The Dwight and Dian Diercks Computational Science Hall is now open at the Milwaukee School of Engineering campus. A new academic center for next-generation technologies is celebrating its grand opening at Milwaukee School of Engineering. The Dwight and Dian Diercks Computational Science Hall, funded by a donation from Dwight Diercks, a MSOE regent and alumnus, and his wife, Dian, was just completed at 1025 N. Milwaukee St. -- in the center of the downtown campus. It will prepare students for such growing fields as artificial intelligence, deep learning, cybersecurity, robotics and cloud computing. Artificial intelligence involves computers simulating human behavior to perform tasks.

Element AI, a company that builds artificial intelligence (AI) tools for enterprises, has raised CAD $200 million (USD $151 million) in a series B round of funding from a host of existing and new investors, including Gouvernement du Québec, Data Collective (DCVC), Hanwha Asset Management, BDC, Real Ventures, Caisse de dépôt et placement du Québec (CDPQ), and McKinsey & Company. Founded in 2016, Element AI develops AI software "that helps people work smarter," according to its marketing blurb. So far, the startup has focused on partnering with enterprises that want to use AI but lack the required expertise, connecting businesses with machine learning experts in-house and elsewhere to address specific problems. Earlier this year, Element AI officially launched its first products for enterprise customers in the form of "decision-making automation tools." Using computer vision, optical character recognition (OCR), and other AI mechanisms, Element AI promises to enable machines to do things like "read" documents or answer workers' questions about internal operations using natural language queries.

Machine learning is one of the hottest topics in tech at the moment. Companies are hungry to hire professionals with machine-learning knowledge, even if it costs them quite a bit more than a "standard" technologist salary. The just-released IEEE-USA Salary & Benefits Salary suggests that engineers with machine-learning knowledge are making an average of $185,000 per year. That places them second among the survey's top-paid engineering jobs; only engineers who specialized in smartphones and wearables made more ($215,771). On the other end of the scale, engineers specializing in robotics and automation only pulled down an average of $130,000.

As part of the government-funded national initiative AI Competence for Sweden, Umeå University is developing and giving a course on ethical, legal, social, economic and cultural aspects on AI, corresponding to 2 ECTs. This course is conceived as a two-day interdisciplinary discussion forum about the impact of Artificial Intelligence (AI) systems on human behaviour and the related ethical, legal, social, economic and cultural issues (ELSEC), combined with assignments to be conducted besides attending the two days. The course is aimed in its first edition at providing a ground for a continued discussion and development of AI-related contents of education and research at Umeå University across faculties, and at providing a ground for collaboration with industry and public organisations on digital innovation and development that include responsible AI. The course and home assignments will be followed up at a later date in conjunction with an open workshop on AI education and research on the ELSEC-theme. Artificial Intelligence (AI), both embedded in systems or embodied in artifacts (e.g robots), is increasingly everywhere.

And on Nov. 2, 2018, NASA's Voyager 2 spacecraft crossed into the vastness of interstellar space, following Voyager 1, which made the leap six years earlier. Since their launch in 1977, the two probes have traveled more than 11 billion miles across the solar system, lasting much longer than scientists anticipated. Powered by plutonium and drawing 400 watts of power each to run their electronics and heat, the probes still snap photos and send them back to NASA. After 42 years, though, only six of Voyager 2's 10 instruments still work, and NASA scientists expect the probe will go dark in 2025, well before it leaves our Solar system. But what if Voyager 2 needed only a couple of watts of power?

And on Nov. 2, 2018, NASA's Voyager 2 spacecraft crossed into the vastness of interstellar space, following Voyager 1, which made the leap six years earlier. Since their launch in 1977, the two probes have traveled more than 11 billion miles across the solar system, lasting much longer than scientists anticipated. Powered by plutonium and drawing 400 watts of power each to run their electronics and heat, the probes still snap photos and send them back to NASA. After 42 years, though, only six of Voyager 2's 10 instruments still work, and NASA scientists expect the probe will go dark in 2025, well before it leaves our Solar system. But what if Voyager 2 needed only a couple of watts of power?

Many application domains increasingly require AD, when anomalies carry critical and actionable information. These include: (1) Cyber-security and intrusion detection in Cloud and IT systems, also in government, defense and security agencies; (2) Fraud detection in financial institutions; (3) Manufacturing, IoT, industry and resource exploration; (4) Healthcare; etc. We shall address the problem of detecting and predicting general anomalies in high-dimension KPI performance metrics, i.e., high dimension and dynamic range multivariate non-stationary time series collected from large Cloud / IT environments. Using Keras / TF etc., we will build an ML-based AD framework for transfer, attention and meta-learning that must remain robust also with reduced/missing and noisy training data. Besides feature engineering – e.g., selection, reduction, compression techniques – explainability will also be necessary for the model prototype.

The global artificial intelligence in cybersecurity market is expected to grow from USD 4.13 billion 2017 to USD 26.80 billion by the end of 2024 at a Compound Annual Growth Rate (CAGR) of 30.64%. "Need to adapt to changing threats landscape from growing adoption of IoT and an increasing number of connected devices is one of the factors largely attributing to the growth of artificial intelligence in cybersecurity market globally" The factors attributing to the growth of the market are need to adapt to changing threats landscape from growing adoption of iot and an increasing number of connected devices, need to handle huge volumes of security data and accelerate detection and response times, and constantly increasing cyber terrorism. However, some factors such as inability of ai to restrict advance threats and zero-day attacks, and rapidly increasing instances of data poisoning attacks may hinder the market growth. The global artificial intelligence in cybersecurity market is expected to showcase the opportunities such as and ai featured security products to reduce false alerts, make investigations more efficient, and aid speed up the discovery of and response to cyber attacks. In the near future, the market may face the possible challenges in the growth due to evolving nature of cyber-attacks, and budgetary constraints.

As fans of Blade Runner and The Terminator can testify, AI and particularly AI disaster scenarios are a subject most people can't get enough of. Therefore, when AI technology and investment began to grow, it quickly caught the public's imagination. The problem is that the technology hasn't kept pace. The resulting gap between the perception and the reality has led us to enter what the Gartner Hype Cycle calls'the trough of disillusionment' with AI. This is especially apparent in the marketing industry, where, for all the talk of AI at industry events and in the media, only 27% of marketers in the UK are actually using it in their jobs.

The robotic revolution is set to cause the biggest transformation in the world's workforce since the industrial revolution. In fact, research suggests that over 30% of jobs in Britain are under threat from breakthroughs in artificial intelligence. Thanks to advances in technology, many jobs that weren't considered ripe for automation suddenly are. Find out how many jobs per sector, are at high risk of being taken by robots by 2035. Note: this design and data is newly updated for 2019..