“You promised me Mars colonies, and instead, I got Facebook” said Buzz Aldrin in a MIT Technology Review article in 2012. PayPal co-founder Peter Thiel, added “We wanted flying cars – instead we got 140 characters. ”In the article, titled“ Why We Can’t Solve Big Problems, ”Editor-in-chief Jason Pontin adds that critics of Silicon Valley feel “venture investing has shifted away from funding transformational companies” toward funding ”features, widgets, irrelevances.”
Pontin feels we Haven’t seen “big things” since the PC revolution due to three reasons. First, many of society’s big problems are bound by political policy, and ideology – not technology. Second, many of the remaining big problems are too complex and we haven’t made the scientific and engineering progress required to address them. Lastly, economic forces – solving “big things” is expensive, and new innovations are often not cost competitive in the market. Tesla’s success in the automotive market is an exception.
But there is good evidence that the constraints of technological progress are about to change. To see why, we need to understand that tech innovations are dependent two types of computational problems.
Two Classes of Innovation
Today’s world does not look like the future many of us saw as children in movies, because there’s been asymmetrical progress between two types of innovation. The first, connectivity-driven innovations, were less anticipated by futurists decades ago. The second, applied science innovations, were eagerly expected. No one’s said predicting the future was easy.
Modern connectivity-driven innovations started with computer networking, leading to e-commerce. By 2010, mobile computing devices, along with cloud and hyperscale infrastructures, made it possible to create seamless digital interactions that were personalized, and in context. Two examples are AirBnB and Uber. While valuable, AirBnB and Uber are essentially just-in-time & personalized brokers of something we’ve been doing for decades – renting houses and riding taxis. Same is true for social media like Facebook and Twitter, whose main product is better targeted advertisements.
What happened on the applied science innovation front during this time? Not so much. While we’ve seen improvements on the quality and efficiency of physical products, it hasn’t changed how we live. No one has flown supersonic commercially for nearly twenty years. Electric cars and clean energy are barely starting to make a dent. No flying cars exist beyond early prototypes. It’s understandable why many are disappointed.
Uneven Progress
) There are several reasons why connectivity-driven innovations have seen the spotlight while applied science innovations have been comparatively starved.
Connectivity-driven innovation has several advantages. First is its faster innovation and monetization cycle. It’s much faster to build a mobile app and try to monetize than to advance scientific breakthroughs, push through regulatory hurdles, manufacture, and develop a product go-to-market. Because of this advantage, it sees more investment from VC’s (who often want returns in (years). This leads to more press and media coverage, and greater intake of talent. Lastly, computing requirements for connectivity-driven innovations are readily available utilities in the public cloud, where the 65% of workloads run. Just add software.
On the other hand, applied science innovations not only require physical manufacturing, but solving problems in the outdated-ly named high performance computing ( HPC) discipline. HPC hasn’t changed much in decades; its common operating model is closer to hugging servers than utility computing. Engineers are resigned to “dumb down their model” to complete their designs with limited computing power, or wait for compute time to run simulations. Project costs explode, time to market is delayed, while IT organizations take pride in the high utilization of expensive HPC hardware they bought three years ago. For anyone that’s spent time in enterprise cloud computing, it can seem downright crazy.
Feeding the Applied Science Innovation Engine
But this is about to change –HPC workloads are shifting to the cloud. This means for the computing part of the equation, applied science innovations will soon be on equal footing as its connectivity-driven cousins. Cloud providers are making specialized HPC infrastructures available on demand. Simulation software vendors are shifting their licensing models for utility consumption. And new platforms are bringing it all together as turnkey solutions.
Today, mainstream enterprises like Nissan are using HPC in the cloud to build better cars with acoustic, airflow, structural, thermal, and crash simulation techniques. We’re also seeing a rapid expansion of VC-funded startups in theelectric car,aerospaceandspaceindustries. For these startups, running simulations in the cloud is the default starting point.
The agility of cloud computing is finally fueling the applied science innovation engine. So for those who’ve had their fill of social / mobile / local webapps and want clean energy, electric cars, and supersonic jets, there is reason to be optimistic.
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