O'Reilly Bots Podcast - O'Reilly Media Podcast

O'Reilly Media
  • 4.8 (6)
  • Business

Exploring bots, conversational interfaces, AI, and messaging.

  1. 05/25/2017

    Jason Laska and Michael Akilian on using AI to schedule meetings

    The O’Reilly Bots Podcast: The technical and social dynamics of solving scheduling problems. 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. Discussion points: How both the Clara bot and its users deal with the often-complex social dynamics of scheduling, which is “fundamentally a negotiation,” says Akilian. How Clara parses and evaluates dates and times Email vs. messaging as a platform for AI bots Other Links Jerry Chen’s article The New Moats: Why Systems of Intelligence are the Next Defensible Business Model Microsoft’s paper on developing calendar help (PDF) Google’s multilingual neural machine translation system Facebook’s Poncho bot for weather forecasts

  2. 05/11/2017

    Chris Messina on Facebook as a utility

    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.

  3. 04/13/2017

    Tom Hadfield on bots in the enterprise

    Messaging as the operating system for the enterprise. 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. Hadfield argues that messaging and bots are the latest in a long evolution of communications technologies that have revolutionized the workplace—from the telegraph through e-mail—and that they are about to become commonplace at very large firms. There, they’ll do everything from monitoring customer feedback to giving employees access to their HR records. “Messaging can be the operating system for the enterprise,” says Hadfield. Links: Botness Enterprise, the conference that Hadfield hosted a few weeks ago The Botness UI Primitives survey, which I wrote along with other members of the Botness steering committee. It aims to collect ecosystem preferences on user interface affordances so that platform managers can standardize their offerings.

  4. 04/03/2017

    Prabhat on deep learning for science

    The O’Reilly Bots Podcast: Solutions from big data sets. 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 talks about his work at the the National Energy Research Scientific Computing Center (NERSC), including a project that aims to locate and quantify extreme weather events. He explains how this moves climate data analysis from a focus on core statistics—especially the change in the average mean temperature of the Earth in any given year—to analyzing the impact of extreme events.  He’s also working on the Celeste project, which uses telescope data to create a unified catalog of all objects in the visible universe. Looking ahead, Prabhat sees broad applications for deep learning in scientific research beyond climate science—especially in astronomy, cosmology, neuroscience, material science, and physics. Links: Prabhat’s new O’Reilly article, "A look at deep learning for science" Prabhat’s 2015 O’Reilly article "Big science problems, big data solutions" Prabhat’s presentation at Strata + Hadoop World 2016

  5. 03/09/2017

    Tom Coates on conversational devices

    The O’Reilly Bots Podcast: Conversational interfaces for the Internet of Things. 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. Coates explains how Thington operates in a way analogous to social media; in fact, he calls it “a Twitter for devices.” Just as people engage with each other in a commons, devices chat with each other in Thington’s messaging commons. He also discusses the value of human-readable output and the challenges involved in writing human-understandable scripts. Other links: Coates’ blog post “The Shape of Things,” an overview of how connected devices will communicate with humans Google Translate’s interlingua The O’Reilly Artificial Intelligence conference, June 27-29, 2017, in New York

  6. 02/24/2017

    Tim Hwang on bots that cause chaos

    The O’Reilly Bots Podcast: Automating “psyops” with AI-driven 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. Until recently, the psychological operations (psyops) conducted by governments and political organizations were mostly analog: dropping leaflets from airplanes, blasting radio messages across frontiers, planting stories with journalists, and dragging loudspeakers through city streets. Now, like some other forms of publishing, the practice of psyops is contemplating an online, AI-driven future in which swarms of carefully targeted bots disseminate information instantly. Compared to traditional psyops, AI-driven bots are highly scalable, offer sophisticated targeting capabilities, and are cheap to deploy—accessible to one-person organizations as well as great-power governments. Hwang is the author, with Lea Rosen, of “Harder, Better, Faster, Stronger: International Law and the Future of Online PsyOps (PDF),” published recently by the Oxford Internet Institute. He outlines a handful of conceptual “future scenarios” in which hostile actors might use bots to sow chaos—for instance, to find people who might be open to radicalization, or to misdirect crowds of bystanders during terrorist attacks. Hwang says existing legal frameworks aren’t sufficient to manage these threats, but we talk about three possible ways to address them: Governments come together to form an international body that brings transparency to the field by cataloging attacks and publicizing methods (a parallel to the INTERPOL approach for policing international crime) Governments pressure social media platforms to regulate and stop hostile psyops campaigns A social approach that emphasizes “media literacy” among the public Other Links: Harder, Better, Faster, Stronger: International Law and the Future of Online PsyOps—Tim Hwang's recent talk at Oxford on the topic of his new paper Bots spread misinformation during the Columbian Chemicals explosion hoax in 2014 The so-called “50 Cent Army,” which the Chinese government uses to discourage political activity O’Reilly’s Artificial Intelligence Conference, June 26-29, 2017

  7. 02/16/2017

    Amir Shevat on workplace communication

    In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I speak with Amir Shevat, head of developer relations at Slack and the author of the forthcoming O’Reilly book Designing Bots: Creating Conversational Experiences.

  8. 01/26/2017

    Chris Messina on conversational commerce

    The O’Reilly Bots Podcast: The 2017 bot outlook with one of the field’s early adopters. In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I speak with Chris Messina, bot evangelist, creator of the hashtag, and, until recently, developer experience lead at Uber. We talk about the origins of MessinaBot, ruminate on the need for bots that truly exploit their medium rather than imitating older apps, and take a look at what’s ahead for bots in 2017. Discussion points: Traditional résumés provide the same comprehensive overview regardless of who’s reading; MessinaBot customizes the experience of learning about its creator, and draws together content that’s ordinarily spread across many channels. “Conversational commerce,” the messaging trend that Messina named in 2015 Messina’s work with Esther Crawford, who launched her résumé bot EstherBot in 2016 The state of bot skeuomorphism Product Hunt’s role in the popular emergence of bots For small businesses, setting up a bot interface could be easier than creating a traditional website. Until recently, Path’s Talk app even had a call center to route messages to businesses that didn’t have messaging capabilities.

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Exploring bots, conversational interfaces, AI, and messaging.

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