Deloitte's award-winning artificial intelligence platform continues to innovate financial statement audits by using advanced machine learning and natural language processing to extract key information from large volumes of audit evidence. FEI Daily spoke with Will Bible, an audit partner at Deloitte & Touche LLP, on innovating financial statement audits with artificial intelligence and how it will impact the world of finance, accounting and auditing. Will is presenting at this year's Current Financial Reporting Issues Conference, November 14-15, 2016 in New York City on the topic. Will Bible: To achieve automation and ubiquitous data analytics, you need data standardization. There's been a lot of progress on digitizing information, and automating processes around that digitized information.

Scientists have found why amputees feel the sensation of phantom limb pain. It is due to this reorganization pain occurs in the amputated limbs of a vast majority of amputees. The researchers also found a proposed way of treating the affliction through the use of artificial intelligence techniques. The researchers used a brain-machine interface to come up with this conclusion. They trained a group of ten amputees so they could control a robotic arm from their brain. The research team found learning to control the prosthetic through the amputated arm resulted in pain.

With plans to insert itself in the driver's seat for a slice of the self-driving car market, Qualcomm said Thursday it has agreed to acquire NXP Semiconductors for about $38 billion. Qualcomm said it would pay $110 per share for the Dutch company, which commands 14% of global automotive semiconductor sales. It expects the deal to close by the end of 2017. "With innovation and invention at our core, Qualcomm has played a critical role in driving the evolution of the mobile industry," Qualcomm CEO Steve Mollenkopf said in a statement. "The NXP acquisition accelerates our strategy to extend our leading mobile technology into robust new opportunities, where we will be well positioned to lead by delivering integrated semiconductor solutions at scale."

The address was cryptic, with a tantalizing whiff of government secrets, or worse. The server itself was exactly the opposite. Government, yes--it was hosted by Los Alamos National Laboratory--but openly accessible in a way that, in those early Internet days of the 1990s, was totally new, and is still game changing today. The site, known as arXiv (pronounced "archive," and long since decamped to the more wholesome address "arXiv.org" As of July 2016, there were more than a million papers on arXiv, leaning heavily toward the hardest of the hard sciences: math, computer science, quantitative biology, quantitative finance, statistics, and above all, physics. ArXiv is the kind of library that, 30 years ago, scientists could only dream of: totally searchable, accessible from anywhere, free to publish to and read from, and containing basically everything in the field that's worth reading.

IBM Watson may be coming soon to an enterprise iOS app near you, the company announced at the IBM World of Watson 2016 event on Tuesday. In a first-of-its-kind move, IBM MobileFirst for iOS apps can now integrate Watson technology to enhance decision-making, productivity, and the employee experience. With Watson's cognitive and conversational capabilities, these enterprise apps will be able to understand, reason, and learn using data analytics, according to a press release. "Apple and IBM set out more than two years ago to define the enterprise mobility market, ensuring that professionals could finally enjoy at work the same experience they'd come to expect as consumers," said Mahmoud Naghshineh, general manager, Apple partnership at IBM, in a press release. "We are taking that to a whole new level by combining the power of Watson with the new speech framework of iOS 10. The combinations and possibilities are virtually endless."

This decrease was mainly due to the Note 7 issue, despite the increase of sales in the memory and OLED businesses. The gross profit for the quarter was KRW18.4 trillion, about KRW1.7 trillion year-on-year decrease. But the gross profit margin as a percent of sale held steady due to higher gross profits from the sales expansion of premium products in the OLED and consumer electronics businesses. Our SG&A expenditures increased Y-on-Y, mainly due to the recall cost related to Note 7. The operating profit decreased by KRW2.2 trillion, year on year to KRW5.2 trillion, and the operating profit margin declined by 3.4 percentage points to 10.9%. The earnings of the component business decreased marginally year on year due to price correction of DRAM during the first half of this year. However, on Q-on-Q basis, this operating profit increased due to sales expansion of high-end products such as SSD, flexible OLED under the stabilized ASP environment. In the set business, earnings declined in the IM division due to the loss resulting from the Note 7 issue, but the consumer electronics business continued to grow year on year, driven by the sales growth of SUHD TVs and premium home appliance products. In this quarter's strengthening of the Korean won against the major currencies such as U.S. dollar and euro had a negative impact on the operating profit quarter on quarter. We figured it's approximately KRW700 billion effect, mostly on the component business. The non-operating profit was KRW540 billion, mainly from the sales of various investments including investments in ASML. Now I would like to address the business outlook. In the fourth quarter we expect the overall earnings to improve year on year. The mobile business is expected to recover its earnings to the similar level as 4Q last year through solid S7 sales, while earnings in the component business is projected to improve year on year. For the semiconductor business, we expect the earnings to improve due to the sales expansion of the V-NAND-based SSD. For the display business, we expect the earnings to improve also from LCD business recovery year on year.

None of deep learning models discussed here work as classification algorithms. Instead, they can be seen as Pretrainin, automated feature selection and learning, creating a hierarchy of features etc. Once trained (features are selected), the input vectors are transformed into a better representation and these are in turn passed on to a real classifier such as SVM or Logistic regression. This can be represented as below.

Qualcomm said Thursday that it had agreed to acquire NXP Semiconductors for about $38 billion, expanding its presence in the increasingly lucrative market for automotive sensors and chips. Qualcomm said it would pay $110 per share for NXP and expects the deal to close by the end of 2017. The deal gives the telecommunications giant a greater foothold in the burgeoning market for technology that will power self-driving cars -- which represents a growth space compared to the saturated market for smart phones and other mobile devices. NXP also has a desirable position in the market for technology powering the so-called Internet of Things as well as security products. The acquisition also marks the latest in a series of deals for the semiconductor business, accelerating the trend of consolidation.

Artificial intelligence (AI) is already becoming entrenched in many facets of everyday life, and is being tapped for a growing array of core business applications, including predicting market and customer behavior, automating repetitive tasks and providing alerts when things go awry. As technology becomes more sophisticated, the use of AI will continue to grow quickly in the coming years, as explored in a new eMarketer report, "Artificial Intelligence 2016: What's Now, What's New and What's Next" (eMarketer PRO customers only). In its most widely understood definition, AI involves the ability of machines to emulate human thinking, reasoning and decision-making. A May 2015 survey of US business executives by Narrative Science found that 31% of respondents believed AI was "technology that thinks and acts like humans." Other conceptions included "technology that can learn to do things better over time," "technology that can understand language" and "technology that can answer questions for me."

Using Artificial intelligence (AI) or machine learning technology, a team of researchers has predicted outcomes in judicial decisions at the European Court of Human Rights (EctHR) with 79 per cent accuracy. The AI method, developed by researchers from University College London (UCL), University of Sheffield and US-based University of Pennsylvania is the first to predict the outcomes of a major international court by automatically analysing case text using a machine learning algorithm. "We don't see AI replacing judges or lawyers but we think they will find it useful for rapidly identifying patterns in cases that lead to certain outcomes," said Nikolaos Aletras, who led the study at UCL's computer science department. "It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights," Aletras added. In developing the method, the team found that judgements by the ECtHR are highly correlated to non-legal facts rather than directly legal arguments, suggesting that judges of the Court are'realists' rather than'formalists'.