Mediaboss Marketing

Artificial intelligence is continuously evolving and propagating across every industry. With much of the groundbreaking innovations moving the industry forward, the technology is continuously making headlines every day. AI refers to software or systems that perform intelligent tasks like those of human brains such as learning, reasoning, and judgment. Its applications range from automation and translation systems for natural languages that people use daily, to image recognition systems that help identify faces and letters from images. Today, AI is used in different forms include digital assistants, chatbots and machine learning, among others.

Heres a look at the top 10 AI Research Labs in the world that are leading the research and development in AI and related technologies.

The Alan Turing Institute is the national institute for data science and artificial intelligence headquartered in the British Library, London. The institute was created as the national institute for data science in 2015. And in 2017, as a result of a government recommendation, it added AI to its remit. Comprised of 13 universities and the UK Engineering and Physical Science Research Council, the institute helps make the UK the best place in the world for data science and AI research, collaboration, and business. Recently, the Alan Turning Institute shifted its focus to exploring the complicated ethics in the use of AI algorithms and data analytics for predictive purposes by police forces.

LIVIA is a research group accredited by TS which brings together several professors, associate members and graduate students. The laboratorys scientific orientation revolves around the key foundations of large-scale processing, analysis and interpretation of images and videos. LIVIAs R&D activities are based on six main conceptual axes and their main fields of application: (1) machine learning, (2) computer vision, (3) pattern recognition, (4) adaptive and intelligent systems, (5) information fusion, and (6) optimization of complex systems.

J.P. Morgans AI Research team is based in New York and present in key hubs worldwide. The goal of its AI Research program is to explore and advance cutting-edge research in the fields of AI and Machine Learning, also in related fields like Cryptography, to develop solutions that are most impactful to the firms clients and businesses. The firms AI Research team involves experts in various fields of AI. They pursue primary research in areas relative to its research pillars as well as concrete problems related to financial services.

The Machine Learning Research Group at the University of Oxford comprises like-minded research groupings led by local faculty. It is a sub-group within Information Engineering in the Department of Engineering Science of Oxford University. This is one of the core groupings that make up the wider community of Oxford Machine Learning and have a particularly strong overlap with the Oxford-Man Institute of Quantitative Finance. The Oxford ML Research Group uses statistics to handle both information and uncertainty in a variety of research fields, including citizen science, biology, public health, autonomous intelligent systems, and animal husbandry.

ElkanIO Research Labs is an AI research lab based in Cochin, Kerala, India. Founded in 2017 with a mindset to tackle real-world problems, this research lab has hands-on experience in developing Artificial Intelligence and Advanced Analytics solutions to cater to various industry needs. Its three major service lines include Artificial Intelligence Chatbot development, Advanced Data Analytics solutions, and Business Automation solutions powered by Computer Vision, Machine Learning, Deep Learning, and NLP solutions.

As a research institute at the Massachusetts Institute of Technology (MIT), CSAIL is the largest on-campus Laboratory for Computer Science and AI. CSAILs research activities are organized around a number of semi-autonomous research groups, each of which is headed by one or more professors or research scientists. These groups are divided up into seven general areas of research: AI, Computational biology, Graphics and vision, Language and learning, Theory of computation, Robotics, and Systems, including computer architecture, databases, distributed systems, networks and networked systems, and software engineering among others.

UTCS AI-Lab addresses the central challenges of machine cognition, both from a theoretical perspective and from an empirical, implementation-oriented perspective. The Lab has expanded to seven faculty in core areas of AI, with about 50 Ph.D. students, numerous research staff, and a dozen affiliated faculty in related departments. It continues to investigate the challenges of machine cognition, especially machine learning, knowledge representation and reasoning, and robotics.

Microsoft Research AI pursues the use of machine intelligence in new ways to empower people and organizations, including systems that deliver new experiences and capabilities that help people be more efficient, engaged and productive. It brings together the range of talent across Microsoft Research to deliver ground-breaking advances in AI. This R&D initiative coalesces advances in machine learning with innovations in language and dialog, human-computer interaction, and computer vision to solve some of the challenges in AI.

The AI Research Lab brings together UC Berkeley researchers across the areas of computer vision, machine learning, NLP, planning, control, and robotics. The Lab includes over 50 faculty and more than 300 graduate students and postdoctoral researchers pursuing research on fundamental advances in the above areas as well as cross-cutting themes. Those include multi-modal deep learning, human-compatible AI, and connecting AI with other scientific disciplines and the humanities.

USC Information Sciences Institute is a world leader in research and development of advanced information processing, computer and communications technologies. A unit of the University of Southern Californias Viterbi School of Engineering, ISI is one of the nations largest, most successful university-affiliated computer research institutes. The institutions work ranges from theoretical basic research, such as core engineering and computer science discovery, to applied R&D, such as design and modeling of innovative prototypes, and devices.

Read the original:
Top 10 Artificial Intelligence Research Labs in the World - Analytics Insight

Healthcare executives today believe AI will deliver value for the industry faster than previously thought, according to a new survey of senior healthcare executives representing leading hospitals, health plans, life sciences organizations and employers.

The third annual Optum Survey on AI in Health Care found that 59% of respondents expect their organizations to see a full return on their AI investments in under three years. Thats up 90% since 2018, when only 31% of respondents expected to break even that quickly.

The overall anticipated time frame to achieve ROI was 3.6 years in this years survey, down from 5.3 years in 2018 and 4.7 years in 2019.

Confidence in recognizing cost savings from AI appeared to increase as organizations progressed on the maturity curve. Among those who identified themselves as being in the late stages of AI deployment, 57% indicated theyd achieve their ROI in less than two years, as compared to respondents in the early (33%) and mid (26%) stages.

The dramatic drop in the amount of time it will take to achieve ROI is underscored by the effects of a turbulent 2020. In fact, 47% of the leaders reported that the effects of the pandemic would delay their achievement of ROI a finding that suggests the tailwinds of the underlying trend are much stronger than the headwinds of COVID-19 and its economic and social consequences.

AI in the current COVID-19 climate

The survey reported that the executives affirm the strategic importance of AI initiatives in healthcare and that they broadly embrace AI across the industry. Nearly all healthcare leaders98% of themhave an AI strategy in place or plan to create one. That includes the 44% whose organizations have already implemented theirs.

In the survey, healthcare execs prioritized three applications they planned to tap AI for, and each has immediate implications in the battle against the pandemic and its economic and social consequences as we navigate forward:

Monitor data from the Internet of Things devices, such as wearable technology (40%). Internet-connected remote patient monitoring devices like these enable more complete virtual health offerings. AI can also help identify signals and trends within those data streams.

Accelerate research for new therapeutic or clinical discoveries (37%). AI can help prioritize potential investigative targets for treatments or vaccines.

Assign codes for accurate diagnosis and reimbursement (37%). This helps automate business processes to help organizations achieve more even when resources are under duress.

AI creates demands for expertise that will take it to the next level

In broadly confirming AIs strategic value, 95% of healthcare executives said hiring talent with experience developing AI is a priority, with 66% of executives in late stages of AI deployment strongly agreeing, compared to 42% in early and 31% in middle stages.

In addition to building AI competency itself, the ability to act upon AI-driven recommendations is critical. To that end, 92% of the surveyed executives expect that their staff who receive AI-driven insights will understand how the AI works. That finding signals the widespread need for knowledge about analytics, predictions and data streams outside of an organizations traditional information technology or informatics teams.

Executives were split on hiring advanced analytic talent to build the AI (51%) versus business talent to apply the AI-driven results (49%).

Learn more about what healthcare execs are saying about AIs power to:

More:
2020 AI survey: Confidence in artificial intelligence expands as health industry leaders project faster return on investment - Healthcare IT News

There are a plethora of AI initiatives in progress across thehealthcareindustry. From drug discovery to thermal scans, AI has transformed this sector significantly over the past decade. While we know AIs contributions to physical healthcare, AI is also easing mental health concerns too. According to the Substance Abuse and Mental Health Service Administration (SAMHSA)s 2016 reporton drug use and health, only 63% of adults identified as having had at least onemajor depressive episodereported receiving any kind of treatment.

In the US alone, one in five adultssuffersfrom a form of mental illness. Suicide rates are at an all-time high, 115 peopledie daily from substance abuse, and one in eight Americans over 12 years oldtake an antidepressantevery day. The economic burden of depression alone isestimatedto be a minimum of US$210 billion annually, which includes costs due to increased absenteeism and reduced productivity in the workplace. The situation is grim in other regions as well. For instance, in Europe, 83 million people are struggling with mental health. Other than this, people also have to endure stigma, lack of mental health professionals and high costs of counselling sessions too.

Currently, during the world pandemic crisis, even the COVID-19 has been tangibly affecting millions of people in terms of their mental peace. Rates of depression and panic attacks are much higher than normal.Isolation due to social distancing has triggered sleep deprivation, social anxiety, and reduced happiness while also causing people to worry about their jobs. As per a report, 70% of people have had more stress and anxiety at work this year than any other previous year. This increased stress and anxiety have negatively impacted the mental health of 78% of the global workforce, causing more stress (38%), a lack of work-life balance (35%), burnout (25%), depression due to lack of socialization (25%), and loneliness (14%). A recent report by Deloittesuggests COVID-19s impact on mental health could last for years

While, AI is proving to be an effective way for clinicians to both make the best of the time they do have with patients, and bridge any gaps in access, it has also helped in early prediction and diagnosis of the diseases too. So, incorporating AI to address mental health issues can achieve similar promising results. For starters, this can be done by employing AI into digital interventions, like web andsmartphoneapps, to enhance user experience and optimize personalized mental health care. One can analyze modern streams of abundant data as a means to develop prediction or detection models for mental health conditions. E.g. Quartet Health, has reduced hospitalization of patients by 15-25% by screening patient medical histories and behavioral patterns to uncover undiagnosed mental health problems.

Vanderbilt University Medical Center in Nashville has created a machine learning algorithm that uses hospital admissions data, including age, gender, zip code, medication, and diagnostic history, to predict the likelihood of any given individual taking their own life.Scientists are experimenting with linear classifiers of Natural Language Processing (NLP) to risk assessment in possible PTSD cases.

Also, while AI would not replace existing therapists and psychiatrists, it surely provides a medium where people can talk about their struggles without the fear of being judges or facing stigma. Further, AIcan help doctors and therapists increase emotional awareness for their patients, such as in expressing empathy. Research has also proved that AI helped employees improvetheir mental health at work.

Next, we have emotional AI-powered chatbots (like Wysa, Woebot) that can provide unprecedented accessibility by being available 24/7 at little to no cost. These apps collect data that allow them to create a level of therapeutic rapport with users and offer relevant responses. Mood tracking apps like Woebot, which is created by a team of Stanford psychologists and AI experts, uses brief daily chat conversations, mood tracking, curated videos, and word games to help people manage mental health. This is faster and comfortable than traditional practice in mental health where professionals rely on the individual to observe and self-report indicative changes. E.g. IBMs Computational Psychiatry and Neuroimaging group, alongside several universities, have built a model using NLP to predict the onset of psychosis in patients. This model can detect differences in speech patterns between high-risk patients who develop psychosis and those who did not. At present, a team of scientists at Dublin, Ireland-based startup Behavidence is currently preparing to launch an effective digital phenotyping solution that can provide an accurate psychiatric diagnosis for ADHD.

Mental health will likely remain a major challenge in todays world due to various reasons. Although AI for mental health still needs to deal with many complexities, its applications and tools are doing an appreciable job in alleviating this issue for many. Soon it will be well equipped to mitigate and manage the stress, depression and trauma, things which are living hell for many.

See original here:
Easing the lives of Mental Health Patients via Artificial Intelligence - Analytics Insight

The ongoing pandemic has undoubtedly impacted business models but it didnt wane the impact AI has on our lives and businesses

In today's digitally driven world, many organisations use AI-powered chatbots in business communication, primarily for customer support and sales

The AI-powered chips are predicted to reach a revenue of $91,185 Mn in 2025

Artificial Intelligence, once a buzzword in the digital world, has become a part of our everyday life. From Google Assistant, Siri, Alexa to Uber and Ola, several AI-enabled services are available today that make our lives easier. The ongoing pandemic has undoubtedly impacted business models but it didnt wane the impact AI has on our lives and businesses. On the contrary, it has become evident that Artificial Intelligence, with its self-teaching and learning algorithms, will play an essential role in transforming businesses in 2021.

Companies have swiftly started leveraging the potential of AI. Companies like Amazon, Microsoft, and Google have grown immensely due to the incorporation of AI for forecasting, adapting to changing market conditions and generating profit. Several companies are already reaping the benefits of their early investment in Artificial Intelligence. Many have started incorporating AI to utilise the huge amount of data generated each day. But how is AI bringing revolutionary changes across industries? Lets take a look.

In todays digitally driven world, many organisations use AI-powered chatbots in business communication, primarily for customer support and sales. Chatbots effectively increase customer engagements, help collect data, and drive business revenues; they effectively bring down operational costs as well. AI-powered chatbots decrease the need for human intervention and enable businesses to engage and interact with customers during non-working hours. This also brings down the need for floor space and conventional customer support equipment. According to a report by Juniper Research, ecommerce transactions via chatbots are predicted to grow up to $112 Bn by 2023.

AI-powered chips will enable applications that run on AI algorithms like object detection, computer vision, facial recognition, and Natural Language Processing (NLP) to perform much faster. These chips boost the performance of applications used in gaming, healthcare, banking & finance, and manufacturing industries.

Qualcomm recently launched its new AI-enabled Snapdragon 732G to enhance the high-tier mobile gaming experience. Another popular example of the implementation of AI in an industrial and commercial environment is the AI-powered BMW factory in Germany. The automobile factory uses AI-based software to check auto parts and perform a complete inspection in milliseconds. The AI-powered chips are predicted to reach a revenue of $91,185 Mn in 2025.

Data is the new currency in todays digitally driven world. The generation of data is growing by leaps and bounds with each passing day. For startups to stay ahead in the competitive business world, it has become imperative to adopt advanced analytics and AI for creating dynamic business models. AI-based systems and solutions will help start-ups with data mining, analysis of business data, and implementing predictive analytics to determine strategic marketing based on customer insights.

With data becoming more accessible, there has been a massive rise in cyberattacks. Companies are investing more in improving their organisations cybersecurity infrastructure. AI, with its advanced predictive algorithms, will play a crucial role in facilitating cybersecurity in organisations. By incorporating AI in cybersecurity, companies will be able to reduce the response time to threats as well as the expense of preventing breaches. AI will also help in preventing cybercrimes by enhancing the organisations cybersecurity measures.

One of the most common examples of AI-powered applications in our daily life is voice-based searches. AI-powered voice-based applications like Apples Siri, Google Assistant, and Amazons Alexa have set the benchmark high on how people will look for anything online. In the future, people will use voice commands more often rather than type it. According to Statista, globally, around 8 Bn digital voice assistants will be in use by 2023.

Innovations in Artificial Intelligence, with its huge potential, is transforming businesses by boosting work efficiency, enhancing productivity, and elevating an organisations profitability, and will continue to do so in the future. AI-powered applications and services provide solutions for every industry, starting from IT, retail, banking, and healthcare to eCommerce.

Read the rest here:
Five Ways How Artificial Intelligence Will Transform Businesses in 2021 - Inc42 Media

CrushBank Insight

Insight Debuts at IT Nation Connect

At the event, CrushBank experts will be available to discuss Insight,which ingests entire support data sets, classifies them precisely andgenerates objective metrics for meaningful classification

SYOSSET, N.Y., Nov. 05, 2020 (GLOBE NEWSWIRE) -- The creators of CrushBank, an artificial intelligence (AI) solution that leverages the power of IBM Watson and Natural Language Processing to provide answers used in IT support, have released a revolutionary new offering, CrushBank Insight. After ingesting a clients entire interactive data set (tickets, time entries and more), Insight classifies each datapoint by key concept (root cause) and by customer and engineering sentiment (client satisfaction). The resulting dataset supports creation of objective metrics for customer success and trends as well as classification by true root cause rather than by initial client or triage best guess.

Insights debut was timed to align with IT Nation Connect, slated for November 10-12, 2020. David Tan, CTO of CrushBank, is speaking at the event, where he will explore the future of AI and the growing imperative for structured access to unstructured data. He and other CrushBank experts will also be available via the firms virtual booth to discuss the development of CrushBank and Insight, as well as how the firm and its AI-powered solutions help IT firms dramatically boost the success metrics and output of their support teams.

IT experts have long envisioned a perfect world where every MSP could gather historical data documents, interactions, names, faces and more into a single resource and use technology to analyze that pool of data, finding and making connections to create a structured web of knowledge, said Tan. This world is here, now, and CrushBank Insight is a key piece of this solution. With any other tool, businesses would remain trapped in the endless cycle of guess-resolve-repair, with their IT departments engaged in perennial firefighting. With CrushBank Insight, IT teams gain meaningful historical insights, backed by actual data, that replace conjecture with educated decision making.

Insight can analyze customer sentiment by any filtered resource (engineer, customer, technology, region, etc.) and, in a matter of seconds, create functional reports to drive internal decision making. It informs and streamlines customer road maps that would otherwise take hours to compose and would still be only as good as the data classification produced by a triage resource.

Through extensive research and interviews, CrushBank found that most IT engineers spend 50% of their time looking for answers to common support questions including system specifications and historical ticketing information. CrushBank also determined that 80% of those answers cant be found even when they are in the database because it hasnt been properly indexed.

Our guiding principal has always been that superior business intelligence begins with great data, and the information that makes a company uniquely valuable to a customer is right there within these datasets, said Tan. With Insight, we now can provide rich, solution-driven understanding based on the greatest possible pool of input, enabling companies to unlock their data and reap maximum value for themselves and the customer.

About CrushBankBorn from the frustration over inefficiencies in operating a managed IT service business, CrushBank is the first IT Help-Desk application built on Watson, the breakthrough cognitive technology developed by IBM. Founded by two veteran MSP owners with more than 25 years of experience, CrushBank uses cognition, the process of acquiring knowledge, to think, learn and inform decisions in the same way engineers and support teams do. CrushBank combines best-practice documentation with a firms proprietary content and historical ticket information to provide invaluable insight. The system ingests large volumes of unstructured data, reads and understands it, and uses machine learning to find the right answers to questions instantly. Simply put, CrushBank streamlines help-desk operations resulting in fewer escalations to Level 2 and above. Your help-desk engineers see an increase in productivity and their end users experience increased satisfaction with more intimate first-call resolutions. For more information, visithttp://www.crushbank.com.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/d7e1c9ef-5b14-4718-a179-8a64a5f7e14d

Read more from the original source:
CrushBank Debuts Insight Just in Time for IT Nation Connect; Exclusive Artificial Intelligence Delivers Support Metrics by Actual Root Cause -...