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exception handling then? or for everything, how does that work when you're talking about computing?
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so that's interesting. but how does, just to be more concrete about that, i mean that makes a lot of sense logically.
H
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what's changed to make big data possible? i know the big obvious things are just more computing power, but more concretely.
N
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can you talk to us a little bit more about what exactly hadoop does and what spark does and how they all live together? and then how that actually fits into big data? for people who don't actually crunch those numbers behind the scenes.
X
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and so just, sorry, just to take a step back for a moment. the reason hadoop and it's ilk we're able to run on commodity hardware is because the hardware's gotten cheap enough.
N
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you essentially doubling the capacity that you can afford every 18 months.
N
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but the first layer that you're describing is a big data layer. that's how you're describing big data, is like storage?
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so i definitely think you're right that we might already even be there in some ways or that we need to be expecting that. but what does that really give us? does it, i mean, because.
N
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a lot of you're talking about is machines inferring and really aiding learning like humans and helping augmenting human intelligence. what happens next?
N
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interesting is people treat deep learning sometimes as discreet from machine learning, but you're basically.
N
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it's interesting academically. and it clearly, it's interesting beyond academically because companies are investing in it left and right. in fact more so in the corporate sphere than even in the university's sphere. but.
H
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well, let's pause here for a minute though because i do think this is a common misconception. we should spend a moment just really getting to the bottom of it because.
N
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... can't participate in the existing financial system, bitcoin is very well suited. take, for example, this week. this month, the price of bitcoin-
X
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it's almost like they're willingly disrupting themselves. and they don't know that. i mean they know that, but it'll be interesting to see how that plays out.
X
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stock certificate and you hold out $115 and we each grab the corresponding and then we pull in the opposite direction.
N
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but for the client experience, what will be different is the bullet points on the marketing.
X
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do you think that the players that you're working with buy into that vision? because right now it seems like they're smartly, opportunistically.
O
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we'd love to hear more insights about what it's like behind the scenes of actually doing this because.
H
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but what does that actually look like? because you're talking about two very different cultures.
X
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two very different technologies, two very different. i mean, there's so many different things.
N
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... to deploy a blockchain network. very strategic. we found that when we start in the innovation lab-
N
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part of what's challenging for us as a startup, is there is so much noise in this market right now.
N
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there will be a handful of networks that will be deployed by serious companies that will.
X
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bits and misconceptions, definitions, interesting things happening in bitcoin and blockchain.
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but one just to start off, because you mentioned database and your discussion about assets that we have this analog stuff and then you have a database.
X
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one thing that i've heard come up a lot is this notion of private and permissioned.
H
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blockchains, which feels really weird because isn't that just like a database then?
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this notion of having multiple networks, even if they are interoperable,
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it won't be hard to exchange across those networks, because, ultimately, we're talking about-
N
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so, a colored coin was the first kind of technical-
N
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yeah, sure. so the basic idea with a side chain was.
N
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the bitcoin network is big. there's 5 billion or today $7 billion of value transmitting on the bitcoin network.
N
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you've talked a lot about the disruption of the fintech and the work that you guys are doing and a lot of these new alternatives and things that are happening, experimentation that's happening on the blockchain.
N
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let's talk more about some of the more interesting native apps that you're seeing because i feel like.
N
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sometimes a conversation around bitcoin and blockchain gets so much into the infrastructural-
N
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... continued to be one of the most powerful use cases and interesting use cases-
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needing to keep money out of the site of corrupt officials, whatever it is. and of course illicit use cases continue to be.
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... getting two dollars off because you bought two dollars worth of coke products. that customer experience flow is just not possible.
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they want to change the way things are done, can backfire if they're applying it to establish processes at work, like sales.
X
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isn't part of what we're looking for, for ceos to have a sense of that roadmap in their head already without needing to-
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to have to get all these inputs. that vision. i mean, i'm thinking of an example, a classic example like steve jobs. did he really ever listen to what his customer said?
N
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that is if you're giving a product to consumers and selling advertising to companies-
N
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there's clearly a difference depending on what type of sales you're doing, whether you're doing big deals, volume of deals, where you're doing it, et cetera.
N
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... premium target to be more upmarket and the decision process to be more complex-
N
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super interesting is that obviously with a startup, your product evolves. at the beginning as a founder, when is the right time to bring on.
N
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it was amazing stories. i mean, those are the stories from the field. it was incredible, and there were so many amazing product-
H
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and you started this whole conversation talking about how founders reinvent.
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they have their own theories for how to reinvent things and frankly.
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so why shouldn't they experiment here? why do they have to stick to all these?
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everything is so dam broken and this is my shot. so now i'm going to definitely change everything.
X
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well thank you guys for another episode of the ‎a16z podcast.
H
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... people. so one of the fundamental techniques in deep mind's work is reinforcement learning.
N
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machine learning, deep learning as a deeper evolution of machine learning. and then sort of like a full ai on a continuum.
N
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... has no discretion and has to just ply their way through a script, and we know how frustrating it is to live in that-
N
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and general intelligence, artificial general intelligence. or human level ai. and we really don't know how to make that yet.
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may just sit down and say, i just want to sit here and do math. we really have no idea what their motivations will be.
H
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and i think what you're actually saying is actually that there's something more in between. because when i think of how i procrastinate as well.
N
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that's so interesting. that's actually a really good point.
H
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there were male characters. there weren't strong female characters, or if there were, they were adjuncts to the male character, instead of the main character.
X
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this is one of those things that's easy to talk about and hard to do, which is you actually have to know what people think.
H
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and online learning is improving at such a rapid rate that.
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they become, later and later, private equity players.
N
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capital is doing the same thing to investment. and that is it's a time when we shouldn't husband the use of capital but be aggressively.
X
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the privilege of owning them. you not only don't get any money, you have to pay.
A
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... so that anything that you need in order to furnish the apartment tomorrow-
N
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and if i have a need in my life and there isn't something i could hire to get that job done.
X
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is when you start up and you organize the company around an inside of a job that needed to be done. and nobody's developed a product to get that job done well.
S
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doing the numbers, they'll be finished very fast.
N
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and i look at my students who graduate every year.
N
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our careers are just filled with tangible, immediate evidence of achievement.
X
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and so when we have a choice about how do we spend this extra ounce of time and energy, unconsciously-
X
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where we get the immediate return and that's not at home.
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just understand for me.
N
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then i might be able to deal with it in a more productive way. so i'll just give you one example, but that's really what motivated.
N
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we need to meet on sunday at 2:00 pm because we have a big client presentation on monday, we got to be sure everything is in place.
N
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and an hour later he came back and he said, "look, clay, i talked to everybody, it's fine. we'll meet on saturday at 2:00 pm."
S
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this fits into two or three big industry preoccupations, like there is one preoccupation which is ai.
N
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then it works. where you'll be going to the website and looking for the support email or the phone number or maybe opening a support chat on the website.
N
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well i think it's important to mention though that the chat bubble is relevant in the sense of identity because part of what messenger announced is that facebook has your identity, they know who you are.
O
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and i think that's a key component to this conversation. how does that fit into making that transaction so seamless? because at the end of the day, a user just wants things.
O
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... on tap. and so if you think about all the apps out there that already have your payments credentials and a login in high frequency, they actually have a leg up, as opposed to facebook messenger, in pulling this off.
X
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the one question i have is, chris, you're working up to this argument about why conversational commerce.
N
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one question i have is, and i think all three of you guys disagree about this is where you guys fall in this.
O
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can we take a step back though and talk why people even care about bots in this paradigm? because.
N
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clearly there is a need to have conversation in a way that isn't populating your inbox with all this extra stuff. i mean, regardless of.
N
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i mean, it's not that it's not irrelevant, the design and the scoping of it, but.
X
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i don't have to go back into my inbox to find the confirmation if i want to change my flight that i can just very easily just go right into and say like, "hey, this is my new time." or.
N
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a richer way of now interacting with an existing brand. when i book my initial.
N
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plane ticket, i'm probably going to go to a travel website. and then when i have the rest of those interactions about updating my travel and doing all the reservations, i'll do all that within a bot.
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... any bit better. but saying, "follow our bot-"
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logistics i think is a little bit more built out in china is my guess than india.
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... is a really big important piece, i think, about that local functionality and local expertise.
N
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that one of the things that the local retailers had was an advantage in the fact that they've designed for systems of different payments.
N
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actually didn't ola in india, which is a competitor to uber in india.
H
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credit card penetration is really low. and the indian central government has a two factor authentication protocol.
N
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oh, why does that matter? is it because it's all happening at the smartphone level? i mean, obviously you're talking about the fact that.
X
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china is a very mobile first place and that's a huge part of what's enabling a lot of this. and you're describing what's happening in the payments in china.
N
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but interesting. so you guys are describing a lot of interesting players and companies and the way things are playing out. what's the funding landscape like there compared to here in both china and india?
N
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yes, but i think people underestimate how much capital is available in china.
X
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private equity players, or is it big conglomerates or big companies with corporate venturing arms? who are these players that are sort of providing this capital in these?
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