Mythic: Bringing AI to the Cutting Edge
July 8, 2021 | Ashley Brindamour
Edge devices are reshaping the AI space. Unlike cloud-based solutions, edge AI offers an integrated approach with many benefits for a wide variety of product developers as information is processed locally — ultimately enhancing speed, design, privacy, and user experience.
Running AI models at the edge rather than in the cloud offers significant advantages to manufacturers: Designs can be simpler, privacy is significantly enhanced, and the overall user experience is superior. However, AI at the edge also means the deployment of millions of devices, which creates another set of challenges, such as the need for low-cost, small form-factor devices with low latency, high performance, and low power consumption. To date, expensive and power-hungry hardware has made it difficult to cost-effectively deploy AI widely.
Alumni Ventures’ portfolio company Mythic is reframing how product designers think about where and how AI is implemented. Mythic’s solution breaks down barriers to innovation, making it significantly easier and cheaper to create and deliver cost-effective AI solutions. The company’s button-sized chips operate at a fraction of the cost and power of a traditional GPU chip, allowing AI to be used in all kinds of edge devices such as smart camera systems, intelligent appliances, gaming, drones, and much more.
A Cutting EDGE AI Solution
While edge-driven AI offers many benefits for product manufacturing companies, it also means deploying millions of devices. Mythic addresses this pain point with its groundbreaking chip technology. This tech delivers higher performance with 20X lower cost and 10X less power — previously unthinkable, through the use of flash memory and analog compute alone.
Just a few of the many applications of AI on the edge include:
- Improving security camera detection
- Expanding data and image processing capacity for autonomous vehicles
- Reducing costs and improving safety for industrial IoT
- Increasing speed and lowering latency for mobile devices
- Enhancing rapid analysis of medical and other complex images
Mythic’s hardware interface and driver model are simple — point to the data, trigger inference, and read the results. Furthermore, for demanding applications, multiple Mythic chips can be chained together to provide computation at a large scale, which is currently impossible with existing solutions.
Strong Investor Syndicate and How We Are Involved
Mythic’s syndicate of investors includes BlackRock Innovation. In just two years, the firm has had four exits, including semiconductor company NUVIA, acquired by Qualcomm for $1.4 billion.
The syndicate also includes other established investors such as Valor Equity Partners, Lux Capital, Threshold Ventures, Data Collective, and Future Ventures. Just a few of the companies backed by these firms include Tesla, Wish, Uber, and Palantir.
Spike Ventures (Alumni Ventures’ fund for the Stanford community) led our investment in Mythic’s $70 million Series C. Sibling funds Bascom Ventures (for the Wisconsin community), Ring Ventures (for the Texas A&M community), and Westwood Ventures (for the UCLA community) also invested in the round. The company is also part of the portfolio of Alumni Ventures’ Deep Tech Fund and was a Syndication opportunity.