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Today, artificial intelligence (AI) applications are reshaping large and small companies products, services, and business models. Decision makers need to make critical hardware and software choices to achieve AI strategy success. As smaller firms to global enterprises assess their business cases and work flows the need for highly-scaled servers and cloud platforms are no longer the only option to build a successful AI infrastructure.

The study results summarized in this white paper, Using Workstations To Reshape Your Artificial Intelligence Infrastructure, show that firms are already using workstations to lower the cost, increase the security, and speed up their AI infrastructure. The addition of workstations into a firms AI workflow allows servers and cloud platforms to be tasked with business cases that require more robust computing while workstations take on tasks with longer time frames and smaller budgets.

Download this white paper, Using Workstations To Reshape Your Artificial Intelligence Infrastructure, to read more about how highly-scaled servers and cloud platforms are necessary to run applications that must be run at top speed and where cost is not a barrier. However, workstations provide excellent support for applications where data security is a priority but where timelines are more flexible or cost is a major consideration.

Originally posted here:
Using Workstations To Reshape Your Artificial Intelligence Infrastructure - insideHPC

I bought my first robot from a Boston-based gadget shop back in 1986, right after completing my studies at Harvard and ready to head back to Saudi Arabia. After landing at an airport in Jeddah and going through customs, it was such a struggle trying to explain to officials why I was bringing a meter-high robot.I had to declare that it was a toy for my younger brother Hattan. For years, among my family and friends, that robot was the most talked about, entertaining, exciting and heavily used piece of furniture at my Jeddah residence.Now, using technology is becoming an important part of our daily lives. Artificial intelligence (AI) became a pillar of the Vision 2030 reform plan when the official announcement was made about the creation of NEOM at the Future Investment Initiative summit a few years back. It is anticipated that NEOM will be a high-tech, renewable-energy city with more robots on the ground, including self-driven cars, than humans.Recently, Saudi Arabia announced its National Strategy for Data and AI at the Global AI Summit, hosted in Riyadh with virtual links to a global audience. The strategy was announced by Saudi Data and AI Authority President Dr. Abdullah bin Sharaf Al-Ghamdi, who spoke on behalf of Crown Prince Mohammed bin Salman.The new strategy will focus on bridging the skills gap, stimulating the market through research and innovation and utilizing applications of AI for government and private-sector agencies.As Saudi Arabia leads the G20 this year with the economic impact of the coronavirus disease (COVID-19) at the top of its agenda, AI is an imperative component for G20 economies future plans. With decision-makers in both public and private sectors involved in fighting the pandemic, using technology in health care, especially in the field of biopharma research and development, will be critical for dealing with the pandemic successfully in the long term.On the other hand, it is worth noting that the speed and scale of the transformations likely to result from AI and associated technologies may create bothopportunities and social challenges. Saudi Arabia could harness these technologies to improve public sector efficiency. Also, savvy investments will boost its sovereign wealth assets and income in the long term. However, there are risks that these technologies may lead to high levels of structural unemployment among citizens.In my opinion, as the Kingdom is planning to be one of the top AI global pioneers by 2030, one thing to agree about is that technology in general, and AI in particular, will be at the center of the future normal.AI will eventually make our lives easier, more intelligent, efficient and safer in terms of health care, mobility, traveling, documentation and other daily activities. But to what degree it will impact human capital employment remains to be seen.I do not know when I will be buying my next robot. I am sure the new one will be far more user-friendly and intelligent than the first one I bought. The only question is: Will it replace the support staff at my residence?

Basil M.K. Al-Ghalayini is the chairman and CEO of BMG Financial Group.

Disclaimer: Views expressed by writers in this section are their own and do not necessarily reflect Arab News' point-of-view

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Will artificial intelligence in KSA be the future normal? - Arab News

In August, the young artificial intelligence process automation company Intelenz, Inc. announced its first U.S. patent, an AI-enabled software-as-a-service application for automating repetitive activities, improving process execution, and reducing operating costs. For company co-founder Renzo Zagni, the patent is a powerful testament to the value of his MIT educational experience.

Over the course of his two-decade career at Oracle, Zagni worked his way from database administrator to vice president of Enterprise Applications-IT. After spending seven years in his final role, he was ready to take on a new challenge by starting his own company.

From employee to entrepreneur

Zagni launched Intelenz in 2017 with a goal of keeping his company on the cutting edge. Doing so required that he stay up to date on the latest machine learning knowledge and techniques. At first, that meant exploring new concepts on his own. But to get to the next level, he realized he needed a little more formal education. Thats when he turned to MIT.

When I discovered that I could take courses at MIT, I thought, What better place to learn about artificial intelligence and machine learning? he says. Access to MIT faculty was something that I simply couldnt pass up.

Zagnienrolled in MIT Professional Educations Professional Certificate Program in Machine Learning and Artificial Intelligence, traveling from California to Cambridge, Massachusetts, to attend accelerated courses on the MIT campus.

As he continued to build his startup, one key to demystifying machine learning came from MIT Professor Regina Barzilay, a Delta Electronics professor in the Department of Electrical Engineering and Computer Science and a member of MITs Computer Science and Artificial Intelligence Laboratory. Professor Barzilay used real-life examples in a way that helped us quickly understand very complex concepts behind machine learning and AI, Zagni says. And her passion and vision to use thepower of machine learning to help win the fight against cancer was commendable and inspired us all.

The insights Zagni gained from Barzilay and other machine learning/AI faculty members helped him shape Intelenz early products and continue to influence his companys product development today most recently, in his patented technology, the "Service Tickets Early Warning System. The technology is an important representation of Intelenz ability to develop AI models aimed at automating and improving business processes at the enterprise level.

We had a problem we wanted to solve and knew that artificial intelligence and machine learning could possibly address it. And MIT gave me the tools and the methodologies to translate these needs into a machine learning model that ended up becoming a patent, Zagni says.

Driving machine learning with innovation

As an entrepreneur looking to push the boundaries of information technology,Zagni wasnt content to simply use existing solutions; innovation became a key goal very early in the process.

For professionals like me who work in information technology, innovation and artificial intelligence go hand-in-hand, Zagni says.

While completing machine learning courses at MIT, Zagni simultaneously enrolled in MIT Professional Educations Professional Certificate Program in Innovation and Technology. Combining his new AI knowledge with the latest approaches in innovation was a game-changer.

During my first year with MIT, I was putting together the Intelenz team, hiring developers, and completing designs. What I learned in the innovation courses helped us a lot, Zagni says. For instance, Blake Kotellys Mastering Innovation and Design Thinking course made a huge difference in how we develop our solutions and engage our customers. And our customers love the design-thinking approach.

Looking forward

While his progress at Intelenz is exciting, Zagni is anything but done. As he continues to develop his organization and its AI-enabled offerings, hes looking ahead to additional opportunities for growth.

Were already looking for the next technology that is going to allow us to disrupt the market, Zagni says. Were hearing a lot about quantum computing and other technology innovations. Its very important for us to stay on top of them if we want to remain competitive.

He remains committed to lifelong learning, and says he will definitely be looking to future MIT courses and he recommends other professionals in his field do the same.

Being part of the MIT ecosystem has really put me ahead of the curve by providing access to the latest information, tools, and methodologies, Zagni says. And on top of that, the faculty are very helpful and truly want to see participants succeed.

Original post:
Staying ahead of the artificial intelligence curve with help from MIT - MIT News

November10, 20204 min read

Artificial intelligence is revolutionizing various industries, markets, and services. However, the creative industries and the art world have not yet been able to use the full potential of this technology. However, two Chilean entrepreneurs devised a platform to go further.

Using the latest technology, they allow creators, amateur filmmakers, visual artists, even the film and music industry to use artificial intelligence algorithms in their work. This is Runway , a platform that integrates machine learning and artificial intelligence to the world of art and creativity.

Founded at the end of 2018 by Cristbal Valenzuela, Alejandro Matamala and Anastasis Germanidis, Runway started as a thesis project that they developed at New York University (NYU) - where they met - while developing a postgraduate degree.

Its creators define the platform as part of the new generation of creative tools. If Photoshop and Adobe revolutionized the creative market a few decades ago, Runway is looking to do so for years to come.

In this case, the bet of this startup is that with their software in the cloud, they can develop "synthetic content", that is, automatically generate, modify, and edit audiovisual content with artificial intelligence algorithms.

Cristobal, Alejandro and Anastasis, founders of Runway. Courtesy photo

"We continue to create audiovisual content in the same way that we have done for decades and that makes the process unnecessarily slow, expensive and difficult. With AI algorithms anyone can create hyper-realistic animations in seconds and edit them automatically. Something that only Hollywood or large production companies and special effects have been able to do so far, "explains Valenzuela.

At the same time, Runway makes it possible to shorten development times, in addition to democratizing access to this technology for as many creators as possible. These technologies are radically changing the way we create content because algorithms are already capable of generating images, text, video and sound in an ultra-realistic way, explains Cristbal; to which Alejandro adds "if we put these tools in the hands of people who have never accessed them before, they will start to think of new ways of producing art, generating content and telling stories".

The impact of the platform started from when they launched a tweet asking how many would use a tool like the one they had in mind. In less than 48 hours, they already had responses from engineers from Facebook, Google, universities and even the media, indicating that they found the possibility of a creative tool to occupy artificial intelligence algorithms incredible. Immediately after this, they created the company and have not looked back.

The path they have already traveled has been fast. As a result of their work, they have already generated interest from different investment funds. In the same year that they created Runway, they completed a $ 2 million investment round with US funds specialized in technology research startups: Lux Capital, Amplify Partners Compound Ventures.

But also, on a practical level, they have already carried out important projects, such as a collaboration with New Balance for the design of a shoe; be the software with which the rock band YACHT created part of the audiovisual content of their latest album - being nominated for a Grammy Award; be working on the creation of short films generated by IA, and even already collaborating with visual artists and the seventh art.

Along with this, the response of cloud software has also come from the academic world, which has led them to close alliances with various universities in the United States, such as NYU, MIT and UCLA; while in Chile the software is already being used at the Universidad Adolfo Ibez, Universidad de las Amricas, and the Pontificia Universidad Catlica.

At the moment, each step that Runway takes is a path towards the future and that is precisely the bet that its founders are making, by developing residencies or internships in the company for artists and researchers, so that they can deepen the uses and applications of the technology they develop. This was a practice that they had implemented before the outbreak of the coronavirus pandemic and that they will resume in a few more weeks, from their offices located in Brooklyn in New York City.

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Machine Learning and Artificial Intelligence to Revolutionize the World of Art and Creativity - Entrepreneur

Automation during the industrial revolution led to a profound change in working practices across the 18th and 19th centuries. Currently, we are in the midst of a fourth industrial revolution, with globalisation and automation affecting every aspect of our working lives and leisure activities. The COVID-19 pandemic has provided a further driver for change, altering how we work and interact with remote working and reduction of human interaction at the centre of global initiatives to try and reduce the spread of the virus.

Healthcare systems generate large quantities of complex datasets pertaining to patients. Artificial Intelligence (AI) can offer solutions to medical problems by attempting to replicate decisions that would otherwise require human intelligence. Specific algorithms can be created in order to make associations between data and predict future outcomes. The COVID-19 pandemic has accelerated change within healthcare systems and driven interest in automated algorithms capable of assisting hospitals in diagnostics, decision making and repetitive clerical tasks thus reducing the potential footfall of staff on site. Automation and intelligent algorithms that learn and improve with further iterative cycles require data and the ethics behind large personal data sets, the challenges of anonymisation remain in their infancy.

AI applications within healthcare can be broadly categorised into diagnosis, research, management and system analysis. Ultimately in the time of COVID, workforce adaptations have led healthcare providers to use their workforce wisely, reducing the staff requirements on site and moving towards remote working.

Healthcare records in most countries have moved from paper-based records and notes to digital media. The electronic health record (EHR) allows the capture of large quantities of data across patient groups. Future patient care aims to develop tailored treatments for patients in a cost-effective manner.

The use of large datasets requires an element of data curation. Data needs to be retrieved from multiple disparate data sources. Data needs to then be cleaned to remove anomalies and harmonised to ensure similar data sets are compared across patient records. An element of these processes needs human oversight to ensure the correct data is fed into the algorithms.

Administrative applications are resource-heavy and repetitive. These applications include workflow management such as uploading referral letters from primary care, setting up referral assessment services and booking patients to the correct service provider in secondary care. Robotic process automation (RPA) consists of computer programmes that obey rules for these manual, resource-heavy tasks.

Additionally, process management systems (PMS), while embedded within commercial businesses, are still in their infancy within a healthcare application. Patients are individuals and tailoring care to them necessitates being able to react to changing physiological parameters within the confines of the organisation. In order to standardise care, clinical pathways have been developed to manage patient care from referral, to ordering diagnostic tests and eventual treatment pathway. While standardisation across patient groups allows for automation of some of these processes (templates for referral, standard test orders), allowing a more tailored approach which is patient-specific is the ultimate goal; thus generating a conflict to resolve between standardisation and a tailored patient approach specific to their individual needs.

Flexibility within a process management system requires technological skills to allow tasks to be postponed or reorganised. However, healthcare professionals lack the technical skillset to implement this, requiring a user-friendly interface. Further work in user interface and user experience (UI/UX) is therefore required to ensure a system that allows flexibility without losing the advantages of rapid automation and processing of large numbers of patients within the pathway management systems.

Increasingly call centre staff for websites have been replaced by chatbots that use natural language processing (NLP) to provide callers with information and manage queries. A chatbot is a type of AI programme that can conduct an intelligent conversation via text or auditory methods. It is predicted that by 2025 the global chatbot market will be worth $1.23bn. For hospitals dealing with upwards of 10,000 patient appointments per week, the use of chatbots to handle patient queries regarding appointment queries is still in its infancy when compared to more established sectors such as banking or commerce.

The current COVID-19 pandemic has highlighted the need for rapid screening and testing of patients to improve treatment pathways and also reduce the risk of cross infection. Clinical testing requires taking biological samples from patients which can be resource heavy and incorporates a time lag before results are available from real-time polymerase chain reaction testing (RT-PCR). The use of AI within this environment accessing electronic health records (EHR) of routinely ordered tests and vital signs can produce an effective tool to screen patients in emergency departments and hospital admission units.

Predictive analytics utilise AI algorithms to analyse healthcare data from EHRs to predict future outcomes thus aiming to improve outcomes and the patient experience as well as reducing costs. Data collected from EHRs can be supplemented with data from wearable technology and medical devices. Risk prediction models utilising AI would improve with successive data collection cycles aiming to supplement decision making by clinicians. Applications include management of chronic diseases such as chronic renal failure, diabetes and cardiovascular disease. Specific patient populations can vary across geographical healthcare providers and the ability of a predictive model to learn from its local population provides an advantage over established static modelling. Scalability across healthcare providers can therefore be challenging due to differences in socio-economic factors and populations based on geographical location. The ethical implications in terms of health insurance and risk stratification are in their infancy; and issues around data governance and data sharing may have a significant impact that is yet to be fully regulated.

Diagnostic applications of AI technological advances have exploded over the past ten years with multiple applications. Imaging studies such as breast mammograms or histological analysis rely on skilled scientists or clinicians performing repetitive tasks to manually identify abnormalities. An inaccurate diagnosis can have serious consequences for patient care. AI programmes can be trained to perform these tasks and have shown an accuracy in correctly diagnosing abnormalities which in some studies has been shown to be as accurate as a trained clinician. Further future applications in diagnostic imaging include the field of radiomics which extracts nuanced features peculiar to imaging modalities such as wavelength, texture and shape. This additional information can provide further data for diagnosis and prognostic indicators specific to patients.

With the potential application of AI within the healthcare setting, the question remains how will this impact the workforce? The fourth industrial revolution has 50% of companies to predict that by 2022, automation will decrease their numbers of full-time staff and that by 2030 robots will replace 800 million workers across the world (McKinsey Global Institute reports). Automation of clerical processes and care pathways could potentially impact on the non-clinical workforce within a healthcare setting. Specialties such as radiology where imaging reports can be automated and produced by AI algorithms may soon be the reality. The ethics of data sharing and the implications for patients and their insurers is a further area of controversy. We enter a brave new world.

Caroline B HingYasmin AntoniouAI for Goodwww.aiforgood.co.uk

This article is from issue 15 of Health Europa. Clickhere to get your free subscription today.

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Artificial Intelligence in healthcare and clinical practice in the COVID era - Health Europa