The new mobile. Our final invention. The new electricity. Artificial intelligence has been hailed as all of the above. As an industry, it was the recipient of more than $5 billion VC dollars in 2016 and is now the noun in tech juggernauts’ newest blank-first strategies (think “mobile first,” “social first,” etc.). Much editorial space and time has been spent pondering whether AI is a fad in the same way the aforementioned trends in tech were – will it sputter out and give way to some more extraordinary force in two years’ time, or is it truly the revolution it purports to be?
Frankly, there is a lot of nonsense out there that leads with “AI” to validate itself while solving exactly zero problems and innovating on precisely nothing. But there are also some pretty spectacular companies deftly using artificial intelligence to take on the most challenging issues facing humanity. So whether AI will make it to the 2020’s – whether its pioneers will hang on hallowed walls next to Galileo, Newton and Einstein – we’ll leave up to you. Instead, we want to take a few moments to shout out a few organizations doing arguably the coolest work we’ve seen and using clever forms of artificial intelligence (machine learning, deep learning, etc.) to do it. For now, we think this conversation is a better use of our time.
Check them out and let us know who we’re missing!
AI Organizations Solving Big Problems
Descartes Labs – applies machine learning to satellite imagery and is helping to prevent global food shortages via agriculture applications. Descartes’ partner, Planet provides organizations with satellite imagery for disaster response, water security and environmental monitoring.
Grail – early stage cancer detection that draws on clinical science, bioinformatics, deep learning and engineering.
HiBot – uses big data and AI to help utilities solve the $1 trillion water infrastructure problem facing the United States.
OpenAI – a non-profit artificial intelligence research company with the mission to build safe AI, and ensure its benefits are as widely and evenly distributed as possible.
Stanford University’s Department of Earth System Science – conducted a study drawing on satellite imagery and machine learning, using night-lighting as an indicator of socioeconomic status worldwide. The aim was for this metric to support the UN’s Sustainable Development Goal of eradicating global poverty.