With the potential of providing'smart' solutions for a variety of challenges, artificial intelligence (AI) and machine learning are getting a lot of attention.

Tata Consultancy Services' (TCS) global report states that 68% of companies use artificial intelligence (AI) for IT functions. However, 70% believe AI's greatest impact by 2020 will be in functions outside of IT such as aspects of customer service and marketing. AI is transforming the media industry, using chatbots to deliver services and optimising media buying spends. In India, customers have been able to experience subtle interventions of AI in their day-to-day functions, such as during interactions with their handheld device or recommendations from e-commerce portals and news feeds on their social media. However, the business ecosystem in India is yet to incorporate the full effectiveness of AI.

Hate crimes unfortunately happen all over the world, such as in America, and according to Google, it is difficult to track since apparently very little official data is collected on such incidents, which makes it harder for journalists to do their jobs on reporting on such issues since there isn't much to go on. However that's something that Google wants to address using machine learning. The company has announced that Google News Lab will be working with ProPublica in launching a new machine learning tool that will help track hate crimes, and in turn will also help journalists find information that they can use for their reporting. According to Google, "The new Index will help make this data easier to understand and visualize. It is one of the first visualisations to use machine learning to generate its content using the Google Natural Language API, which analyses text and extracts information about people, places, and events. In this case, it helps reporters by digging out locations, names and other useful data from the 3,000-plus news reports."

I'm not sure either of these scooped anyone. I think last week I read about an example applied to moss classification, and even there I was unimpressed - it's the obvious mirror to doing random crops for data augmentation, which has been around for years, and I would bet dollars to donuts that'Cutout'/'Random Erasing' have been used before and might be implemented already in libraries because they're so obvious.

Should I bother trying to turn the 3rd one into a paper? I considered it as my architecture/method was somewhat original but there is such an overflow of machine learning/deep learning papers right now that I'm wary of dumping more on the slush pile (and I'm not in academia so there is no pressure on me to publish).

It's 2050 and the world revolves around you. From the contents of your fridge to room temperature -- digital assistants ensure your home runs smoothly. Your screens know your taste and show channels you want to see as you enter the room. Your car is driverless and your favourite barman may just be an android. Predictions for an AI-dominated future are increasingly common, but Antoine Blondeau has experience in reading, and arguably manipulating, the runes -- he helped develop technology that evolved into predictive texting and Apple's Siri.

Google has opened up its Home smart speaker in a big way. Today the search giant has added Bluetooth audio to the device for everyone, after teasing it back at I/O in May and slowly rolling out to select users after that. This is perfect if your app of choice doesn't support Google Cast. You know, like Apple Music, or maybe a legacy piece of audio gear. And here you probably thought that the recent music-related Google Home news would stop with Spotify.

I had been in a years-long relationship with Siri when my affair with the Google Assistant began. Assistant made me laugh with some silly jokes, and we played a cute game she made in the Allo chat app called "Emoji Movie." Soon, Assistant popped up in more places in my life -- whether it was a smartwatch I was reviewing or the Assistant app on my iPhone. Then, for a week, I was tasked with using Assistant exclusively for all the things I would normally ask Siri to do. I thought it would be a fun change, but committing to Assistant required some big adjustments.

Tesla CEO Elon Musk fired off a new and ominous warning on Friday about artificial intelligence, suggesting the emerging technology poses an even greater risk to the world than a nuclear conflagration with North Korea. Musk--a fierce and long time critic of A.I. who once likened it to "summoning the demon" in a horror movie--said in a Twitter post that people should be concerned about the rise of the machines than they are. Reacting to the news that autonomous tech had bested competitive players in an electronic sports competition, Musk posted what appeared to be a photo of a poster bearing the chilling words "In the end, the machines will win." Musk, who is spearheading commercial space travel with his venture SpaceX, is also the founder of OpenAI, a nonprofit that promotes the "safe" development of AI. His stance puts him at odds with much of the tech industry, but echoes remarks of prominent voices like Stephen Hawking--who has also issued dire warnings about machine learning.

Samim Winiger: Welcome to the first episode of Ethical Machines. Pieters: Ethical Machines is a series of con ver sa tions about humans, machines, and ethics. It aims at spark ing a deep er, better-informed debate about the impli ca tions of intel li gent sys tems for soci ety and indi vid u als. Winiger: For our first episode, we invit ed Mark Riedl to come and speak with us. Let's dive into the inter view right now. I'm very pleased that you made it. It's a plea sure to have you on, our first guest. Mark Riedl is an asso ciate pro fes sor at Georgia Tech School of Interactive Computing and Director at the Entertainment Intelligence Lab. You can read more about his very inter est ing biog ra phy on his web site, which we'll link.