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Save the date: Artificial Intelligence and Emerging Technologies Partnership meeting #2 on September 22 – United States Patent and Trademark Office

Published on: 08/31/2022 15:03 PM

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The Artificial Intelligence (AI) and Emerging Technologies (ET) Partnership Series will hold itsnext meeting,AI/ET Partnership Series #2: AI & Biotech, virtually and in person at the United States Patent and Trademark Office's (USPTO) Silicon Valley Regional Office on September 22, 2022 from 9:30 a.m. to noon PT. During this meeting, panelists from industry and the USPTO will explore various patent policy issues with respect to the biotech industry, including:

A full agenda with speakers will be posted prior to the event. This event is free and open to the public, so register early to attend in person or virtually.

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Save the date: Artificial Intelligence and Emerging Technologies Partnership meeting #2 on September 22 - United States Patent and Trademark Office

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From Google Home to Alexa, Artificial Intelligence to play large in trading of cryptocurrencies – The Financial Express

From Google Home to Alexa, the role of artificial intelligence (AI) seems to have grown over the years. It is now believed that AI will play a greater role when it comes crypto being traded. As a greater number of financial institutions start offering crypto-assets as wealth management offering, the roles of AI-supported trading will become more popular. There are over 4,000 cryptocurrencies and even the oldest coins show large fluctuations in their prices. Likewise, Bitcoin 30-day volatility index is twice the value from 2016 (as per data published on buybitcoinworldwide), Saurav Raaj, founder, director, Wize, a non-fungible token (NFT) infrastructure for businesses company, told FE Digital Currency.

As per industry observers, AI is used in intelligent trading systems for stock market prediction and currency price prediction. As per a report by IEEE Access, Generalised Autoregressive Conditional Heteroskedasticity (GARCH), is a time-series statistical model used for understanding volatility. AI is in the area of market sentiment analysis. Unlike traditional stocks, discussions among trading communities and social media reports, can drive trading decisions. AI with natural language processing (NLP) can analyse market and community sentiments and provide valuable insights to the traders, Raaj added.

Courtesy: IEEE Access, ResearchGate.

It is believed that trading decision is usually based on behavioural biases that cause them to act on an emotion which could lead to mistakes while processing information. AI-guided crypto trading is unlikely to get rid of emotional factors, it is likely to amplify that via machine learning. A deliberate fix in AI programmes to avoid trading at large corrections, and surges may help. Still, it is also likely to slow the usual stop-loss or take-profit exercise, Liquing Yu, Economic Intelligence Units (EIU) analyst on India, Indonesia, and Singapore, said.

Furthermore, industry experts noted that if properly implemented and trained, AI can help eliminate human bias. According to Vikram Pandya, director, Fintech, SP Jain, it definitely helps make scientific decisions backed by data and not by impulse.

According to Business Insider Report in June 2019, there are three areas where AI is used in banking, namely, conversational banking, anti-fraud detection, risk assessment, and credit underwriting. AI-based systems can help to process trading data which can assist traders to make better investment decisions. AI with machine learning (ML) can provide safeguards against such attacks and reduce damages in real-time. In extreme cases, it can be utilised to trigger circuit breakers and even stop trading, added Raaj.

Also Read: From centralisation to decentralisation; how blockchain-oriented fintech can benefit the financial sector

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From Google Home to Alexa, Artificial Intelligence to play large in trading of cryptocurrencies - The Financial Express

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The future of AI in music is now. Artificial Intelligence was in the music industry long before FN Meka. – Grid

Music has forever been moved by technology from the invention of the phonograph, to Bob Dylan pivoting from acoustic to electric guitar, to the ubiquity of streaming platforms and, most recently, an ambitious attempt at crossing AI with commercial music.

FN Meka, introduced in 2021 as a virtual rapper whose lyrics and beats were constructed with proprietary AI technology, had a promising rise.

But just days after he signed on with Capitol Records the label that carried The Beatles, Nat King Cole and The Beach Boys and released his debut track Florida Water, the record company dropped him. His pink slip was a response in part to fans and activists widely criticizing his image a digital avatar with face tattoos, green braids and a golden grill and decrying his blend of stereotypes and slur-infused lyrics.

The AI artist, voiced by a real person and created by a company called Factory New, was not, technologically, a groundbreaking experiment. But it was a needle-mover for a discussion that is imminent within the industry: How AI will continue to shape how we experience music.

In 1984, classical trombonist George Lewis used three Apple II computers to program Yamaha digital synthesizers to improvise along with a live quartet. The resulting record a syrupy and spacey co-creation of computer and human musicians was titled Rainbow Family, and is considered by many as the first instance of artificially intelligent music

In the years since, advances in mixing boards popularized the practice of sampling and interpolation igniting debates about remixing old songs to make new ones (art form or cheap trick?) and Auto-Tune became a central tool in singers recorded and onstage performances.

FN Meka isnt the only AI artist out there. Some have been introduced, and lasted, with less commercial backing. YONA, a virtual singer-songwriter and AI poet made by Ash Koosha, has performed live at music festivals around the globe, including MUTEK in Montreal, Rewire in the Netherlands and Barbican in the U.K.

In fact, the most crucial and successful partnerships between AI and music have been under the hood, said Patricia Alessandrini, a composer, sound artist and researcher at Stanford Universitys Center for Computer Research in Music and Acoustics.

During the pandemic, the music world leaned heavily on digital tools to overcome challenges of sharing and playing music while remote, Alessandrini said. JackTrip Virtual Studio, for example, was an online platform used to teach university music lessons while students were remote. It minimized time delay, making audiovisual synchronicity much easier, and was born from machine learning sound research.

And for producers who deal with large music files and digital compression, AI can play a role in signal processing, Alessandrini said. This is important for sound engineers and musicians alike, saving time and helping them more smoothly create, or export, big records.

There are beneficial applications for technology and music to intersect when it comes to accessibility, she said. Instruments have been made using AI to require less strength or pressure in order to generate sound, for example allowing those with injuries or disabilities to play with eye movements alone.

Alessandrinis own projects include the Piano Machine which uses computers and voltages as fingers to create new sounds and Harp Fingers, a technology that allows users to play a harp without physically touching it.

On a meta level, algorithms are the ubiquitous drivers of online streaming platforms Spotify, Apple Music, SoundCloud, YouTube and others are constantly using machine learning, in less transparent ways, to personalize playlists, releases, lists of nearby concerts and music recommendations.

Less agreed upon is the concept of an AI artist itself. Reactions have been split among those loyal to the humanity of art; some who argued that if certain artists were indistinguishable from AI, then they deserved to be replaced; others who invited the newness; and many whose feelings fall somewhere in between.

With any cultural form, part of what youre dealing with are peoples expectations for what things sound like or what an artist looks like, Oliver Wang, a music writer and sociology professor at California State University, Long Beach, told Grid.

Some experts argue that those questions leave out a critical point: Whatever the technology, there is always a human behind the work and that should count.

Sometimes people dont know or see how much human work is behind artificial intelligence, said Adriana Amaral, a professor at UNISINOS in Brazil and expert in pop culture, influencers and fan studies. Its a team of people developers, programmers, designers, people from production and marketing.

But this misunderstanding isnt always the fault of the public, said Alessandrini. It often comes down to marketing. Its more exciting to say that somethings made entirely by AI, Alessandrini said. This was how FN Meka was marketed and promoted online as an AI artist. But while his lyrics, sound and beats were AI-generated, they then were performed by a human and animated, cartoon-style.

If it sounds strange that one would become a dedicated fan of a virtual persona, it shouldnt, Amaral said. The world of competitive video gaming, which is nothing without its on-screen characters, is a multibillion-dollar industry that sells out arenas worldwide.

Still, music purists and audiophiles and any person who appreciates music as an experience, rather than just entertainment may very well resist AI musicians. In particular, Alessandrini said, AI is better at generating content faster and copying genres, though unable to innovate new ones a result of training their computing models, largely, using what music already exists.

When a rap artist has these different influences and their own specific cultural experience, then thats the kind of magical thing that they use to create, Alessandrini said. You can say that Bobby Shmurda is one of the first Brooklyn drill artists because of a particular song. So thats a [distinctly] human capacity, compared to AI.

Alessandrini likens this artistic experience to the advancements of AI in medicine the applications of robotic technologies used during surgeries that are more efficient and mitigate the risk of human error. But, she said, there are some things that humans do better caring for a patient, understanding their suffering.

Its hard to imagine AI vocals ever reaching the emotional and beautifully human depths, say, of a Nina Simone or Ann Peebles; or channeling the authentic camaraderie and bounce of a group like OutKast.

In 2017, the French government commissioned mathematician and politician Cdric Villani to lay ambitious groundwork for the countrys artificially intelligent (AI) future.

His strategy, one that considered economics, ethics and education, foremost straddled the thinning line between creation and consumption.

The division between the noncreative machine and the creative human is ever less clear-cut, he wrote. Creativity, he went on to say, was no longer just an artists skill it was a necessary tool for a world of co-inhabitance, machine and human together.

Is that what is happening?

One cant talk about music on grand scales without also talking about money. Though FN Meka was a failure, AI has strong ties to the music sphere that wont be broken because one AI rapper got cut from a label. And it feels inevitable that another big record company or music festival will give it a go.

Why? It might all come down to cost, say experts and music listeners who run the cynicism gamut.

Wang said he has a sneaking suspicion that record companies and executives see AI musicians as a way to save money on royalty payments and travel costs moving forward.

Beyond the money-hungry music industry, there is also room for a lot of good moving forward with AI, said Amaral. She hopes FN Mekas image, and how he was received, was a wake-up call for whatever AI artist inevitably comes next. She also mentioned YONA, which she saw in concert in Japan, as a thin, white, able pop star not unlike many who dominate the music scene today.

We have all the technological tools to make someone who could be green, or fat or any way we like, and we still are stuck on these patterns, she said.

What will the landscape look like five or 10 or 15 years from now? Wang asks. Pop music, despite peoples cynicism, rarely stays static. Its constantly changing, and perhaps these computer-based attempts at creating artists will be part of that change.

Thanks to Dave Tepps for copy editing this article.

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Artificial Intelligence-powered (AI) Spatial Biology Market Market to Record an Exponential CAGR by 2030 – Exclusive Report by InsightAce Analytic -…

JERSEY CITY, N.J., Aug. 30, 2022 /PRNewswire/ -- InsightAce Analytic Pvt. Ltd. announces the release of market assessment report on "Global Artificial Intelligence-powered (AI) Spatial Biology Market By Data Analyzed (DNA, RNA, and Protein) By Application (Translation Research, Drug Discovery and Development, Single Cell Analysis, Cell Biology, Clinical Diagnostics, and Other Applications) Technology Trends, Industry Competition Analysis, Revenue and Forecast Till 2030"

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According to the latest research by InsightAce Analytic, the global artificial intelligence-powered (AI) spatial biology market is expected to record a promising CAGR of 16.4% during the period of 2022-2030. By region, North America dominates the global market with the major contribution in terms of revenue.

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In recent years, enormous advances in biological research and automated molecular biology have been gained using artificial intelligence (AI). AI has the ability to effectively assist in specific areas in biology, which may enable novel biotechnology-derived medicines to facilitate the deployment of precision medicine approaches. It is predicted that using AI on cell-by-cell maps of gene or protein activity will lead to major inventions in spatial biology. The next significant step in the comprehension of biology might be achieved by incorporating spatially resolved data. When applied to gene expression, spatial transcriptomics (spRNA-Seq) combines the strengths of conventional histopathology with those of single-cell gene expression profiling. Mapping specific disease pathologies is made possible by linking the spatial arrangement of molecules in cells and tissues with their gene expression state. Machine learning has the ability to generate images of gene transcripts at sub-cellular resolution and decipher molecular proximities from sequencing data.

Artificial Intelligence in spatial biology has gained faster development in sequencing and analysis, drug discovery, and disease diagnosis. Increased interest in AI in spatial biology can be attributed to the widespread use of similar technologies in other sectors and the growing popularity of increased use of Artificial Intelligence. Moreover, Market expansion can also be attributed to government spending on research around the world. The increasing demand for novel analysis analytical tools and subsequent funding has resulted in the market launch of high-throughput technology. However, Despite the availability of new high-complexity spatial imaging methods, it is still challenging and labour-intensive to extract, analyze, and interpret biological information from these images.

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In 2021, the market was led by North America. Technological developments, the existence of a well-established research infrastructure and key players, and increased spending in drug discovery R&D are all factors contributing to the expansion of the regional market. Due to the region's large and growing demand from research and the pharmaceutical industry, North America is currently the largest market for artificial intelligence applications in spatial omics.

The major players operating in artificial intelligence-powered (AI) spatial biology market players areNucleai, Inc., Reveal Biosciences, Inc., Alpenglow Biosciences, SpIntellx, Inc., ONCOHOST, Pathr.ai, Phenomic AI, BioTuring Inc., Indica Labs, Rebus Biosystems, Inc., Genoskin, Algorithmic Biologics, Castle Biosciences, Inc. (TissueCypher), and Other Prominent Players. The leading spatial omics solution providers are focusing on strategies like investmenst for innovations, partnerships, collaborations, mergers, and agreements with AI based service providers.

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Key Developments In The Market

In Aug 2022, SpIntellx, Inc. and iCura Diagnostics announced cooperation to revolutionize precision oncology by releasing the power of genomic, proteomic, and transcriptomic data through the application of advanced spatial analytics. This new alliance combines SpIntellx's software-as-a-service (SaaS) solutions for precision pathology applications that leverage unbiased spatial analytics and explainable AI with iCura Diagnostics' technical CRO expertise in accelerating immunotherapy and targeted therapy development.

In July 2022, Nucleai announced a relationship with Sirona DX, a US-based contract research company. The alliance intends to further the AI-driven identification of novel spatial biomarkers indications of solid tumour recurrence, treatment response, and prognosis. Nucleai is developing a precision oncology platform based on artificial intelligence for research and therapy decisions.

In May 2022, OncoHost announced the completion of a Series C investment round worth $35 million. The financing will be used to expand OncoHost's ongoing multicenter PROPHETIC trial utilizing PROphet, the company's machine learning-based host response profiling technology, and to support the upcoming commercial launch of the precision oncology diagnostic solution in the United States.

In March 2022, CellCarta announced the release of imageDx PRISM to significantly improve the spatial biology data that can be obtained from Akoya Bioscience's multiplex immunofluorescence (mIF) tests. imageDx PRISM from Reveal Biosciences integrates the most recent AI advancements to novel pattern discovery and spatial biomarker characterization, providing difficult-to-discover patient insights previously.

In Jan 2022, Single Cell Discoveries and BioTuring announced a partnership to advance the field of single-cell sequencing. Single Cell Discoveries will integrate BioTuring's single-cell data processing solution into its single-cell sequencing services as part of the agreement. The cooperation intends to bridge the gap between wet-lab services for single-cell sequencing and solutions for single-cell data analysis.

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Market Segments

Global Artificial Intelligence-powered (AI) Spatial Biology Market, by Data Analyzed, 2022-2030 (Value US$ Mn)

Global Artificial Intelligence-powered (AI) Spatial Biology Market, by Application, 2022-2030 (Value US$ Mn)

Global Artificial Intelligence-powered (AI) Spatial Biology Market, by Region, 2022-2030 (Value US$ Mn)

North America

Europe

Asia Pacific

Latin America

Middle East & Africa

North America Artificial Intelligence-powered (AI) Spatial Biology Market, by Country, 2022-2030 (Value US$ Mn)

Europe Artificial Intelligence-powered (AI) Spatial Biology Market, by Country, 2022-2030 (Value US$ Mn)

Germany

France

Italy

Spain

Russia

Rest of Europe

Asia Pacific Artificial Intelligence-powered (AI) Spatial Biology Market, by Country, 2022-2030 (Value US$ Mn)

India

China

Japan

South Korea

Australia & New Zealand

Latin America Artificial Intelligence-powered (AI) Spatial Biology Market, by Country, 2022-2030 (Value US$ Mn)

Brazil

Mexico

Rest of Latin America

Middle East & Africa Artificial Intelligence-powered (AI) Spatial Biology Market, by Country, 2022-2030 (Value US$ Mn)

Why should buy this report:

To receive a comprehensive analysis of the prospects for global artificial intelligence-powered (AI) spatial biology market

To receive industry overview and future trends of global artificial intelligence-powered (AI) spatial biology market

To analyse the artificial intelligence-powered (AI) spatial biology market drivers and challenges

To get information on artificial intelligence-powered (AI) spatial biology market size value (US$ Mn) forecast till 2030

To get information on major Investments, Mergers & Acquisition in global artificial intelligence-powered (AI) spatial biology market industry

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Other Related Reports Published by InsightAce Analytic:

Global Spatial Omics Solutions Market

Global Proteome Profiling Services Market

Global Single-Cell Bioinformatics Software and Services Market

Global Oligonucleotide Synthesis, Modification, and Purification Services Market

Global Circulating Cell-Free DNA (ccfDNA) Diagnostics Market

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InsightAce Analytic is a market research and consulting firm that enables clients to make strategic decisions. Our qualitative and quantitative market intelligence solutions inform the need for market and competitive intelligence to expand businesses. We help clients gain competitive advantage by identifying untapped markets, exploring new and competing technologies, segmenting potential markets and repositioning Data Analyzeds. Our expertise is in providing syndicated and custom market intelligence reports with an in-depth analysis with key market insights in a timely and cost-effective manner.

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Companies increasingly rely on technology-based solutions such as artificial intelligence, robots or mobile applications to fill workforce shortage -…

The staff policies of companies around the world increasingly rely on technology to fill the workforce shortage, with almost 60% of them estimating an increase in the use of artificial intelligence (AI), robots or chatbots, while 37% foresee a more intensive collaboration with mobile app developers and providers over the next two years, according to the study Orchestrating Workforce Ecosystems, conducted by Deloitte and MIT Sloan Management Review.

Moreover, most companies consider it beneficial to organize their workforce as an ecosystem, defined as a structure relying on both internal and external collaborators, between whom multiple relationships of interdependence and complementarity are established, in order to generate added value for the organization.

Almost all the companies participating in the study (93%) claim that the so-called external employees, such as service providers, management consultants or communication agencies, fixed-term or project-based employees, including developers and technology solution providers, are already part of the organization. On the other hand, however, only 30% of companies are ready to manage a mixed structure of the workforce.

The main reasons behind the decision to turn to external labour resources are the desire to reduce costs (62%), the intention to migrate to an on-demand work model based on a variable staffing scheme (41%) or the need to attract more employees with basic skills (40%).

The results of the study indicate that the workforce can no longer be defined strictly in terms of permanent, full-time employees. The need for flexibility, increasingly evident lately, amid events that have disrupted the global economy, such as the COVID-19 pandemic or the war in Ukraine, has led companies to look for ways to add to the workforce other solutions, especially in markets where it is deficient. But employers who want to go further in this direction need to make sure that they comply with the labour laws applicable in their jurisdiction, which, from case to case, may be more permissive or more restrictive. In the particular case of Europe, attention and consideration to the new trends in the field of workforce orchestration within a company are still required as the legal framework has yet to catch up with the challenges such new practices bring, said Raluca Bontas, Partner, Global Employer Services, Deloitte Romania.

Almost half of the companies (49%) consider that the optimal staffing structure should include both internal and external collaborators, provided that the first category is dominant. At the same time, 74% of the surveyed directors believe that the effective management of external collaborators is essential for the success of their organization.

At the same time, 89% are convinced that it is important for the external workforce to be integrated into the internal one, in order to create high-performing teams. On the other hand, 83% consider that the two categories have different expectations that require distinct offers in terms of benefits, rewards or flexibility in the way of working.

The responsibility for the workforce strategy lies with the entire top management team, mainly with the CEO (45% of respondents) and the human resources director (41%), but also with the COO, the CFO, the strategy and the legal director, according to the study.

The Orchestrating Workforce Ecosystems study was conducted by Deloitte and the MIT Sloan Management Review among more than 4,000 respondents, executives working in 29 industries, from 129 countries across all continents.

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New fiction novel delves into the emerging field of artificial intelligence, its benefits and disadvanta – Benzinga

Mark C. Giffin announces the release of 'Electronics One: Book 1'

INNISFAIL, Australia, Sept. 2, 2022 /PRNewswire-PRWeb/ -- Mark C. Giffin announces his entry into the publishing scene with the release of "Electronics One: Book 1" (published by Balboa Press AU), a fiction novel that delves into the emerging field of AI, its benefits and disadvantages.

Stephen Frost enjoys becoming a very rich man by being able to use AI. While working hard and inventing an AI doll as well as an electronic body armor and a fuel saving device, he meets his future wife Svetlana who had studied at a facility designed to train women into keeping a millionaire happy and contented. However, Stephen also realized there was a dark side that could come from all this.

Stephen's ability in AI almost got Svetlana kidnapped. His own AI attacked the Pentagon, and then, someone else did the same. He knew it would only be a matter of time before someone designed a powerful AI that would be used for evil purposes. His wife, future children, the great American dream, and the safety of people in general were important to him. At the same time, he would want to keep up his research to produce new technologies to help humanity but there would be many challenges ahead.

"Artificial intelligence is emerging as more and more real to people, with its pros and cons. The book puts forward possible advantages and threats relating to AI. It is a unique story with Stephen and his wife and artificial intelligence that has been the core of his life," Giffin says. When asked what he wants readers to take away from the book, he answers, "Artificial intelligence is an exciting realm with dire consequences if used wrongly. By itself, artificial Intelligence should not go unchecked and out of control." For More details about the book, please visit https://www.balboapress.com/en-au/bookstore/bookdetails/841232-electronics-one

"Electronics One: Book 1" By Mark C. Giffin Softcover | 6 x 9in | 200 pages | ISBN 9781982295110 E-Book | 200 pages | ISBN 9781982295127 Available at Amazon and Barnes & Noble

About the Author Mark C. Giffin grew up in Queensland, Australia. He worked in the field of medical imaging while maintaining an interest in karate and cars. He became a black belt third dan and still teaches today. His cars include a four-wheel drive and a V8 sports sedan. Over the last 15 years, he has made a number of trips to the U.S. for up to three months, spending most of this time in Florida. He has also had an interest in emerging AI.

Balboa Press Australia is a division of Hay House, Inc., a leading provider in publishing products that specialise in self-help and the mind, body and spirit genre. Through an alliance with the worldwide self-publishing leader Author Solutions, LLC, authors benefit from the leadership of Hay House Publishing and the speed-to-market advantages of the Author Solutions self-publishing model. For more information or to start publishing today, visit balboapress.com.au or call 1-800-844-925.

Media Contact

Marketing Services, Balboa Press Australia, 1-800-844-925, pressreleases@balboapress.com

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New fiction novel delves into the emerging field of artificial intelligence, its benefits and disadvanta - Benzinga

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Global Diagnostic Imaging Market Forecast Report 2022: A $53 Billion Market by 2028 – Artificial Intelligence (AI) and Analytics Gaining Traction -…

DUBLIN--(BUSINESS WIRE)--The "Diagnostic Imaging Market Forecast to 2028 - COVID-19 Impact and Global Analysis by Modality, Application, and End-user" report has been added to ResearchAndMarkets.com's offering.

The global diagnostic imaging market is projected to reach US$ 53,410.59 million by 2028 from US$ 38,034.56 million in 2022.

Rise in prevalence of chronic diseases drives the market growth. Also, the use of Artificial Intelligence (AI) and analytics in diagnostic imaging equipment would act as a future trend in the global diagnostic imaging market.

According to the Centers for Disease Control and Prevention (CDC) report, six in ten Americans live with at least one chronic disease, including heart disease and stroke, cancer, and diabetes. Chronic disease are the leading causes of death and disability in North America and stand as a leading healthcare cost.

According to CDC, the leading chronic diseases accounted for almost US$ 4.1 trillion in annual healthcare costs in America in 2020. Additionally, diagnostic imaging is widely adopted for chronic conditions of the geriatric population as the population is more vulnerable to the above chronic indications. For instance, JMIR Publications revealed that the population aged >60 is expected to rise to 2 billion by 2050 worldwide.

Thus, with the increasing prevalence of aging and chronic diseases, it is essential to focus on healthcare innovation to improve health services. For example, innovation in diagnostic imaging with the support of information and communication technology (ICT) has been used in several settings that assist individuals in diagnosing, treating, and managing chronic diseases better. Also, ICT interventions in diagnostic imaging provide solutions to some of the challenges associated with aging and chronic diseases.

Osteoporosis is a significant health problem globally and is responsible for a severe clinical and financial burden owing to increasing life expectancy. Moreover, osteoporosis increases the chances of falls, fractures, hospitalization, and mortality. The age-standardized prevalence of osteoporosis among the European population is 12% for women and 12.2% for men aged 50-79 years, per the statistics of the National Library of Medicine in 2020.

Therefore, it is mandatory to conduct clinical assessments for early diagnosis and to prevent the onset of complications. Several diagnostic imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound imaging provide information on different aspects of the same pathologies for the detection of osteoporosis at an early stage.

For example, MRI provides information on various aspects of bone pathophysiology, and its results play an essential role in diagnosing diseases early in preventing clinical onset and consequences. The factors mentioned above are responsible for driving the overall global diagnostic imaging market.

Artificial intelligence helps improve numerous aspects of the healthcare industry, and diagnostic imaging technique is one of the fields that would benefit greatly. Diagnostic imaging equipment manufacturers worldwide are integrating AI into their products. For example, in September 2018, Nvidia announced launching the Nvidia Clara platform, a combination of software and hardware working together in diagnostic imaging equipment.

Such ground-breaking technology can address the challenges of medical instruments and process enormous amounts of data generated every second that doctors and scientists can easily interpret.

Market Opportunities of Global Diagnostic Imaging Market

Government initiatives that sanction funds and grants for diagnostic imaging services to reach globally are expected to create lucrative opportunities for the overall global diagnostic imaging market growth in the coming years.

The WHO collaborates with partners and manufacturers to develop effective solutions targeting to improve diagnostic services in remote locations. Additionally, the WHO and its partners provide training programs on the use and management of diagnostic imaging, focusing on patient safety.

For example, in February 2022, Siemens Healthineers announced a partnership with UNICEF that assisted in improving access to healthcare in Sub-Saharan Africa for diagnostic techniques.

Key Market Dynamics

Market Drivers

Market Restraints

Market Opportunities

Future Trends

Company Profiles

For more information about this report visit https://www.researchandmarkets.com/r/bjdzvd

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Global Diagnostic Imaging Market Forecast Report 2022: A $53 Billion Market by 2028 - Artificial Intelligence (AI) and Analytics Gaining Traction -...

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Indica Labs Announces Collaboration with The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD) for the…

ALBUQUERQUE, N.M., and GLASGOW, Scotland, Aug. 30, 2022 /PRNewswire/ -- Indica Labs, an industry leader in quantitative digital pathology and image management solutions, and The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD), announced today an agreement to collaborate on the development of an AI-based digital pathology solution for the detection of cancer within lymph nodes from colorectal surgery cases. The primary aim of the innovative research project is to develop a tool which in the future may improve the efficiency of pathology teams within the National Health Service Greater Glasgow and Clyde (NHSGGC) reporting colorectal cancer cases and the detection of metastatic cancer in lymph nodes.

Funded by a combination of Innovate UK and industrial partners, and based in Scotland, and supported by the West of Scotland Innovation Hub, iCAIRD is one of the largest healthcare AI research portfolios in the UK. A collaboration of 30 partners from across the NHS, industry, academia and technology, the program is currently delivering 35 ground-breaking AI projects across radiology and pathology, having grown from just 10 projects at the outset in 2019. The mission of iCAIRD is to establish a world-class center of excellence for implementation of artificial intelligence in digital diagnostics.

Anonymized H&E slides from NHS Greater Glasgow and Clyde's digital pathology archive will be used to train, validate and test the algorithm, which is being developed collaboratively by iCAIRD and Indica Labs. The resulting algorithm will report negative and positive lymph node status and will be compared to pathologist reports. Furthermore, positively involved lymph nodes will be categorized into metastases, micro-metastases, and individual tumor cells.

Dr. Gareth Bryson, Consultant Pathologist at NHSGGC and Clinical Director for Laboratory Medicine of iCAIRD commented on the potential value this tool will bring to the NHS: "Our belief is that AI powered decision support tools, such as the one we are working on, may help to support pathologists by improving the process' efficiency, while simultaneously increasing sensitivity in detecting small metastasis which will direct patient therapy. Colorectal cancer resections are one of the most common cancer resection specimens and a disproportionate amount of pathologist's time is utilized in screening lymph nodes."

Indica Labs, based in Albuquerque, New Mexico, offers a suite of digital pathology image analysis solutions including HALO AI, and HALO AP; both of which will be utilized by Indica Labs and iCAIRD partners for the development of AI-based pathology solutions and their evaluation in an NHS digital pathology workflow.

HALO AI uses deep learning neural networks to classify and quantify clinically significant tissue patterns and cell populations. HALO AP is a CE-IVD certified software platform for digital anatomic pathology labs that can operate as a standalone case and image management system or can be fully integrated within LIS or HIS solutions. HALO AP supports a full range of tissue-based workflows, includingAI-assisted assays, quantitative analytics, synoptic reporting,tumor boards, and secondary consults. In addition to HALO AI and HALO AP, Indica Labs recently received a CE-IVD mark for HALO Prostate AI, a deep learning-based screening tool designed to assist pathologists in identifying and grading prostate cancer in core needle biopsies that is deployed using HALO AP.

"The team at Indica Labs is excited to collaborate with iCAIRD on the development and deployment of a state-of-the-art AI tool that aims to improve diagnostic accuracy, turnaround times, and laboratory efficiency for the benefit of both pathologists and colorectal cancer patients," commented Steven Hashagen, CEO Indica Labs.

HALO AP will be evaluated within simulated digital workflows at the pathology department in NHS GGC, using iCAIRD's research environment to demonstrate interoperability with clinical systems. HALO AP will be used as a platform to deliver the new colorectal cancer algorithm. Through this collaboration, diagnostic accuracy and efficiency will be compared between existing fully digital workflows and one that applies AI through HALO AP.

About Indica Labs

Indica Labs is the world's leading provider of computational pathology software and image analysis services. Our flagship HALO and HALO AI platform facilitates quantitative evaluation of digital pathology images. HALO Link facilitates research-focused image management and collaboration while HALO AP enables collaborative clinical case review. Through a combination of precision, performance, scalability, and usability our software solutions enable pharmaceutical companies, diagnostic labs, research organizations, and Indica's own contract pharma services team to advance tissue-based research, clinical trials, and diagnostics.

About iCAIRD

iCAIRD aims to bring clinicians, health planners and industry together, facilitating collaboration between research-active clinicians and innovative SMEs to better inform clinical questions, and ultimately to solve healthcare challenges more quickly and efficiently using AI. iCAIRD is funded by Innovate UK, under the UK Research and Innovation (UKRI) Industrial Strategy Challenge Fund (ISCF) "From Data to Early Diagnosis in Precision Medicine" challenge. For more information, visit https://icaird.com/ or email info@icaird.com.

Media Contact:

Kate Lillard TunstallIndica Labs, Inckate@indicalab.com

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SOURCE Indica Labs

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The future of malicious artificial intelligence applications is here – Toronto Star

The year is 2016. Under close scrutiny by CCTV cameras, 400 contractors are working around the clock in a Russian state-owned facility. Many are experts in American culture, tasked with writing posts and memes on Western social media to influence the upcoming U.S. Presidential election. The multimillion dollar operation would reach 120 million people through Facebook alone.

Six years later, the impact of this Russian info op is still being felt. The techniques it pioneered continue to be used against democracies around the world, as Russia's troll factory the Russian internet Research Agency continues to fuel online radicalization and extremism. Thanks in no small part to their efforts, our world has become hyper-polar, increasingly divided into parallel realities by cherry-picked facts, falsehoods, and conspiracy theories.

But if making sense of reality seems like a challenge today, it will be all but impossible tomorrow. For the past two years, a quiet revolution has been brewing in AI and despite some positive consequences, its also poised to hand authoritarian regimes unprecedented new ways to spread misinformation across the globe at an almost inconceivable scale.

In 2020, AI researchers created a text generation system called GPT-3. GPT-3 can produce text thats indistinguishable from human writing including viral articles, tweets, and other social media posts. GPT-3 was one of the most significant breakthroughs in the history of AI: it offered a simple recipe that AI researchers could follow to radically accelerate AI progress, and build much more capable, humanlike systems.

But it also opened a Pandoras box of malicious AI applications.

Text-generating AIs or language models can now be used to massively augment online influence campaigns. They can craft complex and compelling arguments, and be leveraged to create automated bot armies and convincing fake news articles.

This isnt a distant future concern: its happening already. As early as 2020, Chinese efforts to interfere with Taiwans national election involved the instant distribution of artificial-intelligence-generated fake news to social media platforms.

But the 2020 AI breakthrough is now being harnessed for more than just text. New image-generation systems, able to create photorealistic pictures based on any text prompt, have become reality this year for the first time. As AI-generated content becomes better and cheaper, the posts, pictures, and videos we consume in our social media feeds will increasingly reflect the massively amplified interests of tech-savvy actors.

And malicious applications of AI go far beyond social media manipulation. Language models can already write better phishing emails than humans, and have code-writing capabilities that outperform human competitive programmers. AI that can write code can also write malware, and many AI researchers see language models as harbingers of an era of self-mutating AI-powered malicious software that could blindside the world. Other recent breakthroughs have significant implications for weaponized drone control and even bioweapon design.

Needed: a coherent plan

Policy and governance usually follow crises, rather than anticipate them. And that makes sense: the future is uncertain, and most imagined risks fail to materialize. We cant invest resources in solving every hypothetical problem.

But exceptions have always been made for problems which, if left unaddressed, could have catastrophic effects. Nuclear technology, biotechnology, and climate change are all examples. Risk from advanced AI represents another such challenge. Like biological and nuclear risk, it calls for a co-ordinated, whole-of-government response.

Public safety agencies should establish AI observatories that produce unclassified reporting on publicly available information about AI capabilities and risks, and begin studying how to frame AI through a counterproliferation lens.

Given the pivotal role played by semiconductors and advanced processors in the development of what are effectively new AI weapons, we should be tightening export control measures for hardware or resources that feed into the semiconductor supply chains of countries like China and Russia.

Our defence and security agencies could follow the lead of the U.K.s Ministry of Defence, whose Defence AI Strategy involves tracking and mitigating extreme and catastrophic risks from advanced AI.

AI has entered an era of remarkable, rapidly accelerating capabilities. Navigating the transition to a world with advanced AI will require that we take seriously possibilities that would have seemed like science fiction until very recently. Weve got a lot to rethink, and now is the time to get started.

Jrmie Harris is the co-founder of Gladstone AI, an AI safety company.

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Cloud bursting: What it is and what its good for – ComputerWeekly.com

One of the key benefits of the cloud is its flexible, or elastic, nature.

Organisations can increase compute resources and storage capacity when they need it with little more than a web browser and a credit card. And, if needs change, they can reduce capacity and cost almost as easily.

This, however, does require applications and workflows to operate natively on public cloud infrastructure. And some organisations are either not ready to move all their systems to the cloud or, for regulatory, security or operational reasons, are unable to.

But hybrid architectures provide a way to harness the flexibility of the cloud and tap into its ability to scale. Firms might prefer or need to keep a base level of IT capacity on-premise, or even keep most of their workloads in-house.

But they still want an affordable and flexible way to deal with peak demand. This is where cloud bursting comes in.

Cloud bursting allows firms to take advantage of the clouds almost limitless scale and capacity on a temporary basis, but without the need to move workloads permanently to the public cloud.

Instead, systems are designed to shift to cloud resources as needed, and to switch back to on-premise IT as soon as the peak is over. This could be for weeks, days or even just a few minutes.

This avoids bottlenecks and a poor user experience, and maximises the utilisation of on-premise infrastructure without needing to build in capacity on-premise for predicted peaks. It minimises cloud usage fees, too, because customers only pay for on-demand cloud capacity during the peak, and avoid the energy and other costs associated with underused on-premise hardware.

Often, companies use cloud bursting to cope with peaks such as end-of-year financial analysis or seasonal variations in usage. According to Tony Lock, analyst at Freeform Dynamics, retailers are among the keenest users of cloud bursting as it allows them to manage periods of high demand.

And at a micro-level, cloud bursting can even be used to provide extra capacity for systems such as virtual desktops when more staff are in the office. This could happen during a shift change or temporary busy periods.

Cloud bursting does, however, require an IT architecture that supports it, although this is becoming easier with technologies such as containers.

This benefits businesses in several ways as it can allow short-term requirements to be fulfilled for relatively low cost, with businesses only consuming resources when they need them, saving any unnecessary capital expenditure, says Neil Clark, cloud services director at IT consultancy QuoStar.

Cloud bursting can also offer firms a way to tailor additional capacity to specific workloads, further saving money. Although virtualisation has helped IT departments consolidate servers and storage, it can still be necessary to build additional peak capacity for different applications.

An artificial intelligence training application is likely to have different demands to an enterprise resource planning system, for example. So, chief information officers can use the clouds flexibility to pick the right compute and storage resources to support each application.

On paper, almost any application that faces capacity constraints will benefit from cloud bursting. In practice, those that rely on large volumes of data or data that is tightly controlled for security, privacy or regulatory reasons are harder to burst. Either moving the data takes too long, or it is not permitted.

Bursting also works best with fairly short duration peaks in workload. Although there is no simple rule for this, if you burst for too long, on-demand cloud pricing starts to look expensive compared with fixed-term agreements.

Cloud bursting is best suited to compute-intensive and non-critical workloads that fluctuate in their capacity requirements, such as batch jobs, says Anay Nawathe, a principal consultant at ISG. He adds that workloads running on the edge are also good candidates for bursting.

Workloads that work less well are those with close ties between the application and storage, and those that demand high performance and low latency.

A further challenge with cloud bursting is to ensure consistent quality of service, especially for web applications or public-facing services such as e-commerce.

If users notice a significant degradation of performance during bursting prompted by a spike in demand, it might disrupt their interaction and prompt them to switch to a competitor. Thorough planning and testing is needed to ensure bursting works and performs as hoped.

As a result, cloud bursting is best suited to workloads with regular, short but fairly predictable peaks that are not too demanding in compute, input/output or latency. It is less suited to high-performance or performance-critical applications.

The technology behind cloud bursting is well established. But although containers, public cloud at core and edge and private cloud technologies make it easier, IT departments still need to plan and test to make sure bursting works.

Also, it is easier to burst a single application than a workflow that depends on several suppliers technologies and a mix of compute and storage. Bursting only compute to the cloud is significantly less complicated than bursting compute and data to the cloud, says ISGs Anay Nawathe.

There are commercial decisions, too. There is, according to Adrian Bradley, head of cloud transformation at KMPG, a technical overhead to cloud bursting.

Also, bursting plans that were based on low spot prices for cloud capacity a few years ago might no longer provide the best value as cloud providers try to move customers to regular commitments. That points towards moving whole workloads to the cloud rather than bursting.

Public cloud providers incentivise you to put the whole workload on there permanently, rather than having your predictable workload on premise and then bursting occasionally into the cloud, said Bradley.

This highlights another financial consideration: who sanctions the additional costs to burst?

You first to have plan it, make sure it works, test it, and then have a process that sets out who actually says we should burst, because theres going to be extra charges involved, says Freeform Dynamics Lock. Someone needs the authority to say okay, we need to go into a cloud burst scenario and pay the extra.

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