Data science and machine learning have long been interests of mine, but now that I'm working on Fuzzy.io I need to keep on top of all the news in both fields. My preferred way to do this is through listening to podcasts. I've listened to a bunch of machine learning and data science podcasts in the last few months, so I thought I'd share my favorites: Every other week, they release a 10–15 minute episode where hosts, Kyle and Linda Polich give a short primer on topics like k-means clustering, natural language processing and decision tree learning, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings.

What happens when you tell two smart computers to talk to each other in secret and task another AI with breaking that conversation? You get one of the coolest experiments in cryptography I've seen in a while. In short, Google Brain researchers have discovered that the AI, when properly tasked, create oddly inhuman cryptographic schemes and that they're better at encrypting than decrypting. The paper, "Learning to protect communications with adversarial neural cryptography," is available here. The rules of the task were simple.

Today, Google Cloud chief Diane Greene announced the company's new push in machine learning and artificial intelligence. There's now a new group in Greene's division that will unify some of the disparate teams that had previously been doing machine learning work across Google's cloud. Two women will take charge of the new team: Fei-Fei Li, who was director of AI at Stanford, and Jia Li, who was previously head of research at Snap, Inc. As Business Insider notes, Jia Li was one of the minds behind the Snapchat feature that lets you attach emoji to real-world objects in your snaps. The news came at the top of a slew of announcements about the product roadmap for Google's cloud services and how they're expanding their use of machine learning, a critical technique for training large-scale AI networks to teach and improve themselves over time. The announcements were all aimed at showing how Google's cloud services include more than just renting time on a server -- that it can provide services to its enterprise customers that are based on its machine learning algorithms.

Slack may have unleashed a new demand among the working world to have better tools to chat to each other about their projects and more, but it's also unleashed something else: a torrent of competing products from other tech firms that sell to the enterprise. Today comes the latest in that trend: BroadSoft, a company known for its cloud-based unified communications services, is launching Team-One, a platform for people to chat to each other, bringing in links and data from other projects, and more. Team-One is making its debut today, but it's built on a product that existed before. Earlier this year, BroadSoft acquired a Slack competitor called Intellinote, which it has now integrated with its bigger platform, including its calling and videoconferencing products, adding in new features such as artificial intelligence and bots to help you source data to get your work done. Apart from being a reflection of just how popular collaboration products have become among businesses, the launch of Team-One also another sign of how Slack's early success in this market is getting attacked by competitors from many angles. The startup has seen some of its fast growth slow down, which presents an opportunity for some of those rivals with established customer bases to move in, or for Slack to demonstrate that it definitely is better than the rest.

A month ago, I interview Gary Illyes at Marketing Land and covered this bit at Search Engine Land but it got lost. In short, Gary Illyes from Google said that machine learning and artificial intelligence within the search algorithm can be used to make new ranking signals. He said that Google can use it to say if you combine ranking signal A with ranking signal B, we can make a new ranking signal C that helps improve quality of the search results. Gary Illyes: They are typically used for coming up with new signals and signal aggregations. So basically, let's say that this is a random example and not know if this is real, but let's say that I would want to see if combining PageRank with Panda and whatever else, I don't know, token frequency.

Weather conditions this week will impact the progress of the search for missing Malaysia Airlines Flight MH370, Australian Transport Safety Bureau (ATSB), said Wednesday. The underwater operation to locate the missing plane had already been pushed to end in January 2017 in accordance with the weather forecast. ATSB, which is leading the search for the Boeing 777-200, said in its operational update that weather conditions are unsuitable for both Autonomous Underwater Vehicle (AUV) and Remotely Operated Vehicle (ROV) operations periodically during the week. This week, search vessel Fugro Equator continued underwater search operations in the north of the search area, which is in a remote part of the southern Indian Ocean, using AUV. During the past week, Fugro Equator has undertaken five missions, each one taking an average of 21 hours.

Google is letting users peek into some of its most experimental artificial intelligence projects. The company unveiled a new website Tuesday called A.I. Experiments that showcases Google's artificial intelligence research through web apps that anyone can test out. The projects include a game that guesses what you're drawing, a camera app that recognizes objects you put in front of it and a music app that plays "duets" with you. SEE ALSO: 7 reasons Google's Assistant stomps Siri Google says the goal of the site is to make some of its machine learning technology more accessible to people who are interested in artificial intelligence but don't have the technical know-how to parse academic papers, where this type of research is typically published. Instead, the site offers hands-on demos that allow you to interact with projects created by Google researchers that show off their AI technology. A project called "Quick, Draw!" for example, is a game that tasks you with drawing an object -- like a ceiling fan or flower or bicycle -- in a limited amount of time while the app tries to guess what you're drawing.

Her name is Alice and she's designed to help you decide what clothes and accessories suit you best. At the recent IoT Solutions World Congress in Barcelona, she was busy making recommendations about men's suits and women's party dresses via Telegram, Facebook Messenger, Skype, SMS, and webchat. Bismart, the Catalan company behind the digital assistant, is a Microsoft Worldwide Partner with a background in big data, machine learning, and artificial intelligence applied to marketing. With 50 employees, it expects to close the year with a turnover of €3m ($3.32m), 50 percent up on 2015. "We've just opened a new office in Singapore, where we anticipate a turnover of up to €500,000 in the first year," says Albert Isern, CEO of the company.

China may be gearing up to pull ahead of the U.S. in the race to overhaul road delivery with fleets of self-driving long-haul trucks. A number of companies are developing automation technologies that promise to lower costs, reduce accidents, and improve overall efficiency for the trucking industry by allowing drivers to make longer trips that include periods of rest. In Europe and the U.S., Volvo, Daimler, Uber, and others are testing trucks capable of driving themselves under expert supervision. But several Chinese-based companies are working on automated trucks, and lenient regulations as well as a desire to overhaul the country's chaotic trucking industry may smooth the way for the technology's introduction. This could provide a handy edge in the race to develop a lucrative new way of hauling goods.

Google's new slew of AI tools includes a kind of game called "Quick, Draw!" that can guess what you're doodling. It's impressive just how good the tool is--though some of its misses would be obvious to the human eye. "This is a game built with machine learning," says a tutorial site. "You draw, and a neural network tries to guess what you're drawing. But the more you play with it, the more it will learn. It's just one example of how you can use machine learning in fun ways."