Apple will never admit it, but the arrival of Apple Music on Amazon's Echo speakers is an obvious admission that HomePod isn't getting the job done. Don't get me wrong, HomePod is a fantastic-sounding "smart" speaker, but its premium pricing, limited Siri capabilities, and missing support for third-party streaming services like Spotify and Pandora make it a device only an Apple fanatic would appreciate. Putting Apple Music on Amazon's Echo devices expands Apple's music-streaming service beyond its own smart speaker and potentially gives it access via over 50 million sold devices if The Information's sales numbers are remotely accurate (Amazon doesn't share how many unit sales for Echo devices). Since installing an Echo in my home three years ago (just thinking about how spoiled I am by Alexa is kind of mind-blowing), Spotify (requires premium account), Amazon Music, Pandora, and iHeartRadio have been my go-to music services on the smart speaker and I can almost always find the song I want to hear between the four services. I can't say I've been pining for Apple Music on Echo speakers.
The Innovation Group's annual trend report, Future 100 outlines the trends and changes to watch in 2019. It shows a glimpse of what is to come and what is important across individual sectors for 2019 including culture, tech and innovation, travel, food and drink, brands, beauty, retail, luxury, health, and lifestyle. Lucie Greene, Director of JWT Innovation has outlined some of the tech trends and innovations predicted to be talked about in 2019 So what can we look forward to? Ethical internet: Tech brands need to take a more proactive approach to exploring ethical implications of their platforms and wares, according to tech journalist Kara Swisher in NYT article. In May 2018, Amnesty International, Access Now and other partner organizations launched the Toronto Declaration, which protects the right to equality and non-discrimination in machine learning systems.
On the surface, The Godfather, The Sixth Sense and Little Miss Sunshine appear to have little in common. But even though these films belong to different genres and have very different plots, technically they have the same "emotional arc" - a journey of highs and lows. Using artificial intelligence, we analysed more than 6,000 scripts from the past 80 years and discovered all films fall within six emotional arcs. These include the emotional rise of "rags to riches" films such as The Shawshank Redemption and the rise and fall of "man in a hole" films such as Who Framed Roger Rabbit. But which of these are the most successful, critically and commercially?
Catchy Christmas songs can now be created by a special songwriting AI, taught by studying existing festive tunes. The system came up with catchy jingles with names like'Syllabub Chocolatebell', 'Peaches Twinkleleaves' and'Cocoa Jollyfluff'. Researchers from Made by AI trained a neural network by inputting one hundred Christmas tunes in the form of Musical Instrument Digital Interface (MIDI) files. It then picked out recurring themes, motifs, instruments and rhythms to generate its own hits. Scientists have trained an AI system to write its own catchy Christmas songs by teaching it existing festive tunes.
We've heard from customers that scaling TensorFlow training jobs to multiple nodes and GPUs successfully is hard. TensorFlow has distributed training built-in, but it can be difficult to use. Recently, we made optimizations to TensorFlow and Horovod to help AWS customers scale TensorFlow training jobs to multiple nodes and GPUs. With these improvements, any AWS customer can use an AWS Deep Learning AMI to train ResNet-50 on ImageNet in just under 15 minutes. To achieve this, 32 Amazon EC2 instances, each with 8 GPUs, a total 256 GPUs, were harnessed with TensorFlow. All of the required software and tools for this solution ship with the latest Deep Learning AMIs (DLAMIs), so you can try it out yourself. You can train faster, implement your models faster, and get results faster than ever before. This blog post describes our results and shows you how to try out this easier and faster way to run distributed training with TensorFlow. Figure A. ResNet-50 ImageNet model training with the latest optimized TensorFlow with Horovod on a Deep Learning AMI takes 15 minutes on 256 GPUs.
This post is part of Science of Sci-Fi, Mashable's ongoing series dissecting the science (or lack of science) in our favorite sci-fi movies, TV shows, and books. Not many American nerds these days know about a golden age sci-fi writer called Edmond Hamilton. If they do, it's because of his Star Wars connections: Hamilton was the husband of Leigh Brackett, space opera queen and author of the first draft of The Empire Strikes Back; he also happened to be the first guy to use a "laser sword" anywhere in fiction. But German nerds tend to remember Hamilton for something completely different, and the future may do, too. Because he didn't just invent lightsabers.
In a world full of smart devices, self-driving cars and voice assistants, Shazam is the closest technology comes to actual magic. The software allows you to hold your phone up to a speaker and answer the age-old question, "what is this song and who's it by?" without the humiliation of having to ask the DJ. And in 2018 the answer, most frequently, was "Solo by Clean Bandit". The song, which features US star Demi Lovato, was tagged 9.1 million times. British artists performed five of Shazam's top 10 songs, with Calvin Harris, Dua Lipa and newcomer Tom Walker all making the chart.
Makes me feel sad for the rest. Actually, that's a movie ("The Spy that Loved Me") that Netflix recommends for me since I'm a James Bond junkie and Netflix knows that. In fact, Netflix knows a lot about me as it knows a lot about all of its viewers, which is one reason why Netflix is a Wall Street darling and has rewarded its stockholders very well over the past couple of years (see Figure 1). But Netflix isn't doing anything that other organizations cannot do. To replicate Netflix's business success starts with thinking differently about the role of data and analytics in powering the organization's business.
In his bestselling book, Up the Organization, former Avis president Robert Townsend captured the problem of automation precisely. Writing at a time when the vast paper systems of corporate America were being transferred to computers, he warned that it was important first to make sure that a company's paper systems are actually effective and accurate. "Otherwise," he quipped, "your new computer will just speed up the mess." Today, we are faced with a new wave of optimism about the prospects of what is called artificial intelligence (AI). It is important to parse these words carefully for they will tell you why artificial intelligence as it is currently conceived will very likely "just speed up the mess."
Panoply, the smart cloud data warehouse built for business intelligence, is excited to announce its status as a finalist in Microsoft and Calcalist's Artificial Intelligence and Big Data Startup Competition. In a stiff competition, Microsoft will host representatives from Panoply and the other finalists at its Seattle headquarters. The first and second place winners will be invited by Calcalist to participate in the newspaper's Berlin conference in 2019, where the companies will meet with potential partners and investors. Panoply's CEO and co-Founder Yaniv Leven said, "We're proud to be announced as a finalist in the Artificial Intelligence and Big Data Startup competition. So far, we've been amazed at the quality of the companies participating and we're psyched to be pitching at the finals. We're a team of engineers and fighters, we set lofty goals and conquer massive challenges to prove how bad our innovative desire is."