need for a new approach to data management and software optimization, as well as the potential for AI to transform industries like robotics, automotive, and healthcare.

Takeaways

• 😀 Krishna Rasah, the founder and CEO of SEA AI, discusses the rapid growth of edge computing in AI infrastructure, emphasizing the company's focus on machine learning and computer vision at the edge.
• 🌟 SEA AI aims to bring AI capabilities to physical industries like robotics, automotive, and medical fields, which have been slower to adopt AI compared to cloud and consumer sectors.
• 💡 The company has raised $270 million and is working with over 50 customers globally, highlighting the significant investment and market interest in edge AI solutions.
• 🚀 SEA AI's mission is to scale AI to the physical edge, making it more accessible and efficient, which is a significant shift from traditional cloud-centric AI approaches.
• 🔍 The discussion highlights the importance of addressing the unique challenges of edge computing, such as power limitations, the need for a platform to scale software across numerous customers, and the integration of multimodal capabilities.
• 🛠️ SEA AI offers a software package called Edge Matic, which allows for no-code ML and computer vision applications, making AI more accessible to a broader range of users.
• 🌐 The interview underscores the need for a robust data management infrastructure at the edge, as AI adoption grows and the volume of data generated increases.
• 🔑 Krishna Rasah shares his personal journey as a founder, emphasizing the highs and lows, the importance of resilience, and the transformative impact of building a startup on his personal growth.
• 💼 The conversation points to the future of AI at the edge, predicting that every appliance will become multimodal, integrating various AI capabilities to enhance user experiences.
• 🌟 The potential for AI in edge computing is vast, with applications in medical, industrial, and government sectors, showcasing the technology's ability to reshape various aspects of society and industry.

Q & A

What is the main focus of the company SEA AI?

SEA AI focuses on deploying machine learning and AI capabilities at the embedded edge, aiming to bring new levels of productivity and efficiency to industries such as robotics, automotive, and medical through AI-enabled solutions.

How does Krishna Rasagam perceive the current state of AI in the cloud and at the edge?

Krishna Rasagam observes that while AI has scaled well in the cloud and consumer personas, the physical, industrialized world, including robotics, automotive, and medical fields, has been left behind. He sees a significant opportunity to scale AI to the physical edge.

What are the key multimodal growth areas SEA AI is targeting?

SEA AI is focusing on computer vision, embedding technology at the edge, and developing multimodal capabilities that include not just visual but also audio, textual, and tactile interactions.

What challenges does Krishna Rasagam highlight for companies trying to deploy AI at the edge?

Krishna Rasagam highlights the challenges of power limitations at the edge, the need to scale software across a large number of customers, and the requirement for a purpose-built platform to enable AI at the embedded edge.

How does SEA AI differentiate itself in the market according to Krishna Rasagam?

SEA AI differentiates itself by focusing on building a purpose-built platform for AI at the embedded edge, emphasizing performance per watt, ease of use, and creating a platform that can be easily adopted by a wide range of customers.

What is the significance of the crowd strike incident mentioned in the script?

The crowd strike incident signifies the importance of safety and security in AI deployments, especially at the edge, and how such incidents can have real-world impacts, highlighting the need for robust AI infrastructure.

What is the role of the ecosystem in SEA AI's strategy?

The ecosystem plays a crucial role in SEA AI's strategy by partnering with ISVs (Independent Software Vendors) to bridge the gap between customer needs and SEA AI's platform, enabling a scalable and diverse range of AI applications across various verticals.

How does SEA AI address the complexity of AI and ML for its customers?

SEA AI simplifies AI and ML deployment through its software package called Edge Matic, which offers no-code ML and computer vision capabilities, allowing customers to drag and drop features and deploy applications easily.

What are some of the coolest use cases of SEA AI's technology mentioned in the script?

Some of the coolest use cases include medical applications that help save lives through improved imaging and prediction, factory floor automation that enhances productivity, and automotive applications that aim to reshape level two plus autonomous driving experiences with lower power consumption.

What advice does Krishna Rasagam have for entrepreneurs and founders in the AI and edge computing space?

Krishna Rasagam advises entrepreneurs to have resilience, believe in their vision, and keep pushing despite challenges. He also emphasizes the importance of building a strong team and being able to innovate and recover quickly in the fast-paced startup environment.