Podcast
O'Reilly Bots Podcast - O'Reilly Media Podcast
Hosted by O'Reilly Media · ENGLISH
Exploring bots, conversational interfaces, AI, and messaging.
25episodes
Episodes
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Jason Laska and Michael Akilian on using AI to schedule meetings
May 25, 201700:44:40Tap to summarizeThe 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
Transcribe →Chris Messina on Facebook as a utility
May 11, 201701:07:40Tap to summarizeThe O’Reilly Bots Podcast: The social impact of Facebook.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.When it opened to users in 2004, Facebook’s essential value was exclusion—it was available at first only to Harvard students, then to students at a handful of top-tier universities. Since then, it has grown to host two billion monthly active users, and along the way has come to feel like a utility—a simple reality of digital existence. Messina, an independent bot enthusiast and social media observer (and creator of the hashtag) calls Facebook “a state of mind, a belief system. It is a way of participating in the common discourse that reinforces your own perceptions.” Discussion points: Augmented Reality (AR) and Virtual Reality (VR) dominated the discussion (especially the keynotes) at F8. In addition to reviewing the new product/project announcements, we talk about what is being done to cultivate the skills that the next generation of AR/VR content creators will need. In an age of fake news, we discuss Facebook’s responsibilities. Despite some calls for Facebook to become a gatekeeper, the company seems to recognize that doing so could alienate a large portion of its user base—and interfere with the safe-harbor protection that it enjoys as an unedited platform. We compare Facebook and Snapchat, and note that Snapchat will face mounting pressure to open its platform to developers. The new features announced for Facebook Messenger, including the Discover tab and parametric QR codes, provide some interesting avenues for bot discovery, one of the most formidable challenges that bot developers face. How much natural language understanding do bots really need? There are plenty of existing processes that can be valuably brought to messaging platforms without really engaging with NLU at all. As Messina says, “the best NLU is still done by humans.”
Transcribe →Tom Hadfield on bots in the enterprise
Apr 13, 201700:36:22Tap to summarizeMessaging 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.
Transcribe →Prabhat on deep learning for science
Apr 3, 201700:26:18Tap to summarizeThe 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
Transcribe →Tom Coates on conversational devices
Mar 9, 201700:51:59Tap to summarizeThe 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
Transcribe →Tim Hwang on bots that cause chaos
Feb 24, 201700:41:57Tap to summarizeThe 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
Transcribe →Amir Shevat on workplace communication
Feb 16, 201700:49:02Tap to summarizeThe O’Reilly Bots Podcast: Slack’s head of developer relations talks about what bots can bring to Slack channels.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.We often talk about consumer bots on the podcast, but workplace bots are arguably a more attractive market for the time being. Companies are able to drive adoption by fiat (“all employees are now required to file TPS reports through the bot”), and bots can draw on large volumes of well-linked internal data in ERP systems, calendars, and so on. Slack is principally a workplace messaging platform, so we kick off our conversation with Shevat by talking about design considerations for workplace bots and bots that can work with groups of human users. We also cover the recent release of Slack Enterprise Grid, a new Slack offering for very large companies with up to half a million users. Discussion points: Developing bots for very large installations How bot developers can test bots for the enterprise Slack’s January release of threaded conversations and its impact on bot development (see Shevat’s VentureBeat post “Building better bots with threads” for more details) The state of conversational AI: Shevat describes two types of conversations—“topical” (for which a great deal of AI is necessary) and “task-led” (which needs less AI) Other Links: Eric Stromberg’s “Startup Idea Matrix,” which outlines markets and ways to create new products for them The O’Reilly Artificial Intelligence conference, June 27-29, 2017, in New York Videos of Siberian Huskies saying “I love you,” the inspiration for Shevat’s choice of an animal for the front cover of his book
Transcribe →Chris Messina on conversational commerce
Jan 26, 201700:53:59Tap to summarizeThe 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.
Transcribe →Brad Abrams on Google Assistant
Jan 12, 201700:46:40Tap to summarizeThe O’Reilly Bots Podcast: A universal bot for messaging, mobile voice, and the home.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.Discussion points: “Actions,” Google’s API for Assistant plug-ins. These are available for Google Home now, and will be rolled out for other instances of Assistant later. The relationship between Assistant and Google’s Pixel phone. Google’s plans for the recently acquired API.ai, and where it fits in with Assistant. Google’s WaveNet technology, a text-to-voice engine that uses neural networks. Google’s voice user interface design guidelines, and how Google uses different voices in different settings.
Transcribe →2016 Bots year in review
Dec 29, 201600:51:35Tap to summarizeThe O’Reilly Bots Podcast: Recapping a revolutionary year in AI and bots, and looking ahead to 2017.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.We recap some of the biggest bot-related stories of 2016, including: People want to use messaging interfaces! Facebook Messenger, Kik, Slack, and Microsoft all made it easier for developers to create bots The field of conversational interfaces exploded Google’s open source TensorFlow library was a major accelerant for the field of deep learning Developments in workflow bots from Smooch to PagerDuty The emergence of god bots—Amazon Alexa, Google Assistant, Facebook M—and what they mean for bot discovery Microsoft’s new Zo bot, which uses “guide rails” to steer conversations away from some of the controversies that plagued Microsoft’s Tay bot The December introduction of Microsoft Teams We also present our predictions for 2017. Pete foresees progress in more seamless payment methods, ways to monetize bots, discovery and installation, and bot-to-bot communication. I expect further development in the micro-features of bots and improvements in NLU. I also think we’ll see more large organizations deploying their first bots next year.
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