center Archives - Artificial Intelligence

New Luddy Center for Artificial Intelligence to open for fall semester

aiuniverse — Mon, 12 Jul 2021 09:23:33 +0000

Source – https://www.idsnews.com/

The building was designed by BSA Life Structures, an architecture firm based in Indianapolis, and construction is being done by Weddle Bros Building Group, a local construction company in Bloomington.

The focus of the research at the new facility will be on robotics, health and social media, according to a press release from the university.

“It will highlight the strengths of IU in regards to artificial intelligence research and teaching,” Interim Dean of Luddy Dennis Groth said.

The Luddy School has over 150 faculty members and is among the top 15 universities for programs in human-computer interaction, computer security, programming languages and computational biology, according to their website.

“At least half of our faculty can connect their research to AI in one way or another,” Groth said.

The AI center will have offices, meeting rooms, research space and classrooms that will benefit students and faculty at Luddy, Groth said.

Associate Dean and Professor of Informatics and Cognitive Science Selma Sabanovic is one of the professors whose research focuses on AI. Her research focuses on human-robot interaction and how to apply social and cultural ideas to make robots more beneficial to humans.

“Having the AI center is a great way to bring together all the folks who are thinking about AI from different perspectives,” Sabanovic said.

Sabanovic and Assistant Professor Donald Williamson have recently been working on a project with the Toyota Research Institute that deals with applying robotics and AI to at-home care for the elderly.

The goal of the project is to create a robot that can observe what activities a person enjoys and then make recommendations to that person that will increase their happiness, Sabanovic said.

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MAKING DATA CENTER SMART: HOW ARTIFICIAL INTELLIGENCE HELPS?

aiuniverse — Thu, 18 Feb 2021 04:37:33 +0000

Source – https://www.analyticsinsight.net/making-data-center-smart-how-artificial-intelligence-helps/

As data centers become enabler to a nation’s economy, employing artificial intelligence can yield higher benefits

Artificial Intelligence (AI) plays a pivotal role in capturing, processing, and analyzing data at much faster rate than ever, today! It is also becoming more efficient and useful to incorporate data elements and managing data centers.

With data becoming a pre-requisite to sustain almost every business operation for insight and business results, data centers are on the crux of this digital transformation. These physical facilities that house the computers and equipment power the information needs of the modern economy. Data centers provide seamless data backup and recovery facilities while supporting cloud storage applications and transactions. Apart from boosting economy, the data center ecosystem attracts many international tech companies for the nation. Moreover, the presence of data centers ensure an excellent investment climate and employment opportunities for the local community.

Despite their key role in bringing digital revolution, they are not without problems. According to Gartner analyst Dave Cappuccio, 80% of enterprises will shut down their traditional data centers by 2025. The figures are fitting considering the host of problems faced by traditional data centers like lack of readiness to upgrade, infrastructure challenges, environmental issues and more. And the remedy for this is leveraging artificial intelligence to enhance the data center functions and infrastructure.

As per a Forbes Insights report, in early 2020, artificial intelligence is poised to have a tremendous impact on data center management, productivity, and infrastructure. Meanwhile, its technologies continue to offer data centers’ potential solutions to improve operations over the long term. In return data centers enabled by accelerated computing capabilities of AI, would be able to process AI workloads more efficiently.

Data centers consume a lot of energy, so training an artificial intelligence network to improve power usage effectiveness (PUE) is a key goal. PUE is essential metric to measure data center efficiency. In 2014 by deploying Deepmind AI in one of its facilities, Google was able to consistently achieve a 40% reduction in the amount of energy used for cooling, which equated to a 15% reduction in overall PUE overhead after accounting for electrical losses and other non-cooling inefficiencies. It also produced the lowest PUE the site had ever seen. Deepmind analyzes over 100 different variables within the data center to improve efficiency and reduce power consumption.

Data centers are also susceptible to various cyber threats. Cybercriminals are always finding new ways to obtain data from data centers or launch their next data breach attack. By learning normal network behavior and detecting cyber threats based on deviation from that behavior, artificial intelligence proves to be resourceful again! Artificial algorithms can complement current Security Incidents and Event Management (SIEM) systems, by analyzing incidents and inputs from multiple systems, and devising an appropriate incident response system.

In a data center, IT devices are often deployed or removed from shelves that brings a lot of fragmented resources, like U space, which cannot be monitored or managed, and are easy to get wasted. By using intelligent hardware and IoT sensors, artificial intelligence allows effective data center infrastructure management that keeps a close eye on the data center and reduces repetitive work through automation. Here, data center managers can automate activities like temperature management, equipment status monitoring, floor security, fire hazards mitigation, ventilation, and cooling systems management. Coupled with predictive analytics, automation also helps in predictive maintenance at data centers.

Further, this AI-based predictive analysis can help data centers distribute workloads across the many servers in the firm. As a result, it will be easy to predict and manage data center loads more efficiently. It will also help in optimizing server storage systems, finding possible fault points in the system, improve processing times and reducing risk factors much faster.

Recently, MIT researchers had developed an AI system that automatically learns how to schedule data-processing operations across thousands of servers. This system was observed to be about 20 to 30% faster, and twice as fast during high-traffic times in completing key data center tasks. The researchers asserts that this artificial intelligence system could enable data centers to handle the same workload at higher speeds, using fewer resources.

Additionally, through deep learning (DL) applications, AI can predict failures and outages ahead of time. E.g. HPE artificial intelligence predictive engine helps in identifying and resolving bottlenecks in the data center. A survey of 200 companies highlighted that downtime results in losses surpassing US$26.5 billion, with the cost per minute of a network outage reaching approximately US$7,900. By monitoring server performance, network congestions, and disk utilization, AI can detect and predict data outages. Besides, it can implement mitigation strategies to help the data center recover from the data outage – thus adding to customer satisfaction and minimal losses during such outages.

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Argo.ai and Carnegie Mellon to found driverless vehicle research center

aiuniverse — Tue, 25 Jun 2019 06:36:27 +0000

Source:- venturebeat.com

Argo.ai, a Pittsburgh, Pennsylvania-based driverless car startup founded by former executives from Google’s and Uber’s autonomous technology divisions, today announced that it’s teaming up with Carnegie Mellon University to form a new center for autonomous vehicle research: the aptly named Carnegie Mellon University Argo AI Center for Autonomous Vehicle Research.

Argo.ai says it’ll pledge $15 million over five years to fund faculty leaders and support graduate students conducting studies in pursuit of their doctorates. Additionally, the company says it’ll provide Carnegie Mellon students engaged in autonomous vehicle research access to data, infrastructure, and platforms like Argoverse, a curated corpus of more than 300,000 vehicle trajectories and 290 kilometers of recorded road lanes.

In a blog post, Argo.ai principal scientist and associate professor at Carnegie Mellon Deva Ramanan said that the Center will investigate smart sensor fusion, 3D scene understanding, urban scene simulation, map-based perception, imitation and reinforcement learning, behavioral prediction, and software validation as they relate to driverless vehicle technology. More broadly, it’ll pursue projects to help self-driving cars overcome hurdles like such as winter weather or construction zones, and Ramanan expects its work will “spur engagements” on topics like safety policy and ethics.

“While the team at [Argo.ai] sees a pathway to achieve initial commercialization opportunities for self-driving technology, there are still advancements required to be able to perceive and navigate autonomously in the most complex, open conditions with dramatically lower compute power,” wrote Ramanan, who added that all of the Center’s findings will be reported in open scientific literature. “And until we’re able to do so at scale, the visionary benefits that have been spelled out for society won’t be achieved.”

Ramanan will serve as the Center’s faculty leader along with Simon Lucey, an associate professor at Carnegie Mellon University’s Robotics Institute specializing in computer vision. The team’s other founding members include John Dolan, David Held, and Jeff Schneider.

“We are thrilled to deepen our partnership with Argo.ai to shape the future of self-driving technologies,” said Carnegie Mellon president Farnam Jahanian. “This investment allows our researchers to continue to lead at the nexus of technology and society, and to solve society’s most pressing problems. Together, Argo.ai and [Carnegie Mellon] will accelerate critical research in autonomous vehicles while building on the momentum of [Carnegie Mellon’s] culture of innovation.”

The Center follows on the heels of Argo.ai’s existing collaboration with Carnegie Mellon and Georgia Tech, but it’s worth noting it’s not the first of its kind. Intel last October announced that it would launch an Institute for Automated Mobility in Arizona, which will combine three state universities; the Departments of Transportation, Public Safety, and Commerce; and companies working on automated cars, trucks, and drones.

Argo has a close relationship with Ford, which in February 2017 said it would invest $1 billion in the startup over the next five years to help it achieve its goal of producing a self-driving vehicle fleet by 2021. This made Ford the company’s largest shareholder and enabled Argo to hire 200 additional employees, many of whom were Ford employees working in the R&D department on a virtual driver system.

Autonomous hardware and software stacks remain Argo’s core projects, along with the high-definition road maps and virtual driver system that will eventually slot into Ford’s self-driving vehicles. Ford has previously said it intends to launch a self-driving taxi and delivery service by 2021.

A.T. Kearney: Get used to competing in digital disorder era

DEAN TAKAHASHI@DEANTAKJUNE 24, 2019 09:01 PM

But the global management consulting firm predicted in a report that by 2030, a new digital era will emerge. The trajectory of the global regulatory environment for technology as well as the extent to which the Internet remains open or balkanized will determine the contours of this period.

To be positioned for the future digital era, businesses must engage in a strategic digital transformation. A.T. Kearney’s Score framework presents a road map for this process.

A.T. Kearney said there are different possible futures, with fears growing about a new “digital cold war” and the “splinternet,” where the Internet becomes more balkanized. This is forcing companies around the world to shift strategies on everything from procurement to customer engagement.

In a new report by A.T. Kearney’s Global Business Policy Council, Competing in an Age of Digital Disorder, the firm said that companies can no longer be passive observers of the digital revolution.

Instead, they must actively adapt to the present disorder while also preparing for the future digital order by embarking on strategic end-to-end digital transformations.

Much attention is focused on the “techlash” nature of new policies on key issues such as consumer privacy, data protection, and anti-competitive practices. But many governments are now seeking to strike a balance in policies that both maximize digital’s upsides and mitigate its downsides as they prepare to regulate the digital environment for the first time. Whether those
governments are able to deftly strike such a balance will influence companies’ ability to use digital technologies effectively in the coming years.

“This cycle of innovation, adoption, and then regulation is consistent with previous waves of technological change,” says Paul Laudicina, chairman of A.T. Kearney’s Global Business Policy Council and co-author of the report, in a statement. “Today, the intense regulatory debate regarding digital technologies is creating a high degree of uncertainty about how the policy environment will evolve.”

After providing a richly researched background on the opportunities and pressure points facing societies, governments, and businesses in this period of digital disorder, the study then offers four scenarios for the digital order that will emerge.

The scenarios are based on two political uncertainties that are unfolding:

Regulatory activity. The extent to which governments in key markets around the world impose new regulations on technology companies and the use of digital technologies more broadly
Digital environment. The extent to which the digital economy is a globalized whole, characterized by extensive cross-border digital flows, or an islandized environment, fragmented into different country-level or regional blocs

“These scenarios are designed to be compelling and plausible visions of the future that challenge and test executives’ capacity to anticipate and plan for their companies’ digital strategies in the coming years,” said Erik Peterson, managing director of the Global Business Policy Council and co-author of the study, in a statement. “In fact, some aspects of these scenarios, such as the
emergence of a digital ‘cold war’ between major global powers and early indications of a ‘splinternet,’ are already playing out in various markets around the world.”

Finally, the study argues that companies cannot be simply spectators of the ongoing digital revolution. Instead, executives will need to guide their organizations through strategic digital transformations across a variety of business functions.

“Companies must adapt to the emerging digital order across strategy, customer experience, operations, risk management and compliance, and employees and culture—our Score framework,” said Courtney Rickert McCaffrey, manager of thought leadership for the Global Business Policy Council and co-author of the study, in a statement. “To compete in the 21st-century digital economy, companies must embark on end-to-end digital transformation in all SCORE

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