Category: Conferences/Events (Page 5 of 80)

Ari Gesher, Engineering Ambassador, Palantir Technologies, just gave an animated talk, starting with the whole history of computing and operating systems (well, compressed a bit), and how it was all so custom (bespoke) — drawing an analogy to where big data is these days. He cited this classic tweet from last year:

@BigDataBorat In Data Science, 80% of time spent prepare data, 20% of time spent complain about need for prepare data.

Here's how Gigaom billed this talk: "The past decade has seen a proliferation of standalone-tools and technology for large scale data processing.  While powerful and transformational, the onus is still on the implementer to do most of the work – 80% of the time is spent on setting up the technology, leaving only a fraction to work on the actual problem at hand.  In the early days of computing, every piece of software had this problem – until operating systems heralded a revolution in building applications cheaply. What does the same innovation look like in the big data space?  How do we get beyond building prototype after prototype?  And what about the elephant that’s not even in the room yet – namely, good user Interface?"

Whew! To get Ari's take, watch the video of his talk on the livestream. And follow Ari on Twitter @alephbass.

This was an amazing session — the speaker's personal story made us all gasp! Wow, follow Ramona Pierson, cofounder and CEO of Declara on Twitter (@ramonapierson). Better than me trying to quickly recap it, watch the video here.

She talks about how machine learning can power platforms that make sure the right people and right content find each other without relying on who they know. Ramona spoke about some great work Declara is doing in Australia right now. (Shout out to my home country!)

Om Malik did a great on-stage interview (as he always does!) of Ben Medlock, CTO at SwiftKey, and Tim Tuttle, CEO, Expect Labs. Check out these two companies — I wish I could type fast enough to cover their insights! (Maybe their technologies can help?)

Here’s how Gigaom billed this session in the program: “Despite the hard work that goes into building systems for deep learning and other methods of understanding human language, users might never know they’re powering their favorite apps. And that’s kind of the point. Hear how voice and text messaging services are learning to predict what users will say to deliver a seamless experience.”

Tuttle especially had some fascinating comments. He said it will only be about six years until we smartphone users have a terabyte on our device! “That changes the game.” No lie — talk about the smartphone as brain…

Cloudera CEO Tom Reilly is on stage with Tom Krazit, Executive Editor of Gigaom. He's now talking about the $160M(!) his firm just raised — from T. Rowe Price (which invests primarily in public companies), Google Ventures, and Dell (led by Michael himself).

How soon will Cloudera be a $1B company? "In a large, accelerating big data market ($50B?), we believe we'll be the largest company?" How soon will you IPO? "We have a long way to go before that." (They just hired their first ceneral counsel!) He's done it before, so he's quite familiar with the process. "Gotta get off Quickbooks first." 🙂

Talking about product and their Enterprise Data Hub: "We have dozens of companies behind us building the platform. We don't need to build up," said Reilly. Cloudera is hiring more engineers to ensure the integrations with partners go smoothly. "Predictive support capability" is part of version 5.0. "Machine learning and SQL are working side by side."

APIs are, or will be, putting cutting-edge capabilities in deep learning, cognitive computing, and artificial intelligence into the hands of developers everywhere.

Stacey Higginbotham, Senior Writer at Gigaom, is interviewing Elliot Turner, CEO of AlchemyAPI, and Stephen Gold, VP-WW Marketing and Sales Operations, Watson Solutions, IBM Software Group.

"How soon before developers can access computer vision capabilities?"  Stacey asks. Turner: "We'll see more and more of this — it won't be called cognition or AI, it will just be solving real world problems — like helping the blind to see."

Stacey: "How much will cognition-as-a-service cost?" Gold: "The original Watson is now 90% smaller and 24 times more powerful…We'll see people who will pay for a given portion of that brain." (More on Watson.)

Okay, "but will cognition ever become a commodity?"  Gold: "For the foreseeable future, I don't think that's in the picture." Turner: "We have seven billion people who can migrate skills and solve problems."

Stacey: "What do you tell your children about what you're doing?" Turner: "We need to move away from rote memorization." Gold: "There's a big movement in universities in how we educate. We need curriculums on how to build these cognitive capabilities."

(UPDATE: Here's an article I found that dives deeper, shall we say, into a topic addressed in this session: The Gigaom Guide to Deep Learning.)