Commentary: AI is slowly, gradually changing the world, which may not be obvious to the casual viewer. Learn about startups that use AI to reduce food waste, improve education and more.
Artificial intelligence has made headlines for the past few years, but most presses ignore the risks and rewards. AI. We read about the inevitable bias of AI, and its deadly use in war. Of course, we also read positively, as Google Computer beat the best Go players in the world.
But these stories fail to accurately reflect the best use of AI today. I wrote years ago IBM needed to stop pitching its Watson as a miracle cure for everything, And instead position it for more hiking tasks. Similarly, we do better to celebrate the adoption of AI in small steps to add big savings – such as food and waste and other sectors.
Here’s how these emerging AI vendors came up with a solution that offers really important work-as-you-know lessons for any business. They present classic examples of real disruptions in the earlier Taro market … one rising phase at a time.
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Remained real with AI
The Term Act is so broad that it is almost useless for an average business, so it is better to be specific. Where AI is quickly gaining traction in “normal” industries is called supervised reinforcement education. Feed enough annotated data (data tags with you, service or special software details) Machine learning (ML) algorithms (usually free and open source) and run results through your application (usually in the public cloud), and suddenly your organization is solving difficult problems faster with more precision. Because ML “goes” as it goes, you create recurring loops to feed new data as well as adjusted old data back into the loop for new information, bias or other problems.
It’s getting better.
Finally, it is the data that powers the AI model. The more they assemble, powering the world’s most popular social platforms like user-generated content, the more useful and powerful their AI engines become. Global tech giants like Facebook, Google, Tesla and more can and have created a competitive threat through growing leadership in AI.
But daily companies can also take advantage of AI. More than six million Java Developers Today they can run their programs through an AI-powered software testing system based on similar AI concepts from DFW that Google used to beat the best Go players. It automatically makes Java unit tests 100X faster with 85% code coverage. Developers can save 20% to 0% of their hard-earned test writing tasks.
How about worldly affairs for some company (so to speak, pretty much every company) sells? Scoring sales leads is usually an arcane art, including expensive, complex systems for learning, or reliance on the intuition of the sales team. AI startup Akkio can suck your Excel Spreadsheets and Spit Out Cut edge-edge, high-quality Predictive analytics Dashboards in a day or two. Achieving similar results usually requires a dedicated application team and an AI scientist, and this can take months.
Or consider education. Startup Reid uses AI to improve education, And created a smartphone app that was free for a couple of years but better yet it collected millions of data bytes from users who wanted to improve their scores in a standardized test of English proficiency. The app can predict your score better than 95 %% accuracy after 10% minutes but later also created a personalized education program to increase the final score from 10% to 20% on average. Riyadh also released the largest public dataset in education and used that data to improve the algorithm of the world’s smartest AI researchers to sponsor the largest Koggle competition in 2020. Reid on Monday rolled out the AI engine to K-12 schools around the world, as well as corporate staff development programs.
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You’ve probably never heard of any of these companies, have you? Good AI projects start small and then build. Success in AI is modest, incremental. It also helps avoid hiring expensive dedicated teams of AI and data scientists. Companies like Scale AI, which offers service-based platforms, and Labelbox, which provides software-led platforms, can show companies how to succeed with AI and get caught up in the costly mistakes that cannot be limited to the dark.
I will end up with food and garbage, two boring problems that are critical to the future survival of our species and the health of our planet.
McKinsey, a research consultant, estimated that in 2020 Reduce food waste through AI By 2030, there could be a market opportunity of १२ 7127 billion. Wonderful and Recent reports Written for children, McKinsey estimated that if all the food products in the world represented -0-slices of bread, we collectively wasted 12 slices a day. As the world’s population reaches 10 billion by 20, the food production will almost double, even if farmland shrinks.
Can AI really help? It already is. Here are some recent examples of Labelbox customers – companies need to annotate mountains of data to train their AI systems – AI works to put food on our tables and cut garbage.
Based in Ireland, Canthaus uses computer vision to monitor herds of animals 2 monitors / 7 and sends alerts to farmers to feed less cattle to more cattle.
Everest Labs, based in Silicon Valley, uses AI and robotics to reduce waste and develop environmentally friendly products. Its robot can sort 600 bins of recyclables per minute.
John Dere’s Blue Reverse Technology Unit sells smart tractors that can spray herbicides properly, reduce costs, increase productivity and reduce pollutants in the environment.
UK-based Winno Solutions uses computer philosophy and AI to track and analyze food waste in industrial kitchens. Its customer, IKEA, reduced food waste by 45 percent in a month, and the company’s solution reduced customer CO2 emissions by more than 600,000.
Based in the Netherlands, Xarvio Digital Farming Solutions uses smartphones, drones and satellite imagery to build AI-powered products that advise farmers on how to maximize productivity.
This is how AI takes over the world, through incremental steps that make food production, education and many other industries more efficient and effective.
Disclosure: I work for AWS, but the views expressed here are mine.