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artificial intelligence

O'Reilly Bots Podcast

Bots

bots

Technical

With the rise of mobile phones equipped with GPS, we're meeting many more data scientists at start-ups and large companies who specialize in spatio-temporal pattern recognition. Analyzing “moving dots” requires specialized tools and techniques. A few months ago, I sat down with Rajiv Maheswaran founder and CEO of Second Spectrum, a company that applies analytics to sports tracking data. Maheswaran talks about the tools and techniques required to analyze new kinds of sports data.

For more on our interview, visit O'Reilly Radar: http://oreil.ly/1t7EcOQ

The science of moving dots

In this episode, Ben Lorica chats with Jay Kreps, a highly regarded data engineer and former technical lead for Online Data Infrastructure at LinkedIn, and most recently CEO/co-founder of Confluent, about Apache Kafka, data integration, event data, and the Internet of Things.

Building Apache Kafka From Scratch

O'Reilly Ben Lorica chats with Ion Stoica, UC Berkeley Professor and Databricks CEO, about the rise of Apache Spark and Apache Mesos.

Apache Spark's Journey From Academia To Industry

O’Reilly’s big data guru Ben Lorica sits down with prominent data scientist DJ Patil to talk about his new ebook (written with Hilary Mason) and other topics in data science and big data.

A Brief Look At Data Science's Past And Future

In this episode of the O’Reilly Data Show, I spoke with Yishay Carmiel, president of Spoken Labs. As voice becomes a common user interface, the need for accurate and intelligent speech technologies has grown. And although computer vision is a common entry point for deep learning, some of the most interesting commercial applications of deep neural networks are in speech recognition. Carmiel has spent several years building commercial speech applications, and along the way he has witnessed (and helped architect) massive improvements in speech technologies.

Commercial Speech Recognition Systems in the Age of Big Data and Deep Learning

In this episode of the O’Reilly Data Show, I spoke withJana Eggers, CEO of Nara Logics. Eggers’ involvement with AI dates back to her days as a researcher at the Los Alamos National Laboratory. Most recently she has been helping companies across many industries adopt AI technologies as a way to enable a range of intelligent data applications.

Enabling Enterprise Adoption of AI Technologies

We’re launching a new pop-up podcast about bots. In this first episode of the O’Reilly Bots Podcast, I’m joined by Peter Skomoroch to talk background: why everyone is suddenly interested in bots and what they promise to do, and what sorts of applications are beginning to emerge.

What are Bots? Here's the Background.

In this episode of the O’Reilly Data Show, I spoke with Adam Marcus, co-founder and CTO of B12, a startup focused on building human-in-the-loop intelligent applications. We talked about the open source platform Orchestra,for coordinating human-in-the-loop projects; the current wave of human-assisted AI applications; best practices for reviewing and scoring experts; and flash teams.

Building Human-Assisted AI Applications

Greylock Partners investor Sarah Guo joins us for episode two of our new pop-up podcast on bots and conversational interfaces. She’s written insightfully on bots and has worked on several investments in bot startups.

Sarah Guo on the Case for Bots

In episode four of the O’Reilly Bots podcast, Pete Skomoroch and I speak with Cathy Pearl, director of user experience at Sensely, and author of the forthcoming O’Reilly book “Designing Voice User Interfaces.” She’s also a speaker at O’Reilly’s upcoming Bot Day on October 19, 2016, in San Francisco.

Cathy Pearl on Voice User Interfaces for Bots

In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I recap O’Reilly Bot Day, held October 19, 2016, in San Francisco. The event gave us a good picture of what the bot community—and bot landscape—looks like, and the diverse group of attendees conveyed a strong sense of optimism about bots. Slides from Bot Day presentations are available here.

We then speak with Shivon Zilis, partner at Bloomberg Beta, who has written extensively about artificial intelligence and its impact on a variety of industries. She wrote influential surveys of what she calls machine intelligence in 2014 and 2015, and she’s planning to publish her 2016 update at the end of October.

Shivon Zilis on the Machine Intelligence Landscape, and Bot Day Wrap-Up

In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I talk with Richard Socher, chief scientist at Salesforce.  He was previously the founder and CEO of MetaMind, a deep learning startup that Salesforce acquired in 2016.  Socher also teaches the “Deep Learning for Natural Language Processing” course at Stanford University. Our conversation focuses on where deep learning and NLP are headed, and interesting current and near-future applications.

Richard Socher on the Future of Deep Learning

In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I look back at 2016, a big year for bots that saw important developments in platforms, tools, and underlying AI.

2016 Bots Year in Review

In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I speak with Brad Abrams, group product manager of Google Assistant, the company’s new AI-driven bot that lives in many different contexts, including the Pixel phone, the Allo messaging app, and the Google Home voice-controlled speaker.

Brad Abrams on Google Assistant

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

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.