Category Archives: Artificial Intelligence
Precision health perspectives – UCI News
In February, UCI launched the Institute for Precision Health, a campus-wide, interdisciplinary endeavor that merges UCIs powerhouse health sciences, engineering, machine learning, artificial intelligence, clinical genomics and data science capabilities. The objective is to identify, create and deliver the most effective health and wellness strategy for each individual person and, in doing so, confront the linked challenges of health equity and the high cost of care.
IPH will bring a multifaceted, integrated approach to what many call the next great advancement in healthcare. The institute is an ecosystem for collaboration across disciplines.
Dr. Daniel Chow is an assistant professor of radiological sciences and a co-director of UCIs Center for Artificial Intelligence in Diagnostic Medicine. Hes been awarded teacher of the year by the Department of Radiology and was recognized by UCI Chancellor Howard Gillman as a 2018 Big Idea Winner for his teams proposal centering on precision health and artificial intelligence. Chow is the A3(applied analytics and artificial intelligence) lead for UCIs Institute for Precision Health. His team brings solutions to inpatient, ambulatory and community settings and supports pilot applications. Here, Chow shares why hes an Institute for Precision Health believer and how data is great, but humans working together are still at the crux of advancements in health care.
What most interests you about launching the Institute for Precision Health?
Im really excited, because I think we are now in a position where within this generation we can actualize some big ideas to improve patient care. Im still a clinician, and I want to figure out how we can deploy AI tools to benefit patients. To me, that should always be the goal.
Explain a little more. Ive heard precision medicine described as the giant leap for health care. Is that how you see it?
I think were on the precipice of that. And I feel a lot of the pieces are there. You look at, say, clinical omics, you look at AI, big data all these terms have been around for a while. I dont think any one of these things is whats going to advance healthcare but when you integrate all these technologies and when you integrate with cohesive goals then I think things can advance. Thats exactly what were doing with IPH.
What do you envision your primary contribution at IPH will be?
All of the groups within IPH have specific focuses. The group I lead focuses on deploying tools and strategies and quantifying the benefits.
Do you mean that youll be taking tools into clinical settings and figuring out how to get them to work within the hospital or clinic?
Thats exactly what it is. And some of the solutions we use will be developed within IPH and some may be already developed within industry. So, well work with a little of both.
You wear a number of hats right now. How quickly do you think IPH will be the thing that really takes over your life?
I feel like for myself right now thats kind of the goal. I want to be able to move in that direction where I dedicate much of my time to IPH.
Is it because you think this is the most important place to put your energy?
Yes. I think growing up this is what I always wanted to do. This is what I dreamed of doing.
What fueled that dream?
What interests me is looking at operational benefits, kind of looking at the downstream effects of tools and strategies. When you start to impact those, then its not about just touching the life of a person or even a group of people. Its about advancing an entire field and touching the lives of countless people. So thats what excites me.
Do you know what your first project within IPH will be?
We have a few things that weve already been working on. One is an AI tool that will automatically detect strokes. From the initial analysis that weve done we have shown that it can drastically improve turnaround time that is, the time between admission and when radiology reports the stroke finding to neurology. However, one thing were still measuring is if this actually results in better patient outcomes. The answer right now is that its kind of mixed.
Do you know why?
The analogy I use is that AI is kind of a cog, and a cog is meant to turn other cogs. In this early generation, people are still treating AIs like wheels, though. And were trying to fit them in our usual and customary workflows. So that will have to adjust. One of the goals must be not just developing cool technology but also developing ways to leverage it. We have to figure out how to actually move these tools into our workflow. So, with the stroke work, we have the new tool for faster stroke detection, but we have to figure out the degree to which the bottleneck with patient care is detection or perhaps something else.
And you were also part of the team that developed the COVID Vulnerability Index, a tool that doctors use to quickly determines how to best treat each patient?
Yes. With the COVID Vulnerability Index, we went from just the idea for it to actually having the tool in place and deployed within four months of the pandemic hitting UCI. And part of the COVID tool is that we use the knowledge gained from each patient to best treat the next. This represents a very big shift. In medicine, knowledge has traditionally been generational. Now its becoming more real time.
An axiom that medical students are taught is that half of what you learn at school is wrong, but you just dont know which half yet. Why? Because historically if we had a new challenge, medical colleagues would share experiences by maybe writing them up for publication in a peer-reviewed journal and learning from each other that way. But that process takes a really long time. And, of course, thats not what we did with COVID. We pulled all the data in real time, and we learned from patients in real time. So that was our testing ground of sorts. It showed that translational medicine the bench to bedside process can move much faster in a precision health paradigm.
And do you now feel that tool has legs?
Exactly. There are other issues that we might use the model to build on. A few ideas: hospital readmission, sepsis there are so many other challenges where we might apply the same formula that we used for the COVID tool. But it wasnt just me or my group that developed it. We collaborated with laboratory medicine, radiology, computer sciences, public health, nursing and many others. To bring it back full circle, its just like its not going to be any one technology thats going to solve the huge modern health issues. Its also not any one field or specialty that will do it. You really have to combine all the different expertise and insights to actually get there. And thats something IPH is doing.
Sometimes when people talk about precision health, they laser focus on the idea of merely getting more data. It sounds like youre acknowledging that the success of precision health and UCIs Institute for Precision Health will also be because it pools so many specialties and so much human expertise?
Precision health really is about the team effort; its bigger than any one person. But, yes, I think historically theres been a lot of focus on specific types of data. Sometimes the problem is that theres almost too much data, though. So I just like to emphasize that we also need to know how we combine all the different types of tools we develop. And we need to know how to best integrate the knowledge within the healthcare setting.
How long before you can confidently say that IPH has improved patient health?
Well, we can already say that because of our work with COVID and stroke detection. Now the task is to find more applications and more uses. What Im most interested in is frequent, incremental successes. Im a firm believer that little successes add up to major advancements.
If you want to learn more about supporting this or other activities at UCI, please visit the Brilliant Future website athttps://brilliantfuture.uci.edu. Publicly launched on October 4, 2019, the Brilliant Future campaign aims to raise awareness and support for UCI. By engaging 75,000 alumni and garnering $2 billion in philanthropic investment, UCI seeks to reach new heights of excellence instudent success,health and wellness, research and more. UCI Health Affairs plays a vital role in the success of the campaign. Learn more by visitinghttps://brilliantfuture.uci.edu/uci-health-affairs/.
About UCI Institute for Precision Health: Founded in February 2022, the Institute for Precision Health (IPH) is a multifaceted, integrated ecosystem for collaboration that maximizes the collective knowledge of patient data sets and the power of computer algorithms, predictive modeling and AI. IPH marries UCIs powerhouse health sciences, engineering, machine learning, artificial intelligence, clinical genomics and data science capabilities to deliver the most effective health and wellness strategy for each individual person and, in doing so, confronts the linked challenges of health equity and the high cost of care. IPH is part of UCI Health Affairs, and is co-directed by Tom Andriola, vice chancellor for information, technology and data, and Leslie Thompson, Donald Bren Professor of psychiatry & human behavior and neurobiology & behavior. IPH is a comprised of seven areas: SMART(statistics, machine learning-artificial intelligence), A2IR(applied artificial intelligence research), A3(applied analytics and artificial intelligence), Precision Omics(fosters translation of genomic, proteomic, and metabolomic research findings into clinical applications), Collaboratory for Health & Wellness(providestheecosystem that fosters collaboration across disciplines through the integration of health-related data sources), Deployable Equity(engagescommunity stakeholders and health-equitygroupsto create solutionsthat narrow the disparities gap in the health and wellbeing of underserved and at-risk populations.) and Education and Training (brings data-centric education to students and healthcare practitioners so they can practice at the top of their licenses).
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Precision health perspectives - UCI News
The Increased Use Of Machine Learning And Artificial Intelligence Is Expected To Fuel The Digital Transformation Market As Per The Business Research…
LONDON, Sept. 14, 2022 (GLOBE NEWSWIRE) -- According to The Business Research Companys research report on the digital transformation market, the increasing adoption of machine learning and artificial intelligence is expected to drive the growth of the digital transformation market going forward. Digital transformation provides traditional businesses with solutions like cloud computing, big data & analytics, data management, and other advanced features such as artificial intelligence and machine learning, which help in the optimization of business operations, leading to reduced efforts in operations and increased efficiency. Thus, their usage increased in various sectors such as healthcare, banking, transportation, manufacturing, and others, increasing the demand in the digital transformation market.
For instance, according to the report published by Cloudmantra, an India-based technology services company, the usage of machine learning in the Indian manufacturing industry has increased manufacturing capacity by up to 20% while reducing material usage by 4% in 2021. It also gives manufacturers the ability to control Overall Equipment Effectiveness (OEE) at the plant level, increasing OEE performance from 65% to 85%. Furthermore, according to the MIT Technology Review Insights report in 2022, approximately 60% of manufacturers are using artificial intelligence to improve daily operations, design products, and plan their future operations. Therefore, the rising adoption of machine learning and AI drives the digital transformation market.
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The global digital transformation market size is expected to grow from $0.94 trillion in 2021 to $1.17 trillion in 2022 at a compound annual growth rate (CAGR) of 24.7%. The global digital transformation market share is expected to grow to $2.64 trillion in 2026 at a CAGR of 22.4%.
Technological advancement in digital solutions is gaining popularity among the digital transformation market trends. Major companies operating in the digital transformation market are focused on developing technologically advanced products to strengthen their market position. For instance, in April 2020, Oracle Corporation, a US-based computer technology corporation and software solutions provider, built a new cloud data storage service called GoldenGate, an oracles cloud infrastructure software that uses real-time data analytics for the analysis of data. Real-time data analysis provides a very quick analysis of data by using different logical and mathematical operations, which helps in understanding business requirements and implementing any decision instantly. GoldenGate provides clients with a highly automated and fully managed cloud service such as database replication, analyzing real-time data, and real-time data ingestion to the cloud, which will make daily business operations easy and analyzable.
Major players in the digital transformation market are Microsoft Corporation, IBM Corporation, Oracle Corporation, Google Inc., Cognizant, Accenture PLC, Dell EMC, Siemens AG, Hewlett-Packard Company, Adobe Systems Inc., Capgemini, Cognex Corporation, Deloitte, Marlabs Inc., Equinix Inc., PricewaterhouseCoopers, Apple Inc., Broadcom, CA Technologies, KELLTON TECH, International Business Machines Corporation, Hakuna Matata Solutions, ScienceSoft Inc., SumatoSoft, Space-O Technologies, HCL Technologies, and Tibco Software Inc.
The global digital transformation market analysis is segmented by technology into cloud computing, big data and analytics, artificial intelligence (AI), internet of things (IoT), blockchain; by deployment mode into cloud, on-premises; by organization size into large enterprises, small and medium-sized enterprises (SMEs); by end-user into BFSI, healthcare, telecom and IT, automotive, education, retail and consumer goods, media and entertainment manufacturing, government, others.
North America was the largest region in the digital transformation market in 2021. Asia-Pacific is expected to be the fastest-growing region in the global digital transformation market during the forecast period. The regions covered in the global digital transformation industry outlook are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa.
Digital Transformation Global Market Report 2022 Market Size, Trends, And Global Forecast 2022-2026 is one of a series of new reports from The Business Research Company that provide digital transformation market overviews, analyze and forecast market size and growth for the whole market, digital transformation market segments and geographies, digital transformation market trends, digital transformation market drivers, digital transformation market restraints, digital transformation market leading competitors revenues, profiles and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographies.
The report also gives in-depth analysis of the impact of COVID-19 on the market. The reports draw on 150,000 datasets, extensive secondary research, and exclusive insights from interviews with industry leaders. A highly experienced and expert team of analysts and modelers provides market analysis and forecasts. The reports identify top countries and segments for opportunities and strategies based on market trends and leading competitors approaches.
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Artificial Intelligence Global Market Report 2022 By Offering (Hardware, Software, Services), By Technology (Machine Learning, Natural Language Processing, Context-Aware Computing, Computer Vision, Others (Image Processing, Speech Recognition)), By End-User Industry (Healthcare, Automotive, Agriculture, Retail, Marketing, Telecommunication, Defense, Aerospace, Media & Entertainment) Market Size, Trends, And Global Forecast 2022-2026
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International Students Conclude Their Participation in Global Summit on Artificial Intelligence – Markets Herald
A group of AI graduate students in several prestigious international universities concluded their participation in the second edition of the Global Summit on Artificial Intelligence, which concluded yesterday in Riyadh, and visited Masmak Palace in the center of Riyadh to be briefed on the history of the capital.
The students represented six countries, joined by several Saudi scholarship students in the same specialization. Their participation came within the knowledge exchange initiative launched by SDAIA and hosted 19 male and female students of different nationalities, including the US, the UK, India, Jordan, Algeria, South Korea, and Nigeria, who study at prestigious international universities and institutes, including the Sorbonne University in Paris, Oxford University, University College London, Durham University, Nottingham University, Sussex University in the UK, the Massachusetts Institute of Technology in the USA, and Kings College London.
Through this initiative, SDAIA aimed to attract global capabilities in artificial intelligence and to enhance the role of distinguished youth based on the Kingdoms Vision 2030 and its aspirations to enable them to lead the future of artificial intelligence in the Kingdom, the region, and the world.
On this occasion, SDAIA President Dr. Abdullah Al-Ghamdi explained that the knowledge exchange initiative was designed to achieve several benefits, including engaging visiting students in knowledge exchange dialogues to explore opportunities for future cooperation and introducing them to the Kingdoms efforts in pioneering the data and artificial intelligence and the future of the sector during a journey that Saudi students will lead with their peers from international universities.
He stressed that SDAIA aims through the initiative to build qualitative partnerships that support its efforts in data and artificial intelligence and help attract global capabilities that achieve qualitative addition to the Kingdom, adding that the initiative contributes to activating the distinguished role of Saudi youth and engaging them in a real dialogue that develops their leadership spirit and shows their knowledge capabilities. Al-Ghamdi said that this would enhance the Kingdoms position in data and artificial intelligence, noting that the initiative provides the opportunity to exchange knowledge and explore opportunities for future cooperation through a constructive dialogue that brings together Saudi youth and foreign graduate students.
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International Students Conclude Their Participation in Global Summit on Artificial Intelligence - Markets Herald
Artificial intelligence (AI) engineer: Learn about the role and skills needed for success – VentureBeat
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The engineers who build and manage AI systems are increasingly valuable to companies across industry sectors. Unsurprisingly, the demand for their services outstrips the supply.
But what is the role of an AI engineer? What are the key qualifications for the role? What really makes a good one? And how can they be made maybe even from current developers on staff if not found? Alternatively, how can the functionality otherwise be filled?
An AI engineer develops, programs, trains and deploys AI models. With 86% of companies in a recent survey reporting that AI is becoming mainstream in their businesses, the AI engineer has become a central figure.
While a data scientist focuses on finding and extracting business insights and applicable data from large datasets, an AI engineer comes from an IT infrastructure background and is charged with developing the algorithms for an AI application and integrating the application into a companys broader tech environment. An engineer focused on algorithms may also be known as a machine learning (ML) engineer. Someone who specializes in integrating AI applications with an organizations other technology may be known as an AI architect. Additionally, a professional specifically focused on writing code might have the title of AI developer.
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Because an important part of an AI engineers job is applying AI to real-world use cases, these workers must understand the problems their companies face and find ways that AI can help solve them. That often includes collaborating with other departments and teaching others about AIs potential.
AI engineers are highly skilled. They face a wide-open job market and are well compensated.ZipRecruiter reports that the average salary of an AI engineer is upwards of $158,000 a year, with top earners offered as much as $288,000 annually. Many companies employing these professionals also offer attractive benefits for these positions. AI engineering is a reasonably future-proof career, as AI is only becoming increasingly important to everyday life.
AI engineers typically require expertise in three broad areas:
Although more AI-specific courses are being added to undergrad and graduate programs all the time, many AI engineers have honed their specialties with certifications or a few courses to augment their foundational degrees.
AI engineers generally need at least a bachelors degree in a field such as computer science, IT, data science or statistics. Some positions may even require a masters degree.
An advanced degree in a related area will qualify applicants for more positions. However, it may become less of a necessity over time. As the need for these workers rises, more companies are seeking experience over education.
Relevant certifications may be more useful. Taking extra AI engineer courses and exams can earn job-seekers AI-specific certifications that ensure they have the needed skills. On top of grabbing employers attention, these certifications will indicate an applicant has some helpful real-world experience with the day-to-day work of AI engineering.
This means a relatively broad pool of tech professionals may be candidates for a mid-career specialty in AI. Such workers, of course, must be able and motivated, and they may be found within or beyond an employers organization.
[ Also read: Creating a powerful data department with data science ]
Lets look at some of the more specific skills required of an AI engineer:
One of the most important skills to have as an AI engineer is proficiency in at least one programming language. Ideally, applicants should have experience working with multiple languages, as some companies may prefer working in one language over another. The more diverse experience, the better.
The top programming languages in the field include:
Python is the most popular language for machine learning applications and the third most popular overall, so is often considered a default requirement for the role. Students should work with at least a few languages in their AI engineering courses, but many professionals are self-taught to at least some degree, and they have likely demonstrated proficiency with personal projects.
While general programming knowledge is important, engineers also need to accrue AI-specific experience. Building and training AI models is a unique practice, and those interested in an AI career seek varied opportunities to build this expertise.
Cultivating this experience is a lot like gaining proficiency in programming languages, and it is best done by working with various types of AI models, including linear regression, classification algorithms, decision trees and deep neural networks. Experimenting with different models can also help AI engineers discover what they enjoy working with the most.
Learning to work with models also resembles the programming language process. Students in AI engineering courses will build and test a few models in their studies, but personal research is valuable too. Forums and exchanges like GitHub are good places for support with AI projects.
AI engineers need a strong grasp of applied mathematics fields such as linear algebra and statistics. Different models require an understanding of different mathematical concepts. Engineers must know how to apply derivatives and integrals to tackle gradient descent algorithms, while probability theory and Gaussian distributions are important for Hidden Markov models. A college-level mathematics education will often provide the skills necessary.
An AI engineers work revolves around data, and data literacy is one of the most important skills to have when entering this field. AI engineers should be able to read, understand, analyze and apply data to various use cases.
Formal data science and statistics classes are useful, but the best practice is engaging with data projects first-hand, which is another reason why experienced tech workers may be good candidates to develop for the role.
Soft skills are also important in this field, although they are often harder to gauge. One of the most important soft skills in AI engineering is critical thinking.
AI models can be complicated, and the solution to a problem is rarely immediately evident. As a result, delivering timely and accurate results with these technologies requires a fast, creative approach to problem-solving.
AI engineers must be able to think through multiple solutions and determine the best course of action.
A skill that is sometimes overlooked but useful for AI engineers to have is a strong grasp of business concepts. Operations optimization and product enhancement are the most common AI use cases for businesses, so AI engineers should understand how these processes work. Effective AI application requires an understanding of how the company operates.
AI is only as effective as its users ability to apply it to their end goals. Top-performing AI engineers know not just how to build functioning AI models, but also how these models can help businesses serve their unique needs. That means understanding general business concepts and company-specific considerations.
Engineers can develop their business acumen in formal courses and/or by working with colleagues in other departments.
Another crucial soft skill to have is communication. AI engineers must be able to explain to their non-technical colleagues how different AI solutions might help teams reach their goals.
A lack of understanding of how AI can benefit businesses is the second-largest barrier to adoption, according to Gartner, with 42% of chief information officers (CIOs) citing it as a problem. Knowing how to explain AI concepts will improve cooperation.
As the technology becomes more important to a wider variety of business functions, AI engineers will work with more departments. They must be able to communicate with other workers effectively for these relationships to work. Presentation and summary skills are particularly critical.
Along those same lines, AI engineers must have excellent teamwork skills to thrive in the current market. This goes beyond telling other departments how to use AI models effectively. AI engineers must be open to feedback and cooperate with other workers to understand the challenges they face.
Many AI engineers also work in groups, even within their own departments and projects. If they are unable to work well with others, they will struggle to excel in the industry. Conversely, strong collaborative skills will help them find effective solutions faster.
Experience working in groups helps naturally build these skills, too, so prospective engineers should seek collaborative projects to improve in this area. The better they can work as part of a team, the more success theyll have in the field.
Building, testing and deploying AI models is often a time-consuming process, and time management is vitally important.
A recent study found that 83% of developers suffer from workplace burnout, with high workloads being the leading cause. While AI engineers may have little control over their workloads, they can adapt their habits to make the most of them. Of course, company culture and strong management are important for keeping such valuable professionals in peak form.
Artificial intelligence engineers should also gain experience in related technologies. Gathering relevant data and deploying AI models will likely involve working with technologies like internet of things (IoT) devices, robotics and cloud computing. Most AI projects fail, and the lack of an integrated environment is one of the most common reasons. If AI engineers hope to deploy their models effectively, working across a companys unique IT environment is important. That means understanding the various technologies they may use.
The AI engineers role is essential and in-demand, but the AI industry is developing tools and options to enable less-specialized workers to build out applications as well:
Organizations will adapt their solutions to their size and resources, the strategic importance of their implementations and their staffing markets and philosophies, and AI skills will continue to be diffused across the wider tech environment. The role of the AI engineer is still gaining importance and will be key to many companies adoption of the technology.
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Artificial intelligence (AI) engineer: Learn about the role and skills needed for success - VentureBeat
‘Step the Brain Along a Path’ explores artificial intelligence and neuroethics through dance WABE – WABE 90.1 FM
Our experiences, self-perception and how we interpret the world around us all emanate from our brains. Interacting with the brain through artificial intelligence that is, AI or other technology can change our understanding. Terminus Modern Ballet Theatre partnered with Georgia Tech Arts, celebrated choreographer Troy Schumacher and the acclaimed new media artist Sergio Mora-Diaz to explore neuroscience and the ethics of intervention with technology.
The world premiere of Step the Brain Along a Path is on stage at the Ferst Center for the Arts this weekend, Sept. 9 and 11. Choreographer Troy Schumacher joined City Lights host Lois Reitzes via Zoom along with Dr. Christopher Rozell, professor of electrical and computer engineering at Georgia Tech, and Dr. Karen Rommelfanger, president and founder of the Institute of Neuroethics.
Interview highlights:
A brief introduction to the emerging field of neuroethics:
Simply put, neuroethics explores the ethical, legal and social implications of neuroscience. So on a daily basis, Im exploring things like how neuroscience and emerging neurotech will impact identity, personhood, privacy and, actually, pretty much life as we know it, Rommelfanger explained. It really emerged alongside the advances of science, not separately from them Even with things like brain injury, memory loss that comes with that, or diseases like dementia, you hear an expression of loss of personal identity that you just wouldnt hear with something like an appendectomy. Now we can create technologies that can help alleviate that kind of suffering in marvelous ways and even possibly augment and enhance that brain function, to enable us to have really powerful lives.
How a choreographer can express neurotechnology themes through dance:
Ive created this entire scenario in which people are tasked with thinking about how they would specifically choose to benefit from a technology like this, whether thats improving your memory, improving your physical control, improving your emotional control, improving your focus and things like that, Schumacher said. Each character in this ballet has a very specific motivation for why they would want to interface with a computer, and the entire work is broken up into different sections where we follow these specific people.
He went on, One of them is trying to slow down their experience of time. One of them is trying to remember something. One of them is trying to improve their physical control. Another one is trying to improve their emotional control. And then finally, we get into this situation where these devices become, maybe, widespread, and then children might end up becoming involved in this process and in this task with surviving in society.
New media artist Sergio Mora-Diazs interactive projections within the show:
When everybody gets to the theater, there is going to be a link where they go, and they take a short quiz, where they basically anonymously provide their thoughts on some of these ideas, like, How would you choose to benefit from technologies? And then it goes into a lot of ethical questions, Schumacher said. What Sergio is doing in the midst of these really beautiful abstract representations of the brain, and action potentials and data is actually, the performance is visually directly impacted by the audiences answers. So the audience gets to see how everybody else in the audience feels about certain topics, and then the audience gets to watch a specific dancer whose character feels a very specific way about these topics. So its all very beautifully integrated into a larger visual world.
Step the Brain Along a Path, presented by Terminus Modern Ballet Theatre and Georgia Tech Arts, takes place Sept. 9 and 11 at the Ferst Center for the Arts at Georgia Tech. Tickets and more information are available at http://www.terminusmbt.com/events/step-the-brain-along-a-path.
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'Step the Brain Along a Path' explores artificial intelligence and neuroethics through dance WABE - WABE 90.1 FM
Artificial Intelligence Is Being Used To Make A Movie – Giant Freakin Robot
By Nathan Kamal| Published 1 day ago
The advent of artificial intelligence promises to change nearly every aspect of human existence, so it makes sense that we will begin with our movie-going experience. We joke, of course. Artificial intelligence has already been here for some time and is constantly growing and changing in unexpected (but often regrettably racist) ways, so its not like filmmaking was first on the docket for this sea change in technology. However, people are beginning to experiment with just how they can use this new aspect of computer technology to create art and a German entrepreneur thinks he has found at least one way.
According to The Byte, German tech entrepreneur Fabian Stelzer is working to create an (almost) entirely artificial intelligence-made movie titled Salt. By using freely available online image-generating software like Midjourney, DALL-E 2, and Stable Diffusion and voice-generators like Murf, Stelzer is building a science fiction movie in serial installments. Basically, Stelzer gives text prompts to these artificial intelligence programs, they build images and voices, and those are edited together to create a narrative. Stelzer views it as a community choice driven story, in which the suggestions of viewers are used to build the next step of the plot. In a sense, it is similar to a Choose Your Own Adventure story, except that rather than human ghostwriters under the employ of Bantam Books, artificial intelligence is creating imagery that feeds to human imagination, which loops it back to the machines for the next step. Neat, right? You can actually see part of what is being developed here:
Salt appears to take its visual cues from lo-fi science fiction films of the 1970s like Silent Running and Dark Star. In particular, it has some real vibes of the original Ridley Scott Alien. From what can be seen from the artificial intelligence-generated footage, Salt appears to be centered on a group of space explorers (possibly some kind of miners or industrial workers, as in Alien) discovers a planet with overwhelming lodes of salt. There are flashes of ships floating in orbit, dark caverns full of mineral deposits, and some real spooky stuff. All of the voices (except Fabian Stelzers) are artificial intelligence-derived, which makes all of this a fascinating look.
As of right now, the artificial intelligence tools being used to make Salt can only work in still images, so it is not exactly a motion picture. However, there is certainly a history of science fiction films that take advantage of the still image (just ask 12 Monkeys), so that does not necessarily detract from what is being done here.
Given that Fabian Stelzer is described as an entrepreneur, it should be no surprise that he describes the project in overwhelmingly hyperbolic terms. Speaking to PCMag, Stelzer describes the experiment as part of a movement in artificial intelligence that rivals the development of photography itself. Not to speak in small terms, he says it might even be akin to the development of the written word, ie, the foundation of most of civilization. But even taking that with a grain of you know what, Salt looks pretty cool.
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Artificial Intelligence Is Being Used To Make A Movie - Giant Freakin Robot
Artificial Intelligence Shows Nefertiti, Julius Caesar And Mo Whether They Exist Today – Nation World News
According to AI Nefertiti would look like this
artificial intelligence In recent years, he has taken on the task of creating images related to a variety of subjects such as art, entertainment and world history.
A Brazilian artist named . Is Hidrelli Diao, Visually presenting symbolic characters of ancient and past civilizations, but rendering them with the present style Algorithms and various artificial intelligence technologies.
The Brazilian is the first to use comprehensive artA website that works with artificial intelligence and Creates artistic images based on machine learning Then he went to Remini, Gradient and FaceApp to create a portrait with the results already achieved, and finally, he makes some adjustments with Photoshop.
To give it a touch of reality, the artist searched the Internet for pictures of people with characteristics similar to the character and then superimposed both images, retouching their eyes and finally achieving that believable appearance.
But Hidrelli Diao hasnt stopped from representing historical figures like Napoleon Bonaparte or George Washington, having drank in a bar, hes also recreated animated characters and childrens stories such as snow White,
Even these hyper-realistic representations of cartoon characters have become the most popular on the web, as people have found it very funny to watch famous figures like Shrek, Fiona, El Chavo Del 8, but especially the Simpsons. Moe Joe has been one of his creations that has turned the most on the internet.
Similarly, South American paintersOr has it shown the world what young leaving the world celebrities like Princess Diana, Freddie Mercury or Marilyn Monroe would look like. And at the same time, he imagined how the characters in Stranger Things would look like people over 50 years old like Eleven who would be 53 today.
One work that caused some trouble to users was that of Adolf Hitler, who was portrayed as an older adult male.
for stories DisneyPrince Eric from The Little Mermaid seemed to be one of the most surprising results to the artists followers, with some users saying that if he were a real man, he would be very handsome.
Hollywood stars who did not get the expected results after going under the knife were also a source of inspiration for the artist, Who showed Instagram users with artificial intelligence how Donatella Versace, Melanie Griffith or Mickey Rourke would look.
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Artificial Intelligence Shows Nefertiti, Julius Caesar And Mo Whether They Exist Today - Nation World News
Artificial Intelligence in Diagnostics Market: Increasing Utilization of AI in Different Medical Care Fields to Drive the Market – BioSpace
Wilmington, Delaware, United States, Transparency Market Research Inc. The increasing need for improving patient care and reducing treatment costs is a primary factor augmenting the growth of global artificial intelligence in the diagnostics market. The growing adoption and popularity of artificial intelligence in clinical imaging brings about quicker judgments and decreased mistakes when contrasted with a conventional examination of pictures delivered by X-beams and MRIs. Simulated intelligence brings more abilities to most diagnostics, including malignancy screening and chest CT tests pointed toward detecting COVID-19.
The global artificial intelligence in the diagnostics market is classified based on component, diagnosis type, and region. In terms of components, the market is divided into three parts namely, services, hardware, and software. Based on classification by diagnosis type, the market is grouped into neurology, chest and lung, radiology, pathology, oncology, cardiology, and others.
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The report provides an in-depth analysis of the global artificial intelligence in the diagnostics market and emphasizes the prime growth trajectories. Besides this, the report also highlights the impact of the novel COVID19 pandemic on this market and how revenues can be drawn for this market in the coming years. The report also discusses the table of segmentation in detail and lists the names of the leading segments and players functioning in this market. The report is available for sale on the company website.
Artificial Intelligence in Diagnostics Market: Company Profile
Companies operating in the global artificial intelligence in the diagnostics market are indulging in joint ventures and collaborative efforts to gain an upper hand in the overall market competition. Apart from this, players are also investing in the research and development of better therapeutics via artificial intelligence and machine learning to gain an upper hand in the overall market competition.
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Some of the prominent players of the global artificial intelligence in the diagnostics market include:
Artificial Intelligence in Diagnostics Market: Notable Developments
Clalit Health Services and Zebra Medical Vision entered into a strategic partnership for the development of cloud-based imaging AI to serve large-scale HMOs in November 2020.
Artificial Intelligence in Diagnostics Market: Trends and Opportunities
Increasing utilization of AI in different medical care fields, including diagnostics and the rising commonness of constant sicknesses, is a portion of the key variables driving the reception of artificial intelligence in diagnostics, is bolstering growth. Likewise, the growing deficiency of the general wellbeing labor force is further supporting the development and reception of innovation-based answers for better persistent administration and analysis.
The rising interest for reducing the expense of determination, reducing machine personal time, and enhancing patient consideration is a portion of the key elements propelling the utilization of AI-based analytic arrangements. Also, increasing interest and need for financially savvy symptomatic advances and methods, speedy demonstrative information age and solidification, and proficient report investigation are a couple of different variables expected to drive the development of this market. This has prompted the improvement of AI arrangements that would to cater these growing necessities.
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Artificial Intelligence in Diagnostics Market: Regional Analysis
Geographically, North America is holding the largest share in the global artificial intelligence in the diagnostics market on account of the presence of an established healthcare infrastructure facility and the latest medical aid. The presence of innovative diagnostic software and the rising adoption of IT healthcare solutions are factors augmenting the growth of this region. Besides this, the growing popularity of AI-driven surgeries and minimally invasive operations are also expected to help this region continue dominating the market in the coming years.
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Artificial Intelligence in Diagnostics Market: Increasing Utilization of AI in Different Medical Care Fields to Drive the Market - BioSpace
How artificial intelligence is helping to restore works of art – Forbes India
Vincent van Gogh probably painted "Two Wrestlers" in 1886. Image: Courtesy of Oxia Palus
This year, visitors to the Focus Art Fair were treated to a special kind of exhibition at the MORF Gallery booth. It was a selection of paintings by Vincent van Gogh and Leonardo da Vinci that the general public has never previously been able to see because they are covered over by other works by the two artists.
However, the Dutch painter covered it over with a still life, titled "Still life with meadow flowers and roses," currently kept in the Krller-Mller Museum in the Netherlands. The Oxia Palus start-up recreated this underpainting by teaching artificial intelligence how to reproduce Van Gogh's style.
The researchers trained a neural network on other works by Van Gogh. They thus taught it how to reconstruct Two Wrestlers with precision from an X-ray-style image. This gave rise to a result that is "very convincing -- by far the best guess we can get with current technology," according to Anthony Bourached, one of the co-founders of Oxia Palus, speaking to Artnet News.
This artificial intelligence has also managed to accurately reconstruct "Standing Female Nude" by Vincent van Gogh, "Madonna" by Leonardo da Vinci, "Beatrice Hastings" by Amedeo Modigliani and "Parc del Laberint d'Horta" by Santiago Rusiol.
These high-tech replicas have been dubbed "NeoMasters." They have the particularity of offering a precise idea of the original color and texture of the long-lost paintings. Oxia Palus' aim is to continue to put technology at the service of art restoration. "With potentially thousands of works of art hidden dormant beneath existing paintings, destroyed and missing, the journey in resurrecting the worlds lost art has only just begun," reads the start-up's website.
Proof of this ambition can be seen with the firm's latest project, "TextMasters." This resembles "NeoMasters," with the key difference being that the AI reconstructs lost paintings from textual descriptions, not from X-ray images -- a feat made possible by DALL-E 2, the innovation developed by the American company, OpenAI. This text-to-image artificial intelligence software uses language comprehension models, as well as learning without human supervision on very large amounts of data, to generate credible artificial images.
Oxia Palus researchers have already used DALL-E 2 to reproduce paintings by Diego Velzquez, Giotto, Leonardo da Vinci, Johannes Vermeer, Eugne Delacroix and Sandro Botticelli, among others. Some of them are currently being offered for sale as NFTs on the KnownOrigin platform, in order to attract the interest of crypto-collectors. "We hope that by starting with some of the most notable lost pieces in history, we will be able to generate wider public interest in restoring our collective cultural heritage," said Oxia Palus.
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How artificial intelligence is helping to restore works of art - Forbes India
The air force industry found it harder to fill artificial intelligence vacancies in Q2 2022 – Airforce Technology
Artificial intelligence related jobs that were closed during Q2 2022 had been online for an average of 30 days when they were taken offline.
This was an increase compared to the equivalent figure a year earlier, indicating that the required skillset for these roles has become harder to find in the past year.
Artificial intelligence is one of the topics that GlobalData, our parent company and from whom the data for this article is taken, have identified as being a key disruptive technology force facing companies in the coming years. Companies that excel and invest in these areas now are thought to be better prepared for the future business landscape and better equipped to survive unforeseen challenges.
On a regional level, these roles were hardest to fill in the Middle East and Africa, with related jobs that were taken offline in Q2 2022 having been online for an average of 31 days.
The next most difficult place to fill these roles was found to be North America, while Europe was in third place.
At the opposite end of the scale, jobs were filled fastest in Asia-Pacific, with adverts taken offline after ten days on average.
While the air force industry found it harder to fill these roles in the latest quarter, these companies actually found it easier to recruit artificial intelligence jobs than the wider market, with ads online for 25% less time on average compared to similar jobs across the entire jobs market.
GlobalData's job analytics database tracks the daily hiring patterns of thousands of companies across the world, drawing in jobs as they're posted and tagging them with additional layers of data on everything from the seniority of each position to whether a job is linked to wider industry trends.
You can keep track of the latest data from this database as it emerges by visiting our live dashboard here.
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The air force industry found it harder to fill artificial intelligence vacancies in Q2 2022 - Airforce Technology