Many AI companies are flush with cash and raising money at increasingly eye-watering levels and valuations. How could it be that these robotics firms, run and operated by some of the most celebrated people in the AI industry could be failing when seemingly less-compelling solutions such as process automation tools and facial recognition applications are raising billions of dollars? Is robotics really that hard or is there something else going on in the industry?
In the past few years, a staggering amount of venture capital has been raised by companies in the AI, machine learning, and cognitive technology spaces. According to a report by KPMG, over $12 Billion dollars in venture capital was raised in 2017 alone, more than doubling the previous year’s record tally of over $5 Billion. This is a dramatic increase from 2008 when total AI funding was less than $200 million. According to Crunchbase, the average early-stage round for an AI startup in 2010 was about $4.8 million. In 2017, that ballooned to $11.7 million. In 2018, a single company, SenseTime, raised over $1.2 Billion in venture capital, with a rumored additional $1 Billion coming from venture giant Softbank. This is more money than was raised in the entire industry just a few years ago.
So, how can it be in this industry awash with money, where anyone with a half-rational business plan spouting the terms AI and machine learning can raise ridiculous amounts with little market validation while the well runs dry for others run by industry veterans? Is the problem with AI? Is the problem with venture capital? Is the problem with robotics? Or is there something specific happening at each one of these notable robotics failures that bears closer examination?
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