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Artificial Intelligence, Machine Learning Help Shrimp, Vegetable Farmers Reap Good Harvest

Aibono works with about 500 farmers and has about 200 acres are under active cultivation

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A team from Germany, the United States and France taught an artificial intelligence system to distinguish dangerous skin lesions from benign ones, showing it more than 100,000 images.
There are about 232,000 new cases of melanoma, and 55,500 deaths, in the world each year, the research added.

Artificial Intelligence (AI) and machine learning have entered aquaculture and agriculture farms in some states benefitting the farmers in cutting down their labour and the uncertainties of trial and error methods.

Thanks to artificial intelligence and machine learning technologies used by companies like the city-based Coastal Aquaculture Research Institute (CARI) and Aibono Smart Farming Pvt Ltd, Bengaluru, shrimp and vegetable farmers are able to increase their yield, cut their costs and have better market access.

V. Geetha, who practices aquaculture in Andhra Pradesh, told IANS: “Before signing up for CARI’s ‘FarmMOJO’ — an AI app-enabled farm advisor tool — we used to jot down the critical data in a notebook and act on it. But we wouldn’t know how much to feed the shrimp. There would either be over or under feeding.”

Since he tied up with CARI six months back, Prakash said, the company takes care of water quality tests in his pond and all the required data is available on his mobile with suggested action to be taken.

“Earlier the quantum of feed used would differ. Now we use the correct feed quantity, which has reduced the feed cost. The cost of medicines has also decreased. Earlier many would suggest several things. Now we go by what CARI says,” Prakash remarked.

“At 600,000 ton a year, India’s shrimp exports stand at Rs 45,000 crore annually. But no major technology was used so far in shrimp farming,” Rajamanohar Somasundaram, Co-Founder and CEO, CARI told IANS.

He said, now that the shrimp farming has been digitised, the data collected has been fed into the FarmMOJO programme.

“From the data, we have built machine learning. The software advises farmers on the use of feed, medicines and other things. The tool also helps in predicting the chances of a disease outbreak in the client farm based on the data available from other ponds,” he said.

The company has two revenue streams viz., subscription fee for FarmMOJO and commission on sales of products of partner companies. “At present, we have about 750 ponds spread over Tamil Nadu, Andhra Pradesh, Gujarat and Odisha. We will soon enter West Bengal.This year we plan to cover 2,500 ponds,” Somasundaram said.

Farmers, India
An Indian woman helps her farmer husband irrigate a paddy field using a traditional system, on the outskirts of Gauhati, India, Feb. 1, 2019. VOA

In agriculture, Bengaluru-based Aibono Smart Farming Pvt Ltd and its AI product are helping the farmers in Nilgiris district of Tamil Nadu to match the supply and demand of hill vegetables.

“In India, the land holdings by farmers are small. So, precision farming could be used only if the supply and demand are matched. The other problem is, good price realisation if the yield is good. Farmers do not have a foresight on what to produce and when,” Vivek Rajkumar, Founder told IANS.

Rajkumar said fruits and vegetables are a $250 billion market in India far bigger than that of fast moving consumer goods. But there are no e-commerce players in this segment.

“Aibono is like a dairy cooperative. It assures farmers of buying every kilogram of their produce at a good price so that they can make money. The average land holding of the farmers in the network ranges between 0.5 to 1.5 acre,” Rajkumar said.

“We collect about 2,000 data points like weather, soil tests, photographs etc. Open farm is like a factory without a roof. It is dynamic. But farmer’s activities are routine and predictable. But agronomy has to be changed to dynamic mode,” Rajkumar said.

With farmers seeing increasing yield but not commensurate increase in realisation, Aibono decided to look at the demand side and started to study the consumption pattern.

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“At the retail end, people buy a fixed quantity of the vegetables. The buying pattern in predictable but it is the supply that varies,” Rajkumar said.

“We signed up with retailers and hotels assuring them of supplies. For the farmers, we started calibrating issue of seeds so that the supplies could be assured at certain quantities at a specified time,” Rajkumar said.

Aibono works with about 500 farmers and has about 200 acres are under active cultivation. Rajkumar said: “we about 300 retailers in its network and next year the number is set to grow several times. We charge Re 1 per kg as fee for service to the farmers.” (IANS)

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Is Oracle Digital Assistant Smarter Than Amazon Alexa? Find Out Here!

Here's Why Oracle's digital assistant better than Amazon's Alexa

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Amazon and oracle
Amazon Alexa may lag behind Oracel Digital Assistant. Pixabay

Alexa may be your perfect living room assistant, but when it comes to specific queries with particular vocabulary from enterprises, it lags behind in rich capabilities that Oracle Digital Assistant (ODA) has to offer, a top company executive has stressed.

Oracle Digital Assistant can become your intelligent front-end — your smart router that’s able to send all your specific questions to relevant bots, according to Suhas Uliyar, VP-Product Management, Oracle Digital Assistant and Integration Cloud.

“It knows how to handle conflicts, manage security and so on and so forth. It has got Artificial Intelligence (AI) and is AI-trained so we call the routing of your questions to be relevant, and call it a skill now. Instead of bot, it’s a skill,” Uliyar told IANS during an interaction.

According to him, there are a couple of differences compared to Alexa as it works on the same model.

“Alexa is very implicit, where you have to say — Alexa, ask this skill to do something. While Oracle Digital Assistant is both explicit and implicit and you don’t need to sort of say ‘go ask the HCM (Human Capital Management) bot,’ for instance. It’ll just figure out that the question is for HCM bot and will answer accordingly,” Uliyar elaborated.

The other thing is to use the word ‘assistant’ and, according to him, we are overloading the term ‘assistant’ because if you have an ‘assistant’, she or he is smart enough to understand who you are, what your preferences are, know how you work.

“Most of the chatbots respond to a simple question and answer. Next time, it will probably remember who you are. So, the whole context is memory, and also the process side of things,” the Oracle executive added.

Oracle Digital Assistant provides the platform and tools to easily build AI-powered assistants that connect to your backend applications.

The digital assistant uses AI for natural language processing and understanding, to automate engagements with conversational interfaces that respond instantly, improve user satisfaction, and increase business efficiencies.

Most of those voice-enabled application programming interfaces (APIs) are being trained using what’s called Open Common Domain Models, which means that it understands our normal speaking style and content.

“What if an enterprise has a specific vocabulary? For example, a very common thing in Enterprise Resource Planning (ERP) is what’s EBITDA for a company. You try saying EBITDA to Alexa or any other such assistant in the market today, and you’ll most likely draw a blank,” Uliyar told IANS.

Oracle AI
Oracle digital assistant uses AI for natural language processing and understanding. Pixabay

Earnings before interest, tax, depreciation and amortization (EBITDA) is a measure of a company’s operating performance.

According to him, to serve customers with delightful experiences every single time, there has to be a lot of innovation happening — whether it’s mobile, chatbots, Blockchain, AI or AR/VR.

“With all these new realities, what enterprises really need is a platform that can pull that ‘holistic experience’ altogether. That’s sort of the topmost challenge that enterprise customers want to solve,” he noted.

Oracle Digital Assistant is very sophisticated. It has got deep learning and is based on a technology called Sequence-to-Sequence vectoring and creates what we call as logical forms of the statement.

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“We call it a deep semantic parsing. It’s the underlying technology and is very different given the advancements of deep learning. We can do a much better job instead of understanding the linguistic constructs, versus in the past. This is quite a bit of advancement. We’re definitely very excited about pushing the boundaries,” said Uliyar. (IANS)