What Made AI Mainstream, Part 2: Big Compute (Video)
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Read the complete transcript of this clip:
Paco Nathan: The other factor is Big Compute. That really started in the early aughts. How many people use cloud services? Amazon, Google, Microsoft, it's a lot more hands these days. Back in 2006 or even into like 2010, it was still kind of iffy. What happened there was in the early aughts, VMware and Cambridge and some others came out with software to do virtualization. So you could have your computer running but then you could run a smaller virtual version of a computer inside out it and partition your resources. And so that was, let's see, I think Hypervisor was like 2002, 2001. Intel did hardware for virtualization in about 2003, 2004. In 2006, Amazon launched AWS. And the other thing that's not mentioned a lot is in 2006, Google contributed a library to Linux. It's called 'Cgroups'; it's kind of obscure but it allowed for virtualization. And they contributed open source, it was in the 2.6 release of Linux, like I say, 12 years ago. But what that enabled was a bunch of other software.
How many people here have run across Docker? Or used containers? Okay, more. So that all came out of Google making a contribution to Linux. And again, that all started in the early, mid aughts. And you can see now that again, about 12 years later, this is really becoming commodified. And that's moving forward, I'll talk more. But that space of hardware in the cloud is really changing rapidly, and it's a big driver.
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O'Reilly Media's Paco Nathan discusses the explosive growth in CPUs and GPUs that have opened new vistas for natural-language processing applications and rendered old approaches obsolete in this clip from his SpeechTEK 2018 keynote.