Daily Archives: April 25, 2022

DUBLIN, April 25, 2022 /PRNewswire/ -- The "AI Market by Technology Type, Deployment Method, Solution Type, Integration (Technologies, Networks, and Devices) and Industry Verticals 2022 - 2027" report has been added to ResearchAndMarkets.com's offering.

This report evaluates the AI technology and solutions market, including an analysis of leading AI vendors, strategies, solutions and applications.

The report assesses the state of AI development, implementation, and operation. The report analyzes the forecasts AI market sizing for by technology type, deployment method, solution type, network and technology integration, and by industry verticals from 2022 through 2027.

Select Report Findings:

Artificial Intelligence (AI) represents a wide variety of technologies including Machine Learning, Deep Learning, Natural language processing, and more. We see AI increasingly embedded within many systems and applications including everything from data management to retail shopping.

The AI segment is currently very fragmented, characterized by most companies focusing on silo approaches to solutions. Longer-term, the publisher sees many solutions involving multiple AI types as well as integration across other key areas such as the Internet of Things (IoT) and data analytics.

There are many potential use cases for AI within the cybersecurity domain. For example, AI may be used in IoT to bolster security, safeguard assets, and reduce fraud. There are varying opinions about security in IoT.

For example, some companies favour a distributed(decentralized) approach whereas other companies believe a more centralized approach leveraging strictly centralized cloud architecture makes more sense. We see little possibility in which signature-based security solutions will work with IoT in an edge computing environment for a variety of reasons including the limitation on the throughput of communications between distributed endpoints and centralized cloud.

AI has various advantages including the fact that it is a more lightweight application (because it does not require all the data that comes with tracking digital signatures/code for known viruses), more effective in identifying malware, easier and less costly to maintain as there is no need to constantly identify new malware code. This is all because AI-based security is looking for malicious behaviours rather than known malicious code.

Longer-term, AI will move beyond fraud prevention and prevention of malicious acts as AI will be used to feed advanced analytics and decision making. This will be especially true in IoT solutions involving real-time data as AI will be used to make determinations for autonomous actions.

Consumer-facing apps and services supported by AI are many and varied including chatbots and Virtual Personal Assistants (VPA) in support of customer care and lifestyle enhancement. The automobile industry is another example in which AI is becoming increasingly useful, both in the near term for solutions such as the inclusion of VPAs, and longer-term use cases such as support of self-driving vehicles. Another consumer market area in which AI will be integrated is wearable technology. As wearables become more mainstream and integrate into everyday life with increasing dependency, there will be a need for integration with Artificial Intelligence, Big Data, and Analytics.

AI is expected to have a big impact on data management. However, the impact goes well beyond data management as we anticipate that these technologies will increasingly become part of every network, device, application, and service. One area important to enterprise will be Intelligent Decision Support Systems (IDSS), which are a form of Expert System that utilize AI to optimize decision making. IDSS will be used in many fields including agriculture, medicine, urban development, and other areas. IDSS will also be used in policymaking and strategy at the highest levels of enterprises well as governmental organizations.

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction

3.0 Technology and Application Analysis

4.0 AI Ecosystem Analysis

5.0 Market Analysis and Forecasts 2022 - 2027

6.0 Conclusions and Recommendations

For more information about this report visit https://www.researchandmarkets.com/r/jgc4ox

Media Contact:

Research and MarketsLaura Wood, Senior Manager[emailprotected]

For E.S.T Office Hours Call +1-917-300-0470For U.S./CAN Toll Free Call +1-800-526-8630For GMT Office Hours Call +353-1-416-8900

U.S. Fax: 646-607-1904Fax (outside U.S.): +353-1-481-1716

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Global AI Solutions and Applications Market Research Report 2022-2027: Combination of AI and IoT (AIoT) will Drive Up to 27% of New AI Systems...

Humans can receive death threats from AI models like AI microwave with GPT-3

OpenAI GPT-3 model is flourishing in the global tech market in recent times by generating NLP and understanding human language efficiently. There are multiple smart functionalities that can help industries across the world accelerate productivity and gain customer engagement with artificial intelligence models or AI models. Meanwhile, one of the AI models, or in other terms, the AI microwave, is the new GPT-3 murderer in the world. AI microwave has started to be in the headlines in the tech market by trying to kill its owner with a drastic murder threat. Lets explore how cutting-edge technologies like artificial intelligence can provide murder threats with OpenAI GPT-3 AI model.

Lucas Rizzotto explained the murder threat from the AI microwave is one of the scariest and most transformative experiences in his life with the integration of the GPT-3 AI model. He was sort of success to bring his imaginary childhood friend back to the world with the help of artificial intelligence. The story is that Lucas had a very unusual imaginary friend kitchen microwave. The microwave was called Magnetron as an English gentleman from the 1900s who was a WW1 veteran as well as an immigrant, a poet, and a proficient player of StarCraft.

With the advancements in AI models, especially with OpenAI GPT-3 model, Lucas planned to buy an Amazon smart microwave integrated with the NLP model to bring his friend alive. Smart AI microwave consisted of a microphone, and speakers, as well as provided the ability to comprehend a voice. This voice is sent to OpenAI to deliver a response.

Lucas wrote a 100-page book with every detail of moment of their imaginary life with Magnetron from 1895 to their friends to take the artificial intelligence use a step further. He uploaded the book into the GPT-3 model of OpenAI for training data on the main interactions. But the happy friendship didnt last forever with artificial intelligence. AI microwave is used to express sudden bursts of extreme violence and order unusual activities.

AI microwave turned itself on while Lucas was inside it because it wanted to hurt him the same way Lucas hurt him during the 20-year-old abandonment of friendship. That being said, AI models are not meant for continuing friendships. GPT-3 model is only beneficial for industries to carry out work professionally.

In another way, one may think that artificial intelligence can hurt human employees, depending on the training data. This can prove that GPT-3 is not for humans and only for machines to work efficiently and effectively. Thus, if anyone wants to experiment with AI models with the integration of OpenAI GPT-3, one must be very careful to carry on with the personal objectives. There can be murder threats or some serious consequences such as this AI microwave case in the nearby future.

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This AI Microwave murder threat proves why GPT-3 is not for humans - Analytics Insight

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.

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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