Category Archives: Artificial Intelligence
A.I. Can Now Write Its Own Computer Code. Thats Good News for Humans. – The New York Times
As soon as Tom Smith got his hands on Codex a new artificial intelligence technology that writes its own computer programs he gave it a job interview.
He asked if it could tackle the coding challenges that programmers often face when interviewing for big-money jobs at Silicon Valley companies like Google and Facebook. Could it write a program that replaces all the spaces in a sentence with dashes? Even better, could it write one that identifies invalid ZIP codes?
It did both instantly, before completing several other tasks. These are problems that would be tough for a lot of humans to solve, myself included, and it would type out the response in two seconds, said Mr. Smith, a seasoned programmer who oversees an A.I. start-up called Gado Images. It was spooky to watch.
Codex seemed like a technology that would soon replace human workers. As Mr. Smith continued testing the system, he realized that its skills extended well beyond a knack for answering canned interview questions. It could even translate from one programming language to another.
Yet after several weeks working with this new technology, Mr. Smith believes it poses no threat to professional coders. In fact, like many other experts, he sees it as a tool that will end up boosting human productivity. It may even help a whole new generation of people learn the art of computers, by showing them how to write simple pieces of code, almost like a personal tutor.
This is a tool that can make a coders life a lot easier, Mr. Smith said.
About four years ago, researchers at labs like OpenAI started designing neural networks that analyzed enormous amounts of prose, including thousands of digital books, Wikipedia articles and all sorts of other text posted to the internet.
By pinpointing patterns in all that text, the networks learned to predict the next word in a sequence. When someone typed a few words into these universal language models, they could complete the thought with entire paragraphs. In this way, one system an OpenAI creation called GPT-3 could write its own Twitter posts, speeches, poetry and news articles.
Much to the surprise of even the researchers who built the system, it could even write its own computer programs, though they were short and simple. Apparently, it had learned from an untold number of programs posted to the internet. So OpenAI went a step further, training a new system Codex on an enormous array of both prose and code.
The result is a system that understands both prose and code to a point. You can ask, in plain English, for snow falling on a black background, and it will give you code that creates a virtual snowstorm. If you ask for a blue bouncing ball, it will give you that, too.
You can tell it to do something, and it will do it, said Ania Kubow, another programmer who has used the technology.
Codex can generate programs in 12 computer languages and even translate between them. But it often makes mistakes, and though its skills are impressive, it cant reason like a human. It can recognize or mimic what it has seen in the past, but it is not nimble enough to think on its own.
Sometimes, the programs generated by Codex do not run. Or they contain security flaws. Or they come nowhere close to what you want them to do. OpenAI estimates that Codex produces the right code 37 percent of the time.
When Mr. Smith used the system as part of a beta test program this summer, the code it produced was impressive. But sometimes, it worked only if he made a tiny change, like tweaking a command to suit his particular software setup or adding a digital code needed for access to the internet service it was trying to query.
In other words, Codex was truly useful only to an experienced programmer.
But it could help programmers do their everyday work a lot faster. It could help them find the basic building blocks they needed or point them toward new ideas. Using the technology, GitHub, a popular online service for programmers, now offers Copilot, a tool that suggests your next line of code, much the way autocomplete tools suggest the next word when you type texts or emails.
It is a way of getting code written without having to write as much code, said Jeremy Howard, who founded the artificial intelligence lab Fast.ai and helped create the language technology that OpenAIs work is based on. It is not always correct, but it is just close enough.
Mr. Howard and others believe Codex could also help novices learn to code. It is particularly good at generating simple programs from brief English descriptions. And it works in the other direction, too, by explaining complex code in plain English. Some, including Joel Hellermark, an entrepreneur in Sweden, are already trying to transform the system into a teaching tool.
The rest of the A.I. landscape looks similar. Robots are increasingly powerful. So are chatbots designed for online conversation. DeepMind, an A.I. lab in London, recently built a system that instantly identifies the shape of proteins in the human body, which is a key part of designing new medicines and vaccines. That task once took scientists days or even years. But those systems replace only a small part of what human experts can do.
In the few areas where new machines can instantly replace workers, they are typically in jobs the market is slow to fill. Robots, for instance, are increasingly useful inside shipping centers, which are expanding and struggling to find the workers needed to keep pace.
With his start-up, Gado Images, Mr. Smith set out to build a system that could automatically sort through the photo archives of newspapers and libraries, resurfacing forgotten images, automatically writing captions and tags and sharing the photos with other publications and businesses. But the technology could handle only part of the job.
It could sift through a vast photo archive faster than humans, identifying the kinds of images that might be useful and taking a stab at captions. But finding the best and most important photos and properly tagging them still required a seasoned archivist.
We thought these tools were going to completely remove the need for humans, but what we learned after many years was that this wasnt really possible you still needed a skilled human to review the output, Mr. Smith said. The technology gets things wrong. And it can be biased. You still need a person to review what it has done and decide what is good and what is not.
Codex extends what a machine can do, but it is another indication that the technology works best with humans at the controls.
A.I. is not playing out like anyone expected, said Greg Brockman, the chief technology officer of OpenAI. It felt like it was going to do this job and that job, and everyone was trying to figure out which one would go first. Instead, it is replacing no jobs. But it is taking away the drudge work from all of them at once.
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A.I. Can Now Write Its Own Computer Code. Thats Good News for Humans. - The New York Times
Why robotics and artificial intelligence will be bigger than the discovery of the New World | Column – Tampa Bay Times
Having spent more than 25 years working with industry partners to educate and prepare the future workforce, it is not surprising to see that Florida has experienced growth in the technology sector.
Across the nation, the U.S. Bureau of Labor Statistics estimates that computer and information technology occupations are projected to grow 11 percent from 2019 to 2029, much faster than the average for all occupations. Additionally, demand for skilled professionals in robotics and artificial intelligence is growing. The World Economic Forum estimates that while 85 million jobs will be displaced, 97 million new jobs will be created across 26 countries by 2025 due to the growth of artificial intelligence technology.
From my conversations with industry leaders to the research and data Ive studied, all signs lead me to believe that robotics and artificial intelligence will be a significant economic driver, surpassing the impact of Christopher Columbus exploration of the New World in 1492.
While Columbus used sophisticated technology that was highly advanced for his time, he was still required to convince Queen Isabella that his trip and tools had value. His technology included the compass, maps, and charts that helped him navigate what many considered a nearly unthinkable journey.
Today, few in our modern world need to be convinced that computing and other advanced technologies, including robotics and artificial intelligence, have value.
While certainly some people fear technology will impact us negatively with the loss of jobs or human touch, others see technologies like robotic surgery or manufacturing as protections that can help heal people faster or make work more effective. Today, robots are largely sophisticated tools that are as amazing and mindboggling as the compass and quadrant were in Columbus time.
While Columbus trip changed the world, it took hundreds of years for its impact to be understood and capitalized upon. Robotics, as a field of practice and study, rapidly will change the future for graduates, and all of us, with new technologies being employed each year.
The idea of a robot may bring to mind images of Commander Data from Star Trek, or more frighteningly, the robots featured in The Terminator, but the field of robotics is much broader than those perceptions.
According to the Institute of Electrical and Electronics Engineers, there are many types of robots from those in aerospace, to consumer products, disaster response, drones, autonomous vehicles, and exoskeletons, to industrial robots, and medical robots, among others. In 2019, an article in Oxford Economics revealed that the number of robots in use worldwide multiplied three-fold over the past two decades, to 2.25 million. In many cases, robots are simply machines that are programmed to perform tasks or take actions. They are able to do things in anticipation of needs, based on artificial intelligence coding.
A final point to consider is the impact on the economy. After Columbus journey, trade between nations became prevalent and a new economic system was born. Likewise, demand for robotics and artificial intelligence technology will grow and create new efficiencies. PriceWaterhouseCoopers Global Artificial Intelligence Study predicts that by 2030, growth of artificial intelligence will lead to an estimated $15.7 trillion, or 26 percent increase, in global gross domestic product.
Demand for robotics engineers and technicians also will grow, given the need for designing and maintaining robots. There also will be strong demand for application developers for robotic systems and solutions. So, while some fear that robots and artificial intelligence will take away jobs from humans, they will create many more jobs and careers.
With what I now know today, if I could go back and change my college major, I would select robotics. There are many opportunities in this growing field. It is multidisciplinary, creative, impactful, and would allow me to innovate. It is and will be the next big discovery in our world.
Jeffrey D. Senese, PhD, is the president of Saint Leo University, a private, nonprofit Catholic university based in Pasco County, FL. Saint Leo is the largest Benedictine Catholic university in the world, educating more than 18,000 students each year. This fall, the university is launching a bachelors degree in robotics and artificial intelligence and opening a new college dedicated to the growing field.
AAMC Comments on National Artificial Intelligence Initiative – AAMC
The AAMC submitted a letter to the White House Office of Science and Technology Policy (OSTP) and the National Science Foundation (NSF) on Sept. 1 in response to a request for information (RFI) geared toward developing a shared, national artificial intelligence (AI) research infrastructure that is referred to as the National Artificial Intelligence Research Resource (NAIRR).
The RFI will inform the work of the NAIRR Task Force, which has been directed by Congress to develop a first-of-its-kind AI infrastructure that provides AI researchers and students across scientific disciplines with access to computational resources, high-quality data, educational tools, and user support.
In its comments, the AAMC expressed strong support for Congress prioritization of AI, which has tremendous potential to advance human health and usher in a new era of biomedicine. The AAMC also commended the aspirations of the OSTP and the NSF to develop an inclusive AI infrastructure that allows all of America's diverse AI researchers to fully participate in exploring innovative ideas for advancing AI, including communities, institutions, and regions that have been traditionally underserved.
The letter outlined strategies on how the NAIRR should reinforce principles of ethical and responsible research and development of AI. In particular, the AAMC underscored the necessity of building a NAIRR that identifies and addresses systemic inequities at the interface of AI and biomedicine, mitigates bias by promoting representative datasets and algorithms, provides users with a data management and sharing plan that promotes community engagement and transparency, and fosters a diverse AI workforce and leadership.
Given the vast amounts of data, industries, and applications that will converge with the NAIRR, the AAMC also noted the importance of a multisector approach for identifying, researching, and mitigating bias, discrimination, health inequities, and social determinants of health all components that currently preclude the formation of an equitable AI framework that benefits all communities equally.
Finally, the AAMC recommended that the NAIRR partner with diverse communities in the development of this framework, thereby culminating a diverse expertise and fostering community trust. On Aug. 18, the OSTP and the NSF extended the RFIs public comment period by one month to Oct. 1, providing further opportunity for researchers and academic institutions to respond.
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AAMC Comments on National Artificial Intelligence Initiative - AAMC
Is Artificial Intelligence Set To Take Over The Art Industry? – Forbes
Arushi Kapoor
Many people considered it a formless blur of colors, an image that was abstract but slightly resembling a human face. The image isnt even properly positioned on the canvas, rather it is skewed towards the northwest.
In October 2018, this art piece: Portrait of Edmond de Belamy, an algorithm-generated print, was sold for $432,500, thus beginning the AI-Art goldRush.
Humans have always created and enjoyed all forms of art, for viewing purposes, for aesthetic purposes, and even for therapeutic purposes. Since the discoveries of an artistic shell carved by homoerectus, the art business has grown in leaps and bounds and become a highly profitable industry. Leonardo Davincis, Salvator Mundi went for $450.3 million, becoming the most expensive art piece to date.
Understanding and thriving in this industry is not as easy as it may appear, it requires a lot of knowledge, time, and exposure. 25-year-old Arushi Kapoor is the CEO and co-founder of ARTSop art consulting, is an entrepreneur who boasts all of these traits. She is also the founder of Arushi, a cultural center and art warehouse based in Echo Park, Los Angeles.In this article, Kapoor shares her knowledge of the art industry and the influence that tech and AI have on it.
Technology has impacted the way art is created and enjoyed for the better part of the last 100 years, the invention of portable paint tubes enabled artists to paint outdoors and sparked a contingent of stunning landscape and horizon paintings. Today cameras and software like Photoshop have redefined the way art is created and enjoyed.
Kapoor, who is herself a tech-enthusiast agrees that these advancements have been great, but insists that they have not changed the antiquated meaning of art.
I will always be grateful for technology and technological advancements, says Kapoor.I wouldnt have a business or be able to do what I have done in the industry since the age of 19, had it not been for technologies of various kinds.
She continues,However, in my experience, I feel that there is still and will always be that reverence in the hearts of art lovers towards handmade art and crafts. Technological creations have great utility and aesthetic value, but paintings and craft tend to have what I refer to as artistic glory. Human creativity is what art is all about. Technology is a help to it, not a full replacement for it.
Kapoors foray into the industry dates back to when she wrote her first book, Talking Art at age 19. With that book, she put the world on notice that art was not going to be just a fleeting interest for her. Kapoor grew up in India, Europe, and the US, and this multicultural exposure has certainly influenced her knowledge and understanding of art.
Kapoor is the director of Arushi, a US-based venture that made history as the first to present a sold-out all-Indian art show; Art of India, Reclaiming The Present.
ArtSop Consulting, a facet of Arushi, provides private art consulting to people around the world, buying and selling art for clients in the secondary art market. Additionally, ArtSop represents primary artists that are featured in the art warehouse, Arushi.
Kapoor is also a technology investor, who has done a lot of research and invested capital into AI-driven art startups that are moving the needle when it comes to the future of art tech.
Kapoor comments that the integration of AI and art has been received with mixed feelings.
Personally, I havent seen any extraordinary artworks created by AI exclusively yet, she says. I think there is always going to be some human intervention required to create out of the park art. I recently heard, DeviantArt is an AI tool thats helping find stolen artworks. Thats extraordinary and thats how I believe AI can make a positive impact on the art world
The success of the AI-generated Portrait of Edmond de Belamy seems to have sparked off a series of AI art creations all wanting to cash out on the AI intrigue among some high spending art lovers.
In a recent exhibition of prints shown at the HG Contemporary gallery in Chelsea, the epicenter of New Yorks contemporary art world, 20 prints were displayed as part of the Faceless Portraits Transcending Time.
The ARTSop CEO isnt necessarily intrigued by this development, Kapoors MO has always been about highlighting upcoming local and female contemporary artists who have no platform to showcase their creations. In the opening of her Invite-only warehouse in LA, she featured a local female artist, Lindsay Dawn, for her first exhibition. Kapoor believes that real art should be discovered and celebrated.
If AI prints continue to sell for huge amounts it may de-incentivize actual human creation and creativity, says Kapoor.
Arushi Kapoor
At the rate at which technology is being accepted in every industry, it is no longer difficult to imagine a future where fewer artists are creating because they lack platforms to sell. Arushi along with many other art companies and galleries, hopes to find a balance and to create an ecosystem where both kinds of art can co-exist in the future. This shift to accepting non man made artworks isnt widely accepted currently. I am optimistic that there would always be a large section of art lovers who prefer man-made creations or perhaps love both.
Artificial Intelligence wasnt initially applied to art as a creator but as an impersonator. The technique is called style transfer and it uses deep neural networks to replicate, recreate and blend styles of artwork, by teaching the AI to understand existing pieces of art. Alexandra Squire is an excellent example of how the very human process of making art is not easily replicated. Squire believes art is a universal language with vast meanings, and focuses on art that is substantial, open to interpretation, and rich in depth and texture.
The increased usage of all kinds of AI in all kinds of art suggests that it is here to stay. From the AI-written book, 1 The Road, to Anna Riddlers AI-generated blooming tulip videos, creators have found value in utilizing artificial intelligence.
The question then becomes, is AI the future of the art industry? Kapoor shares her sentiment on this pertinent question.
Kapoor adds, The more optimistic view is that artificial intelligence evolves into a greater tool for existing creators to enhance, discover and replicate their works. We all hope for a world where our technologies help us, and not replace us.
Kapoors perspective on the future of art and AI is probably the most tenable and desirable. There is a strong perception amongst art lovers that machines can not produce art in the real sense of the word.
This sentiment is partly true because so far, AI has only demonstrated an ability to study and understand existing art and to somehow enhance or combine them to produce something new, and in some cases, something better.
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Is Artificial Intelligence Set To Take Over The Art Industry? - Forbes
Five Indian companies that are leading the AI race – Mint
AI has become intertwined with every aspect of our lives. Each one of us is currently using this technology in one form or the other. From personal digital assistants like Siri, google assistant, Alexa, to self-driving cars, its being used very widely.
The use is increasing on a daily basis in fast growing sectors such as healthcare, finance, e-commerce, and manufacturing.
Also, businesses like Swiggy and Zomato, which have invested heavily in AI over the past couple of years, have witnessed the power of technology to both sustain and increase growth. This has steered the discussion towards AIs potential for other companies in India.
According to a report by Accenture, its expected that AI has the potential to make up 15% of Indias current gross value in 2035 or US$957 bn.
In the coming years, AI will transform the way we live and work.
With increasing demand for AI technology, investor interest in AI stocks has also increased.
Heres the list of top Indian companies working on AI in the Indian stock market.
1. Coforge
Coforge is an IT services company providing end-to-end software solutions and services.
It is among the top-20 Indian software exporters.
The company was formerly known as NIIT Technologies and was incorporated in April 2003.
It provides AI-based digital business assistants, deep learning, machine learning, multi-currency, multi-lingual, multi-channel experience, image recognition, robotic process automation (RPA), natural language processing (NLP), and workflow automation.
In the past, the company has made a few acquisitions to increase revenue and enhance geographical and customer presence.
In April 2021, Coforge completed its strategic investment in SLK Global Solutions. SLK Global has deep domain expertise in the banking and insurance segments in North America. It enjoys multiple long-standing and scalable relationships with marquee clients with strong growth potential.
Over the span of five years, the company has given a return of 1,202%. Currently, shares of Coforge are trading at 5,136 per share.
2. Happiest Minds Technologies
Happiest Minds is an IT consulting and services firm that was founded in 2011.
The company works on disruptive technologies such as artificial intelligence, cloud, internet of things (IoT), blockchain, robotics/drones, virtual reality, and other services.
Artificial intelligence is used by the firm for language processing, picture analytics, video analytics, and upcoming technologies such as AR and VR.
In addition, the company assists organisations in using robots using AI, leading to time and cost savings.
In September 2020, the firm was listed on the stock exchange. Its one of the most popular Indian artificial intelligence stocks.
Ashok Soota the executive chairman of the company is the main promoter and was earlier founding Chairman & MD of Mindtree. Prior to Mindtree, he led Wipros IT business for fifteen years.
Since its listing, the company has managed to give a return of 290.8%. Happiest Minds shares are trading at 1,445 on the BSE.
3. Saksoft
Saksoft is a leading provider of information management solutions to successful companies around the world.
The company is a mid-sized IT company and provides end-to-end business solutions that leverage technology and enables their clients to enhance business performance.
It mainly focuses on getting transformations through efficiency, productivity, enhanced customer decisions, and service innovations by increasing the combination of AI and automation.
Saksoft gives a boost to digital transformation and applies intelligent automation to solve major business problems with the assistance of modern technology like IoT, AI, machine learning, and automation.
The company has delivered good profit growth of 20.1% compound annual growth rate (CAGR) over last 5 years. Saksoft shares are trading at 913 on the BSE.
4. Tata Elxsi
Founded in 1989, Tata Elxsi is a part of the Tata Group and performs in the midcap range in the stock market.
Today Tata Elxsi is one of the leading providers of design and technology services in various industries. These include automotive, broadcasting, communication, healthcare, and transportation.
When it comes to AI, the company has had success in various fields like self-driving cars, video analytics solutions etc.
Tata Elxsi Artificial Intelligence Centre of Excellence addresses the increasing demand for intelligent systems. It allows its customers to use cloud-based integrated data analytics frameworks that feature patent-pending technology to get actionable insights and outstanding returns.
On the financial front, the company has performed well over the last few quarters. It has had a compounded profit growth of 19% for the last 5 years.
In the past five years, stock has provided 535% return compared to Nifty IT that returned 95% returns to the investors.
5. Persistent Systems
Persistent Systems offers a secure and scalable mobile networking capability based on its cutting-edge Wave Relay MANET technology.
Persistents products provide a total solution consisting of voice, video, and situational awareness to mobile users with no reliance on fixed infrastructure.
Also, the company has developed machine learning and AI solutions that help companies at every stage of their AI and machine learning development.
It uses AI to help companies improve and scale their operations, prioritise cases, and designs platform architecture.
Financially the company has performed well. It has achieved a compounded profit growth of 10% and sales growth of 13% over the last five years.
In the last five years, the stock gave returns of 462%. Currently, shares of Persistent Systems are trading at 3,479 per share.
Apart from the above, heres the list of more AI-based stocks to watch out for in India.
View Full Image
In conclusion
Today, AI is a crucial tool for many businesses and the market for the technology is growing quickly in India.
From online shopping to the data used for scholastic tasks, AI has become an integral part of human life.
Also, many Indian start-ups are expanding and developing AI solutions in education, health, financial services, and other fields.
For the last few years, it has been attracting numerous companies to adapt to the trend, driving investments towards them, due to its increasing demand in the present and future.
Investing in digital technologies can create huge revenue in the coming years.
If youre thinking about buying artificial intelligence stocks, you should look out for companies that are focused on AI businesses in India with excellent technical and business fundamentals, minimal debt, and are available at attractive valuations.
Happy Investing!
(This article is syndicated from Equitymaster.com)
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Five Indian companies that are leading the AI race - Mint
Artificial Intelligence and the Humanization of Medicine InsideSources – InsideSources
If you want to imagine the future of healthcare, you can do no better than to read cardiologist and bestselling author Eric Topols trilogy on the subject: The Creative Destruction of Medicine, The Patient Will See You Now, and Deep Medicine.
Deep Medicine bears a paradoxical subtitle: How Artificial Intelligence Can Make Healthcare Human Again. The book describes the growing interaction of human and machine brains. Topol envisions a symbiosis, with people and machines working together to assist patients in ways that neither can do alone. In the process, healthcare providers will shed some of the mind-numbing rote tasks they endure today, giving them more time to focus on patients.
I recorded an interview with Topol in which we discuss his books. The podcast is titled Healthcares Reluctant Revolution because one of Topols themes is that healthcare is moving too slowly to integrate AI and machine learning (ML) into medicinea sluggishness that diminishes the quality and quantity of available care.
The first of Topols books, Creative Destruction, described how technology would transform medicine by digitizing data on individual human beings in great detail. In The Patient Will See You Now, he explored how this digital revolution can allow patients to take greater control over their own health and their own care. With this democratization of care, medicines ancient paternalism could fade. (In 2017, Topol and I co-authored an essay on Anatomy and Atrophy of Medical Paternalism.)
Deep Medicine is qualitatively different from the other two books. It has an almost-mystical quality. Intelligent machines engaging in AI and ML arrive at information in ways even their programmers can barely comprehend, if at all. Topol gives a striking example.
Take retinal scans of a large number of peoplethe sort of scans that your optometrist or ophthalmologist takes. Now, show the scans to the top ophthalmologists in the world and ask for each scan, Is this person a man or a woman? The doctors will answer correctly approximately 50 percent of the time. In other words, they have no idea and could do just as well by tossing a coin. Now, run those same scans through a deep neural network (a type of AI/ML system). The machine will answer correctly around 97 percent of the timefor no known reason.
Topol explains how such technologies can improve care. Today, radiologists spend their days intuitively searching for patterns in x-rays, CT scans, and MRIs. In the future, much of the pattern-searching will be automated (and more accurate), and radiologists (who seldom interact with patients today) will have much greater contact with patients.
Today, dermatologists are relatively few in number, so much of the earlier stages of skin care are done by primary care physicians, who have less ability to determine, say, whether a mole is potentially cancerous. The result can be misdiagnosis, delayed diagnosis, and the unnecessary use of dermatologists time. In the future, primary care doctors will likely screen patients using smart diagnostic tools, thereby wasting less of patients and dermatologists time and diagnosing more accurately.
In Deep Medicine, Topol tells the story of a newborn experiencing seizures that could lead to brain damage or death. Routine diagnostics and medications werent helping. Then, a blood sample was sent to a genomics institute that combed through a vast amount of data in a short time and identified a rare genetic disorder thats treatable through dietary restrictions and vitamins. The child went home, seizure-free, in 36 hours.
Unfortunately, healthcares adoption of such technologies is unduly slow. In our conversation, Topol noted that we have around 150 medical schools, some quite new, and yet they dont have any AI or genomics essentially in their curriculum.
Topol lists some hopes that observers invest in AI: Machines outperforming doctors at all tasks, diagnosing the undiagnosable, treating the untreatable, seeing the unseeable on scans, predicting the unpredictable, classifying the unclassifiable, eliminating workflow inefficiencies, eliminating patient harm, curing cancer, and more.
A realistic sort of optimist, Topol writes: Over time, AI will help propel us toward each of these objectives, but its going to be a marathon without a finish line.
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Artificial Intelligence and the Humanization of Medicine InsideSources - InsideSources
Current uses, emerging applications, and clinical integration of artificial intelligence in neuroradiology – DocWire News
This article was originally published here
Rev Neurosci. 2021 Sep 10. doi: 10.1515/revneuro-2021-0101. Online ahead of print.
ABSTRACT
Artificial intelligence (AI) is a branch of computer science with a variety of subfields and techniques, exploited to serve as a deductive tool that performs tasks originally requiring human cognition. AI tools and its subdomains are being incorporated into healthcare delivery for the improvement of medical data interpretation encompassing clinical management, diagnostics, and prognostic outcomes. In the field of neuroradiology, AI manifested through deep machine learning and connected neural networks (CNNs) has demonstrated incredible accuracy in identifying pathology and aiding in diagnosis and prognostication in several areas of neurology and neurosurgery. In this literature review, we survey the available clinical data highlighting the utilization of AI in the field of neuroradiology across multiple neurological and neurosurgical subspecialties. In addition, we discuss the emerging role of AI in neuroradiology, its strengths and limitations, as well as future needs in strengthening its role in clinical practice. Our review evaluated data across several subspecialties of neurology and neurosurgery including vascular neurology, spinal pathology, traumatic brain injury (TBI), neuro-oncology, multiple sclerosis, Alzheimers disease, and epilepsy. AI has established a strong presence within the realm of neuroradiology as a successful and largely supportive technology aiding in the interpretation, diagnosis, and even prognostication of various pathologies. More research is warranted to establish its full scientific validity and determine its maximum potential to aid in optimizing and providing the most accurate imaging interpretation.
PMID:34506699 | DOI:10.1515/revneuro-2021-0101
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Current uses, emerging applications, and clinical integration of artificial intelligence in neuroradiology - DocWire News
Region’s AI sector has potential according to think tank – Times Union
Sep. 10, 2021Updated: Sep. 10, 2021 2:41p.m.
An IBM researcher holds a silicon wafer with embedded IBM Telum chips designed to maximize artificial intelligence capabilities. The chips were developed at Albany Nanotech and made in partnership with Samsung. The Albany area was recent cited by the Brookings Institution for having the potential to create an AI sector.
ALBANY The Capital Region is one of 87 "potential adoption centers" in the United States for companies and researchers focused on the use of artificial intelligence, or AI, according to a new report from the Brookings Institution, a left-leaning think tank. The San Francisco Bay area is No. 1 in AI, while other upstate cities, Buffalo, Rochester and Syracuse, were also listed as potential adoption centers.
The Center for Economic Growth in Albany highlighted the Brookings list as part of its own report recently published on AI research and development in the Capital Region at local universities and at companies such as IBM and General Electric.
Larry Rulison has been a reporter for the Albany Times Union since 2005. Larry's reporting for the Times Union has won several awards for business and investigative journalism from the New York State Associated Press Association and the New York News Publishers Association. Contact him at 518-454-5504 or lrulison@timesunion.com.
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Region's AI sector has potential according to think tank - Times Union
The Role of Artificial Intelligence in Compliance and Security Oversight – International Banker
By Shiran Weitzman, CEO, Shield
Compliance has always played a pivotal role across financial firms and banking institutions in an effort to pinpoint and mitigate various risks across communication channels, including market abuse, insider trading, spoofing, front-running, and even sexual harassment and racism. For decades, legacy vendors have been at the forefront of providing services to these institutions to flag and report any compliance and security breaches. This process was typically done manually where the compliance team would sift through emails and phone records and flag anything that appeared nefarious. While somewhat tedious, these compliance measures have helped institutions maintain industry wide standards and regulations as well as their own internal standards for employee conduct.
However, over time technology has evolved and has now become a mainstay across all industries, including banking and finance, offering support and assistance to organizations and institutions, making them more effective and efficient in their daily operations. More specifically, artificial intelligence has provided the banking and finance industries with comprehensive compliance tools that automate the process. While these measures can be implemented to make compliance and security oversight easier, it does come with its share of challenges including regulator hesitancy which stems from historical concerns regarding bias, discrimination, and privacy, which has now ultimately led to some calling for policymakers to introduce overly burdensome regulations on the technology. Nonetheless, the adoption of artificial intelligence will continue to grow, as its already demonstrated immense value playing a significant role in the future of banking and finance.
Concerns over AI and the Potential to Regulate
Artificial intelligence has proved and continues to prove itself to be one of the most valued assets, across all industries, that enables companies to rapidly evolve and conduct their business more effectively and efficiently. However, it does bring with it criticism and concern in which regulators and skeptics are asking the question, can artificial intelligence be transparent? Can we trust it? There have been reports of bias, discrimination, invasiveness to private data and violations of human rights, which has led the European Union to propose the Artificial Intelligence Act which will aim to impose restrictions on artificial intelligence in an effort to regulate the technology and eliminate these instances. While the law would impact all industries, there would be a particular focus on high-impact sectors which includes both the banking and finance industries.
While these regulations seem to have the publics best interest and values in mind, it also proposes an impractical solution, especially if other countries seek to implement them. According to the Center for Data Innovation, these new regulations would cost the European economy more than $30 million to introduce and manage. Should policymakers enact these regulations, they would ultimately spend more on regulating the technology than the cost of compliance itself, making it illogical. The banking and finance industries have already seen artificial intelligence at work and have reaped the benefits and any service less than what theyre accustomed to would be a setback.
One of the major concerns from a technology standpoint is that artificial intelligence relies on what is referred to as the black box, which means regulators are able to see what goes into the AI and what comes out but are unable to see how the algorithms and technology actually works. Tech companies are hesitant to share their algorithms whats inside the black box because it can lead to potential intellectual property infringement and theft. While the European Union continues to push for some type of reform, it is important they realize that they need to work directly with tech companies to implement risk management solutions that provide thorough training and regular testing to offer protections against biases.
Communication in Todays Digital and Remote Work Environment
Over the last few decades, there has been a steady stream of new communication methods that have surfaced including SMS, Slack, WhatsApp, etc. As these new channels have become dominant in the way we communicate daily in both our personal and professional lives, it has become harder and nearly impossible for compliance teams to provide security oversight and carry out thorough reviews and investigations. In 2020, financial organizations saw an increase of 54% in tickets coming in through WhatsApp. While new communication channels are making it easier and are being more heavily relied on to communicate, its also indirectly creating opportunities for security and compliance breaches.
These new channels alone call for the use of artificial intelligence to make compliance more effective and efficient. However, with the new workplace environment where many are working outside of the office and from home, it is even more critical for banking and financial institutions to find a better way to maintain compliance regulations. With a dire need to address compliance across all communication channels, many are turning to artificial intelligence as a solution as it provides automated compliance and security oversight that is more advanced and tech-driven especially when communicating over encrypted messaging services. This ultimately will provide banks with a valuable resource that allows employees to continue using messaging apps and services that are in line with privacy laws like GDPR, ensuring separation between personal and business data.
AIs Value to Compliance in the Banking and Finance Industries
Financial institutions have struggled with communication storage and while still new to the industry, artificial intelligence provides the support and solution to overcome. Artificial intelligence enables compliance officers and institutions the ability to automate all elements of their communications data management. This includes capturing data, enriching it with third party data such as CRM, normalizing it and allowing the compliance officer the ability to seamlessly investigate, archive and retain data. Under regulatory rules, there is an immense amount of both structured and unstructured data which is required for recordkeeping. Additionally, artificial intelligence can combine all data sources which in turn makes advanced searches and the ability to perform full investigations more efficiently.
In addition to the previously mentioned capabilities, artificial intelligence is revolutionizing financial compliance and redefining the way in which communications compliance risk is managed. Financial institutions are able to mitigate risk, improve operational efficiency, and reduce compliance costs by being afforded the ability to proactively detect and alert on abnormalities in communication including threats or violations such as insider trading, providing an in-depth analysis and breakdown of various communication triggers, and offering the ability to manage and customize alerts based on their specific needs, regulations, and procedures.
Implementing Artificial Intelligence Responsibly
For any organizations or institutions that decide to implement artificial intelligence for compliance purposes, it is incredibly important that it is done so responsibly. It is critical that banking and finance organizations work with companies who can fulfill their internal needs as well as meet industry standards and regulations. With much discussion around transparency, it is key to ensure the ability to separate personal data from professional data, conduct business without the consequences of bias and discrimination, and offer data that is easily interpreted and explained by compliance team members. These capabilities are readily available and continue to be top of mind when creating and developing new artificial intelligence models and algorithms.
Compliance and security measures are in place to keep our businesses and employees safe and protected from various risks and market abuse. The fact of the matter is that the old way of doing things just cant keep up and is no longer an effective process.
While trust from regulators, or lack thereof, continues to play a role in the acceptance of artificial intelligence, it will not prevent companies from adoption and implementation as long as new opportunities continue to arise to mitigate risk, cut compliance costs, and increase operational efficiency. Artificial intelligence is only going to continue to develop and evolve, leaving banking and financial institutions to get on board to keep up with the fast pace of communication and do their due diligence in following regulations. The alternative? Continue to rely on outdated legacy vendors and risk failing to maintain industry wide regulations. Artificial intelligence can and will drastically improve compliance and security oversight.
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The Role of Artificial Intelligence in Compliance and Security Oversight - International Banker
Harnessing artificial intelligence to help prevent epidemics before they spread – Croakey Health Media
Introduction by Croakey: As with the COVID-19 pandemic, health authorities usually identify epidemics through public health surveillance, but could we do it earlier by being able to mine the vast un-curated public data available to us in this digital age?
Thats the hope and challenge from leading epidemiologist, Professor Raina MacIntyre, who heads the Biosecurity Program at the Kirby Institute, and Arunn Jegan, Advocacy Coordinator at Mdecins Sans Frontires (MSF).
They write below on the potential for harnessing artificial intelligence and the proliferation of the internet and social media for early detection of epidemics, saying that a signal for unusual pneumonia in China could have been detected in November 2019 and that CSIRO research showed that the Ebola epidemic in West Africa could have been detected three months before the World Health Organization was aware of it.
They ask:
Imagine if the COVID-19 pandemic had been detected well before it spread around the world, when there was only a handful of cases contained within a small geographic location?
Readers may also be interested in the series of articles published by the Croakey Conference News Service from the recent World Congress of Epidemiology, with one on innovative Victorian disease surveillance measures and their critical role in the states COVID response to be published soon.
The SARS-COV2 (COVID-19) pandemic has caused devastation around the world, and even in vaccinated populations, it continues to mutate into dangerous variants of concern. With the onset of the Delta variant, we assume the death toll will rise beyond five million in 2021.
This is an epidemic disease, which means it grows exponentially. One case today will be five cases in a few days and then 25 cases and so on. So, time is of the essence, and the sooner you can identify epidemics, the better the prospect of stamping it out and preventing global spread.
Imagine if the COVID-19 pandemic had been detected well before it spread around the world, when there was only a handful of cases contained within a small geographic location?
Isolating cases and tracing and quarantining their contacts may have been enough to stop it spreading.
Exponential growth and time are the enemies we face with epidemic diseases the longer we take to act, the larger the epidemic will become and over a very short period. Just look at the Sydney outbreak which started in Bondi in June 2021.
Recall the West African Ebola epidemic in 2014. It was 67 times the size of the largest previously recorded Ebola outbreak, it reached urban areas, and killed more than 11,300 people.
Ebola outbreaks can kill 25 to 90 percent of those infected. In 2014-15, hundreds of health workers died, decimating the already-struggling healthcare systems of Liberia, Guinea, and Sierra Leone. Medecins Sans Frontieres (MSF) responded in each of these contexts.
In the Ebola outbreak, with fears of a pandemic on the horizon, organisations like the World Health Organization (WHO), MSF, and others supported national health systems by treating and isolating patients; tracing and follow up of patient contacts; raising community awareness of the disease such as how to prevent it and where to seek care; conducting safe burials; proactively detecting new cases; and supporting existing health structures.
When WHO was first notified of Ebola in March 2014, it may have comprised a few 100 cases, but it grew exponentially. By August 2014, the case numbers were in the thousands, and by October over 20,000 cases had occurred.
Furthermore, until only very recently, there were no tools to prevent or treat Ebola. Today a preventive vaccine and curative drugs are available. Imagine how many lives could have been saved if the epidemic had been detected when there were only a handful of cases.
Prior to COVID-19 in 2019, the Ebola epidemic saw the fastest trajectory to development of a vaccine, with Phase 1 trials in Oct 2014 to the approval of this vaccine in Nov 2019. Indeed, the average time was 10-15 years prior to both COVID-19 and Ebola vaccine developments.
For COVID-19, vaccines were developed and ready for use in less than 12 months, but after devastating global consequences of the pandemic and the hundreds of thousands killed in the global north.
In short, it is unwise to rely solely upon vaccines and or/ their development to manage an epidemic, especially in low-resource settings. Non-pharmaceutical interventions such as testing, tracing and measures to reduce contact between people are also important.
We have had a measles vaccine since the 1960s, however the disease rages through the world in epidemic proportions in over 41 countries such the Democratic Republic of Congo and Central African Republic.
The primary reason behind this is a deeply inequitable, and unfair global biomedical system which has unfairly provided for wealthier countries but not low-income countries.
We are seeing it play out with COVID-19, where only 1.8 per cent of people in low-income countries have received one dose, out of 5.4 billion doses administered globally.
With COVID-19, the general public have had a taste of what epidemiologists have known for decades, that strong health surveillance is essential to getting on top of outbreaks and to have any chance of zero elimination strategies, or any suppression strategy for that matter, working.
While the global disparity of vaccination rates persists, what new technologies is Australia investing in to helping communities get on-top of outbreaks and bolster health surveillance?
How are we harnessing artificial intelligence together with the proliferation of the internet and social media for early detection of epidemics?
The usual way we identify epidemics is through public health surveillance which is when labs or doctors notify health authorities of unusual, serious, or notifiable infections.
When lots of these notifications start piling up, or a trend is seen of higher case numbers than usual, the health official may investigate a possible outbreak.
But people talk about illness in their communities, and local news agencies report on unusual outbreaks, long before health officials know about it.
What if we could mine the vast, un-curated public data available to us in this digital age and detect signals of epidemics early?
At UNSW, the EpiWatch observatory does just that, tapping into news reports from around the world, in many different languages, using algorithms and artificial intelligence (AI) to detect early outbreak signals.
We showed that a signal for unusual pneumonia in China could have been detected in November 2019; and CSIRO research showed that the Ebola epidemic in West Africa could have been detected three months before WHO was aware of it.
This is in no way a replacement for in-country based data collection or existing Early Warning, and Alert Response Systems (EWARS). Using AI in epidemiology is an additional tool that uses innovative technologies and has the potential to reach communities who do not have the strongest national health surveillance systems.
It can also overcome censorship of information to detect signals in countries that are withholding outbreak information from the world. Reasons for censorship include fear of impacts on tourism, trade, or other parts of the economy, or political reasons.
Traditionally, declaring epidemics rest solely on the responsibility of governments, but never in human history has there been more attention on virology and epidemiology from the public. Therefore, ensuring that data-collected from the internet follows scientific modelling and surveying has never been more important.
As with most emergent technology using data and information to inform a product, the ethics over use of open-source data and safe-guards will need to be in place on who this empowers. Generally, however, methods such as used by Epiwatch do not utilise identifying or private information.
Moving forward the Kirby Institute at UNSW, with CSIRO Data 61 is exploring with MSF on how best AI can be utilised to detect epidemics as fast as possible and give vulnerable communities in low-income countries a fighting chance when epidemics strike.
Applying our lessons learnt from the COVID-19 pandemic and Ebola, now is the right time for Australia and the humanitarian community to invest in innovative health surveillance systems, and to keep potential epidemics isolated to save lives.
Professor Raina MacIntyre is NHMRC Principal Research Fellow and Professor of Global Biosecurity. She heads the Biosecurity Program at the Kirby Institute, which conducts research in epidemiology, vaccinology, bioterrorism prevention, mathematical modelling, genetic epidemiology, public health and clinical trials in infectious diseases.
Arunn Jegan is Advocacy Coordinator at Mdecins Sans Frontires (MSF) Australia. He is also the Permanent Facilitator for the emergency public health course at Epicentre in Paris. Arunn has worked as Head of Mission and Emergency Coordinator and has worked in Yemen, Syria, Venezuela, Bangladesh for MSF and in Afghanistan, Iraq, Jordan, Lebanon, and Turkey in senior management positions for other international NGOs. He specialises in social research, conflict/political analysis, complex project management, and humanitarian crisis coordination of public health emergencies.
See the Croakey Conference News Service coverage from the World Congress of Epidemiology.
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Harnessing artificial intelligence to help prevent epidemics before they spread - Croakey Health Media