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The Transportation Security Administration is planning to increase and share information it collects, including that gleaned from employees, with other federal agencies and the private sector in an effort to prevent insiders from perpetrating various harmful malfeasance.

Artificial Intelligence, probabilistic analytics and data mining are among tools the agency lists in a document it issued today loosely outlining the problem and the plan to create an Insider Threat Mitigation Hub.

The Insider Threat Roadmap defines the common vision for the Transportation Systems Sector that insider threat is a community-wide challenge, since no single entity can successfully counter the threat alone, TSA Administrator David Pekoske wrote in an opening message.

In July 2019, a surveillance camera at the Miami International Airport captured footage of an airline mechanic sabotaging a planes navigation system with a simple piece of foam. The TSA road map describes this incident along with a number of others dating back to 2014 spanning a range of activities including terrorism, subversion and attempted or actual espionage, to stress the need for a layered strategy of overall transportation security.

A TSA press release identified three parts of that strategy as promoting data-driven decision making to detect threats; advancing operational capability to deter threats; and maturing capabilities to mitigate threats to the transportation sector.

Under the first objective, TSA plans to develop and maintain insider threat risk indicators, which could include behavioral, physical, technological or financial attributes that might expose malicious or potentially malicious insiders.

We must identify key information sources, and ensure they are accurate and available for use in informing risk mitigation activities, the document adds.

For the second objective, the document describes information-sharing plans with other federal agencies and industry.

We will establish an Insider Threat Mitigation Hub to elevate insider threat to the enterprise level and enable multiple offices, agencies, and industry entities to share perspectives, expertise, and data to enhance threat detection, assessment, and response across the TSS, the document reads. This capability will allow us to fuse together disparate information points to identify intricate patterns of conduct that may be unusual or indicative of insider threat activity and drive enhanced insider threat mitigation efforts.

Meeting the third objective would require seeking out the appropriate technology to improve detection and mitigation of insider threat TSA writes, and expanding it throughout the agencys supply chain.

TSA pre-empted concerns usually associated with massive data collection practices by including the protection of privacy and civil liberties among the guiding principles it said would accompany its efforts.

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TSA Issues Road Map to Tackle Insider Threat With Artificial Intelligence - Nextgov

In the current scenario, COVID-19 doesnt seem to have an end as this virus does not discriminate based on caste and creed. This pandemic situation has brought the world to a standstill and forced the plans of every individual to be rethought in a different dimension altogether concerning the new economic crisis that can be visualized by the experts.

We have always observed how things get outmoded with time and in the case of technology, it is even at a rapid rate. Keeping this theory in mind everyone is afraid about the changes in technology that will take place post the pandemic bringing concern in various fields. The effect is going to be massive and long-lasting, but we need to learn a lot of things with the current situation and be ready for any kind of further circumstances impacting the lives and bringing it to a standstill.

As human beings are learning, machines also need to be more advanced to understand these situations and react early and alert us for the upcoming catastrophes. Artificial Intelligence also termed as self-learning mechanism for the machines needs enormous advancement to make them future-ready. At present, the AI is evident in the areas of Healthcare, Automotive, Cybersecurity, Video games, Military operations etc.

Speaking with Safura Begum, CEO of Inventateq, he mentioned that Artificial Intelligence is going to be the future for all the technologies being developed. Describing in detail on the topic he mentioned cited the role of AI in the healthcare industry. The innovation of technology in the medical field has helped the researchers identify the diverse methods of treatment more rapidly. It has also helped in doing the research work at a faster rate and achieve the results with supreme accuracy than those testing without AI. He seemed to have complete conviction in the Doctors and researchers that the pandemic situation will be controlled soon and everything will get back on track. Further, he mentioned that the healthcare industry that he can visualize today wouldnt have been possible without the intervention of AI in the sector.

Speaking on the advancement of artificial intelligence in the specific sector, he said that there is always a room for the new invention and hopefully in the coming years we will experience the AI in a new way where it will be able to detect the syndrome at a very primary stage, along with the cure and prevention at the first place so that we will never see this kind of situation in the future ever again. He also mentioned about the use of AI to identify the potential threat (the carriers of the virus) of COVID-19 that has been undertaken by Google and Apple by tracking the movements of the infected publics, which is possible with the history of map location, thus it will play an important role in detecting the spread of the virus.

When asked about the loss due to COVID-19, he mentioned his grief and said that education is the key to success and with education and its advancement we can recover the losses except for the life of human beings lost. Taking the conversation to the next level, Safura mentioned that we need to analyze what we need to learn and unlearn at the first place. The time that we lost will not return, so we must prioritize our learning curve and focus on the same. He added that the new requirements that the industry is going to have are very much important and needs to be considered by the individuals before taking up any course.

The current trends are indicating that there will be survival for the fittest, it is very much necessary to analyze our core strength and act accordingly to fit in the market. AI is going to play an important role in the course design and its delivery in the future. As the scenario has changed due to lockdown and there has been a halt in almost all the industry, there is going to be a hunger for education so that the people will try to outcast others in all possible ways. In this scenario, everyone must be very careful while choosing any stream for their education.

Talking about the national level of education and its impact, Safura Begum mentioned that Artificial Intelligence is going to play a very important role in understanding the needs of the students. When there is less time, the important and urgent graph needs to be plotted properly so that everyone gets the benefit. The plotting for the country like India needs to be very much accurate otherwise the consequences can be different.

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Artificial Intelligence: Technology Of The Future - Forbes India

The Promise Of Artificial Intelligence In Chillers And Rooftops | 2020-05-15 | ACHR News This website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more. This Website Uses CookiesBy closing this message or continuing to use our site, you agree to our cookie policy. Learn MoreThis website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.

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The Promise Of Artificial Intelligence In Chillers And Rooftops - ACHR NEWS

Couples are putting their trust in artificial intelligence to help them become parents, with an Australia-first trial proving a success.

Sarah and Tim Keys from Queensland have been trying to conceive for a number of years and after suffering a number of miscarriages decided to turn to IVF.

When their GP suggested joining the AI trial, the couple did their research and discovered it would improve their chances of getting through the pregnancy.

"It's really hard to go through those miscarriages so anything that could decrease the chances, let's go with that," Ms Keys said.

Doctors are hailing the technology as the biggest leap forward in IVF in over three decades.

"It's completely new, completely different and ... it's all to do with the evolution of computer technology," Associate Professor Anusch Yazdani from the Queensland Fertility Group said.

As part of the international study, led by national fertility provider Virtus Health, 1000 patients will be recruited at five IVF clinics across Australia, alongside sites in Ireland and Denmark.

During each IVF cycle, embryos will be grown in an incubator fitted with tiny time-lapse cameras which will record 115,000 images over five days.

Each embryo is then given a rating based on predicted fetal heart outcomes and the one with the greatest chance of survival is implanted.

If the trial is successful the technology will be rolled out around the world.

So far, the trial at seven fertility clinics around the country has a 90 per cent success rate.

"That's much better than our embryologists have managed to do so this is a really exciting time to," Professor Yazdani said.

Ms Keys is now 26 weeks pregnant and cautiously optimistic for the future.

"We're very excited we're expecting a little girl," she said.

"I think we'll still be a bit stressed until we're holding her, but where we're at, at the moment is really awesome."

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Trial of Artificial Intellience boosts IVF success and brings joy to Queensland couple - 9News

With the advancements in deep learning, the recent years have seen a humongous growth of artificial intelligence (AI) applications and services, traversing from personal assistant to recommendation systems to video/audio surveillance. All the more as of late, with the expansion of mobile computing and Internet of Things (IoT), billions of mobile and IoT gadgets are connected with the Internet, creating zillions of bytes of information at the network edge.

Driven by this pattern, there is a pressing need to push the AI frontiers to the network edge in order to completely release the potential of the edge big data. To satisfy this need, edge computing, an emerging paradigm that pushes computing undertakings and services from the network core to the network edge, has been generally perceived as a promising arrangement. The resulting new interdiscipline, edge AI or edge intelligence (EI), is starting to get an enormous amount of interest.

In any case, research on EI is still in its earliest stages, and a devoted scene for trading the ongoing advances of EI is exceptionally wanted by both the computer system and AI people group. The dissemination of EI doesnt mean, clearly, that there wont be a future for a centralized CI (Cloud Intelligence). The orchestrated utilization of Edge and Cloud virtual assets, truth be told, is required to make a continuum of intelligent capacities and functions over all the Cloudifed foundations. This is one of the significant challenges for a fruitful deployment of a successful and future-proof 5G.

Given the expanding markets and expanding service and application demands put on computational data and power, there are a few factors and advantages driving the development of edge computing. In view of the moving needs of dependable, adaptable and contextual data, a lot of the data is moving locally to on-device processing, bringing about improved performance and response time (in under a couple of milliseconds), lower latency, higher power effectiveness, improved security since information is held on the device and cost savings as data-center transports are minimized.

Probably the greatest advantage of edge computing is the capacity to make sure about real-time results for time-sensitive needs. Much of the time, sensor information can be gathered, analyzed, and communicated immediately, without sending the information to a time-sensitive cloud center. Scalability across different edge devices to help speed local decision-making is fundamental. The ability to give immediate and dependable information builds certainty, increases customer engagement, and, in many cases, saves lives. Simply think about all of the businesses, home security, aviation, car, smart cities, health care in which the immediate understanding of diagnostics and equipment performance is critical.

Indeed, recent advances in AI may have an extensive effect in various subfields of ongoing networking. For example, traffic prediction and characterization are two of the most contemplated uses of AI in the networking field. DL is likewise offering promising solutions for proficient resource management and network adoption therefore improving, even today, network system performance (e.g., traffic scheduling, routing and TCP congestion control). Another region where EI could bring performance advantages is a productive resource management and network adaption. Example issues to address traffic scheduling, routing, and TCP congestion control.

Then again, today it is somewhat challenging to structure a real-time framework with overwhelming computation loads and big data. This is where EC enters the scene. An orchestrated execution of AI methods in the computing assets in the cloud as well as at the edge, where most information is produced, will help towards this path. In addition, gathering and filtering a lot of information that contain both network profiles and performance measurements is still extremely crucial and that question turns out to be much progressively costly while considering the need of data labelling. Indeed, even these bottlenecks could be confronted by empowering EI ecosystems equipped for drawing in win-win collaborations between Network/Service Providers, OTTs, Technology Providers, Integrators and Users.

A further dimension is that a network embedded pervasive intelligence (Cloud Computing integrated with Edge Intelligence in the network nodes and smarter-and-smarter terminals) could likewise prepare to utilize the accomplishments of the developing distributed ledger technologies and platforms.

Edge computing gives an option in contrast to the long-distance transfer of data between connected devices and remote cloud servers. With a database management system on the edge devices, organizations can accomplish prompt knowledge and control and DBMS performance wipes out the reliance on latency, data rate, and bandwidth. It also lessens threats through a comprehensive security approach. Edge computing gives an environment to deal with the whole cybersecurity endeavors of the intelligent edge and the wise cloud. Binding together management systems can give intelligent threat protection.

It maintains compliance regulations entities like the General Data Protection Regulation (GDPR) that oversee the utilization of private information. Companies that dont comply risk through a significant expense. Edge computing offers various controls that can assist companies with ensuring private data and accomplish GDPR compliance.

Innovative organizations, for example, Amazon, Google, Apple, BMW, Volkswagen, Tesla, Airbus, Fraunhofer, Vodafone, Deutsche Telekom, Ericsson, and Harting are presently embracing and supporting their wagers for AI at the edge. Some of these organizations are shaping trade associations, for example, the European Edge Computing Consortium (EECC), to help educate and persuade small, medium-sized, and large enterprises to drive the adoption of edge computing within manufacturing and other industrial markets.

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The Future of Artificial Intelligence: Edge Intelligence - Analytics Insight