European researchers from Capgemini have developed a platform called Project FARM (Financial and Agricultural Recommendation Models) which aims to boost farmers’ yield, optimise the value chain, and bolster the global food supply.

Project FARM is first going to be used in Kenya to assist coffee farmers. The platform was built in collaboration with East Africa-based social enterprise firm Agrics which provides local farmers with agricultural products and services on credit.

Julian van Velzen, a data analyst at Capgemini who leads Project FARM, said:

“By connecting farming communities with data science, and big data with traditional farming methods, the FARM platform is built to optimise the value chain and bring parties together as an ecosystem around one data-driven platform.

The platform can pave the way for bringing automated farming to small-scale farmers. With the increasing availability of open data and decreasing prices of sensors and satellite imagery, the future of farming is bright.”

AI is used to analyse farm data sourced from Agrics in addition to satellite data from Project Sobloo, a Copernicus Data and Information Access Service (DIAS). 

A dashboard provides insights to the farmer with tailor-made advice on how to optimise production. This advice can also be sent via SMS so, for example, an alert can be issued to take precautions if a crop-damaging thunderstorm is due the next day.

On the business-side, Agrics is able to use the data to foresee any risks that may impact each farmer and their investment.

Violanda de Man, Innovation Manager at Agrics East Africa, commented:

“Through our interactions with the farmers, we are on top of a huge reservoir of data. We can now turn this data into meaningful insights, which allows us to provide time and location-specific products and services to increase yield and lower risk at farm and value chain level.

Increased value chain effectiveness will help to directly improve the income and food security of rural populations.”

The global demand for food is expected to increase by 60 percent by 2050 and most of the world’s population is fed primarily by small farmers in developing countries. Supporting these farmers isn’t just the moral thing to do; it also helps to keep food on all of our plates.

Earlier this week, Fairtrade warned that coffee could become a luxury due to climate change affecting production. According to Catherine David, head of commercial partnerships at Fairtrade, issues like extreme temperatures, increased humidity, and pests are hitting farmers’ crops.

Meanwhile, a growing population is living longer and the demand for coffee is increasing. Combined with the expected production issues, the quality of coffee is expected to decrease while prices rocket.

I don’t know about you, but I need my coffee and would rather not have to take out a loan for my fix.

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Last week, AI News reported on a Microsoft study which highlighted that high-growth companies are over twice as likely to be using AI. 41 percent of high-growth companies are using AI compared to just 19 percent of low-growth.

This divide needs to change or small businesses risk falling even further behind. However, overall, less than two in 10 of even high-growth companies are integrating AI which presents a huge opportunity.

Microsoft is launching AI Business School which provides lectures, case studies, guides, talks, and resources from industry leaders as well as Microsoft’s own executives. The course is designed to be for people with a business background so it’s non-technical.

“There is a gap between what people want to do and the reality of what is going on in their organisations today, and the reality of whether their organisation is ready,” said Mitra Azizirad, corporate vice president for AI marketing at Microsoft.

“Developing a strategy for AI extends beyond the business issues,” she explained. “It goes all the way to the leadership, behaviours and capabilities required to instill an AI-ready culture in your organisation.”

The new ‘Business School’ is an extension of Microsoft’s existing ‘AI School’ which is a more technical course.

You can find out more about the AI Business School here.

deepgeniusai.com/">AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, , & .

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One standout result of the study is that German, British, Russian, Dutch, Swiss, and Italian business leaders are – on the whole – reporting they’re “actively implementing” AI ahead of the US.

In fact, of business leaders from the countries surveyed, only France was behind the US.

The survey did not include all countries and is missing several notable countries including the likes of Japan, Canada, and Australia. Of course, the biggest omission is China.

China and the US are leaders in AI development but Microsoft’s study indicates that isn’t translating into adoption by American businesses.

Another interesting highlight in Microsoft’s study is the disparity in adoption between high and low growth companies.

High-growth companies, defined as having double-digit growth, are over twice as likely to be using AI. 41 percent of high-growth companies are using AI compared to just 19 percent of low-growth.

This disparity is most prominent in Germany where 67 percent of high-growth companies are using AI compared to just 17 percent of low-growth.

Susan Etlinger, Industry Analyst with the Altimeter Group, said:

“What’s striking about the research is the difference between double-digit growth companies and those with lower growth.

Double-digit growth companies are further along in their AI deployments, but also see a greater urgency in using more AI. They are looking at a one to three year timeframe – often really focused on the coming year. Lower growth companies are looking at more of a 5-year timeframe. What this says to me is that the more you know, the higher your sense of urgency is.”

Most of the businesses are either in the ‘exploring’ or ‘experimenting’ stages on their AI journey. The competitive advantages to using AI are clear, but it’s worth starting small and scaling up deployments over time.

deepgeniusai.com/">AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, , & .

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The company is using the data for a new feature called ‘Profile Recommendations’ whereby the app will recommend switching to a correct profile for your journey.

Many people will have two Uber profile – one for personal use, and the other for business.

Ronnie Gurion, GM and Global Head of Uber for Business, says:

“Using machine learning, Uber can predict which profile and corresponding payment method an employee should be using, and make the appropriate recommendation.”

When quickly booking a ride, it can be easy to forget to switch. Accidentally booking a ride home from a night out using a business account set up with a workplace’s payment details is an unwanted conversation with an employer.

Uber believes its success rate for determining the correct profile is around 80 percent.

To help reduce the 20 percent it gets wrong, businesses can assign ‘trip reviewers’ who know whether an employee’s use is supposed to be personal.

Any questionable rides can be flagged by the reviewer and the employee can decide in the app if it was supposed to be a personal ride or not. The whole process is designed to be much quicker than starting email threads about the issue and similar bureaucratic processes.

What are your thoughts on Uber’s use of AI for its latest feature?

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