Scale-out NAS hits the spot for large datasets, AI and machine learning ComputerWeekly.com

Data centers running artificial intelligence (AI) will be significantly more efficient than those operating with hand-edited algorithm schedules, say experts at MIT. The researchers there say they have developed an automated scheduler that speeds cluster jobs by up to 20 or 30 percent, and even faster (2x) in peak periods. The school's AI job scheduler works on a type of AI called "reinforcement learning" (RL). That's a trial-and-error-based machine-learning method that modifies scheduling decisions depending on actual workloads in a specific cluster. AI, when done right, could supersede the current state-of-the-art method, which is algorithms.

It is undeniable that acceleration in technology requires firms to revisit the core of their business. Success stories enabled by data analytics and machine learning are becoming public at accelerating pace as firms try to position themselves as digital leaders. This creates urgency to evaluate automation as a new source of growth across all industries. However, companies that rush into sophisticated artificial intelligence before getting control of their data and setup structured analytics might end up paralyzed. Let s outline a typical bad scenario.

According to IBM's survey of 6,000 executives, 66% of CEOs believe that cognitive computing can drive significant value in the Human Resource domain. About half of the HR executives back that up, saying that they recognize that cognitive computing and AI has the power to transform various crucial areas of Human Resource. Also, 54% of HR executives believe that AI or cognitive computing will affect their key roles in the HR organization. The Human Resources Professional Association (HRPA) reported in a survey that about 52% of respondents indicated their businesses were unlikely to adopt AI or cognitive computing in their HR departments in the next 5 years or so. Also, approximately 36% believe their company was too small to do it, while 28% said that their senior leadership didn't see the need for such technology in the near future.

August 22, 2019 – The Industrial Internet Consortium (IIC) has launched a new testing project for artificial intelligence (AI) solutions in factories and transportation companies. The Negotiation Automation Platform Testbed is open to both IIC members and non-members and uses a variety of AI infrastructure technologies, which automatically negotiate with each other, in order to find mutually agreeable contract terms. In the future, the testbed aims to promote standardization activities that support the growth of AI throughout society. The project is being led by NEC Corporation with support from Kabuku Inc., Fraunhofer IOSB and Korea Electronics Technology Institute (KETI). How the testbed works "In a manufacturing use case, automatic negotiation on conditions for the trading of products benefits both buyers and sellers," says Dr. Satoshi Morinaga, IIC Testbed lead and research fellow for NEC.

With the increased need of many AI enthusiasts to adopt data science and machine learning techniques in their career path, one has to wonder what it takes for an individual to become a valuable resource and fill in the skill shortages we hear so much about. Andre Violante's answer: This is a tough question to definitively answer since each persons journey I to data science is different. I believe that overall the skills to be a data scientist (business acumen coding statistics) are more important that the degrees. I also see this sentiment echoed online on LinkedIn by many professionals and leaders. However, and it's a big "however", when you look at data science job descriptions many of them require or prefer grad school of either MS or PhD. So even though many people have good intentions with focusing on the skill, I still believe the higher level education at this point is very valuable and almost necessary to be considered unfortunately.

Over this summer, I've noticed an even greater focus on the topic of artificial intelligence (AI) and how it might impact education and work in the future. After attending ISTE 2019 in Philadelphia, several edtech startups caught my attention because of the mention of AI. After doing some research, I came across a few other AI tools beginning to gain ground in classrooms. There is so much information out there that finding time to explore it all can be a challenge. To make it easier, I signed up to receive Google alerts about cutting edge and emerging trends with AI.

Project description Our society is changing. Artificial Intelligence (AI) and related technologies are playing an increasingly important role in our society. To this end Leiden University has started a new, university wide initiative to enable collaboration on the use of AI. By building on and expanding the already existing expertise of AI the project intends to advance science and improve the quality of our life. All the disciplines of the University of Leiden are involved: Archeology, Humanities, Social Sciences, Law, Public Administration, Sciences, and also the Leiden University Medical Centre (LUMC), to collaborate and appoint new staff with joint interests.

Disruptive technologies and Artificial Intelligence (AI) are making their way into classrooms as humanoid robots to teach students and interact with them as teachers do, at a school in Bengaluru. Though the 5 foot 7 inch robots, dressed in formal female attire, do not replace real teachers, they complement them in teaching lessons in the subjects and reply to FAQs (frequently asked questions) from students. "We have programmed the interactive robots to answer questions students frequently ask on the subjects and related to them. With AI in play, the robots are able to respond to questions and doubts of our wards after a lesson is taught," said Mr Rao. The private international day-cum-boarding school has 25 co-ed students in each of the four sections for Classes 7-9.

Engineering has always been considered an evolving industry that helps businesses transform. Keeping up with the evolution of engineering means that engineers must keep themselves actively embracing change, industry evolution, constant and consistently learning new skills, and always actively ready to move their careers forward when times of change come. Resisting change in times of rapid technological advancement and innovation has never been a good option for anyone. Let alone for engineers in the age of Industry 4.0. You can be very comfortable in your job.