O'Reilly Bots Podcast

it is playlist about data science. I'm putting here all podcast in english in related topic. If you know something that should be here please drop me a message with link. And follow me on twitter: @hyzhak_en

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bots

What does it take to build a data-driven culture? In this O’Reilly Podcast episode, I pose that question to Ashish Thusoo, founder of Qubole. With his co-founder Joydeep Sen Sarma, Thusoo built a self-service data infrastructure at Facebook beginning in 2007. That infrastructure transformed Facebook’s culture and became part of practically every product decision that the company made.

Building a Data-Driven Culture

In this episode I spoke with Michael Franklin, co-director of UC Berkeley’s AMPLab and chair of the Department of Computer Science at the University of Chicago. AMPLab is well-known in the data community for having originated Apache Spark, Alluxio (formerly Tachyon) and many other open source tools. Today marks the start of a two-day symposium commemorating the end of AMPLab, and we took the opportunity to reflect on its impressive accomplishments.

Building the Next-Generation Big Data Analytics Stack

In this episode of the Super Data Science Podcast, I chat with Chief Data Scientist Damian R Mingle. You will learn about how to build models with 95% accuracy rates, know the 3 top tips on quick wins and winning people over; and get ideas on how to save lives with data science.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/13

The Super Data Science Podcast: Big Data | Analytics Careers | Mentors | Success

SDS 013 : 95% Accuracy Models, Winning People Over, and Saving Lives with Damian Mingle

In this episode, I sit down with Brad Knox, founder and CEO of Emoters, a startup building a product called bots_alive—animal-like robots that have a strong illusion of life. We chat about the approach the company is taking, why robots or agents that pass themselves off as human without any transparency should be illegal, and some challenges and applications of reinforcement learning and interactive machine learning.

Brad Knox on Creating a Strong Illusion of Life

In this episode I spoke with Ion Stoica, cofounder and chairman of Databricks. Stoica is also a professor of computer science at UC Berkeley, where he serves as director of the new RISE Lab (the successor to AMPLab). Fresh off the incredible success of AMPLab, RISE seeks to build tools and platforms that enable sophisticated real-time applications on live data, while maintaining strong security. As Stoica points out, users will increasingly expect security guarantees on systems that rely on online machine learning algorithms that make use of personal or proprietary data.

Data is Only as Valuable as the Decisions it Enables

In this episode of the O’Reilly Bots Podcast, I speak with Dennis Mortensen, founder and CEO of X.ai, a personal assistant bot that handles meeting scheduling through email.

Dennis Mortensen on Email Bots

In this episode of the O’Reilly Bots Podcast, I speak with Tim Hwang, an affiliated researcher at the Oxford Internet Institute, about AI-driven psyops bots and their capacity for social destabilization.

Tim Hwang on Bots That Cause Chaos

In this episode of the O’Reilly Bots Podcast, I speak with Tom Coates, co-founder of Thington, a service layer for the Internet of Things. Thington provides a conversational, messaging-like interface for controlling devices like lights and thermostats, but it’s also conversational at a deeper level: its very architecture treats the interactions between different devices like a conversation, allowing devices to make announcements to any other device that cares to listen.

Tom Coates on Conversational Devices

Dan Gailey (@dpg) and Nathan Ross (@nathantross) talk about Enterprise Chatbots, Bot-to-Bot Communication, Bots as first class citizens, and Bot UX.

BotWorld Podcast #1 - Dan Gailey and Nathan Ross

In this episode of the O’Reilly Bots Podcast, I talk about deep learning at the extremes of scale and computing power with Prabhat, who leads the data and analytics group at Lawrence Berkeley National Laboratory’s supercomputing center. If you’re working on commercial AI, it’s worth glancing across the divide at scientific AI.

Prabhat on Deep Learning for Science

In this episode of the Bots Podcast, we peer into the giant companies that are beginning to adopt messaging and bots. My guest is Tom Hadfield, founder of Message.io, a service that syndicates bots across many different messaging platforms.

Tom Hadfield on Bots in the Enterprise

In this episode of the Bots Podcast, Chris Messina and I reflect on what Facebook has become, the role that it now plays in our lives, and what it all means for developers. We recorded this discussion shortly after attending Facebook’s F8 Developer Conference in San Jose.

Chris Messina on Facebook as a Utility

In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I talk to Jason Laska and Michael Akilian of Clara Labs, creator of a virtual assistant—Clara—that schedules meetings and interacts in natural language through email.

E-mail is, to me, a highly promising (and somewhat underrated) venue for bots. Messaging is growing quickly, but e-mail is still the standard way to communicate within businesses and especially between businesses. E-mail conventions are somewhat standardized, and much of it is highly routinized—automatically generated reports, receipts, etc.—so it’s ripe for automation.

Laska, who leads the machine learning efforts at Clara Labs, and Akilian, the company’s co-founder and CTO, talk about the reality of developing an AI-driven product, and explain Clara’s human-in-the-loop system. “People are still there to do some of the most challenging aspects of this work, and that’s exactly what you want to use people for,” says Laska.

Jason Laska and Michael Akilian on Scheduling Bots

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

Tim Hwang on Bots That Cause Chaos

O'Reilly Radar