Accenture has teamed up with a coder, an orchestral composer and a datavis company to put artificial intelligence (AI) and big data to music, in a project called Symphonologie. Looking to combine data with art, Symphonologie's visual music piece has three influences: business, technology and the new digital world. To combine all of these into one artistic experience, Accenture looked to Hannah Davis, a musician and creative technologist; Rare Volume, an interactive design and data company; and composer Mathieu Lamboley. The project began with Davis' thesis, which dealt with putting music to words. She built a computer programme called TransProse, which reads bodies of text and determines the "densities" of eight emotions: joy, sadness, anger, disgust, anticipation, surprise, trust, and fear.

One of my favorite deep learning papers is Learning to Generate Chairs, Tables, and Cars with Convolutional Networks. It's a very simple concept – you give the network the parameters of the thing you want to draw and it does it – but it yields an incredibly interesting result. The network seems like it is able to learn concepts about 3D space and the structure of the objects it's drawing, and because it's generating images rather than numbers it gives us a better sense about how the network "thinks" as well. I happened to stumble upon the Radboud Faces Database some time ago, and wondered if something like this could be used to generate and interpolate between faces as well. To implement this, I adapted a version of the "1s-S-deep" model from the chairs paper.

The crew in Redmond has revealed that Office 365 is wielding cloud-based AI to automate many tasks. Tap for Word and Outlook surface relevant content from your company to help finish a project, for instance. PowerPoint and Sway will have a QuickStarter feature that gives you curated outlines for given topics, saving you the trouble of creating the foundation of a presentation from scratch. Excel, meanwhile, will have a way to turn raw geographic data into Bing-based maps. Some of these intelligent features are available now, although you'll have to wait until later this year to get the Excel and PowerPoint helpers.

NVIDIA (NVDA) is already the clear leader in the artificial intelligence chip segment, and the company scored yet another win by getting International Business Machines (IBM) to use its NVIDIA Tesla P100 Pascal GPUs through NVIDIA NVLink. Last week IBM revealed a series of Linux-based servers which, according to the company, deliver higher levels of performance and greater computing efficiency than any other x86 based server. IBM has been steadily building its cognitive division, and its analytics segment alone is now nearing 5 billion in quarterly revenues. Since the decision to put Watson at the center of things the company has been expanding its AI capabilities, and the decision to use NVIDIA's products clearly underscores the lead NVIDIA has created in this segment. "The open and collaborative model of the OpenPOWER Foundation has propelled system innovation forward in a major way with the launch of the IBM Power System S822LC for High Performance Computing," said Ian Buck, vice president of Accelerated Computing at NVIDIA.

Artificial intelligence is an increasingly popular term that lacks a unified, concrete definition. Nils J Nilsson, one of the founding researchers in the field of AI gave us one. "Artificial intelligence is that activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment." AI today is a buzzword in technology that has everyone sitting up to pay attention. With every other billboard in the Bay area talking about AI and machine learning, it appears like the time of Jarvis from Iron Man, Samantha from'Her' and even the creepy'HAL' from 2001 – a space odyssey is fast approaching.

Microsoft wants the world to know it's not falling behind in the race for artificial intelligence. The technology giant--like Google goog, Facebook fb, and IBM ibm --has been pushing into the trendy field of artificial intelligence, catch-all for various technologies that help computers recognize patterns from massive amounts of data. Microsoft CEO Satya Nadella emphasized A.I. on Monday at the company's annual IT conference in Atlanta by describing how his company is using the technology and how it plans to do so a lot more in future. "We are not pursuing A.I. to beat humans at games," said Nadella, taking a subtle hit at competitors like Google and IBM, whose A.I. technologies got some attention for beating humans at the ancient Chinese board game Go and on the game show Jeopardy. Microsoft's overarching goal is to "democratize A.I.," which Nadella explained has something to do with analyzing the mountains of data produced by consumers and businesses and then presenting the findings to people who have far less free time than they used to have.

The analysis has identified nearly 200 real-world enterprise use cases for AI that are classified into 25 industry sectors. The firm forecasts that revenue for enterprise AI applications will increase from 358 million in 2016 to 31.2 billion by 2025, representing a compound annual growth rate (CAGR) of 64.3%. Artificial intelligence (AI) technologies are quickly gaining mindshare among corporate executives around the world, driving a proliferation of use cases that touch virtually every industry. AI technologies, which include deep learning, machine learning, natural language processing (NLP), and computer vision, among others, are designed to endow computers with human-like faculties such as hearing, seeing, reasoning, and learning. But AI enables computers to do some things better than humans, especially when it comes to processing very large amounts of data quickly, efficiently, and accurately.

Big data is in many ways still a wild frontier, requiring wily smarts and road-tested persistence on the part of those hoping to find insight in all the petabytes. On Tuesday, IBM announced a new platform it hopes will make things easier. Dubbed Project DataWorks, the new cloud-based platform is the first to integrate all types of data and bring AI to the table for analytics, IBM said. Project DataWorks is available on IBM's Bluemix cloud platform and aims to foster collaboration among the many types of people who need to work with data. Tapping technologies including Apache Spark, IBM Watson Analytics and the IBM Data Science Experience launched in June, the new offering is designed to give users self-service access to data and models while ensuring governance and rapid-iteration capabilities. Project DataWorks can ingest data faster than any other data platform, from 50 to hundreds of Gbps, deriving from sources including enterprise databases, the internet of things (IoT) and social media, according to IBM.

Anti-money laundering, fraud prevention and sanctions processing are three of the key areas people working in in the payments industry see potential for artificial intelligence (AI) to play a role. In a survey of senior payment professionals in banks and corporates, 63% of those polled identified these three areas as potentially benefiting from AI that can learn from previous experience and behaviour patterns. That's according to Pelican, a company that – it should be noted - helps financial institutions apply application technologies to transactions. Formerly known as ACE software solutions, Pelican says it combines tools such as natural language processing and machine learning to profile payments and apply human-like logic to transactions. Pelican CEO Parth Desai says it's time the industry "wakes up" to the need to replace manual processes and legacy systems for payments processing. He says the gradual appearance of AI into everyday life will raise consumer expectations of faster results and services in their banking products too.

"Powered by advanced machine learning, deep learning, predictive analytics, natural language processing and smart data discovery," it said. "Einstein's models will be automatically customized for every single customer, and it will learn, self-tune, and get smarter with every interaction and additional piece of data." John Ball, the program's general manager, said in a news article from USA Today that Salesforce Einstein AI will take the burden of the executives and sales team to find patterns in customer behavior in the hopes of sustaining or expanding that relationship. Without getting too technical, the computer will study the data and craft a model as well as detect patterns "that aren't as easy for humans to detect." The Salesforce Einstein AI unburdens businesses without the resources to hire expert personnel.