Christopher Mims at The Wall Street Journal is not worried about robotic overlords. He writes, “…as chief scientist and AI guru Andrew Ng of Chinese search giant Baidu Inc. once put it, worrying about takeover by some kind of intelligent, autonomous, evil AI is about as rational as worrying about overpopulation on Mars.”
Mims notes that AI startups are attracting investment, and 40 have been acquired this year. Further, companies are competing with universities for AI talent. Nevertheless, he quotes Angela Bassa, head of the data-science team at energy-intelligence-software company EnerNOC Inc., as saying, “Everyone wants to think the AI spring is going to blossom into the AI summer, but I think it’s 10 years away.”
Mims cites Bassa as describing three problems with AI. The first two are straightforward: first, many companies lack sufficient data to make AI work, and second, they lack sufficient AI talent. The third might be called insufficient ROI. He notes that a bank may be willing to invest heavily to cut credit-card fraud by 1%, but a mid-sized manufacturer might not find it worthwhile to invest in AI to improve the productivity of a particular line by 1%.
But Mims undercuts his own argument somewhat by citing the example of n-Join, a company in the machine-condition-monitoring space. “Israel’s n-Join sells manufacturers a small box that collects data from machines on an assembly line, and then uses machine learning to spot aberrations that could presage a breakdown,” he writes.
Mims adds, “The key to n-Join’s utility, says Guy Tsur, a senior technologist at Strauss Group Ltd., one of Israel’s largest manufacturers of dairy products and an early n-Join customer, is that it doesn’t have to know the type of assembly line it’s attached to, or what the sensors feeding it data are measuring. It’s simply looking for correlations that indicate the manufacturing process is operating differently than usual. It then alerts its human supervisors, who can use their own experience and judgment to diagnose a specific problem.”
But Mims remains unimpressed. “One thing an astute reader has noted by now is that none of these triumphs and shortcomings of AI resemble the sci-fi visions of machines taking over the world,” he writes. He puts today’s AI “…at the jellyfish stage in the evolution of biological intelligence.”
I think he sells AI short, and efforts of companies such as NI and HPE as well as ADLINK, IBM, and Intel will drive the technology forward.
