3 Artificial Intelligence Applications from Sentient
Unfortunately for retail investors, you can’t invest in artificial intelligence yet. There just aren’t any publicly traded companies so we’ll have to wait for an IPO or an acquisition to happen. With over 900 “artificial intelligence” (AI) startups to evaluate, how can we possibly predict who the winners will be? Since artificial intelligence isn’t able to answer this question about itself yet, we can try to look at the companies with the most funding to see where sophisticated institutional investors are placing their bets. The AI company with the most funding to date is Sentient Technologies.
Founded in 2007, San Francisco based Sentient Technologies has taken in just over $135 million in funding so far. Their last funding round was a Series C of $103 million that closed November of 2014. The small pool of investors backing Sentient include Indian telecommunications company Tata Communications and an American conglomerate called Access Industries which focuses on three areas; chemicals, media and telecommunications, and real estate. In late 2014, Sentient Technologies emerged from stealth to unveil their massively distributed AI platform that is already trading stocks on its own.
Sentient refers to their AI technology as “Evolutionary Intelligence”. Inspired by biological evolution, Evolutionary Intelligence creates trillions of “genes” that are unique solutions to a problem. They then test each solution using real data and rank the best performers. The process is repeated in the same way that natural selection works with the lower ranked solutions being eliminated over time as seen below:
Using this method, Sentient was able to solve the “70 multiplexer problem“, a problem “with a search space so vast, it has never been solved using a direct method until now“. We don’t really know what that means either but all the
nerds math aficionados seem to think it’s a big deal and it certainly sounds like it. So why is this suddenly possible? Co-founder and Chief Scientist of Sentient Babak Hodjat explains:
“Evolutionary Computation (EC) has been around since the advent of computation and artificial neural networks have been around for years, but being able to run an EC at massive scale and continuously produce new and better results, that’s new.”
Sentient is not the first to harness the power of millions of computers. An initiative out of Berkeley called SETI claims to have the largest distributed computing effort with over 3 million users that look for evidence of alien life. Sentient appears to have taken the same concept and applied it to artificial intelligence while developing a growing patent portfolio that protects their AI technology. They refer to this as “distributed artificial intelligence” or DAI:
To do this, we link together two million CPU cores and 5,000 GPU cards dispersed around 4,000 sites worldwide to create one massive distributed compute resource. Our AI + distributed scale = distributed artificial intelligence (DAI). This creates a scale that is simply not available from the leading cloud providers.
So what artificial intelligence applications are Sentient targeting with their AI platform? Chief executive Antoine Blondeau, the man who invented the tech behind Siri, told The Telegraph that “humans can be replaced in finance, healthcare, and retail“.
The application in finance isn’t being talked about much but we do know they built trillions of AI traders and distilled them into an AI trader that was successful enough that they are considering spinning it out as a prop trading company or asset management firm. If it’s really that successful, they may just keep it in house and away from prying eyes.
As for the retail application, they have built “Sentient Aware”, an e-commerce visual search and product discovery solution which was used by Shoes.com to increase order values and conversion rates for their online shopping portal.
The healthcare application seems to be in exploratory stage with Sentient releasing an interesting case study with MIT in which they were able to predict the onset of sepsis 30 minutes before a fatal event took place with a 90 percent accuracy. Sepsis affects a million people a year and is the most expensive condition treated in U.S. hospitals with a yearly cost exceeding $20 billion a year.
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