Tom Taulli has been developing software since the 1980s. In college, he started his first company, which focused on the development of e-learning systems. He created other companies as well, including Hypermart.net Along the way, Tom has written columns for online publications such as BusinessWeek.com, He also writes posts on Artificial Intelligence for Forbes.com

In 1956, John McCarthy setup a ten-week research project at Dartmouth University that was focused on a new concept he called "artificial intelligence." The event included many of the researchers who would become giants in the emerging field, like Marvin Minsky, Nathaniel Rochester, Allen Newell, O.G. Selfridge, Raymond Solomonoff, and Claude Shannon. Yet the reaction to the phrase artificial intelligence was mixed. Did it really explain the technology? Was there a better way to word it?

According to data from PitchBook, the funding for AI deals has continued its furious pace. In the latest quarter, the amount invested came to a record $31.6 billion. Note that there were 11 deals the closed more than $500 million. Granted, plenty of these startups will fade away or even go bust. But of course, some will ultimately disrupt industries and change the landscape of the global economy.

"For example, when you type in a search for a job title, say with the phrase'job manager,' the LinkedIn engine will not only look for the title itself, but also people with relevant skills like time management, team coordination, risk assessment and so on," said Sakshi Jain, who is the Engineering Manager on LinkedIn's Responsible AI team. It can index and surface information on people from hundreds of sources as passive candidates typically aren't on job or career sites, and many people tend to only include piecemeal information on their LinkedIn and other profiles." "With the use of automated scheduling and email follow-ups, AI can help free up valuable time and solve the major pain point of extensive back-and-forth coordination with candidates and interviewers." "While there is no need to inspect every transaction or process run by the AI, there is a need to constantly review the performance of the AI steps to ensure that the outputs are in line with expectations. Tom (@ttaulli) is an advisor/board member to startups and the author of Artificial Intelligence Basics: A Non-Technical Introduction, The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems and Implementing AI Systems: Transform Your Business in 6 Steps.

Founded in 2005, Rimini Street is a provider of support services for enterprise applications from companies like SAP, Oracle and Salesforce.com. The goal is to reach $1 billion in revenues by 2026. And to accomplish this, the company evaluated a myriad of AI solutions. But they all fell short. "In the end, we leveraged a combination of best of breed open source technology and tools to build our own AI platform that is very powerful, intelligent, extensible and scalable," said Brian Slepko, who is the Executive Vice President of Global Service Delivery at Rimini Street.

Snell, second from left, comes out of the game against the Dodgers in the 6th inning in Game 6 of the World Series at Globe Life Field on October 27, 2020 in Arlington, Texas. I'm a lifelong Dodgers fan and I waited for 32 years for the team to win another World Series. But during this period of time, the sport has certainly seen much change. With the availability of huge amounts of data, sophisticated computers and advanced analytics, the strategies have become increasingly based on the numbers. It seems that AI (Artificial Intelligence) has dominated the decision making process.

AI (Artificial Intelligence) governance is about evaluating and monitoring algorithms for effectiveness, risk, bias and ROI (Return On Investment). But there is a problem: Often not enough attention is paid to this part of the AI process. "AI projects are rarely coordinated across a company and data science teams are often isolated from application development," said Mike Beckley, who is the CTO of Appian. "And now regulators are starting to ask questions businesses don't now how to answer." Keep in mind that AI introduces unique problems.

According to research from IDC, the global spending on AI (Artificial Intelligence) is expected to hit $97.9 billion by 2023, up from $37.5 billion in 2019. This represents a compound annual growth rate of 28.4%. No doubt, this is an enormous opportunity for startups. "These days, almost every company needs to leverage AI in order to thrive and build a meaningful future," said Saar Yoskovitz, who is the CEO of Augury. "This is true for younger startups, and it is true for the largest companies, even in the most traditional and nascent industries like manufacturing and insurance. In a sense, AI has become another layer in the tech stack, like databases, and not a business model."

According to research from IDC, the global spending on AI (Artificial Intelligence) is expected to hit $97.9 billion by 2023, up from $37.5 billion in 2019. This represents a compound annual growth rate of 28.4%. No doubt, this is an enormous opportunity for startups. "These days, almost every company needs to leverage AI in order to thrive and build a meaningful future," said Saar Yoskovitz, who is the CEO of Augury. "This is true for younger startups, and it is true for the largest companies, even in the most traditional and nascent industries like manufacturing and insurance. In a sense, AI has become another layer in the tech stack, like databases, and not a business model."

This week IBM, Microsoft and Amazon announced that they would suspend the sale of their facial recognition technology to law enforcement agencies. But the moves from the tech giants also illustrate the inherent risks of AI, especially when it comes to bias and the potential for invasion of privacy. Note that there are already indications that Congress will take action to regulate the technology. In the meantime, many cities have already instituted bans, such San Francisco. Because of the advances of deep learning and faster systems for processing enormous amounts of data, facial recognition has certainly seen major strides over the past decade.