When Apple launched the HomePod in February of this year, early users squawked in equal measures about its unbelievable audio capabilities and the fact that it was a WiFi-connected smart speaker that didn't "talk" to other speakers. Its limits, not just around stereo pairing and multi-room audio but also around some basic voice commands, established it early on as a $349 product that only true Apple fans or audiophiles should consider. But Apple promised then that key updates were in the works for HomePod, that super impressive sound machine built into a body like a soft roll of toilet paper. Now, a week ahead of its giant annual software conference, those key updates have come. HomePod is still one of the more expensive smart speakers in its class, and Apple doesn't plan to offer any kind of bundle deal on the hardware.

Maeve Millay (Thandie Newton) has ventured into ShogunWorld this Season 2 of HBO's "Westworld," and being in the Japanese theme park is quite an eye-opener for the host. "There's a parallel experience between what she went through and what's been going on with these other AIs," Newton told The Hollywood Reporter about Maeve's journey. "There's a betrayal, that not only is her story her story, but countless others in the park." However, her being there is helping other hosts gain more independence. "We're seeing how these characters are also breaking free from their loops," Newton continued.

A number of recent articles discuss Hollywood's concern over the recent wave of multi-million dollar Netflix deals with stars like Shonda Rhimes, Ryan Murphy or the Obamas to produce content for the platform. In contrast to the dynamism of Netflix, the traditional movie industry is hamstrung by a business model that depends heavily on sequels, prequels and remakes of popular movies from several decades ago and where success seemingly depends on random or unknown factors. The simple truth is that right now, thanks to several global hits and a steady revenue stream from its 125 million subscribers, Netflix can afford to take risks and produce any project it wants and hire the talent required to make it a success. The company's valuation, at $164 billion, has grown more than 70% since January, overtaking Disney as the world's most valuable media company, which is worth $152 billion, and with some key differences: Netflix employs fewer than 5,000 people, compared to Disney's almost 200,000, and also seems to have found the secret of permanent success for the vast majority of its productions. In October 2015, just days before Netflix entered the Spanish market, I wrote a position paper (in Spanish) predicting "a first year of moderate position taking, followed by intense expansion and progressive growth as it increases its product offering thanks to the recovery of the contracts of its best-known series and the development of its own productions." It now appears my initial optimism has been surpassed, due fundamentally to having introduced into the analysis a fundamental factor: the supremacy of models based on data analytics.

Pandora appears to be challenging Apple Music with the launch of its new Premium Family plan. The music streaming and automated music recommendation internet radio service introduced a new plan on Monday, and it is one that directly rivals Apple Music's plan in terms of cost and the number of users it allows to share the service. The Pandora Premium Family plan is a $14.99/month subscription service ($164.89 As what its name implies, the service is intended for families. Hence, family members can enjoy full access to Pandora Premium offers if they are subscribed to this plan.

I am currently going into my 2nd semester of my junior year, majoring in mathematical science. Last semester I took numerical linear algebra, and while difficult, I found it very interesting. We didn't do any machine learning but did talk about it a lot and I got to know python quite well. Since this class I have been juggling the idea of possibly going to grad school for machine learning/AI. I need some advice on what I should do.

We propose an adversarial learning approach to the generation of multi-turn dialogue responses. Our proposed framework, hredGAN, is based on conditional generative adversarial networks (GANs). The GAN's generator is a modified hierarchical recurrent encoder-decoder network (HRED) and the discriminator is a word-level bidirectional RNN that shares context and word embedding with the generator. During inference, noise samples conditioned on the dialogue history are used to perturb the generator's latent space to generate several possible responses. The final response is the one ranked best by the discriminator. The hredGAN shows major advantages over existing methods: (1) it generalizes better than networks trained using only the log-likelihood criterion, and (2) it generates longer, more informative and more diverse responses with high utterance and topic relevance even with limited training data. This superiority is demonstrated on the Movie triples and Ubuntu dialogue datasets in terms of perplexity, BLEU, ROUGE and Distinct n-gram scores.

As making money with drone photography gets tougher, pilots are flying into new uncharted territories. What goes up must come down. This rule applies to both flying drones, and now unfortunately, to making a buck off them. With more affordable models entering the mass market, any enthusiast with a few thousand ringgit to spare can try his hand at aerial photography. While the lower barrier to entry may be good news for newbies, the increased competition is driving down remuneration.

Artificial Intelligence (AI) is basically intelligence demonstrated outside the human mind, essentially by machines. Machine Learning (ML) is a way of achieving AI and can be defined as the ability of computers to learn using statistical techniques without being specially programmed. Both the terms are symbiotic but also mutually exclusive in their own right with different definitions. We are not unfamiliar with the concept of AI, which has been time and again explored and exploited by popular media. Movies have gone as far as to show us a world dominated by AI-enabled machines and robots, and these movies, more often than not, have ended up portraying negative repercussions of an AI-enabled society. This has more or less shaped up the general feeling revolving around AI in the society.

DURHAM – Google Brain's Magenta project, which is exploring the creative potential of machine learning (ML) and artificial intelligence (AI), has developed considerably since Google announced it at Moogfest three years ago. And, Magenta makes many of its ongoing developments available publicly online and collects feedback from musicians, artists and other users to advance the project. Adam Roberts, senior software engineer and ML researcher discussed the nuts and bolts of Magenta at Moogfest over the weekend. Roberts, who did undergraduate work at the University of North Carolina at Chapel Hill, earned his PhD at Berkley, California, where he studied machine learning applied to genomics. Google is developing both hardware and software to explore the potential of machine learning via its Magenta research, Roberts said.

We offer an opportunity for companies and individuals working on interesting problems in AI to introduce their work to the community through the IAMA. Please contact /u/dejormo for more information. We would love to hear from you!