The disruptive force of artificial intelligence

There are good reasons to view artificial intelligence as the disruptive force of the next decade. Just look at the evidence.

Autonomous cars already run in tests from California to Germany, chatbots, such as Amazon’s Alexa, answer questions for consumers, and Facebook uses AI to track offensive material in video streams.

Not to be overlooked, Google Translate runs smarter with AI under the hood, and young companies talk of intelligent drones that can follow you around and new ways to develop drugs and diagnose disease.

AI has quite a resume. And it’s just getting started.

New opportunities on the horizon may revolutionize object recognition and optimize decision making for corporations and individuals. Think of real time sales call analysis or apps that quickly tell people how to get from point A to point B. Opportunities also should evolve for detecting anomalies, such as unusual network loads, or deciphering which customer channels generate most of a product’s super users.

“The next wave, we think, is AI,” said John Frankel, a founding partner at ff Venture Capital. “We think it’s coming into its stride over the next few years.”

Frankel said he sees AI as a major shift in the tech landscape, much as the Internet, cloud computing and mobile have been. AI, or machine learning, has been around for decades, but this time it is real, he said.

Several key factors are behind this. For one, larger data sets exist, with data from phones, TVs, medical records, genomic sequencing and other sources digitalized and widely available. At the same time the amount of processing power and storage capacity in the cloud and available elsewhere has grown, with algorithms more mature and networks increasingly optimized for GPUs and AI. This has brought the costs of using AI down.

Technical breakthroughs meanwhile have taken place in image recognition. And companies such as Amazon and Google are driving the market on the consumer side, with trained talent on the rise.

VCs, by in large, believe the investment cycle with AI is early, with the technology is on its way to become part of everything.

“We think it’s one of the most profound elements that will change productivity for the entire workforce,” said Matt Murphy, a managing director at Menlo Ventures.

Over the past 5 years, investors in AI and machine learning have focused mostly on security and advertising. More recently, money has chased machine vision for autonomous cars and robots, speech recognition and natural language.

Now that Google has put out its Tensorflow open source software library and Amazon Web Services has unveiled its AI platform, there should be a rise in company formation, though using tools such as TensorFlow still remain difficult.

Some investors also expect an increase in M&A activity this year after a wave of mid-market and smaller deals last year from buyers, such as Salesforce, which stepped up efforts to build its platform by acquiring such companies as MetaMind.

“Every company is going to be asked what their AI strategy is” and the answer from many will be M&A, said Colin Beirne, a managing director at Two Sigma Ventures. Activity has quieted down since the election. “I definitely think it’s going to pick up.”

For many VCs, the distinction between AI and machine learning is a significant one. Machine learning relies on predictive algorithms that have been around for a while. AI, on the other hand, attempts to give computers the capacity to mimic human learning and decision-making, and has come to fruition in the past several years.

For this reason, “there will be a lot of hype in this space, a lot of smoke and mirrors,” Frankel said. “But we also think there will be a lot of reality.”

Photo of robot touching the words on a hexagon grid courtesy of BeeBright/iStock/Getty Images