O'Reilly Bots Podcast - O'Reilly Media Podcast

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

Chris Messina on Facebook as a utility

The 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.”

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.

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

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