Artificial Intelligence and Machine Learning have been some of the hottest startup buzzwords over the last few years, but their adoption has been much less widespread than one would expect.
“90% of companies doing AI/ML are doing nothing even remotely related,” tweeted former Flipkart CPO Punit Soni. “The number is probably 99% for startups,” he added.
90% of companies doing doing AI/ML are doing nothing even remotely related. The number is probably 99% for startups.
Applies to Robin too. Long way to go before @gorobinai lives up to the last 2 letters of it's name. AI is an aspiration. Just don't have enough data yet.
— punitsoni (@punitsoni) December 24, 2017
It’s a startling admission coming from someone who’s a veteran of the industry, and even runs his own “Artificial Intelligence” startup. But Soni admits that Robin.Ai, his own healthcare startup that he’d founded last year, doesn’t use a lot of Artificial Intelligence in its operations. “Applies to Robin too,” he continued. “Long way to go before GoRobin.ai lives up to the last 2 letters of its name. AI is an aspiration. Just don’t have enough data yet.”
Soni has gone ahead and said what many in the industry have been quietly hinting at for a while now — the extent to which startups have been using Artificial Intelligence in their operations has been vastly overhyped. Artificial Intelligence and Machine Learning were touted to be transformational technologies that could create great value for companies, so startups benefited immensely in terms of funding and exposure from claiming they were employing cutting-edge AI.
But it’s often impossible to tell from the outside the extent to which these companies were using AI. There are long-running jokes that several startups simply use basic if-then loops and pass off their work as AI.
— Flink Labs (@flinklabs) September 28, 2017
— macoymejia.com (@macoymejia) July 4, 2017
And others have pointed out at Artificial Intelligence and Machine Learning aren’t business models by themselves, but a merely way to provide a better solution to end users.
Sorry if I burst your bubble but AI/ML/CV/AR/VR are not business models. They are just means to an end to satisfy a scalable need.
— Sampad Swain (@sampad) December 18, 2017
AI’s detractors aren’t coming only from the world of startups. Infosys founder Narayan Murthy yesterday said that the impact of AI was often vastly overblown. “There is this whole thing about automation and artificial intelligence. That is much more hype than the reality, at-least in the software services,” he said at a conference.
There have, of course, been some spectacular advances thanks to Artificial Intelligence and Machine Learning in the recent past. Last year, DeepMind, a Google company, had managed to beat the world’s best players at Go, and earlier this year, an Artificial Intelligence created by researchers at CMU had managed to beat the world’s best players at poker. Machine Learning has created some impressive results in certain user-facing products — it’s hard not be a little awed by how Google Photos neatly classifies photos into those of sunsets and those of your pets.
But therein, perhaps, lies the rub. Most of the significant results in AI and Machine Learning have come from large and established companies like Google and Facebook, which have both the infrastructure to run intensive Machine Learning tasks, and the deep pockets to hire the very best AI researchers. The average startup usually has neither of these advantages, meaning that meaningful AI results aren’t always easy to achieve for smaller companies.
But that hasn’t stopped legions of startups from claiming that they’re working with cutting-edge AI and Machine Learning. These were, of course, incentives to claim to work in these fields — it made it easier to raise funds and command high valuations. AI startups also enjoyed greater media exposure than their peers working in less exciting fields. But with few AI startups coming up with breakthrough products — no Indian AI startup has yet made its mark in a big way — questions are being raised as to whether the entire space might have been more than a little over-hyped.