Apple is once again looking to Asia to turbocharge its research and development process, this time to improve its artificial intelligence efforts. In an interview with Nikkei Asian Review, CEO Tim Cook said the future of the iPhone is AI, which will be supported by its new research and development center that will open by the end of the year in Yokohama, Japan. Cook seemed to suggest that AI in the iPhone would move beyond Siri and would actually help increase your battery life through resource management. It would also recommend music more skillfully, and perform other background tasks. As is typical with Apple, Cook stayed tight-lipped on specifics but said the Yokohama team will deal with "deep engineering" and be quite different from its planned R&D effort in China.

MediaGamma has announced the launch of a new Audience Prediction product, which is set to make a major impact on the ad tech market. By applying deep learning to unique data sets, coupled with MediaGamma's unique AI Decision Support Engine, the product is set to provide players in the ecosystem with over 90% certainty about a user's interests and demographic profile. The new product will help people to navigate uncertainty to make better decisions, and a major telecoms company has already signed up. The Audience Prediction product is the latest in a broad portfolio of products created by MediaGamma (http://www.mediagamma.com/), The start-up's world-renown team of data scientists deliver bespoke real time, prediction-based data science solutions focusing on online user behaviour.

Consider a personal assistant bot, a machine or application that you could ask to organise a meeting or arrange bookings just as you would a live, human assistant. As artificial intelligence (AI) becomes more prevalent and approaches advance, such a scenario is becoming increasingly realistic. This is according to DataProphet managing director, Frans Cronje who highlights that there will be a number of exciting developments and new approaches to AI in the short- and long-term future as the application matures and continues being explored. Machine learning extends AI "A subset of AI, machine learning has driven the majority of advances in recent years, many of which are improvements on or augmentations to existing processes." Cronje explains that there are multiple cases where improved machine learning models have extended the capability of AI.

Over the past few years AI has exploded, and especially since 2015. Much of that has to do with the wide availability of GPUs that make parallel processing ever faster, cheaper, and more powerful. It also has to do with the simultaneous one-two punch of practically infinite storage and a flood of data of every stripe (that whole Big Data movement) – images, text, transactions, mapping data, you name it.

Most traditional data management products aren't equipped to handle the increasingly complex and diverse information that is flowing into the corporate network these days. As a result, organizations are turning to new solutions like Neo4j. The widely used graph store, which sets itself apart by providing the ability to easily log the relationships among records, received a major update last week that promises to streamline large-scale analytics initiatives. The biggest change is in the way that Neo4j synchronizes queries and information across the servers on which it's deployed. Neo Technology Inc., the company behind the database, replaced the nearly 20-year-old PAXOS algorithm that was used for the task before with a much newer alternative called RAFT.

More recently, research has suggested that quantum effects could offer similar advantages for the emerging field of quantum machine learning (a subfield of artificial intelligence), leading to more intelligent machines that learn quickly and efficiently by interacting with their environments. In a new study published in Physical Review Letters, Vedran Dunjko and coauthors have added to this research, showing that quantum effects can likely offer significant benefits to machine learning. "The progress in machine learning critically relies on processing power," Dunjko, a physicist at the University of Innsbruck in Austria, told Phys.org. "Moreover, the type of underlying information processing that many aspects of machine learning rely upon is particularly amenable to quantum enhancements. As quantum technologies emerge, quantum machine learning will play an instrumental role in our society--including deepening our understanding of climate change, assisting in the development of new medicine and therapies, and also in settings relying on learning through interaction, which is vital in automated cars and smart factories."

Driven by a declining population, a trend for developing robotic babies has emerged in Japan as a means of encouraging couples to become "parents". The approaches taken vary widely and are driven by different philosophical approaches that also beg a number of questions, not least whether these robo-tots will achieve the aim of their creators. To understand all of this it is worth exploring the reasons behind the need to promote population growth in Japan. The issue stems from the disproportionate number of older people. Predictions from the UN suggest that by 2050 there will be about double the number of people living in Japan in the 70-plus age range compared to those aged 15-30.

When it comes to neural network design, the trend in the past few years has pointed in one direction: deeper. Whereas the state of the art only a few years ago consisted of networks which were roughly twelve layers deep, it is now not surprising to come across networks which are hundreds of layers deep. This move hasn't just consisted of greater depth for depths sake. For many applications, the most prominent of which being object classification, the deeper the neural network, the better the performance. That is, provided they can be properly trained!

Anesthesiologists' jobs look safer than radiologists' jobs. In H. G. Wells's classic The War of the Worlds, the narrator pauses a moment to rue the fact that he didn't react sooner to the arrival of an "intelligence greater than man's"--in his case, Martians landing on earth. Comparing himself to a comfortable dodo in its nest, he imagined those ill-fated birds also dithering as hungry sailors invaded their island: "We will peck them to death tomorrow, my dear." As intelligent technologies take over more and more of the decision-making territory once occupied by humans, are you taking any action? Are you sufficiently aware of the signs that you should?

Apple Inc. hired a prominent artificial intelligence researcher from Carnegie Mellon University as it seeks to regain lost ground against competitors such as Google, Microsoft Corp. and Amazon.com He posted a link to an Apple job application page seeking machine learning specialists. Apple is seeking scientists with "experience in Deep Learning, Computer Vision, Machine Learning, Reinforcement Learning, Optimization, and/or Data Mining," it said in the job listing. Machine learning has gained mounting importance for tech companies to improve their research and enable virtual assistants such as Siri to better anticipate and predict users' needs. Siri is competing with the Google Assistant, Microsoft's Cortana and Amazon's Alexa to become the virtual assistant of choice and the access point for users seeking online services.