Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

Full Bio 
Follow on

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

3 Best Programming Languages For Internet of Things Development In 2018
346 days ago

Data science is the big draw in business schools
519 days ago

7 Effective Methods for Fitting a Liner
529 days ago

3 Thoughts on Why Deep Learning Works So Well
529 days ago

3 million at risk from the rise of robots
529 days ago

Top 10 Hot Artificial Intelligence (AI) Technologies
310584 views

Here's why so many data scientists are leaving their jobs
80796 views

2018 Data Science Interview Questions for Top Tech Companies
76641 views

Want to be a millionaire before you turn 25? Study artificial intelligence or machine learning
76083 views

Google announces scholarship program to train 1.3 lakh Indian developers in emerging technologies
61392 views

This Startup Is Raising $3.5 Million To Add Machine Learning To Fish Farms

By Nand Kishor |Email | Jan 31, 2018 | 8157 Views

Machine learning and vision startup Aquabyte announced Tuesday that it has raised $3.5 million in seed funding in order to build out a team of developers to refine its software, which is geared toward using machine learning and vision to reduce costs for fish farming. The round was co-led by Costanoa Ventures and New Enterprise Associates. Princeton University and other investors also participated in the round.

The main purpose of the round is to help the company build out a team to develop its technology, both at its headquarters in San Francisco as well as Norway, where the company is working with pilot customers. The company is also focused on Norway because there's significantly more fish farming there than there is in the United States.

Initially, the company is focused on developing its machine learning and machine vision software to develop two algorithms: one to determine the size of salmon over time, and the other to determine the presence of sea lice, a parasite sometimes found on salmon. But it won't be easy.

webinar

"[F]ish are exothermic - and respond to their environment - which means that a lot of data, from both camera data using computer vision, multi-sensory environmental data like temperature and oxygen, and human input data such as how much to feed - make this a very rich data problem for machine learning," Aquabyte CEO Bryton Shang told me in an email.

That rich problem is something the company is working to solve in a number of areas, both in fish farms in net pens in open water as well as tanks - a growing area of aquaculture. The data is gathered using underwater 3D cameras.

"We're in the middle of building those algorithms," Shang said. "Then we'll commercialize those and use the data to develop feeding algorithms."

The company's ultimate goal is to use those feeding algorithms to more finely control the amount of food that fish farmers use. If it's successful, the company claims it could save fish farmers 20-30% of the cost of food currently used. That's a big deal, considering that feed accounts for about half the cost of the average fish farm.

Once the company has optimized its algorithms for feeding salmon, it intends to move on to other kinds of fish as well as other markets.

"Our plan is to start in the Norwegian market then expand to Chile, Canada and Scotland," the company wrote in a briefing document. "The same technology is applicable to other species such as trout, seabass, and seabream."

Source: Forbes