DeepSig, a company developing AI to transform wireless for 5G, IoT, and security, raised $5M in its Series A Financing, adding to the $3.5M previously raised. Leawood Venture Capital led the Series A round with participation by Scout Ventures, Blu Venture Investors, and Lockheed Martin Ventures. The additional funding will accelerate DeepSig's AI and machine learning (ML) software development and deployment to improve performance and security while reducing power consumption and cost in 5G and other wireless systems. "We are excited to include DeepSig as a portfolio company in our Fund. Their proven leadership team, combined with their groundbreaking patented technology will have a significant impact across wireless access, 5G networks, and defense markets," said Brendan Fallis, Co-Founder and Managing Partner of Leawood Venture Capital.

The major factors propelling the growth of the Global Artificial Intelligence (AI) market include the rise in the adoption of cloud-based applications and services and the growth of big data across the globe. The advanced AI technologies is continuously enhancing the performance of economies, businesses and different industries. The growing demand for intelligent virtual assistants across different verticals in several industries will have a positive impact on the Global Artificial Intelligence (AI) market during the forecast period. The increased integration of image recognition technology with optical character recognition, pattern matching and face recognition in various end-use applications such as drones, self-driving cars and robotics will propel the growth of the artificial intelligence market during the forecast period. Various multinational giants are largely focusing on mergers and acquisitions with emerging start-ups in order to capture the highest market share and gain a competitive advantage over the other market players.

Data Science is helping the banking industry become smarter in managing the myriad challenges it faces today. While basic reporting and descriptive analytics continue to be a must-have for banks, predictive and prescriptive analytics are now starting to generate powerful insights, resulting in a significant value add. Banks are increasingly using machine learning to power their operations, but the adoption of these new technologies is not widespread across the other departments. The road to comprehensive implementation of machine learning to solve challenging business problems in banking is fraught with technological and organizational challenges. Moreover, banks today generate huge volumes of internal data (customer accounts, credit scoring, payments, assets, etc.) and now need to understand its linkages to external data (interest rates, macroeconomic variables, and customer preferences).

For instance, a mixture of primary and secondary research has been used to define Artificial Intelligence Software market estimates and forecasts. Sources used for secondary research contain (but not limited to) Paid Data Sources, Technology Journals of 2013-2018, SEC Filings Company Websites, Annual Reports, and various other Artificial Intelligence Software industry publications. Specific details on the methodology used for Artificial Intelligence Software market report can be provided on demand. In addition, It highlights the ability to increase possibilities in the coming years by 2023, also reviewing the marketplace drivers, constraints and restraints, growth signs, challenges, market dynamics. "Global Artificial Intelligence Software Market" gives a region-wise analysis like growth aspects, and revenue, Past, present and future forecast trends, Analysis of emerging market sectors and development opportunities in Artificial Intelligence Software will forecast the market growth. Regional scope: Artificial Intelligence Software market is divided into various regions like North America, Middle-East a and Africa, Asia-Pacific, South America, and Europe. Country scope: Artificial Intelligence Software market is divided into United States, Mexico, Canada, Germany, Singapore, U.K., Italy, Russia, France, Spain, China, India, Japan, South Korea, Australia, Brazil, Colombia, Paraguay, Saudi Arabia, South Africa, Egypt, and UAE, ASEAN countries.

Artificial intelligence can be found in many of the devices and software systems we use for our personal lives and professional responsibilities. Whether it's the digital assistant you keep in your kitchen to set voice timers while cooking or the customer service representative you're sending messages to about return policies online, this technology is encountered more and more each day as its capabilities expand. Many organizations are integrating digital software programs that come with AI technology built into them in order to modernize, digitize, and increase efficiency for purchasing and production. Chatbots, one of the most popular types of tech benefiting businesses, are digital assistants often incorporated into digital software programs internally to save the time and energy of an employee. The chatbot serves the purpose of answering site visitor questions and handling customer service requests, which can free up time on employees' busy schedules and allow them to dedicate more time to other projects.

The UK has a well-documented decades-long 20% labour productivity gap with the US, Germany and France. With Brexit potentially creating extra challenges in overcoming this competitive disadvantage, the UK could fall even further behind. But if you are an optimist it could also be a moment for the UK to take a giant leap forward as it has done in the past when confronted with no other choice. Britain has been very good at doing this recently but it could be even better and Brexit could galvanise a new era of even more productive collaboration between public institutions and private business. There are many sectors of the UK economy that have bright sparks of world class performance but McKinsey Global Institute Productivity research shows very clearly they are held back by vexing bottlenecks.

The UK has a well-documented decades-long 20% labour productivity gap with the US, Germany and France. With Brexit potentially creating extra challenges in overcoming this competitive disadvantage, the UK could fall even further behind. But if you are an optimist it could also be a moment for the UK to take a giant leap forward as it has done in the past when confronted with no other choice. Britain has been very good at doing this recently but it could be even better and Brexit could galvanise a new era of even more productive collaboration between public institutions and private business. There are many sectors of the UK economy that have bright sparks of world class performance but McKinsey Global Institute Productivity research shows very clearly they are held back by vexing bottlenecks.

Introductory statistics courses teach us that, when fitting a model to some data, we should have more data than free parameters to avoid the danger of overfitting -- fitting noisy data too closely, and thereby failing to fit new data. It is surprising, then, that in modern deep learning the practice is to have orders of magnitude more parameters than data. Despite this, deep networks show good predictive performance, and in fact do better the more parameters they have. It has been known for some time that good performance in machine learning comes from controlling the complexity of networks, which is not just a simple function of the number of free parameters. The complexity of a classifier, such as a neural network, depends on measuring the "size" of the space of functions that this network represents, with multiple technical measures previously suggested: Vapnik–Chervonenkis dimension, covering numbers, or Rademacher complexity, to name a few.

If you're concerned that automation and artificial intelligence are going to disrupt the economy over the next decade, join the club. But while policymakers and academics agree there'll be significant disruption, they differ about its impact. On one hand, techno-pessimists like Martin Ford in "Rise of the Robots" argue that new forms of automation will displace most jobs without creating new ones. In other words, most of us will lose our jobs. On the flip side of the debate are techno-optimists such as Erik Brynjolfsson and Andy McAfee.

Siri means a secret in Swahili and in Norse, a beautiful woman who leads you to victory. To those of us in Appleland using the voice-controlled personal assistant, it stands for "Speech Interpretation and Recognition Intelligence." And when you put Siri to work, she can move productivity mountains. I use Siri to give me directions while driving with Apple CarPlay. I ask her to remind me to stop by the grocery store on my Apple Watch.