WHY THIS MATTERS IN BRIEF
Companies with better brand recognition, and deeper pockets, are cornering the market for AI talent, but now companies want break that hold, and they have a way to do it.
Despite how easy the combination is to mock, the idea of applying the Blockchain to Artificial Intelligence (AI), something that IBM is under taking to help analyse and secure healthcare data in new ways, is attracting a growing roster of serious entrepreneurs and venture capitalists, many of them with impressive academic credentials. And Dawn Song, a computer science professor at the University of California, and Ben Goertzel, the chief scientist at Hanson Robotics, have been among the big names arguing that the blockchain could be a crucial way to push back against some of the most worrying trends facing the field of AI and democratise it for all – something that also chimes well with Microsoft who also recently said they too want to “democratise AI.”
Many AI experts are concerned that Facebook, Google and a few other big companies, and that’s before I even mention the Chinese companies, like Baidu, who are going all in on AI, are hoarding talent in the field. The internet giants also control the massive troves of online data that are necessary to train and refine the best machine learning programs.
Professor Song, Goertzel and other entrepreneurs say they believe the blockchain could encourage a broader distribution of the data and algorithms that will determine the future development of AI.
“It’s important to have machine learning capabilities that are more under the user’s control, rather than relying on these big companies to get access to these capabilities,” Professor Song said in an interview. And the start-ups working toward this goal are applying blockchains in a number of ways. At the most basic level, just as the blockchain allows money to be moved around without any bank or central authority in the middle, AI experts are hoping that blockchain can help AI networks access large stores of data without any big company in control of the data or the algorithms. And several start-ups are now setting up blockchain-based marketplaces, where people can buy and sell data.
Ocean Protocol, for example, a project based in Berlin, is building the infrastructure so that anyone can set up a marketplace for any kind of data, with the users of data paying the sources with cryptocurrency.
Unlike Google and Facebook though, which store the data they get from users, the marketplaces built on Ocean Protocol will not have the data themselves; they will just be places for people with data to meet, ensuring that no central player can unfairly access or exploit the data.
“Blockchains are incentive machines – you can get people to do stuff by paying them,” said Trent McConaghy, one of the founders of Ocean Protocol, who has been working in AI since the 1990s.
The goal, McConaghy said, is to “decentralize access to data before it’s too late.”
Ocean is now working with several automakers to collect data from cars to help create better AI’s for autonomous cars. All the automakers are expected to share data so none of them have a monopoly over it.
Another start-up, Revel, using their Hadron Cloud platform, will pay people to collect the data that companies are looking for, like pictures of taxis or recordings of a particular language. Users can also let their phones and computers be used to process and categorize the images and sounds, again, all in exchange for digital tokens. Over a thousand people already have put their computers to work.
These sorts of marketplaces are only the outer layer of the blockchain-based systems that are being built to handle AI data.
One of the biggest concerns that people have about the data being collected by Google and Facebook is the access it gives these companies to the most private details of our lives.
Professor Song is working on a blockchain, known as Oasis Labs, that will use advanced techniques to secure the data being bought and sold, so that no one — not even the company using the data — will get a copy of it.
In the Oasis network, all data moving through the system will be locked into encrypted bundles. Researchers will be able to run the data through their machine learning algorithms — and prove that the calculations were done correctly — without ever actually seeing the underlying data.
One project building on top of Oasis, known as Kara, will allow medical researchers looking at the behavior of specific diseases to train their machine learning models with data from actual patients, without the data ever being exposed.
Oasis has already raised $45 million from several big-name venture capital firms, but MIT, called Enigma.
Enigma got started before Oasis and is working with partners like Ocean Protocol to ensure that people contributing data to marketplaces can set the exact terms under which their data can be used.
Other start-ups are using blockchains to open access to the AI models themselves. Goertzel has created SingularityNET, a blockchain that will serve as a link between different AI services around the world. If one AI module, for example, is unable to come up with an answer, it can consult with others, and provide compensation if one of the other modules is able to get it right.
“It let’s you have a network of AI’s that nobody owns,” says Goertzel.
Hanson Robotics is planning to use SingularityNET to feed information into its humanoid robot, Sophia. Unlike Amazon’s Alexa service, which answers questions using services approved by Amazon, Goertzel wants Sophia to reach out to other AI providers if she can’t find the right answer.
“We are now using SingularityNET to upgrade Sophia’s intelligence,” Goertzel said. “In principle, it is much more flexible because we don’t have a centrally controlled market.”
As with most blockchain applications, a lot of technical work still must be done before these new systems can take off though, and it is not clear that all of the roadblocks are surmountable. Fred Ehrsam, the co-founder of the cryptocurrency exchange Coinbase, for example, is investing in the area, but he says he believes it will take some time before these systems can prove themselves. But none the less he hopes that when they do they will play an important role in democratizing the industry.
“Right now the data isn’t really being valued in an open market, it’s just being given to a few companies,” Ehrsam said. “What if there was now a free market for data?”