ML meets Aquaculture (sustainable fish farmering)

Aquabyte's applying machine vision / machine learning to directly solve the world’s food sustainability issues. 

By improving fish farm efficiency (#1 growing sector of food production, $180B globally), we help close the world’s impending protein deficit.

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To begin with, Aquabyte will roll out a tightly coupled hardware and software solution, using advanced MV/ML techniques, to automate biomass estimation and parasite detection (starting with sea lice).

This will be achieved through placement of a stereo camera in each cage, hooked into a central ML appliance, the Aquabyte Brain, that processes these images locally from a given farms' pens. 

The appliance also interacts with Aquabyte's cloud to

(1) allow experts‑in‑the‑loop to continue refining the solutions accuracy, 

(2) allow all customers to benefit from the network effects of a larger dataset, and

(3) provide dashboard, analytics, and take-action functionality to the fish farmers based on the observed data.

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To summarize, the business plan is to start with these basic test -- which farmers desperately need and demand today --  and build higher order products over time.

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Aquabyte's continuous, accurate solution will assist farmers drive more operational efficiency and effectiveness via precision feeding programs,  targeted parasite management programs, and reducing supply chain uncertainty*.

Aquabyte is starting with Salmon in Norway, then will roll out to other salmon growing geographies worldwide. 

After which, Aquabyte will adapt its algorithm to other farm raised species.

* inherent to low accuracy levels in estimating a pen's biomass distribution

ML / MV technologies deployed to aquaculture challenges.

Requires stereo vision sensors collecting underwater footage, connected to our ML processing appliance, Aquabyte Brain.

ML/MV is hard, especially underwater.

R&D deployment is going into the water in May.

Inaugural customers should be live in October 2018.

Aquabyte will impact fish farmers' effectiveness and efficiency.

By improving fish farm efficiency (#1 growing sector of food production, $180B globally), we help close the world’s impending protein deficit.

When the tech works, non-customers will be forced to uplevel their capabilities. There's broad interest, we just need to continue refining the ML/MV data pipelines to hit adequate (and eventually super-human) levels of accuracy.

R&D deployment of sensor and ML appliance going into water in next several weeks

There are only ~100 ultimate farmers in Norway. We expect to slowly ramp, then increase sales velocity, starting in October 2018.