Impact AI Improving Fish Farm Efficiency with Bryton Shang from Aquabyte
Today I'm joined by the Founder and CEO of Aquabyte, Bryton Shang, to discuss his mission to improve and enable fish farm efficiency and sustainability. Bryton fills us in on the role machine learning plays in monitoring underwater fish farm environments, the challenges of gathering and annotating data to build and train their models, and how their human-in-the-loop QA process converges to find solutions. Tune in to discover how Aquabyte’s mission-oriented, multidisciplinary, and multimodal nature impacts recruitment, and hear Bryton’s astute recruitment advice for leaders in the field. Aquabyte is a stellar example of an AI-powered startup looking to create a better, more sustainable future for the world at large.
Key Points:
- Bryson Shang’s background and what led him to create Aquabyte.
- Aquabyte’s mission to enable efficient and sustainable fish farming.
- The role machine learning plays in monitoring underwater fish farm environments.
- How Aquabyte built their ML models.
- The practical challenges of training their models and their solution-finding systems.
- How Aquabyte’s mission-oriented, multidisciplinary, and multimodal nature impacts recruitment.
- Bryton’s recruitment advice for other leaders of AI-powered startups.
- His vision for Aquabyte’s impact in the next three to five years.
Quotes:
“[At] Aquabyte, we're focused on how machine learning and computer vision can help fish farmers be more efficient and sustainable.”
“There’s definitely a mission-oriented aspect to [Aquabyte], which is attractive to a lot of folks that are looking for more of a mission-oriented bent.”
“AI is a broad label, and I think the business domain in which you apply AI and how you apply it is really important, ultimately, to the success.”
“By having autonomous fish farms, or even on land where you can have much more scalability of fish farming, then you can really increase the supply of fish.”
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