Category Archives: Artificial Intelligence

The Qraft AI-Enhanced US Large Cap Momentum ETF (NYSE:AMOM), an exchange-traded fund driven by artificial intelligence, bought about $1.4 billion worth of Tesla Inc. (NASDAQ:TSLA) shares on the dip earlier this month.

What Happened: The ETF now has Tesla as its third-largest stock holding, behind social media giant Facebook Inc. (NASDAQ:FB) and e-commerce giant Amazon.com Inc. (NASDAQ:AMZN). Tesla now accounts for more than 5% of the funds portfolio.

According to MarketWatch, the fund has a history of accurately predicting the price moves of Tesla shares.

The fund had previously sold its entire Tesla holdings before the start of February this year when the electric vehicle makers shares were near their all-time high of $900.40.

See Also: Tesla, Nio Significantly Cut From Baillie Gifford Portfolio, Here's What The Firm Bought Instead In Q1

Why It Matters: Teslas stock has shed more than a third of its peak valueand emerged as a strong buy the dip candidate. It has dropped 16.4% year-to-date.

Tesla and other automakers are grappling with semiconductor shortages. Of late, the Palo Alto-based company is also facing rough weather in China, a market that contributes nearly 30% of the electric vehicle maker's global sales and is its second-largest market after the U.S.

AMOM, a product of South Korea-based fintech group Qraft, tracks 50 large-cap U.S. stocks and reweighs its holdings each month. The fund uses AI technology to automatically search for patterns that have the potential to produce excess returns and construct actively managed portfolios.

See also:How to Invest in Tesla Stock

AMOM has delivered year-to-date returns of 3.7%, compared to its benchmark the Invesco S&P 500 Momentum ETF (NYSE:SPMO) which has returned just 0.3% so far this year.

Price Action: Tesla shares closed almost 3.2% higher on Friday at $589.74.

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Famed Artificial Intelligence-Based ETF Has Loaded Up $1.4M Tesla Shares On Dip This Month - Benzinga

Wondering who that hot new collaborator is, on your favorite artists new album?

It might just be artificial intelligence.

Progress in AI music is accelerating rapidly, thanks to researchers and musicians at major tech conferences and universities who want to integrate widespread AI into the music world.

How Artificial Intelligence (AI) Is Helping Musicians Unlock Their Creativity

Many artists feel were about to enter a golden age of creativity, powered by artificial intelligence, that can push music in new directions.

Lets look at some of the newest ways artificial intelligence is transforming the music industry from top to bottom.

For 30 years, musician and composer David Cope has been working on Experiments in Musical Intelligence (EMI). EMI originally began in 1982 as an effort to help Cope overcome "composer's block," and now his algorithms have produced a large number of original compositions in a variety of genres and styles.

AIVA uses AI and deep learning algorithms to help mainstream users compose their own soundtrack music and scores. Its the perfect tool for content creators on Youtube, Twitch, Tik Tok, and Instagram who need a steady supply of music but dont have an endless budget for royalties.

Grammy-nominated producer Alex da Kid used IBM Watson to analyze five years of hit songs, as well as cultural data from films, social media, and online articles to figure out a theme for an AI-generated song that fans would enjoy. The final song, Not Easy, reached number four on the iTunes Hot Tracks chart within 48 hours after its release.

Composers Drew Silverstein, Sam Estes, and Michael Hobe were working on music for big-budget movies like The Dark Knight when they started getting requests for simple background music for television and video games. They worked together to create Amper, a consumer-friendly online tool that helps non-musicians and online content creators make royalty-free music using their own parameters in a few seconds.

One thing is clear: Since the start of the pandemic, fans miss going to concerts.

To fill the void, Authentic Artists has introduced a large collection of AI-powered virtual artists who can deliver new music experiences.

Authentic Artists animated virtual musicians generate all-original compositions to play on screen, and also respond to audience feedback by increasing or decreasing the tempo or intensity, or even fast-forwarding to the next song in the set.

Audio-on-demand streaming like Spotify totaled $534 billion in the United States alone, according to Buzz Angle Musics 2018 report.

So how do promising new artists get discovered, with all that competition?

Artificial intelligence helps the music industry with A&R (artist and repertoire) discovery by combing through music and trying to identify the next breakout star.

Warner Music Group acquired a tech start-up last year that uses an algorithm to review social, streaming, and touring data to find promising talent. In 2018, Apple also acquired Asaii, a start-up that specializes in music analytics, to help them boost their A&R.

AI technology is transforming the music industry in a myriad of ways, but creatives shouldnt be worried about losing their jobs and being replaced by computers. Were still a long way from artificial intelligence being able to create hit songs on their own.

But as tools develop and the music industry learns how to use AI as a supplement to human creativity, our world will continue to sound sweeter and sweeter every year.

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How Artificial Intelligence (AI) Is Helping Musicians Unlock Their Creativity - Forbes

PR.com2021-05-17

Geneva, Switzerland, May 17, 2021 --(PR.com)-- At its 8th General Assembly, the international, unaffiliated Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) standards association has received substantial proposals in response to its Call for Technologies on AI-based Company Performance Prediction Use Case. Meanwhile the development of its foundational AI Framework standard is steadily progressing and the technical review of responses to the Context-based Audio Enhancement (MPAI-CAE) and Multimodal Conversation (MPAI-MMC) Calls for Technologies has been completed.

The goal of the AI Framework (https://mpai.community/standards/mpai-aif/) standard, nicknamed MPAI-AIF, is to enable creation and automation of mixed Machine Learning (ML) - Artificial Intelligence (AI) - Data Processing (DP) inference workflows, implemented as software, hardware, or mixed software and hardware. A major MPAI-AIF feature is enhanced explainability of MPAI standard applications.

Development of two new standards has started after completing the technical review of responses to the Calls for Technologies. Context-based Audio Enhancement (MPAI-CAE https://mpai.community/standards/mpai-cae/) covers four instances: adding a desired emotion to a speech without emotion, preserving old audio tapes, improving the audioconference experience and removing unwanted sounds while keeping the relevant ones to a user walking in the street. and Multimodal Conversation (MPAI-MMC https://mpai.community/standards/mpai-mmc/) covers three instances: audio-visual conversation with a machine impersonated by a synthesised voice and an animated face, request for information about a displayed object, translation of a sentence using a synthetic voice that preserves the speech features of the human.

Substantial proposals received in response to the MPAI-CUI Call for Technologies (https://mpai.community/standards/mpai-cui/#CfT) has allowed starting the work on a fourth standard, AI-based Company Performance Prediction, part of the Compression and Understanding of Industrial Data standard. The standard will enable prediction of performance, e.g., organisational adequacy or default probability, by extracting information from governance, financial and risk data of a given company.

The MPAI website provides information about other AI-based standards being developed: AI-Enhanced Video Coding (MPAI-EVC https://mpai.community/standards/mpai-evc/) will improve the performance of existing video codecs using AI, Server-based Predictive Multiplayer Gaming (MPAI-SPG https://mpai.community/standards/mpai-spg/) will compensates the loss of data and detect false data in online multiplayer gaming and Integrative Genomic/Sensor Analysis (MPAI-GSA https://mpai.community/standards/mpai-gsa/) will compress and understand data from combined genomic and other experiments produced by related devices/sensors.

MPAI develops data coding standards for applications that have AI as the core enabling technology. Any legal entity who supports the MPAI mission may join MPAI (https://mpai.community/how-to-join/join/) if it is able to contribute to the development of standards for the efficient use of data.

Visit the MPAI website (https://mpai.community/) and contact the MPAI secretariat (secretariat@mpai.community) for specific information.

Contact Information:MPAILeonardo Chiariglione00390119350461Contact via Emailhttp://mpai.community

Read the full story here: https://www.pr.com/press-release/836616

Press Release Distributed by PR.com

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Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Standards Association Has Received Substantial Proposals in Response to Its...

Using your data effectively can help your organization stand out from the competition. However, doing so requires an IT infrastructure capable of the digital transformation needed to meet your business objectives. And no matter where your data is stored, it must remain secure to be effective.

The use of automation and zero-trust security strategies will be the focus of the nextCDW Tech Talk series webcast.

Allen Whipple, distributor business development channel consultant, and Rony Adaimy, category manager, at Hewlett Packard Enterprise will join the conversation to highlight the value of zero trust security strategies to protect data and defend against cybercrime. Theyll also delve into the advantages offered by the use of artificial intelligence and machine learning.

Corey Carrico, senior field marketing manager at CDW, will also join us to talk about using zero trust to stay ahead of cybercriminals--as well as your competitors.

REGISTER:To watch Tuesday's session live at 1 p.m. Central time, register for the CDW Tech Talk series below.

The CDW Tech Talk series is a weekly webcast that covers a wide variety of IT topics demonstrating how businesses can gain a competitive edge, reimagine the future of work and manage evolving infrastructures.

Most recently, we took a closer look at what you need to build your organizations optimal infrastructure.

Other recent topics of discussion includebuilding resilient workspaces, wireless technology,worker flexibilityandemployee workflows. Register for the serieshere, and followBizTechs full coverage of the eventhere.

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CDW Tech Talk Explains How to Get Ahead with Automation and Security - BizTech Magazine

Artificial Intelligence

A Citizens Guide to Artificial Intelligence, by a cast of thousands (John Zerilli, John Danaher, James Maclaurin, Colin Gavaghan, Alistair Knott, Joy Liddicoat, and Merel Noorman) is a nice high level view of some of the issues surrounding the adoption of artificial intelligence (AI). The author bios describe them as all lawyers and philosophers except for Noorman, and with that crowd its no surprise the book is much better at discussing the higher level impacts than AI itself. Luckily, theres a whole lot more of the latter than there is the former. The real issue is theyre better at explaining things than at coming to logical conclusions. Well get to that, but its still a useful read.

The issue about understanding of AI is shown early, when they first give a nice explanation of false positives and false negatives, but then write Its hard to measure the performance of unsupervised learning systems because they dont have a specific task. As this column has repeatedly mentioned, the key use of unsupervised learning is the task of detecting anomalous behavior, especially when anomalies are sparse. The difference between supervised and unsupervised learning is in knowing what youre looking for:

Supervised: Hey, heres attack XYZ!

Unsupervised learning: Hey, heres this weird thing that might be an attack!

So skim chapter one to get to the good stuff. Chapter two is about transparency, and Figure 2.1 is a nice little graphic about the types of transparency they are describing. What I really like is that accessibility is in the top tier. It doesnt matter if the designers and owners of a system are claiming to be responsible and are also inspecting the results to check accuracy; if the information isnt accessible to all parties involved in and impacted by the AI system, theres a problem.

The one issue I have with the transparency chapter is in the section human explanatory standards. They seem to be claiming that since were hard to understand, why should we expect better from AI systems? They state, A crucial premise of this chapter has been that standards of transparency should be applied consistently, regardless of whether were dealing with humans or machines. Yes, a silly premise. We didnt create ourselves. Were building AI systems for the same reasons weve built other thing in order to do things easier or more accurately than we can do them. Since were building the system, we should expect to be able to require more transparency to be built into a system.

The next three chapters are on bias, responsibility & liability, and control. They are good overviews of those issue. The control chapter is intriguing because its not just about us controlling the systems, but also covers issues about giving up control to systems.

Privacy is a critical issue, and chapter six is nice coverage of that. The most interesting section is on inferred data. We talk about inference engines, making inferences on the data; but the extension of that to privacy is to say there might be ethical limits to what engines should be allowed to infer. Theres the old case of a system knowing a young woman is pregnant and sending pregnancy sales pitches to her home before she had told her parents, but there are far worse situations. Consider societies that are intolerant of sexual orientation, but that can be inferred from other data. A government could use that to persecute people. Theres a wide spectrum in between those examples, and the chapter does a nice job of getting people to think about the issue.

The next chapter covers autonomy and makes some very good points. One is that humans have always challenged each others autonomy, but that AI and lack of laws and regulations make it far easier for governments and a few companies to remove our autonomy in much more opaque ways than have previously been available.

Algorithms in government and employment are given a good introduction in the next chapters, but with a lot of the same information seen elsewhere. The most interesting part of the back portion of the book comes in chapter ten, about oversight and regulation. There is a suggestion that, given the complexity of AI, there is logic to creating a new oversight agency for the national government. As they point out, an FDA for AI. Think of it in business terms, its a center of excellence in AI, able to formulate national policy for business and citizens, while also serving to help other agencies adapt the general policies to their specific oversight areas. That makes excellent sense.

No book is perfect, but Im partially surprised that a book with so many authors attached flows as well. Then I remember they all are academics, used to research papers with multiple authors. Of course, with that many academics, the risk is always that a book will sound like a research paper. Fortunately, they seem to have escaped that problem. A Citizens Guide is a good read to help people understand key issues in having AI make the major impact on society that it will. More people need to realize that quickly and get governments to focus on protecting people.

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A Citizens Guide To Artificial Intelligence: A Nice Focus On The Societal Impact Of AI - Forbes

The Institute for Protein Design (IPD) at the UW announced March 31 a $5 million grant from Microsoft to collaborate on applying artificial intelligence to protein design.

Microsofts chief scientific officer Eric Horvitz and the IPDs director David Baker, in an article with GeekWire, said they believe that this collaboration will lead to major strides in medicine and technology, and accelerate the scientific response to future pandemics.

The IPD designs proteins molecules that carry out a wide range of functions from defending against pathogens to harnessing energy during photosynthesis from scratch, with the goal of making a whole new world of synthetic proteins to address modern challenges, according to the institutes website.

Researchers at the IPD have developed promising anti-viral and ultra-potent vaccine candidates against SARS-CoV-2, the virus that causes COVID-19, that are currently in human clinical trials.

And in protein design, form follows function.

We use 3D protein structures on the computer to design the protein sequences, Brian Coventry, a research scientist in the Baker Lab at the IPD, said. When we order the protein sequence, its function in real life should exactly mirror that on the computer.

But that does not always happen.

The problem with this method, which is based on the first principles of both physics and chemistry, is that it produces an abundance of possible proteins which must be tested, the majority of which do not have the exact desired form, Coventry said.

Coventry recently worked on a team that developed a SARS-CoV-2 antiviral medication candidate, and he stressed that for antivirals, it is important that the designed protein be precisely atomically correct.

In the context of a pandemic, the fast development of highly accurate therapeutic synthetic proteins is desirable. This is where deep learning, a subset of artificial intelligence modeled after the brains neural networks, comes into play.

There is a lot of room for improvement, Minkyung Baek, a postdoctoral scholar in the Baker Lab at the IPD, said about the first principles-based method of protein design. Baek believes that deep learning methods can be used to quickly discriminate between possible proteins and optimize design to produce proteins that are more stable and bind more tightly to targets.

Deep learning models are given a training data set, in this case experimental results of the structures of designed proteins, and then can learn based on real-world data. They use that information to predict and design protein structures, Baek said.

Microsoft has given the IPD access to their cloud computing service Azure, which will enable them to train and test deep learning models about 10 times faster, according to Baek.

Baek hopes that this will speed up the development of effective deep learning models, which will be helpful not only for designing proteins that match existing biological proteins, but also for discovering the structure of naturally occurring proteins.

There are many real-world situations where the structure of the target is not precisely known. In these situations, researchers must predict the shape of the metaphorical lock and design the key simultaneously.

Being able to better predict the structure of a protein when given its genetic code is important, with Baek using the variants of the COVID-19 virus as an example.

Using our deep learning base, we can predict the protein structure of the variant, and starting from there we may get some clue [about] why that variant may have been more severe or easy to spread, Baek said.

But these deep learning models have some limitations. They are limited by the available training data set, are not always generalizable to multiple situations, and do not explain the reasoning behind their decisions, Coventry said.

Despite these factors, Coventry and Baek are both optimistic about the potential for deep learning to improve the protein design process.

At the end of the day, Id like to see a 100% success rate, you know, Coventry said. Someday Im sure its possible.

Reach reporter Nuria Alina Chandra at news@dailyuw.com. Twitter: @AlinaChandra

Like what youre reading? Support high-quality student journalism by donatinghere.

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Proteins, artificial intelligence, and future of pandemic responses - Dailyuw

Matrix style graphics are seen on an Apple iPhone in this photo illustration on January 22, 2019. (Photo by Jaap Arriens/NurPhoto via Getty Images)

Have you ever wondered how Netflix knows the perfect show to recommend next? Or how Facebook suggests just the person you were looking to follow?

Researchers have found the power of those predicting algorithms can also "predict" the biological language of cancer and neurodegenerative diseases like Alzheimers - which could help change completely what researchers know about treating and preventing such diseases.

The study, done at St. Johns College, University of Cambridge, found the artificial intelligence technology could "crack the language" of such diseases. The study was published in the scientific journal PNAS.

The findings could be used in the future to "correct the grammatical mistakes inside cells that cause disease," a news release from the college stated.

One in three people will be diagnosed with cancer in their lifetime, according to the American Cancer Society. And one in three older adults dies with Alzheimers or another dementia, according to the Alzheimers Association. Other neurodegenerative diseases, like Parkinsons and Huntingtons, affect millions worldwide.

Researchers say this breakthrough in technology could lead to learning how to help alleviate symptoms - and maybe even prevent the disease from happening at all.

"Bringing machine-learning technology into research into neurodegenerative diseases and cancer is an absolute game-changer," said Professor Tuomas Knowles, lead author of the paper and a Fellow at St Johns College. "Ultimately, the aim will be to use artificial intelligence to develop targeted drugs to dramatically ease symptoms or to prevent dementia happening at all."

A combination of physical activity, not smoking, light alcohol consumption, a good diet and cognitive activities may help lower the risk of the disease by as much as 60 percent, a study found.

Technology users encounter a variety of algorithms daily. The algorithms use "powerful machine-learning" data to "make highly educated guesses about what people will do next," as St. Johns College explained it. Thats how Netflix and other streaming services can offer you the best recommendations.

Dr. Kadi Liis Saar, first author of the paper and a research fellow at St Johns College, used similar machine-learning technology to train a large-scale language model to look at what happens when something goes wrong with proteins inside the body to cause disease, the college wrote.

Further use of machine-learning could transform future cancer and neurodegenerative disease research. Discoveries could be made with machine-learning beyond what scientists already know - and potentially even beyond what the human brain could ever understand, the college said.

Excerpt from:

Artificial intelligence, like algorithms, could crack the language of cancer and Alzheimers, study finds - FOX 2 Detroit

For some, artificial intelligence and data science are fantastic technologies that will benefit people and society. For others, theyre terrifying assaults on individual privacy and dire threats to human existence. The point is, these latest innovations are evolving fast in the hotbeds of business, science and government, and it can be difficult for regular citizens and civil society to keep up, particularly nonprofits and others involved in addressing the spectrum of societys needs. What is philanthropys role in the growth, use and regulation of these powerful and protean technologies?

These are some of the questions Vilas Dhar considers in his role as president of the Patrick J. McGovern Foundation, a relatively young grantmaker whose late founder built a fortune in publishing and industry research, tracking the expanding computer industry in the late 20th and early 21st centuries. McGoverns International Data Group published a number of popular computer industry magazines such as Computerworld, PC World and InfoWorld.

McGovern the person was a believer in technologys potential to improve society and the human condition. He is remembered for some notable philanthropic moves involving science and technology, including a $350 million pledge in 2000 that established the McGovern Institute for Brain Research at MIT.

McGovern the foundationestablished in 2015, a year after the death of its namesakeis also active in the information technology world. The foundation has so far made about $295 million in grants, in areas like tech education, climate change, digital health and pandemic response, as well as data science and AI ethics.

Now, in a move common in business but rare in the philanthropy and nonprofit world, the McGovern Foundation has augmented its powers through a high-profile merger. It recently announced that the Cloudera Foundationa philanthropy created by Silicon Valley data and AI software company Cloudera Inc. to bring data analytics technology to the nonprofit sectorhas merged its $9 million endowment, staff and operations into McGovern.

Dhar says the merger with Cloudera creates an organization thats neither exclusively a philanthropic foundation nor a technology company. Its a hybrid that says were an impact-driven organization that will pull from the private sector when we need to, will pull from technology companies when we need to, and will pull from the long history of philanthropy in this country to build something that actually drives outcomes for people, he said. To me, thats the direction of where the field is already going and should be going.

Most often, grantseekers just require cash to maintain or expand services, pay employees and to keep the lights on. But when it comes to a novel and developing field like data science, it can pay to have a funding partner with the experience to envision potential solutions and the hands-on expertise to design those solutions. Toward that end, the newly expanded McGovern Foundation plans to be something of a technology consulting group for philanthropy and nonprofits.

Claudia Juech, the now-former CEO of Cloudera Foundation, will have a central role in the new hybrid organization, directing activities around data enablement for nonprofits as the head of its new Data and Society program. According to Juech, McGoverns approach will involve resourcing the field as nonprofits seek new ways to apply data science to their work. While creating solutions for specific nonprofits will be part of the job, more central to the mission going forward will be creating tools to let nonprofits everywhere access new technology. We can only work with so many organizations, she said.

McGoverns Data and Society team will create and share a portfolio of solutions to serve as practical examples of whats possible in the field of data and AI for social change, guided by equity principles and the ethical use of data. The bigger question, Juech said, is how can we make this accessible to the broader sector?

What are some possibilities for nonprofits as they delve into these new data and AI applications? As in business, one potential area is predictive tools that let organizations better plan and prepare for future problems and needs. Its evolving, Juech said. A lot of nonprofits are using data science to look backward, to understand what happened. But what is possible these days is to see more of what could happen. For example, the Cloudera Foundation helped Womens World Banking create tools to predict the future of womens financial inclusion and empowerment in emerging markets. Another grantee is using data to forecast malaria outbreaks in West Africa.

Of course, artificial intelligence and data science are hot-button issues these days, with many observers voicing unease about potential dangers, including racial and algorithmic biases or the loss of privacy. This is no theoretical worry. One of the most widespread applications of AI affects nearly everyone in the U.S. and billions around the worldthat is, social media companies use of algorithms to populate individual newsfeeds, which has contributed to political polarization, volatility and even violence in the U.S. and abroad.

Those concerns have not escaped Dhar. Though hes a self-described tech optimist, he nevertheless believes philanthropy must keep potential pitfalls front and center, and that nonprofits and the people they serve must be part of the conversationrather than leaving it all up to tech companies and government. The answer isnt to get rid of one or get rid of the other, he said. Its to let civil society be the ones who are coming into that conversation and promoting all of our best interests.

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Artificial Intelligence and Data Science Are Top of Mind as These Two Grantmakers Join Forces Inside Philanthropy - Inside Philanthropy

ByPelion Press Team

Today,Pelion, theConnected IoT Device service provider, and subsidiary of Arm, jointly announced a partnership withJohnson Controls(NYSE: JCI), the global leader for smart, healthy and sustainable buildings. This partnership will accelerate innovation in connectivity, security and intelligence at the edge for Johnson Controls OpenBlue technology.

This partnership combines Johnson Controls deep domain expertise in healthy buildings with Pelions device and edge management capabilities to usher in an era of truly smart, updatable facilities at cloud scale. OpenBlues AI capabilities at the edge will consolidate diverse points of intelligence distributed across various floors, sites or even continents into insights and actions, creating an updatable building that can self-heal and evolve over its lifespan.

This innovation mirrors the automotive sector, where software, multiple sensors and AI-trained models have transformed the industry by enabling autonomous driving and software updates that blend data to continually improve vehicle capabilities and experience. Johnson Controls is applying the concept to the built environment. They will leverage Pelions flexible device management capabilities to unite diverse device types and application layers to feed AI models that respond to dynamic workloads.

Johnson Controls has the strategic foresight to rely on a partner to streamline the complexity of IoT device management security and secure firmware updates over the air. Pelions connected device platform will standardize the onboarding process for all systems, including the edge and endpoint devices that run on them, plus offer world-class public key infrastructure for secure and simple integration with third-parties.

This secure, open and flexible approach to device management will allow OpenBlue to run any device and hardware configuration, from hardware gateways to constrained temperature sensors.

In order to provide sustainable, low cost and low power intelligent processing at the edge, the partnership will utilize proven energy-efficient processors from Pelions parent company, Arm, which are a key part of Johnson Controls distributed hardware deployment.

Read more about the future of smart, healthy, and sustainable buildings in this blog.

Excerpt from:

Johnson Controls and Pelion Partner on Artificial Intelligence / Internet of Things (AIoT) For Smart, Healthy, and Sustainable Buildings - IoT For All

DUBLIN, April 12, 2021 /PRNewswire/ --Cosmo Pharmaceuticals NV (SIX: COPN) today announced the FDA approval of GI Geniusintelligent endoscopy system, its revolutionary device for lesion detection during colonoscopy.

The GI Genius module FDA approval marks a pivotal milestone for Cosmo after more than 10 years of research and investments focused to generate disruptive innovations in the field of colon's disease and optimization of the colonoscopy procedure. The development of GI Genius intelligent endoscopy module has been possible thanks to the leadership position of Cosmo, its unique proprietary library of high-definition loss-less videos of colonoscopies and its proprietary software and algorithms. The device is the first of its kind to obtain the FDA approval through the De Novo application. The device operates in real time to assist the endoscopist in the detection of lesions, is very simple to use and is compatible with all endoscopes. Cosmo is the sole manufacturer. Medtronic is the exclusive world-wide distributor.

According to Prof. Michael Wallace, Fred C. Andersen Professor of Medicine at Mayo Clinic and Editor in Chief of Gastrointestinal Endoscopy:"While colon cancer is the second deadliest cancer worldwide, it is the most preventable cancer yet full prevention remains unfulfilled. 1 in 20 US adult will be diagnosed with this disease in their lifetime but, encouragingly, 90% of patients can beat it if it is diagnosed early enough. Colonoscopy is the gold standard and most common screening method, but it's not perfect, as performance varies based on many factors including physician skill level. The GI Genius intelligent endoscopy module will help improve the accuracy of colonoscopy and reduce the number of undetected precancerous lesions, as has been shown in a recent randomized study (Repici et al.), where detection rates improved very significantly with GI Genius technology versus standard colonoscopy, regardless of skill level or endoscope used."

Mauro Ajani, Chairman of Cosmo, commented:"This landmark approval is tremendous news for Cosmo. The first ever approval of an artificial intelligence device for lesion detection in colonoscopies further strengthens Cosmo's commitment to fight colorectal cancer. This approval is a major milestone after many years of strategic investments into the colon diseases and positions Cosmo at the forefront of cutting-edge innovation. Through the strong partnership with Medtronic over the last two years, Cosmo has expanded its position in the medical device market within its core GI expertise, has gained global access and will ultimately reach more patients. We are extremely pleased and very optimistic about the impact the GI Genius intelligent endoscopy module will have on the US patient population undergoing colonoscopy."

Alessandro Della Ch, CEO of Cosmo, said:"This approval is gratifying in many ways as it is aligned with our mission of serving markets with unmet needs. Through our global distribution partnership with Medtronic we are excited to pursue an opportunity which is worth at least $ 1.1bn, looking only at the opportunity for artificial intelligence in the colonoscopy market. Leveraging on the strength of Medtronic's large US commercial footprint, we look forward to successfully and rapidly developing this market."

The GI Geniusintelligent endoscopy system is a registered trademark of Medtronic plc.

The FDA announcement of the approval can be found at the following link: https://www.fda.gov/news-events/press-announcements/fda-authorizes-marketing-first-device-uses-artificial-intelligence-help-detect-potential-signs-colon.

About Cosmo Pharmaceuticals

Cosmo is a specialty pharmaceutical company focused on developing and commercialising products to treat selected gastrointestinal disorders and improve endoscopy quality measures through aiding the detection of colonic lesions. Cosmo has also developed medical devices for endoscopy and has recently entered into a partnership with Medtronic for the global distribution of GI Genius its artificial intelligence device for use in coloscopies and GI procedures. Cosmo has licensed Aemcoloto Red Hill Biopharma Ltd. for the US and has licensed Relafalkto Dr. Falk Gmbh for the EU and other countries. For additional information on Cosmo and its products please visit the Company's website: http://www.cosmopharma.com.

Calendar Annual General Meeting, Amsterdam - May 28, 2021 Half-Year 2021 Report -July 30, 2021

Disclaimer

Some of the information contained in this press release contains forward-looking statements. Readers are cautioned that any such forward-looking statements are not guarantees of future performance and involve risks and uncertainties, and that actual results may differ materially from those in the forward-looking statements as a result of various factors. Cosmo undertakes no obligation to publicly update or revise any forward-looking statements.

This communication is not an offer of securities of any issuer. Securities may not be offered or sold in the United States absent registration or an exemption from the registration requirement of the US Securities Act of 1933.

This press release constitutes neither an offer to sell nor a solicitation to buy securities and it does not constitute a prospectus within the meaning of article 652a and/or 1156 of the Swiss Code of Obligations or a listing prospectus within the meaning of the listing rules of the SIX Swiss Exchange or any similar document. The offer will be made solely by means of, and on the basis of, a securities prospectus to be published. An investment decision regarding the securities to be publicly offered should only be made on the basis of the securities prospectus.

This press release is made to and directed only at (i) persons outside the United Kingdom, (ii) investment professionals falling within Article 19(5) of the Financial Services and Markets Act 2000 (Financial Promotion) Order 2005 (the "Order"), and (iii) high net worth individuals, and other persons to whom it may lawfully be communicated, falling within Article 49(2)(a) to (d) of the Order. Any person who is not a relevant person should not act or rely on this press release or any of its contents.

This press release does not constitute an "offer of securities to the public" within the meaning of Directive 2003/71/EC of the European Union (the "Prospectus Directive") of the securities referred to in it (the "Securities") in any member state of the European Economic Area (the "EEA"). Any offers of the Securities to persons in the EEA will be made pursuant to an exemption under the Prospectus Directive, as implemented in member states of the EEA, from the requirement to produce a prospectus for offers of the Securities.

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Contact: Niall Donnelly, CFO & Head of Investor Relations Cosmo Pharmaceuticals N.V.Tel.: +353 1 817 03 70 [emailprotected]

SOURCE Cosmo Pharmaceuticals N.V.

https://www.cosmopharma.com

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Cosmo announces FDA approval of GI Genius intelligent endoscopy module, its revolutionary Artificial Intelligence device for lesion detection during...