Two of the hottest trends in technology right now are robotics and artificial intelligence (AI). These technologies are closely intertwined. As AI becomes more sophisticated, it will inevitably control the robots of the future. Both technologies provide ample opportunities for intelligent entrepreneurs.
In artificial intelligence, the current hot topic for research and development is machine learning.
Machine learning (ML) is not just a critical piece of artificial intelligence needed for fully autonomous robots. Machine learning also has wide applications in business, healthcare, and government. It’s no wonder that machine learning startups are the new “dot-coms” of the modern era.
What is Machine Learning?
Machine learning and artificial intelligence are often used interchangeably, but they are slightly different ML is an aspect of AI. Artificial intelligence is the ability of a machine to mimic intelligence. Machine learning refers to the ability of machines to learn from experience.
Machine learning takes a computer, that might otherwise be a mindless calculator or number crunch machine, and turns it into a “living,” evolving technological entity. A machine that “learns” can then make better “choices” about what actions to take.
For example, let’s say a business has a UPS system (the UPS computer term means “uninterruptible power supply”). This system might be used to keep important computer servers online in the event of a power outage. No UPS, however, can last forever, so a machine learning algorithm could be set up to teach a computer to prioritize which servers and systems will receive the UPS power and for how long.
Because machine learning is still a relatively new field, many startups are turning to ML as a potential cash cow. Will some of these companies become the tech giants of tomorrow? Possibly, although many of the most promising ML startups have been already bought up by big companies like Apple and Microsoft.
3 Business Opportunities for Machine Learning Startups
Opportunities for ML companies abound, but the time has come and gone to be just a generic “machine learning” company. High-tech investors are now looking for more specific, applied uses of machine learning to support with their dollars. Companies that are targeting specific needs of certain industries may have an easier time obtaining funding.
Here are just some of the areas machine learning is poised to create change:
1. Healthcare Support
Image source: http://www.eweek.com/cloud/google-launchpad-to-support-startups-in-ai-machine-learning-space
From diagnostics to managing patient records, AI has many applications in the field of healthcare. With increasing demands on hospitals and healthcare providers to manage patient records, billing, and follow-up, companies are looking to apply machine learning as a solution.
For example, in September 2017, Cogitativo, Inc., which bills itself as “the first-to-market machine learning and data-science-as-a-service company for healthcare organizations,” announced it had received $5 million in Series A funding. The company provides machine learning solutions for healthcare organizations, including “improving payment accuracy, care anomaly detection and real-time monitoring of payers’ care delivery networks.”
2. Supply Chain Logistics
Image source: http://www.samvedaresources.com/supply-chain-management-total-logistics.html
The supply chain is what connects products from manufacturers to customers. With machine learning, this crucial lifeline (especially when it comes to food and necessities) can be made more efficient and secure.
The unfortunate devastation of Puerto Rico after Hurricane Maria in 2017 is a clear demonstration of what happens when the supply chain is disrupted. After Hurricane Maria, many supplies were sent to Puerto Rico, only to sit at the docks. Truckers were cut off from their trucks due to the power outages, gas shortages, and blocked roads.
With artificial intelligence, disaster planners might have better ways to prepare for disruptions caused by natural disasters and other events. ML technologies can help predict trends, consumer demand, and potential bottlenecks, so that goods and services can reach people more efficiently and cost effectively.
3. Cybersecurity and Fraud
Image source: https://uiux.blog/design-case-study-caulis-cybersecurity-startup-brand-identity-bbca047429cb
With an increasing number of high-profile computer hacking incidents and breaches, such as the Equifax consumer data fiasco, cybersecurity is only becoming more and more important. ML technologies can help with predictive algorithms to identify vulnerabilities before they happen, and much more.
Internet fraud is not just an American problem. The country of Israel has more than 430 AI startups, and the most active sector for funding is “Cyber Security for Enterprises” at $575 million. “Insurance & Fraud in Fintech” is another hot AI startup focus at $189 million in funding. The challenge will probably be that rogue organizations are likely to use machine learning to speed up and improve hacking.
Machine Intelligence is the Future of Business
With applications in healthcare, consumer goods, cybersecurity, and more, machine learning provides ample opportunities for the ambitious entrepreneur. However, competition is and will be fierce, so the most successful AI companies will not only have to be the best innovators, but, like the company Apple, the best marketers as well.
