SpaceX and Tesla CEO Elon Musk is backing a brain-computer interface venture called Neuralink, according to The Wall Street Journal. The company, which is still in the earliest stages of existence and has no public presence whatsoever, is centered on creating devices that can be implanted in the human brain, with the eventual purpose of helping human beings merge with software and keep pace with advancements in artificial intelligence. These enhancements could improve memory or allow for more direct interfacing with computing devices. Musk has hinted at the existence of Neuralink a few times over the last six months or so. More recently, Musk told a crowd in Dubai, "Over time I think we will probably see a closer merger of biological intelligence and digital intelligence."

The marketing industry is rapidly evolving. It's at a new phase where Big Data and AI (Artificial Intelligence) are driving strategy development and decision making. Because conventional analytics scale at a gradual pace, marketers are beginning to utilise AI to analyse the large volume of unstructured data to improve marketing research, forecasting accuracy and campaign experiences. A research of CMOs from the US, UK, and China from companies with more than $500 million in revenue revealed that around two thirds of these think Artificial Intelligence will play a significant role in their future marketing operations. But only a third claimed to have good knowledge of how it is actually implemented.

Interest in machine learning may be at an all-time high. Per Google Trends, people are searching for machine learning nearly five times as often as five years ago. And at the University of California San Diego (UCSD), where I'm presently a PhD candidate, we had over 300 students enrolled in both our graduate-level recommender systems and neural networks courses. Much of this attention is warranted. Breakthroughs in computer vision, speech recognition, and, more generally, pattern recognition in large data sets, have given machine learning substantial power to impact industry, society, and other academic disciplines.

Global AI investment fever has hit Russia, with a recently launched $100 million fund making its inaugural investments. Announced in late 2016, the fund is backed by Larnabel VC, the venture arm of the Gutseriev family, one of the richest in Russia, and VP Capital, the investment vehicle of Belarussian businessman Viktor Prokopenya. The joint fund is sector-agnostic. "We are interested in a wide range of companies that apply AI technologies in interesting, unique, and impactful ways. We don't restrict ourselves to specific industries or sectors. We are interested in every application of artificial intelligence, from fintech to entertainment, to education, and beyond," Prokopenya told East-West Digital News.

Feel free to forward this email or share it with your network. How Google used artificial intelligence to transform Google Translate, one of its more popular services and how machine learning is poised to reinvent computing itself. Zuckerberg's dead-eyed delivery during a two-minute humblebrag about his artificial intelligence tool Jarvis makes you question who the real robot is. DEEPMIND HAS SURPASSED the human mind on the Go board. Watson has crushed America's trivia gods on Jeopardy.

According to The Wall Street Journal, Musk has played an active role in launching the new a company called Neuralink, which seeks to create devices that can be implanted in the human brain. The neuroscience startup is still in its infancy but aims to create cranial computers for treating diseases and, eventually, help humans merge with software, enabling mortals to keep pace with advancements in artificial intelligence. Musk is on record as saying that AI poses a great threat to humanity. The billionaire inventor recently told Vanity Fair that he believes the technology for "a meaningful partial-brain interface" is only "roughly four or five years away." The company plans to present a working prototype which will likely be a brain implant to help treat diseases like epilepsy, Parkinson's or depression.

Possessing over 20 years of experience in IT, Al Mansoori provides overall operational and strategic leadership to ADSIC and orchestrates the development of Abu Dhabi's e-government programme.

The relationship between humans and robots is a tricky thing. If the latter looks too much like the former, but is still clearly a machine, people think it's creepy, even repulsive--a feeling that's become known as the "uncanny valley." Or, as is sometimes the case, the human, with "Star Wars" or "The Jetsons" as his or her reference points, is disappointed by all the things the robot can't yet do. Then, there is the matter of job insecurity--the fear of one day being replaced by a tireless, unflappable, unfailingly consistent device. Human-robot interactions can be even more complicated for one group in particular--older adults.

Artificial intelligence has already stolen the headlines in 2017 by defeating poker champions and ordering us cups of coffee. Besides this, there are ways the technology is being used to improve the world. AI is the most important investment for companies in the near future. IDC predicts a widespread adoption of cognitive systems and AI will drive worldwide revenues from nearly $8bn in 2016 to more than $47bn in 2020. Banking, securities and investments and manufacturing have been identified as the industries with the most lucrative short-term opportunities but there are also many ways in which artificial intelligence is being used for philanthropic purposes.

Automatic Music Transcription (AMT) is one of the oldest and most well-studied problems in the field of music information retrieval. Within this challenging research field, onset detection and instrument recognition take important places in transcription systems, as they respectively help to determine exact onset times of notes and to recognize the corresponding instrument sources. The aim of this study is to explore the usefulness of multiscale scattering operators for these two tasks on plucked string instrument and piano music. After resuming the theoretical background and illustrating the key features of this sound representation method, we evaluate its performances comparatively to other classical sound representations. Using both MIDI-driven datasets with real instrument samples and real musical pieces, scattering is proved to outperform other sound representations for these AMT subtasks, putting forward its richer sound representation and invariance properties.