When John Deere debuted its first-ever autonomous tractor at CES 2022, it signaled a new era of AI & robotic farming would soon be upon us. While other companies have been talking about autonomous tractors for some time, it's an altogether different matter when the U.S.'s biggest manufacturer of farming equipment signals that this is the future. Still in the trial phase, early versions of the 8R are now being tested by what the company describes as its "paying test cooperators." But since it won't be long before the final production model of the autonomous tractor is rolling off the production line, I thought it would be a good time to sit down with one of the company's computer vision leads, Chris Padwick, the Director of Computer Vision and Machine Learning at Deere's Blue River Technology division, to get an idea of the how the company got to this point. According to Padwick, since its acquisition by John Deere in 2017, Blue River has helped accelerate the farming equipment giant into precision agriculture with its "see and spray" computer vision technology.

AI is having an impact in business, government and healthcare. But nowhere is it having more impact than for the biggest companies with the most resources. Advantages big companies have include access to lots of data and funds to buy smaller companies with the expertise to do something innovative and profitable with the data. Each company has had to decide on the best way to leverage AI for their business. "The question is how do you use AI right or use it wisely," stated Ed McLaughlin, Chief Emerging Payments Officer for Mastercard, at the recent EmTech Digital event on AI and big data, as reported in MIT Sloan Review.

At the end of 2019, BlueDot, a Toronto-based company specializing in infectious disease surveillance using artificial intelligence and machine learning, let its customers know about the Wuhan coronavirus outbreak in China. That was a full week ahead of the U.S. Center for Disease Control and Prevention, which let Americans know on Jan. 6, and nine days ahead of the World Health Organization on Jan. 9. More than 100 people have died from the coronavirus worldwide. While the virus continues to spread, BlueDot was able to prevent its customers from exposing themselves to any issues before the outbreak had left China and traveled by plane to North America. BlueDot founder Kamran Khan founded the company in 2014 after seeing first hand what the SARS epidemic did to Toronto a decade earlier.

Automated farming equipment has perhaps never been a hotter topic than right now. Adding fuel to the fire, farm equipment giant John Deere had a big splash at last week's Consumer Electronics Show (CES) in Las Vegas, NV. Last year was a tough act to follow. In 2019, it exhibited its machine learning (ML) and artificial intelligence (AI) enabled S-Series combine. This year, Deere brought out the big guns with its R4038 sprayer.

In just 30 years' time, it is forecasted that the human population of our planet will be close to 10 billion. Producing enough food to feed these hungry mouths will be a challenge, and demographic trends such as urbanization, particularly in developing countries, will only add to that. To meet that challenge, agricultural businesses are pinning their hopes on technology, and that idea that increasingly sophisticated data and analytics tools will help to drive efficiencies and cut waste in agriculture and food production. Leading the way is John Deere – the 180-year-old manufacturer of farming and industrial machinery which has spent the past decade transforming itself into an artificial intelligence (AI) and data-driven business. I have covered John Deere before here.

Summary: Now that we've detailed the four main AI-first strategies: Data Dominance, Vertical, Horizontal, and Systems of Intelligence, it's time to pick. Here we provide side-by-side comparison and our opinion on the winner(s) for your own AI-first startup. In our last several articles we've taken a tour of the four major strategies for creating a successful AI-first company. So which one is best? Since we're going to offer a side-by-side comparison you may want to refer first to the foundation articles on the four strategies: There is wide agreement that controlling a unique data set is the most effective way to create a defensible moat.

YVERDON-LES-BAINS, Switzerland/CHICAGO (Reuters) - In a field of sugar beet in Switzerland, a solar-powered robot that looks like a table on wheels scans the rows of crops with its camera, identifies weeds and zaps them with jets of blue liquid from its mechanical tentacles. Undergoing final tests before the liquid is replaced with weedkiller, the Swiss robot is one of new breed of AI weeders that investors say could disrupt the $100 billion pesticides and seeds industry by reducing the need for universal herbicides and the genetically modified (GM) crops that tolerate them. Dominated by companies such as Bayer, DowDuPont, BASF and Syngenta, the industry is bracing for the impact of digital agricultural technology and some firms are already adapting their business models. Herbicide sales are worth $26 billion a year and account for 46 percent of pesticides revenue overall while 90 percent of GM seeds have some herbicide tolerance built in, according to market researcher Phillips McDougall. "Some of the profit pools that are now in the hands of the big agrochemical companies will shift, partly to the farmer and partly to the equipment manufacturers," said Cedric Lecamp, who runs the $1 billion Pictet-Nutrition fund that invests in companies along the food supply chain.

In a field of sugar beet in Switzerland, a solar-powered robot that looks like a table on wheels scans the rows of crops with its camera, identifies weeds and zaps them with jets of blue liquid from its mechanical tentacles. Undergoing final tests before the liquid is replaced with weedkiller, the Swiss robot is one of new breed of AI weeders that investors say could disrupt the $100billion pesticides and seeds industry by reducing the need for universal herbicides and the genetically modified (GM) crops that tolerate them. Dominated by companies such as Bayer, DowDuPont, BASF and Syngenta, the industry is bracing for the impact of digital agricultural technology and some firms are already adapting their business models. Herbicide sales are worth $26billion a year and account for 46 percent of pesticides revenue overall while 90 percent of GM seeds have some herbicide tolerance built in, according to market researcher Phillips McDougall. 'Some of the profit pools that are now in the hands of the big agrochemical companies will shift, partly to the farmer and partly to the equipment manufacturers,' said Cedric Lecamp, who runs the $1billion Pictet-Nutrition fund that invests in companies along the food supply chain.

YVERDON-LES-BAINS, Switzerland/CHICAGO: In a field of sugar beet in Switzerland, a solar-powered robot that looks like a table on wheels scans the rows of crops with its camera, identifies weeds and zaps them with jets of blue liquid from its mechanical tentacles. Undergoing final tests before the liquid is replaced with weedkiller, the Swiss robot is one of new breed of AI weeders that investors say could disrupt the US$100 billion pesticides and seeds industry by reducing the need for universal herbicides and the genetically modified (GM) crops that tolerate them. Dominated by companies such as Bayer, DowDuPont, BASF and Syngenta, the industry is bracing for the impact of digital agricultural technology and some firms are already adapting their business models. Herbicide sales are worth US$26 billion a year and account for 46 percent of pesticides revenue overall while 90 percent of GM seeds have some herbicide tolerance built in, according to market researcher Phillips McDougall. "Some of the profit pools that are now in the hands of the big agrochemical companies will shift, partly to the farmer and partly to the equipment manufacturers," said Cedric Lecamp, who runs the US$1 billion Pictet-Nutrition fund that invests in companies along the food supply chain.

Among the many topics discussed at this year's World Economic Forum in Davos, artificial intelligence ((AI() was pervasive throughout the multi-day meeting of some of the most powerful business people and political leaders in the world. The head of Google, Sundar Pichai, even went as far as saying that it was more important to humanity than fire or electricity. That's a bold claim, but Pichar may end up being right. Three of the big problems that companies are using AI to help address are disease and medical errors, feeding a growing population and access to clean water. The top three killers in the U.S. are heart disease, cancer and… medical errors?