Category Archives: Ai

Timely access to critical information is more important than ever as enhanced collaboration among different specialties becomes increasingly crucial to delivering optimised patient care. At Oslo University Hospital (OUH), an advanced mechanism for labelling and editing recorded procedures has been developed in partnership with Olympus to support the standardisation of procedures and enhance teaching workflows for surgeons.

COOPERATION BENEFITS DIGITAL HEALTH

In addition to supporting teaching workflows, the Vaultstream Medical Content Management System gives healthcare teams real-time access to clear visual information and collaborative insights across the wider hospital environment.

There are 24 Olympus nCare medical recorders integrated into the system in 22 operating rooms and two surgical ENT rooms at OUH. Video footage can be adjusted before submission. The AutoClip feature allows users to edit procedure clips for length and focus, while AutoLabel enables standardised labelling, helping to make data readily available for reference and analysis.

Dag Tidemann Frland, chief surgeon at OUH, says: We like the standardisation of the procedure, and that bookmarks can be made stepwise. Residents can easily bookmark specific parts and later compare these steps with previous procedures, for a shorter and rapid learning curve and to become more confident in the end, to ensure the safety of the patient, which is the main goal.

PAVING THE WAY FOR AI

Projects such as this OUH/Olympus partnership are helping to transform operating rooms into valuable data sources, which in turn can be used in the development of AI solutions without requiring further editing or labelling.

This is a significant benefit. McKinsey recently identified data labellingas one of the most challenging aspects of AI adoption for many industries, including healthcare. Removing this expensive and time-consuming barrier with a simple, automated tool will help to build a foundation for future AI solutions that improve patient safety, clinical outcomes and the efficiency of surgical procedures.

se Schiefloe, project leader at OUH, says: I think we have finally found a system that is going to match our needs. We have been searching for a good system for our surgeons for quite a long time.

OUH will now be a Reference Centre for Olympus. For further information, visit Olympus Europa.

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Automating Oslo: how advanced content management is paving the way for AI - Healthcare IT News

Tomi Poutanen says hes thought for years about how to apply AI to health care.Fred Lum

Four years ago, Tomi Poutanen sold his artificial intelligence startup Layer 6 to Toronto-Dominion Bank for more than US$100-million and became TDs chief AI officer. TD used Layer 6s AI engine for dozens of applications, such as predicting when customers might buy homes and detecting fraudulent insurance claims.

Now Mr. Poutanen is pursuing a higher goal using AI to save lives. Mr. Poutanen is leaving TD to lead his latest startup, Signal 1 AI Inc. It is aiming to bring to market an artificial intelligence tool that will help hospitals predict which patients are at greatest risk of dying and need immediate intervention.

Mr. Poutanen, a doctors husband, said hes thought for years about how to apply AI to health care.

Theres a lot of hype around AI and health care but its justified because theres so much promise, he said in an interview. Theres so much data flowing through hospitals, but nobody is using it appropriately. Machines can help add value to improve health outcomes.

The company will commercialize AI technology developed at St. Michaels Hospital, a part of Unity Health Toronto, funded by billionaire benefactor Li Ka-shing. Unitys 30-person data science and advanced analytics group is led by researcher Muhammad Mamdani.

Mr. Poutanen brings an extensive background to the startup. He studied computer engineering at University of Toronto under deep-learning pioneer Geoff Hinton and sold startups to Yahoo! and Microsoft, building key search tools for them using machine learning. He is a co-founder of the Vector Institute for Artificial Intelligence and an original fellow of the Creative Destruction Lab accelerator program.

He studied neural networks and wrote his masters thesis on cryptocurrency in the 1990s. I was always ahead of my time, he said.

His Signal 1 co-founder, Mara Lederman, is leaving a tenured professorship and $364,000 salary at University of Torontos Rotman School of Management and a leadership role with the CDL, where she helped health-oriented startups.

Her career plan was never to teach permanently, but rather to move into a position of taking things I had studied, written about and taught about, and start doing them in real life, Ms. Lederman said. Early on in getting to know [Mr. Poutanen], I told him, When Im done with this, I would love us to do something together.

Mr. Poutanen is leaving not only with TDs blessing (he will remain an adviser to the bank) and six employees, but also funding. TD is kicking in $4-million of a US$10-million seed financing for Signal 1. The financing was led by Inovia Capital.

Other investors include Prof. Hinton, former Rogers Communications Inc. chief executive officer Nadir Mohamed, and venture capital firm Radical Ventures, where Mr. Poutanen serves as partner alongside Layer 6 co-founder Jordan Jacobs.

They have demonstrated examples and can say these are the lives that have been saved, said Inovia partner Steven Woods. You want impact in a startup? Thats impact.

The bank is also licensing to Signal 1 use of its globally renowned AI engine that Mr. Poutanens team built. That, combined with the St. Michaels technology, will make its product faster and more effective, Mr. Poutanen said. This is the most innovative thing a Canadian bank has ever done, he said.

Andres Vives, TDs chief data analytics officer, acknowledged it is unusual for a bank to license out a core piece of proprietary technology. It takes a very compelling reason for a bank to do that, he said. We saw a great opportunity to put a fantastic asset in the hands of a [non-competitive] industry that can benefit from it, too.

TD will also benefit from any improvements to the engine the Signal 1 team makes. Both partners stressed stringent privacy and security standards will ensure no sensitive data is shared.

This is a landmark step for Canadian health care, said Unity CEO Tim Rutledge. Its a first partnership that will result in scaling up health care innovation that can make a difference globally. Its not our core business [selling technology] so we really need partners like Tomi to come in and help.

The genesis of Signal 1 is the work of Dr. Mamdani, who has spent his career analyzing health care data. By the mid-2010s, he felt that applying AI to harnessed data in hospitals could help improve health outcomes. His team cleaned up the hospitals disparate data sources to make them usable by his group, and asked medical staff what problems they faced, setting out to develop AI solutions for them.

That led to the creation of 20 to 30 programs used at the hospital. One pulls in data from inside the hospital and out, including weather, to predict emergency room volumes and adjust staffing. Another creates a visual timeline of patient medical histories to help residents get a quick read on their rounds.

The most successful has been a patient risk-monitoring system developed at the request of internists after a patient with a swollen gall bladder in for a routine checkup died after a rapid deterioration. With only hours to react to such circumstances, they asked Dr. Mamdani if his team could help predict who was at greatest risk of dying.

So his group developed ChartWatch, which pulls in vitals from internal medicine patients, lab results and demographic information every hour, with machines monitoring and automatically paging doctors if results deteriorate. Since its deployment in October, 2020, Dr. Mamdani said ChartWatch has resulted in a more than 15-per-cent drop in mortality rates among high-risk patients.

As word spread to other hospitals about the effectiveness of AI, Unitys foundation board and management looked to bring in a commercial partner to turn its tools into sellable products.

Dr. Mamdani knew Mr. Poutanen. They had met at a job fair in 2018 when they were both trying to hire the same students. When Mr. Poutanen looked at their code, he felt the AI was really good but I knew we could do much better, he said. I turned to my boss at TD and said, Im going to do this next, I want you to license the Layer 6 engine, I think it could be really impactful on health care.

TD agreed. The souped-up ChartWatch will be tested for a month at St. Michaels before launching in market this year.

Signal 1 will look to take other Unity products to market. A hospital committee must first sign off, guided by a mission of putting purpose over profit and ensuring privacy, security and confidentiality are not compromised, Dr. Mamdani said.

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TD's AI chief quits to start health care firm, backed by bank and Inovia Capital - The Globe and Mail

Porsche says car manufacturers need new technologies for AI calculations that can help the algorithms learn much faster.

By : HT Auto Desk |Updated on: 25 Apr 2022, 03:37 PM

The function of artificial intelligence is becoming increasingly important in the functioning of vehicles today and hence Porsche is intensively focusing to amp its game in the AI sector as it believes the calculations derived from AI are vital. Porsche believes that car manufacturers need new technologies for AI calculations that can help the algorithms learn much faster. As automakers are now venturing into autonomous driving technology, the latter is being touted as the most demanding application of artificial intelligence.

Porsche shares that conventional data centres are increasingly unable to cope with the growing demands and thus, it takes days to train a single variant of a neural network. And since car manufacturers need AI calculations to speed up the learning of algorithms which can be achieved by as many vector-matrix multiplications as possible executed in parallel in the complex deep neural networks, says Joachim Schaper, Senior Manager AI and Big Data at Porsche Engineering. The algorithms learn from a multitude of examples collected by test vehicles using cameras, radar, or other sensors in real traffic," adds Schaper.

(Also read | Porsche, Audi form premium charging partnership in Japan)

Porsche has maintained the use of artificial intelligence in various fields to refine the functioning of its vehicles. Such as the premium sports car manufacturer developed an AI that was a digital assistant called Sounce that helped to detect noise in a much-improved manner. In a past report, it was mentioned that this AI used deep learning methods to detect noise precisely for example in endurance tests. Porsche had stated it also helped to make error documentation more accurate and simplify root cause analysis.

(Also read | Porsche invests $75 million in eFuel production company)

Another report had stated Porsche's development of an AI function, in collaboration with start-up Viscopic, that helped to avoid mistakes while assembling electric drives. This AI ensured the correct installation of EV drive systems.

First Published Date: 25 Apr 2022, 03:37 PM IST

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How Porsche is strengthening AI calculations to advance automotive functions - HT Auto

Conference call and webcast to follow at 5:30 p.m. EDT

LONG BEACH, NY , April 25, 2022 (GLOBE NEWSWIRE) -- authID.ai(Nasdaq: AUID), a leading provider of secure, mobile, biometric identity authentication solutions, today announced it will report financial results for the first quarter ended March 31, 2022 on Monday, May 9, after market close. Following the earnings release, authID.ai Chief Executive Officer Tom Thimot, and Chief Financial Officer Stu Stoller will host a webcast and conference call at 5.30 p.m. EDT to discuss the financial results and provide a corporate update.

To listen to the webcast and view the presentation, investors can follow this link: https://edge.media-server.com/mmc/p/3sjqwpia.

The slides can also be accessed via authID.ais Investor Relations web page at: https://investors.authid.ai/

To participate in the live call, investors can use the following dial in numbers with the Conference ID: 8076654:

A replay of the conference call will be available for seven days, through May 16 at 5:30pm EDT, by dialing: (855) 859-2056 or (404) 537-3406 and referencing Conference ID: 8076654. The presentation will also be available for 90 days on the IR section of the companys website.

About authID.aiauthID.ai (Nasdaq: AUID), formerly Ipsidy, provides secure, mobile, biometric identity verification software products through an easy-to-integrate Identity as a Service (IDaaS) platform. authID.ais suite of self-service biometric identity proofing and authentication solutions frictionlessly eliminate passwords through a consent-based facial matching system. authIDs mission is to enable every organization to recognize their customers, workforce, and other users instantly, without friction or loss of privacy. Powered by sophisticated biometric and artificial intelligence technologies, authID.ai aims to strengthen security and trust between businesses and their customers. We Are Digital Identity. For more information, go to http://www.authid.ai.

Investor Relations Contacts:

Grace DeFriesauthID.ai SVP, Marketing Communications &Investor Relationsinvestor-relations@authID.ai

Ina McGuinnessThe Bliss Group(805) 427-1372

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authID.ai to Report First Quarter 2022 Financial Results on May 9 - GlobeNewswire

C3.ai ( AI 4.71% ) has experienced its fair share of volatility but can it ignite its revenue growth and better diversify its customers? In this clip from "IPO & SPAC Show" on Motley Fool Live, recorded on April 11, Motley Fool contributors Jason Hall and Danny Vena discuss some of the areas of concern around C3.ai, and what they want to see the AI stock improve going forward.

Jason Hall: There's a lot of positive result that's happening in the energy industry. Baker Hughes ( BKR -4.53% ) is its most important customer and it's not even close. One way to read this headline, Baker Hughes collaborates with C3, Accenture ( ACN 1.94% ) and Microsoft ( MSFT 2.44% ) on industrial asset management solutions and say, "Hey, that's a real positive because now it's starting to work with some of the big consulting firms that are going to play a huge role in enterprise AI." It's working with Microsoft, the most important software company on Earth. That's positive. The other way to look at this is,where does C3 fit in with these? Is it getting pulled into this because of its deep relationship with Baker Hughes? Or, is it truly a value-added part of that? I think at this point, it's too early to tell. I want to pull up the stock chart one more time and I want to say that this could be a better risk adjusted opportunity to buy the company than here. But with that said, it's burning an increasing amount of cash above its revenue growth. It's not exactly any less concentrated to a couple of large customers now than it was back here. I really want to see C3 begin to really start diversifying its revenue streams in a more broad way. That really hasn't happened yet. It's becoming more of a government contractor and has ties to the energy industry. I'm not sure if those are going to be clear positives. I want to see more growth across corporate and that enterprise AI story they talk about that they advertise, I want to see it actually start being more reflected in their results. I'm not giving up. I own a pretty modest position. I'm not adding right now. I want to see more diversification of their customers, more enterprise business, more recurring revenue from their enterprise businesses, and the revenue growth start to exceed operation expense growth.

Danny Vena: Yes. I want to make one quick comment before we move on and that is, that contract with Baker Hughes was essentially all of the RPO growth that they showed. Without that, their remaining performance obligation would've actually sank for the quarter. That's definitely a concern for investors and part of the reason why the stock has taken as big of a hit as it has.

Hall: Makes that customer growth metric even more suspect.

This article represents the opinion of the writer, who may disagree with the official recommendation position of a Motley Fool premium advisory service. Were motley! Questioning an investing thesis even one of our own helps us all think critically about investing and make decisions that help us become smarter, happier, and richer.

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Why It Might Be a Great Time to Buy This Enterprising AI Stock - The Motley Fool

New York, New York--(Newsfile Corp. - April 25, 2022) - Bloom Technology, one of the fastest-rising blockchain expert companies developed a fully decentralized blockchain "Locus Chain" even capable of operating on mobile devices with low computational power, announced that it has executed a strategic business partnership agreement with Kontur, an AI company in the U.S. to cooperate on all upcoming AI Smart City projects. The U.S.-based Kontur developed a "Mapping & Geospatial Data Solution" applied to smart cities, and also provides artificial intelligence data analysis and prediction solutions in response for natural disasters, which are increasing in scope and severity due to the overcrowded regions across the Earth.

Through the strategic partnership agreement, Kontur has agreed to cooperate as the leading technology partner for all smart city projects of Bloom Technology and also to appoint Locus Chain as the blockchain partner for all AI DATA solutions currently in service. Kontur currently supplies its technology to PDC (Pacific Disaster Center), an artificial intelligence big data analysis entity that provides disaster analysis prediction solutions to NGO and governments of over 70 different countries around the world, and has decided to co-develop various convenience solutions and technologies, necessary for smart city businesses where data authentication and effective data distribution is crucial, with Bloom technology's highly scalable blockchain.

The business partnership agreement between Bloom Technology and Kontur symbolizes the great significance of the companies entering the global AI smart city businesses, with plans to apply the next-generation blockchain Locus Chain to all smart city projects conducted by Kontur in the future.

Arben Kane, the CEO of Kontur, is an investor and advisor to several blockchain projects such as IOTA and BadgerDAO, and is acknowledged as an expert that leads the blockchain and AI industries.

Story continues

Arben Kane said, "The technology that needs to be applied to the field of smart city must be a decentralized public blockchain that guarantees the highest scalability and performance, which is very rare to find. After reviewing several blockchain protocols around the world, I strongly believe 'Locus Chain' is the only solution that is stable and suitable for this project. The collaboration between Bloom Technology and Kontur will create an unprecedented ecosystem in unexplored blockchain territory." "With existing know-how and new technologies, we will definitely lead Bloom Technology's smart city project to success," he added, expressing his firm will and confidence.

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USA, New York 444 Madison Ave,18th Floor, NY 10022

USA, Hawaii 1305 North Holopono St,Ste 2 Kihei, HI 96753

Poland ul. Bitwy Warszawskiej1920 r. 7, 02-366 Warszawa

Contact for PR:misha@kontur.io

BLOOM TEHCNOLOGY :Korea Office: RM 802, Pangyo Seven Venture Valley1 2dong, 15, Pangyo-ro 228beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea (13487)

Contact for PR:David Wangdavid@bloomtechnology.co.kr

To view the source version of this press release, please visit https://www.newsfilecorp.com/release/121529

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Bloom Technology Enters into a Strategic Partnership Agreement with Kontur, AI Specialist Company Based in North America, to Engage in Co-Developing...

GUILFORD, Conn., April 25, 2022 (GLOBE NEWSWIRE) -- AI Therapeutics, Inc., an AI driven clinical-stage biopharmaceutical company developing novel therapeutics for rare diseases, today announced the acquisition of EntreChem, S.L.s investigational drug candidate EC-8042 (redesignated AIT-102), a novel targeted cancer therapy in development for rare pediatric and other cancers.

Despite recent advances in the understanding of tumor biology, treatment for many pediatric cancers remains limited to surgery, radiation and chemotherapy which often have poor outcomes and are associated with significant side effects. AIT-102 specifically targets the mutations responsible for the formation and progression of two notable pediatric tumors, rhabdoid tumors and Ewing sarcoma, and holds the potential to treat a broader family of tumors that share a common mechanism of mutated or dysregulated SWI/SNF activity.

As a physician treating children with cancer on a daily basis, I am acutely aware of the need for more effective and less toxic therapies, said Patrick Grohar, M.D., Ph.D., Director of Translational Research with the Center of Childhood Cancer Research at Childrens Hospital of Philadelphia, a leader in the study and treatment of pediatric tumors. For many tumor types, the biological culprit is well understood, but has proven difficult to target with pharmaceuticals. I have dedicated the last 15 years of my professional career to understanding the mechanism of tumor biology in children and finding new, targeted, therapies to treat these tumors. I am particularly impressed with the strong preclinical data from our studies of AIT-102 in rhabdoid tumors and Ewing sarcoma, and I believe that AIT-102 has the potential to transform the treatment of these cancers, as well as many others.

AIT-102 is a powerful addition to AI Therapeutics rare disease treatment pipeline, said Brigette Roberts, M.D., Chief Executive Officer of AI Therapeutics. Cancer is the leading cause of death by disease in children in the US today. With AIT-102, we hope to change these statistics. Beyond pediatrics, AIT-102 has the potential to treat up to 20% of cancers with altered SWI/SNF activity, either through mutation or dysregulation, including epithelioid sarcoma, synovial sarcoma, lung adenocarcinoma, colorectal cancer, and others. We are thrilled to have this opportunity to bring forward a promising new agent to help fight these tumors.

Financial terms of the transaction were not disclosed.

About SWI/SNF and AIT-102

SWI/SNF is a protein complex involved in the winding and unwinding of DNA around proteins called chromatin, thereby regulating the expression of thousands of genes. SWI/SNF is mutated in approximately 20% of all cancers. Mutations either in SWI/SNF itself or in transcription factors that associate with SWI/SNF alter the expression of a wide range of genes leading to cancer. AIT-102 is a targeted cancer therapy that inhibits the activity of SWI/SNF in certain tumors where SWI/SNF is mutated (such as Rhabdoid tumors) and in other tumors where SWI/SNF associates with oncogenic transcription factors (such as EWS-FLI in Ewing Sarcoma).

About Rhabdoid Tumor

Rhabdoid tumor is a rare and rapidly progressive pediatric cancer, with an average age at diagnosis of 15 months. In 90% of cases, rhabdoid tumors are due to a mutation in SMARCB1, a tumor suppressor gene encoding a member of the SWI/SNF remodeling complex. There is currently no widely accepted, effective standard of care therapy for the treatment of Rhabdoid Tumors. Patients have an average four-year survival of 1040%.

About Ewing Sarcoma

Ewing Sarcoma is a rare aggressive malignant bone tumor most commonly diagnosed in adolescents and young adults between the age of 10-20. In 85% of cases, Ewing sarcoma is caused by a translocation between chromosomes 11 and 22 which creates a fused EWS-FLI oncogenic transcription factor. Standard of care treatment for Ewing Sarcoma includes the five-chemotherapy regimen VDC/IE with surgery and/or radiation. These therapies are associated with significant short and long-term side effects. The three-year survival rate for patients diagnosed with metastatic Ewing Sarcoma is approximately 30%. For relapsed Ewing Sarcoma, 6-month progression-free survival is just 12.7%.

About AI Therapeutics

AI Therapeutics was founded by Dr. Jonathan Rothberg, serial entrepreneur and Recipient of the National Medal of Technology and Innovation for inventing high speed Next-Gen DNA sequencing, with the goal of utilizing artificial intelligence to accelerate the clinical development of drugs for rare diseases. The company is building out an expansive rare disease pipeline with the help of its Guardian AngelPlatform, a suite of artificial intelligence tools that use deep learning to understand complex disease biology and the action of potential new therapeutics. To learn more, visit: AI-Therapeutics.com.

About 4Catalyzer

AI Therapeutics is part of biotechnology accelerator 4Catalyzer, which has launched Butterfly Network, Quantum-Si, Hyperfine and Liminal Sciences, Detect, Tesseract, and Protein Evolution. All of the 4Catalyzer companies strive to transform 21st century medicine and improve our planet by solving todays most challenging problems across life science research tools, medical devices, therapeutics and the environment. To learn more, visit:4Catalyzer.com.

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AI Therapeutics Announces the Acquisition of Novel Cancer Drug Candidate EC-8042 (AIT-102) - GlobeNewswire

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Grass Valleys 2022 NAB Show push is focused on transformation, showcasing how broadcasters can embrace the cloud and what it can enable.

With this in mind, we recentlyspoke with Sydney Lovely, Grass Valleys CTO, about cloud production the continued expansion of the AMPP ecosystem and new technologies impacting broadcasters like AI and machine learning.

Our conversation has been condensed and edited for clarity.

From my perspective, running R&D globally, about 70 to 80% of our engineering resources are software engineering and have been for quite some time. And even products like our iconic production switchers theyre a complex beast with five million lines of code. So were not really new to the software game.

Were still in reasonably early days in cloud adoption. And the way I would think about it is that technology falls into three main buckets. The first is the hardware-defined technology, like our production switcher is a good example of that, with complex software under the hood but people consume it through the form of hardware. The middle bucket would be products that are more software-based, and people have consumed in a traditional software way through on-prem servers or virtual machines. And those would be products like our playout systems or our MAM system, Stratus.And then the new third bucket is elastic or cloud computing capabilities. What weve seen is that over the last couple of years, those products that were traditional software solutions are moving pretty rapidly to the cloud, things like traditional playout systems.

The things that are going to the cloud sooner are some of these derivative content or streaming channels, etc.

In the past, our customers had to stand up totally different solutions for their digital and streaming channels than theyve had to do for their live production environment. As you can imagine, thats a real hassle for them. So being able to do that in a more joined-up manner is really helpful to them.

If you look at one of the biggest drivers of cloud computing economically elasticity.

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If Im doing something only two hours a day, those types of things really shine in the cloud because you can spin it up, you pay for what youre using and then you shut it down.

And the areas that are always on are less economically interesting. However, the juxtaposition here is that the technical difficulty of playout is by far the easiest and live production is by far the hardest. So thats one of the reasons that this whole industry hasnt really moved to the cloud faster than it has.

With our Grass Valley Media Universe approach, we said, we have to solve the live problem first. And if we solve the live problem first, everything else should be downhill from there.

We started with that live space and then just recently weve released an entirely new application suite around playout that lets customers deliver channels to air, brand them, subtitle them, monetize them with traffic, and so on.

Weve also released our production application suite, with a native HTML editor, a fully elastic ingest service, etc.

Weve really completed the core of the Grass Valley applications. Of course, well continue to add applications to the ecosystem and enhance those applications, but at this point, you can build an entire TV station in the cloud based on the Grass Valley AMPP solution.

If you look at our customers, theyre under a lot of pressure due to digital disruption and the democratization of video in general.

They need things to be simpler and easier. So you used to have many, many, many, many different best-of-breed steps in creating a media supply chain, and each one of those things required specialized expertise on the part of the customer and the vendor community to pull all this stuff together.

Were trying to really streamline this and make it far easier, so it really boils down to a simpler workflow for them.

At this point, its probably less about building it all ourselves or buying it. Its probably more focused on the partner side.

Weve spent five years building a true cloud-native microservices platform. And a lot of the partners weve talked to, theres just no way they can get there on their own. But our customers need those types of solutions to be available in the cloud.

I think Andrews experience with building out those ecosystems is key, absolutely key. And so thats something that has always been part of the vision for this. (Editors note: Lovely means Andrew Cross, Grass Valleys CEO.)

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Its a mixed bag. There are certainly traditionalists that are uncomfortable and if we contrast that with a lot of our more digital native customers, theyre extremely comfortable with it.

There are folks on the broadcast side that are still a little bit uncomfortable with it, but Id say thats really changed a lot in the last couple of years. Necessity is the mother of invention.

The platform weve built, it had an intention of making and giving those customers a familiar experience, so they dont have to have a Ph.D. in AWS or in Kubernetes.

I think its changing. Id say were beyond the first innings of the baseball game, so to speak. Were kind of in the middle innings. So its a mixed bag, but some of our customers that came from very traditional backgrounds have learned this stuff very, very quickly. But theres certainly a lot of demands on everybody because they need to keep their current stuff running. They need to adopt the new technologies and push forward.

I see this unfolding in three phases. So the first phase is going to be AI and machine learning making what Ill call editorial suggestions.

The next piece is going to be fully automated AI and ML with final director-level approval, well call it. So itd actually go through and create content, then you would approve it, and then eventually its lights-out, create it on your own.

Lights-out is created all by automation. So I think the lights-out stuff is a ways off.

Were already there with the suggestive AI capabilities and even some of the capabilities that were able to take advantage of around creation with editorial approval, that second stage.

For example, our automated caption creation is integrated into our AMPP platform and you can use it either way.

Then Id say on the live production side, were also starting to be able to see things like a capability around automated highlighting.

A lot of times with AI and ML, you think about it in terms of image analysis. Its actually even simpler technology than that. Its data wrangling. Weve recently evaluated a partner technology thats automated highlight generation where itll go through and take an entire soccer game, three hours long, and automatically generate a highlight reel.

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Grass Valley's Sydney Lovely on the cloud, AI and the road ahead - NewscastStudio

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence In Diagnostics Market Size, Share & Trends Analysis Report by Component (Software, Services), by Diagnosis Type (Neurology, Radiology, Oncology), by Region (Europe, APAC), and Segment Forecasts, 2022-2030" report has been added to ResearchAndMarkets.com's offering.

The global artificial intelligence in diagnostics market size is expected to reach USD 5.5 billion by 2030, registering a CAGR of 26.3% over the forecast period. The growing demand for integrating AI-enabled algorithms in diagnostics to provide precise and accurate diagnosis at the earliest, which enhances clinical and operational outcomes, is driving the growth of this market.

The rapidly growing cases of acute & chronic disorders across the globe are driving the demand for AI-based solutions since most of these ailments could be either prevented or delayed if diagnosed early and given appropriate treatments. The shortage of healthcare personnel is also supporting the product demand.

The emergence of startups, increasing funding opportunities, and growing public-private partnerships are also boosting market growth. Furthermore, medical technology is witnessing significant transitions & transformations and is rapidly adopting advanced AI-powered solutions to provide precise diagnosis, which enables care providers to design adequate treatment plans. Radiology and pathology are widely implementing AI-based algorithms & solutions and have provided proven results. In radiology, these solutions use information collected from multiple modalities to create image datasets to run data analysis, which could be used by the radiologist in delivering an accurate and timely diagnosis. Similarly, in pathology, these solutions could be integrated to run data analysis and provide accurate results.

The growing burden of chronic conditions across the global population is also driving the demand for AI-based diagnostic solutions. The key participants in AI in diagnostics market are focusing on the development of new, innovative products and the expansion of their business offerings to gain a competitive edge over others. In addition, many startups specializing in the development of advanced AI-based technologies are receiving favorable support and funding opportunities. This will also have a positive impact on the overall market growth. For instance, in September 2018, IDx received funding of USD 33 million from Optum Ventures and 8VC and the company will use this funding for the development of innovative AI-based solutions.

Artificial Intelligence In Diagnostics Market Report Highlights

Key Topics Covered:

Chapter 1 Methodology and Scope

Chapter 2 Executive Summary

Chapter 3 Artificial Intelligence (AI) in Diagnostics Market Variables, Trends & Scope

3.1 Market Lineage Outlook

3.1.1 Parent market outlook

3.1.2 Related/ancillary market outlook

3.2 Penetration and Growth Prospect Mapping

3.3 User Perspective Analysis

3.3.1 Consumer behavior analysis

3.3.2 Market influencer analysis

3.4 Artificial Intelligence (AI) in Diagnostics Market Dynamics

3.4.1 Market Driver Analysis

3.4.1.1 Early detection and classification of diseases

3.4.1.2 Access to smart electronic medical records

3.4.1.3 Increasing use of AI in chronic disease management

3.4.1.4 Increasing number of startups, collaborations, and venture capitalist funding

3.4.2 Market Restraint Analysis

3.4.2.1 Highly regulated industry

3.4.2.2 Procurement costs and maintenance

3.5 Artificial Intelligence in Diagnostics Market Analysis Tools

3.6 Major Deals & Strategic Alliances Analysis

Chapter 4 Global Artificial Intelligence (AI) in Diagnostics Market: Competitive Analysis

Chapter 5 Artificial Intelligence (AI) in Diagnostics Market: Component Estimates & Trend Analysis

Chapter 6 Artificial Intelligence (AI) in Diagnostics Market: Diagnosis Type Estimates & Trend Analysis

Chapter 7 Artificial Intelligence (AI) in Diagnostics Market: Regional Estimates & Trend Analysis: By Component, and Diagnosis Type

Chapter 8 Competitive Landscape

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Artificial Intelligence in Diagnostics Market Analysis Report 2022, Featuring Profiles of Key Players Aidoc, Alivecor, Vuno. Siemens Healthineers and...

Artificial intelligence was thrust into the public consciousness in the late 1960s courtesy of the Stanley Kubrick movie, "2001: A Space Odyssey." Now our fascination with AI has broadened to include its potential to revolutionize the business world. We're able to spot changing trends and consumer habits in near real time, automatically detect fraud and anomalous behavior, and help sales and marketing teams fine-tune messaging to hit targeted audiences with laser precision.

No wonder 81 percent of senior executives say their business uses AI (up from 48 percent in 2018), and 93 percent report that AI makes their business more competitive, according to the Emerging Tech Executive Report from RELX.

But all is not well in the land of AI. Big HR challenges lie firmly across the path of broad adoption and the realization of AI's potential.

A talent shortage stands in the way of the deployment and full utilization of AI in U.S. companies. Whether through lack of training, difficulties in hiring or headhunters luring away top talent, AI technologists are in short supply. Yet they are needed more than ever, and their skills will be coveted for many years to come.

Supply and Demand

Another study by application development firm Reign, based in Santiago, Chile, found that the U.S. witnessed a 21 percent increase in the number of AI jobs, plus a 27 percent increase in AI-related job wages, over the past decade.

"The demand for workers who can develop AI technology is increasing, as are the effects of AI on workers around the world," said Felipe Silberstein, vice president of strategy at Reign. "Jobs requesting AI or machine-learning skills are expected to increase by 71 percent in the next five years."

The demand is there. So what is choking the AI market and its anticipated expansion? The COVID-19 pandemic can perhaps be partially blamed for slowing the momentum of AI. Yet the RELX survey revealed that the pandemic spurred 48 percent of executives to invest in new AI technologies. The Great Resignation, then, is probably more at fault. With millions quitting their jobs during 2021, companies have been left short-staffed and scrambling for talent. A shortage of resources prevents some companies from maximizing their AI capabilities.

"Companies have scaled up their AI capabilities and are hiring more technologists who are AI-savvy," said Vijay Raghavan, RELX technology forum director. "At the same time, American workers are reconsidering the role that work plays in their lives. This has created a tension that intensified the battle for talent in the tech industry."

Hence, 95 percent of respondents see hiring and retaining AI talent as a challenge. The RELX survey noted a drop among those hiring external talent to assist in building out AI-related projects from 59 percent to 50 percent over the past year. But there may be more to it than lack of supply.

AI Backlash

Returning to our movie theme: HAL, of "2001: A Space Odyssey" fame, turned nasty and began killing its crew members. In the case of the business world, the negative consequences revolve around loss of jobs and the need to retrain the workforce. RELX numbers reveal that 39 percent of respondents who think AI has a negative impact on their industry said it is because it requires more training or upskilling of workers. That may be one reason why those investing in upskilling of employees to use AI dropped from 65 percent in 2020 to 56 percent in 2021, and those investing in the future AI workforce through educational initiatives fell from 65 percent to 52 percent.

The Reign survey came up with similar concerns. Over half (54 percent) of respondents were either moderately or very concerned that AI would negatively disrupt their job.

These are just a few of the statistics that indicate that AI's luster has dimmed slightly over the past year. After three years of increasing adoption and enthusiasm according to executive responses, 2021 saw fewer executives than the previous year agreeing that AI helps them to be more competitive and a drop in concern about being left behind by other companies and countries being more advanced in AI.

Upskilling Needed

It may be uncomfortable to face the prospect of upskilling the workforce (or at least portions of it). But it has to be done. And there is willingness among a good portion of the workforce. Silberstein noted that 44.8 percent of people said they were very likely to consider learning tech skills related to working with AI in the near future. Among Millennials, the numbers are even higher.

But stiff job competition means those with the deepest pockets have a definite advantage now. Many companies are reluctant to retrain workers as they have either experienced, or expect to experience, them being snatched up by rivals.

"Some companies are hesitant to invest in upskilling their employees on the basis that they're liable to be lured away after a year or two by a rival company, a hesitancy which ultimately results in less effective AI systems," Raghavan said.

That hesitancy will have to be overcome and a great deal of training and upskilling will be required if the true promise of AI is to manifest in the real world.

Drew Robbis a freelance writer in Clearwater, Fla., specializing in IT and business.

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The AI Revolution Hits an HR Roadblock - SHRM