When Steve Jurvetson speaks, Silicon Valley listens. Recently the billionaire investor gave a fast-paced talk at the SLUSH conference on the compounding effect of deep learning.
Steve Jurvetson is widely recognized as one of the smartest people in Silicon Valle. He graduated in engineering from Stanford at the top of his class in two-and-a-half years and is friends and associates with fellow billionaires and the biggest names in the tech industry. He also serves on the Board of Directors for deep learning company Nervana Systems (recently acquired by Intel), as well as Planet Labs, a company that has launched the largest constellation of Earth-observation micro-satellites, and D-Wave, a quantum computing company which counts Google, NASA and Lockheed-Martin as customers.
When Jurvetson speaks, it is worth listening to. Recently he gave a fast-paced talk at the SLUSH conference on the compounding effect of deep learning. See the full video below.
"If the internet is in your business in any way, there is something happening in the next five years that you should definitely have on your road map. And that is, we are going to see the greatest change in people's access to the internet than we've ever seen," states Jurvetson. "This is the greatest delta shift in people's connection to the global economy than ever before."
"Specifically," he continues, "I'm referring to broadband satellite connections."
"Deep learning, as applied to all forms of engineering, is the biggest advance since the scientific method itself."
Previously, Jurvetson was an R&D Engineer at Hewlett-Packard, where seven of his communications chip designs were fabricated. He also worked in product marketing at Apple and NeXT Software and management consulting with Bain & Company. He also holds a MSc in electrical engineering and MBA from Stanford and is the first non-Europe to become an Estonian e-resident.Related articles
The fast-talking Jurvetson concludes his talk with thoughts about deep learning. "I would argue that deep learning, as applied to all forms of engineering, is the biggest advance since the scientific method itself." We are building learning machines that can learn better than we can learn, and systems that we cannot efficiently comprehend. Adversarial learning is even pitting one AI against another to learn faster. Such a system was used by DeepMind in the development of AlphaGo.Quoting Danny Hillis, from The Pattern on the Stone:
"The greatest achievement of our technology may be the creation of tools that allow us to go beyond engineering -- that allow us to create more than we could understand."
We are at the cusp of this change, projects Jurvetson.
The scientific method was a profound change in how we accumulate learning over time, and how we move from random guesses to how we might accumulate ideas that might actually hold merit and predict the future, and have descriptive power, and throw away the ones that are bad. I think deep learning is as powerful as that.
"We humans are no longer at the vanguard of evolution. We are parenting the next generation, and we should get used to that."
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. He is co-founder and chancellor of Singularity University and a director of engineering at Google, heading up a team developing machine intelligence and natural language understanding.
, The End of Faith, Letter to a Christian Nation, The Moral Landscape, Free Will, Lying. The End of Faith won the 2005 PEN Award for Nonfiction. Harris's writing and public lectures cover a wide range of topics -- neuroscience, moral philosophy, religion, spirituality, violence, human reasoning -- but generally focus on how a growing understanding of ourselves and the world is changing our sense of how we should live.
from best-selling AI writer Calum Chace, he argues that within a few decades, most humans will not be able to work for money.
where he claims that AI’s developmental path is a lot faster paced than human’s biological cognition evolution and it would radically outperform us which eventually leads to a form of Superintelligence. In addition, game AI and the AI’s ability to perform at various complex games were cited as huge milestones towards developing human-level intelligence AI. Bostrom proposes that once human-level intelligence AI is achieved, the time frame in which Superintelligence is achieved may be relatively short and faster than we expect. We employ these concepts extensively within our multimedia project, most evidently in Day 1 and the lead-in into Day 2. 
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