For some time now, Google has been investing in artificial intelligence and machine learning, and some of this evolution feeds the growing ecosystem that l & # 39; surrounds, development tools to startups. Their latest effort, Launchpad Studio, is aimed at one vertical at a time, favoring startups looking to make profound changes to the lagging industries of the avant-garde; the first batch is for the data rich medical world.
The Studio is independent of Google's accelerators and investment organizations, and does not invest in the companies it works with at all. It is more of exploiting the knowledge and hunger of startups to identify future areas of investment and development.
It's rather a competitive advantage that Google has that this program does not need to make a profit or produce an impressive portfolio; it can burn money by supporting and exercising due diligence with respect to intelligent ideas and advanced algorithms, essentially by outsourcing some of the R & D and hunt for opportunities while generating goodwill.
"Our hypothesis is that there is much to learn from examining an industry and all the ways that machine learning can be applied to this industry," said Malika Cantor, Program Manager at Launchpad . "We have asked startups to write a project proposal that addresses a significant machine learning problem that they are addressing in the next 6 months. We focus on solving technical challenges. "
The medical world is kind of a logical starting point, because the amount of data generated is huge, as are the potential benefits of unlocking all the hidden ideas in that data. Regulatory hurdles, FDA roadblocks and other obstacles in the road will have to be mostly defeated by the start-ups themselves, in which Google has no interest, and whose difficulties could help future efforts in the sector – perhaps at Verily.
All this sounds very cynical, but there is no doubt that the company is eager to do good. It's not like they're embarking on drug discovery and patenting. The first series of companies in the six-month program seems very focused on improving outcomes for patients using readily available data.
BrainQ, whom I briefly talked to with the founder, Yotam Drechsler, uses EEG data to improve the electromagnetic treatment plans of stroke patients. Now, as a rule, I am skeptical about studies and products based on the EEG because the EEG is a hundred year, noisy and often superficial measure of brain activity.
But bad or noisy data "is exactly where AI progress comes into play," Drechsler said. Just like machine learning can be used to separate the signal from the noise in the audio, images and other areas, it can be applied here too – that is the theory, of anyway. If it works, it may help to bring feelings and movement back to affected limbs, by putting patients back on their feet or using their hands faster.
CytoVale is another goal to improve hospital outcomes, particularly with respect to sepsis, a serious blood infection that can be fatal if it is not treated promptly, but which is unfortunately rather difficult to detect. The company uses a high-speed camera to inspect thousands of cells per second and monitor the signs of sepsis with the help of computer vision. Every minute counts with infections, so a test that does not require an outside lab, large blood samples and so on could be a lifesaver.
Google Glass makes an unexpected comeback in Augmedix which makes it possible to put patient files under the control of the doctors, thus freeing them from having to use a terminal or a page of nurse or specialist. I hope that they will not check Twitter during the consultations. I've never really bought Google Glass as a consumer product, but maybe in niche situations like this, it could be really useful. Where the AI comes in, that's the guesswork of someone, though.
The last is Byteflies which manufactures a modular portable system that can be configured according to the requirements of clinical trials – tracking "" any vital sign, no matter what. anytime, anywhere ", according to Google's press release.This is a great promise that would also have a lot of time and savings for teams that can not afford to build a blood sugar monitor or something from scratch, or buy a price premium from a medical provider.Byteflies would also handle the data produced by the device, also offering a powered analysis by ML
All companies will be exposed to many experts and investors, as well as hardware and credits on cloud services, but Google does not retain any special rights such as the first refusal on a round of seed or something like that. They will keep in touch as part of a loose "wallet", but the accelerator is "agnostic investors," Malika said.
There is no word on the number of startups that will come through Launchpad Studio – registration is not scheduled – but at some point, the team will move to another industry, agriculture or housing. The idea is that the lessons learned in the first verticals will stack up and make the impact bigger and easier in the later ones.
If this sounds like a good path for your business, you can apply now, regardless of the industry for which you want to apply the AI and the ML; in fact, there is a good chance that the team uses applications to evaluate the industry to target.
Image of the hotel: Google