Pete Skomoroch and Jon Bruner will be hosting O'Reilly Bot Day October 19, 2016, in San Francisco. Subscribe to the O'Reilly Bots Podcast to learn about advances in conversational user interfaces, artificial intelligence, and messaging that are revolutionizing the way we interact with software. Find us on Stitcher, iTunes, SoundCloud and RSS. 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. We open by asking how bots fit into Sarah's investment thesis and why bot startups are appealing right now (short answer: they sit at the intersection between messaging, AI-based search, and mobile commerce).

Artificial Intelligence refers to computer systems able to perform tasks normally requiring human intelligence. These computer programs are increasingly used in a full range of sectors to help humans do their jobs faster and more efficiently. In this press review, you'll learn how some industries use and develop artificial intelligence to their advantage. Read more: Chatbots and artificial intelligence: where do we stand? Google's DeepMind is learning how to better apply radiotherapy to cancer patients.

Could the armies of lawyers needed to close billion-dollar deals soon be a thing of the past? That's what Invoke Capital, the London-based venture firm run by former Autonomy Plc Chief Executive Officer Mike Lynch, is betting with its latest project financing. Invoke said Wednesday that it's making an investment in Luminance, a U.K. startup using artificial intelligence to process legal documents and automate due diligence in mergers and acquisitions. While the amount of the investment was not disclosed, Lynch said in an interview that the figure was "in the low millions." Luminance says its software can read and understand hundreds of pages of legal documents a minute, enabling lawyers to carry out due diligence far faster than previously.

Dmitry Malioutov can't say much about what he built. As a research scientist at IBM, Malioutov spends part of his time building machine learning systems that solve difficult problems faced by IBM's corporate clients. One such program was meant for a large insurance corporation. It was a challenging assignment, requiring a sophisticated algorithm. When it came time to describe the results to his client, though, there was a wrinkle. "We couldn't explain the model to them because they didn't have the training in machine learning." In fact, it may not have helped even if they were machine learning experts.

This would limit me to predicting changes one district at a time. I'm still in the planning stage of this homework assignment, but before I went too far down the HMM track I wanted to see if I'm barking up the right tree. I want to predict the number of Ebola cases by geographical district, over time. I have a data set which tracks new confirmed Ebola cases across 20 districts, through 100 weeks. This data is in the form of discrete integers representing the number of confirmed new cases.

I am happy to announce that Prelert and Elastic are joining forces. Ever since we started Elastic, our goal has been to allow users to easily find relevant data or insights within large amounts of data. Search is a wonderful way to do it, and the ability to slice, dice, and aggregate the data in an unconstrained way allowed users to feel they are in control of the data, compared to the other way around. But we can take it a step forward, and with Prelert, we just did. Prelert has developed an unsupervised machine learning engine that can plow through large amounts of data and automatically find those insights our users today have been proactively finding using search.

After suffering its first defeat in the Google DeepMind Challenge Match on Sunday, the Go-playing AI AlphaGo has beaten world-class player Lee Se-dol for a fourth time to win the five-game series 4-1 overall. The final game proved to be a close one, with both sides fighting hard and going deep into overtime. AlphaGo is an AI developed by Google-owned British company DeepMind, and had already wrapped up a historic victory on Saturday by becoming the first ever computer program to beat a top-level Go player. The win came after a "bad mistake" made early in the game, according to DeepMind founder Demis Hassabis, leaving AlphaGo "trying hard to claw it back." By winning the final game despite its blip in the fourth, AlphaGo has demonstrated beyond doubt its superiority over one of the world's best Go players, reaffirming a major milestone for artificial intelligence in the process. It was "the most mindblowing game experience we've had so far," said DeepMind founder Demis Hassabis at the post-match press conference, with an "incredibly close and tense finish." Lee said that he felt sorry the match was coming to an end, while expressing how difficult it has been from a psychological perspective.

Tech giants like Facebook, Google, and Baidu know that people aren't filling their devices with apps anymore. Just 35 percent of smartphone users download a single app in an average month, and the average app loses 90 percent of its daily active users within 30 days of release. While it might be fun to slice fruit or slingshot cartoon birds while waiting for the bus, these apps can't offer the frictionless experience users crave. Consumers want a new, on-demand kind of app: one clad in a conversational interface, ready to serve, and capable of complex actions. Want to check your flight status, book an Uber for when you land, and schedule your meetings for that afternoon?

Ben Robinson, chief strategy & marketing officer at banking software firm Temenos, explains how the future of finance will be shaped by artificial technology. Google's DeepMind triumph this year over one of the world's highest ranked champions at Go is a sign: computers with artificial intelligence (AI) are learning how to outperform us. If computers can learn to beat us at a game, why not at things that we can't afford to get wrong – medical diagnostics, risk analysis, legal and investment advice? And what affect over time – say 20 years – will this have on the way a host of services, such as banking, are delivered? "Service will be all about data and algorithms," David Brear, co-founder and CEO at 11:FS recently suggested.