WASHINGTON Raytheons intelligence and space business is partnering with C3.ai, a software company known for its predictive maintenance business with the U.S. Air Force, the companies announced Monday.

The alliance between C3.ai and Raytheon Intelligence and Space aims to speed up artificial intelligence adoption across the U.S. military. The partnership will pair Raytheons expertise in the defense and aerospace sector with C3.ais artificial intelligence development and applications.

The military and intelligence community have access to more data now than any time in history, but its more than theyre able to make quick use of, said David Appel, vice president of defense and civil solutions for space and C2 systems under Raytheon Intelligence and Space. Artificial intelligence can be used to help them make sense of that data, which will allow them to make smarter decisions faster on the battlefield. And thats just one of the benefits.

In recent years, C3.ai has positioned itself as a trusted partner of the Air Force, providing predictive maintenance capabilities for the services E-3, C-5 Galaxy, F-15, F-16, F-18 and F-35 aircraft. The Pentagons Silicon Valley arm that helped bridge C3.ai into the Pentagon, the Defense Innovation Unit, estimated that the program could save the service $15 billion annually in maintenance funds if it was scaled to the Defense Departments entire aircraft fleet.

In January, DIU awarded a five-year, $95 million contract to C3.ai for predictive maintenance. The alliance between the two companies will also focus on helping the intelligence community.

Raytheon and C3.ai are driven by similar purposes: Anticipating and solving our customers most difficult problems, said Thomas Siebel, CEO of C3.ai. Together, we offer an end-to-end enterprise AI platform and mission-tailored applications that will dramatically reduce cost and risk, accelerate adoption and deployment of AI solutions, and scale the impact of AI across any organization.

In September, the Air Forces rapid sustainment office selected C3.ais C3 AI Suite platform and C3 AI Readiness product to support predictive maintenance across the services enterprise.

Raytheon and C3.ai represent key partners for the U.S. Air Force, and specifically the Rapid Sustainment Office, in realizing the vision of harnessing AI to transform the military into a digital organization, said Nathan Parker, deputy program executive officer for the Air Force Rapid Sustainment Office. Fulfilling this vision of broad implementation requires identifying applicable use cases for AI across the Air Force, rapidly piloting solutions, and scaling successes across our enterprise to accelerate the transformation.

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Also on Monday, C3.ai announced that it will be launching an initial public offering. It expects shares to be valued between $31-$34.

Originally posted here:
Raytheon and C3.ai announce alliance on artificial intelligence solutions - C4ISRNet

By J. William Middendorf| The Providence Journal

J. William Middendorf, who lives in Little Compton, served as Secretary of the Navy during the Ford administration. His recent book is "The Great Nightfall: How We Win the New Cold War."

Thirteen days passed in October 1962 while President John F. Kennedy and his advisers perched at the edge of the nuclear abyss, pondering their response to the discovery of Russian missiles in Cuba. Today, a president may not have 13 minutes. Indeed, a president may not be involved at all.

Artificial intelligence is the future, not only for Russia, but for all humankind. It comes with colossal opportunities but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world.

This statement from Vladimir Putin, Russian president, comes at a time when artificial intelligence is already coming to the battlefield and some would say it is already here. Weapons systems driven by artificial intelligence algorithms will soon be making potentially deadly decisions on the battlefield. This transition is not theoretical. The immense capability of large numbers of autonomous systems represent a revolution in warfare that no country can ignore.

The Russian Military Industrial Committee has approved a plan that would have 30% of Russian combat power consist of remote controlled and autonomous robotic platforms by 2030. China has vowed to achieve AI dominance by 2030. It is already the second-largest R&D spender, accounting for 21% of the worlds total of nearly $2 trillion in 2015. Only the United States at 26%ranks higher. If recent growth rates continue, China will soon become the biggest spender.

If China makes a breakthrough in crucial AI technology satellites, missiles, cyber-warfare or electromagnetic weapons it could result in a major shift in the strategic balance. Chinas leadership sees increased military usage of AI as inevitable and is aggressively pursuing it. Zeng Yi, a senior executive at Chinas third-largest defense company, recently predicted that in future battlegrounds there will be no people fighting, and, by 2025, lethal autonomous weapons would be commonplace.

Well-intentioned scientists have called for rules that will always keep humans in the loop of the military use of AI. Elon Musk, founder of Tesla, has warned that AI could be humanitys greatest existential threat for starting a third world war. Musk is one of 100 signatories calling for a United Nations-led ban of lethal autonomous weapons. These scientists forget that countries like China, Russia, North Korea and Iran will use every form of AI if they have it.

Recently, Diane Greene, CEO of Google, announced that her company would not renew its contract to provide recognition software for U.S. military drones. Google had agreed to partner with the Department of Defense in a program aimed at improving Americas ability to win wars with computer algorithms.

The world will be safer and more powerful with strong leadership in AI. Here are three steps we should take immediately.

Convince technological companies that refusal to work with the U.S. military could have the opposite effect of what they intend. If technology companies want to promote peace, they should stand with, not against, the U.S, defense community.

Increase federal spending on basic research that will help us compete with China, Russia, North Korea and Iran in AI.

Remain ever alert to the serious risk of accidental conflict in the military applications of machine learning or algorithmic automation. Ignorant or unintentional use of AI is understandably feared as a major potential cause of an accidental war.

See the original post:
Opinion/Middendorf: Artificial intelligence and the future of warfare - The Providence Journal

A 50-year-old science problem has been solved remarkably early with artificial intelligence, researchers have announced. The news could now fast-track how diseases are both treated and cured.

Scientists have long been hampered by an issue known as protein folding.

This computational work represents a stunning advance on the protein-folding problem, a 50-year-old grand challenge in biology

Professor Venki Ramakrishnan

This involves mapping the 3D shapes of the proteins identified as responsible for diseases ranging from coronavirus to cancers.

Googles Deepmind claims to have created an artificially intelligent program called 'AlphaFold' capable of solving those problems within days.

If all goes according to plan, experts suggest the solution has come decades earlier than expected, potentially leading to revolutionary ways diseases are treated.

READ MORE:AI-manipulated media will be WEAPONISED to trick military

Although 200 million proteins are known to exist, only a fraction have actually been unfolded to fully understand how they work.

And the minority that are understood have relied upon on expensive and time-intensive techniques.

These often involved scientists spending years and millions unfailing each structure.

Google DeepMind worked on the AI project with 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), scientists investigating the matter since 1994.

Dr John Moult, chair of CASP14, said "Proteins are extremely complicated molecules, and their precise three-dimensional structure is key to the many roles they perform, for example the insulin that regulates sugar levels in our blood and the antibodies that help us fight infections.

"Even tiny rearrangements of these vital molecules can have catastrophic effects on our health, so one of the most efficient ways to understand disease and find new treatments is to study the proteins involved.

"There are tens of thousands of human proteins and many billions in other species, including bacteria and viruses, but working out the shape of just one requires expensive equipment and can take years."

DeepMind has announced AlphaFold understood the shape of around two-thirds of the proteins with accuracy comparable to laboratory experiments.

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DeepMind has published the results of those tests on its website, allowing verification to be made by external scientists.

The team behind the AlphaFold project will next focus on determining how multiple proteins form complexes and their interaction with human DNA.

Professor Venki Ramakrishnan, Nobel Laureate and president of the Royal Society, said: "This computational work represents a stunning advance on the protein-folding problem, a 50-year-old grand challenge in biology.

"It has occurred decades before many people in the field would have predicted.

"It will be exciting to see the many ways in which it will fundamentally change biological research."

Among other revelations, Google DeepMind noted predicted protein structures could play an important role in responding to future pandemics.

Such machine learning technology has already been used on the protein structures of the SARS-CoV-2 virus, responsible for Covid-19.

View original post here:
Artificial intelligence solves 50-year-old science problem - 'Its a game changer' - Daily Express

DUBLIN, Nov. 30, 2020 /PRNewswire/ -- The "Europe Artificial Intelligence in Healthcare Diagnosis Market Forecast to 2027 - COVID-19 Impact and Regional Analysis by Diagnostic Tool; Application; End User; Service; and Country" report has been added to ResearchAndMarkets.com's offering.

The Europe Radiology Information Systems (RIS) market is projected to reach from US$ 315.32 million in 2019 to US$ 574.44 million by 2027. This represents a CAGR of 8.0% from 2020 to 2027.

The growth of the Europe Radiology Information Systems (RIS) market is primarily attributed to advancements in diagnostic imaging solutions coupled with rising number of diagnostic procedures, and increasing partnerships and collaborations are driving the adoption of radiology information systems.

The healthcare industry has always been a leader in innovation. The constant mutating of diseases and viruses makes it difficult to stay ahead of the curve. However, with the help of artificial intelligence and machine learning algorithms, it continues to advance, creating new treatments and helping people live longer and healthier. Medical imaging is a vital part of medical care and treatment across the globe. Rising awareness regarding early diagnosis of diseases has led to an increase in the total number of diagnostic tests procedures performed around the world.

For instance, as per NHS England report, in 2018, ~42.7 million imaging tests were performed in England, an increase of 1.4% than the previous year. X-ray was the most performed method with 22.9 million procedures, followed by diagnostic ultrasonography (9.51 million), CT Scan (5.15 million), and magnetic resonance imaging (3.46 million).

In 2019, the Integrated RIS segment held a considerable share of the for Europe Radiology Information Systems (RIS) market, by the product. This segment is also predicted to dominate the market by 2027 owing to rising demand for AI based application for radiology.

Key Topics Covered:

1. Introduction

1.1 Scope of the Study

1.2 Report Guidance

1.3 Market Segmentation

2. Europe Artificial Intelligence in Healthcare Diagnosis Market - Key Takeaways

3. Research Methodology

3.1 Coverage

3.2 Secondary Research

3.3 Primary Research

4. Europe Artificial Intelligence in Healthcare Diagnosis Market - Market Landscape

4.1 Overview

4.2 PEST Analysis

4.3 Expert Opinion

5. Europe Artificial Intelligence in Healthcare Diagnosis Market - Key Market Dynamics

5.1 Market Drivers

5.1.1 Rising Adoption of Artificial Intelligence (AI) in Disease Identification and Diagnosis

5.1.2 Increasing Investment in AI Healthcare Start ups

5.2 Market Restraints

5.2.1 Lack of skilled AI Workforce and Ambiguous Regulatory Guidelines for Medical Software

5.3 Market Opportunities

5.3.1 Increasing Potential in Emerging Economies

5.4 Future Trends

5.4.1 AI in Epidemic Outbreak Prediction and Response

5.5 Impact analysis

6. Europe Artificial Intelligence in Healthcare Diagnosis Market - By Diagnostic Tool

6.1 Overview

6.2 Europe Artificial Intelligence in Healthcare Diagnosis Market Revenue Share, by Diagnostic Tool (2019 and 2027)

6.3 Medical Imaging Tool

6.3.1 Overview

6.3.2 Medical Imaging Tools: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)

6.4 Automated Detection System

6.4.1 Overview

6.4.2 Automated Detection System: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)

6.5 Others

6.5.1 Overview

6.5.2 Others: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)

7. Europe Artificial Intelligence in Healthcare Diagnosis Market Analysis, by Application

7.1 Overview

7.2 Artificial Intelligence in Healthcare Diagnosis Market Revenue Share, by Application (2019 and 2027)

7.3 Eye Care

7.3.1 Overview

7.3.2 Eye Care: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)

7.4 Oncology

7.5 Radiology

7.6 Cardiovascular

8. Europe Artificial Intelligence in Healthcare Diagnosis Market - By End-User

8.1 Overview

8.2 Artificial Intelligence in Healthcare Diagnosis Market, by End-User, 2019 and 2027 (%)

8.3 Hospital and Clinic

8.3.1 Overview

8.3.2 Hospital and Clinic: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)

8.4 Diagnostic Laboratory

8.5 Home Care

8.5.1 Overview

8.5.2 Home Care: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)

8.5.3 Doctors

8.5.4 Patients

9. Europe Artificial Intelligence in Healthcare Diagnosis Market - By Service

9.1 Overview

9.2 Artificial Intelligence in Healthcare Diagnosis Market, by Service, 2019 and 2027 (%)

9.3 Tele-Consultation

9.3.1 Overview

9.3.2 Tele-Consultation: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)

9.4 Tele-Monitoring

9.5 Others

10. Europe Artificial Intelligence in Healthcare Diagnosis Market - Country Analysis

11. Impact Of COVID-19 Pandemic on Europe Artificial Intelligence in Healthcare Diagnosis Market

11.1 Europe: Impact Assessment Of COVID-19 Pandemic

12. Company Profiles

12.1 Key Facts

12.2 Business Description

12.3 Products and Services

12.4 Financial Overview

12.5 SWOT Analysis

12.6 Key Developments

For more information about this report visit https://www.researchandmarkets.com/r/dj2zk7

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

Media Contact:

Research and Markets Laura Wood, Senior Manager [emailprotected]

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

U.S. Fax: 646-607-1907 Fax (outside U.S.): +353-1-481-1716

SOURCE Research and Markets

http://www.researchandmarkets.com

Here is the original post:
Europe Artificial Intelligence in Healthcare Diagnosis Markets, 2019-2020 & 2027 - AI in Epidemic Outbreak Prediction and Response Gaining...

DUBLIN, Nov. 30, 2020 /PRNewswire/ -- The "Modular Robotics Market Research Report: By Offering, Robot Type, Payload Capacity, End User - Global Industry Analysis and Growth Forecast to 2030" report has been added to ResearchAndMarkets.com's offering.

The revenue of the market will rise from $5.6 billion to $15.1 billion from 2019 to 2030, with the market demonstrating a CAGR of 9.9% from 2020 to 2030.

The rising requirement for automation in manufacturing and warehouse operations is pushing up the global demand for collaborative modular robotics systems. This is, in turn, boosting the sales of modular robotics systems all over the world, which is causing the surge of the global modular robotics market.

A key market driver is the rising usage of collaborative modular robotics systems or cobots as they are sometimes called, in the logistics industry. With the adoption of these robots, the operators can hand over the parts to the robots for performing the rest of the tasks, which results in faster production processes, lesser expenditure, and lesser floor space requirements. These robots are also being used for load carrying and transporting tasks, because of their versatility.

Another factor fueling the progress of the market is the rising requirement for automation in manufacturing processes. The increasing requirements for faster manufacturing times, high efficiency in production processes, and higher manufacturing outputs are augmenting the need for automation in industries. As a result, modular robotics systems are being increasingly used in various operations in factories and warehouses. When offering is taken into consideration, the modular robotics market is classified into software, hardware, and services.

Out of these categories, the software category is predicted to exhibit the fastest growth in the market in the future years, mainly due to the burgeoning requirement for software for checking the real-time functioning of a modular robotics system and the growing integration of IoT and AI in these robots. However, despite this factor, the highest market growth will be demonstrated by the hardware category, under the offering segment, in the upcoming years.

According to the forecast of the market research company this category will hold the highest revenue share in the market in the future. Depending on robot type, the market is divided into SCARA (selective compliance assistance robot arm) modular robotics systems, collaborative modular robots, cartesian modular robots, parallel modular robots, and articulated modular robotics systems, out of which, the articulated modular robotics system division will register the highest growth in the market in the forthcoming years.

Historically, the modular robotics market exhibited the highest growth in the Asia-Pacific (APAC) region and this trend will continue in the coming years as well, primarily because of the ballooning investments being made in electricals, electronics, and automotive industries, especially in the regional nations such as China, South Korea, and India. In addition to this, the rising usage of collaborative modular robotics systems in manufacturing operations is massively propelling the sales of these robots in the region.

Hence, it can be inferred from the above paragraphs that the sales of modular robotics systems will rise steeply throughout the world in the coming years, mainly because of the growing requirement for automation in factory, warehouse, and logistics operations and the rising usage of collaborative modular robotics systems in various industries.

Key Topics Covered:

Chapter 1. Research Background

1.1 Research Objectives

1.2 Market Definition

1.3 Research Scope

1.4 Key Stakeholders

Chapter 2. Research Methodology

2.1 Secondary Research

2.2 Primary Research

2.3 Market Size Estimation

2.4 Data Triangulation

2.5 Currency Conversion Rates

2.6 Assumptions for the Study

2.7 Notes and Caveats

2.8 Impact of COVID-19 Outbreak

Chapter 3. Executive Summary

Chapter 4. Introduction

4.1 Definition of Market Segments

4.1.1 By Offering

4.1.1.1 Hardware

4.1.1.1.1 Controller

4.1.1.1.2 Driver module

4.1.1.1.3 Manipulator

4.1.1.1.4 Sensor

4.1.1.1.5 Other

4.1.1.2 Software

4.1.1.3 Services

4.1.2 By Robot Type

4.1.2.1 Articulated modular robots

4.1.2.2 Cartesian modular robots

4.1.2.3 SCARA modular robots

4.1.2.4 Parallel modular robots

4.1.2.5 Collaborative modular robots

4.1.2.6 Others

4.1.3 By Payload Capacity

4.1.3.1 1-16.0 Kg

4.1.3.2 16.1-60.0 Kg

4.1.3.3 60.1-225.0 Kg

4.1.3.4 More Than 225.0 Kg

4.1.4 By End User

4.1.4.1 Industrial

4.1.4.1.1 Automotive

4.1.4.1.2 Electrical & electronics

4.1.4.1.3 Plastics & rubber

4.1.4.1.4 Metals & machinery

4.1.4.1.5 Food & beverages

4.1.4.1.6 Healthcare

4.1.4.1.7 Others

4.1.4.2 Commercial

4.1.4.3 Residential

4.2 Value Chain Analysis

4.3 Market Dynamics

4.3.1 Trends

4.3.1.1 Penetration of IIoT in industrial manufacturing

4.3.2 Drivers

4.3.2.1 Surging demand for automation in manufacturing industry

4.3.2.2 Growing demand for collaborative modular robots

4.3.2.3 Impact analysis of drivers on market forecast

4.3.3 Restraints

4.3.3.1 Complexity in design of modular robots

4.3.3.2 Impact analysis of restraints on market forecast

4.3.4 Opportunities

4.3.4.1 Use of artificial intelligence to improve productivity

4.4 Porter's Five Forces Analysis

Chapter 5. Global Market Size and Forecast

5.1 By Offering

5.1.1 Hardware, by Type

5.2 By Robot Type

5.3 By Payload Capacity

5.4 By End User

5.4.1 Industrial, by Type

5.5 By Region

Chapter 6. North America Market Size and Forecast

Chapter 7. Europe Market Size and Forecast

Chapter 8. APAC Market Size and Forecast

Chapter 9. LATAM Market Size and Forecast

Chapter 10. MEA Market Size and Forecast

Chapter 11. Competitive Landscape

11.1 List of Players and Their Offerings

11.2 Ranking Analysis of Key Players

11.3 Competitive Benchmarking of Key Players

11.4 Global Strategic Developments in the Market

11.4.1 Product Launches

11.4.2 Facility Expansions

11.4.3 Partnerships

11.4.4 Client Wins

Chapter 12. Company Profiles

12.1 Business Overview

12.2 Product and Service Offerings

12.3 Key Financial Summary

For more information about this report visit https://www.researchandmarkets.com/r/jb90fd

More:
Modular Robotics Markets, 2030 - Opportunities in the Use of Artificial Intelligence (AI) to Improve Productivity - WFMZ Allentown

RICHMOND HILL, N.Y.--(BUSINESS WIRE)--iHealthScreen CEO Alauddin Bhuiyan, Ph.D. along with collaborators at New York Eye and Ear Infirmary at Mount Sinai (NYEEI), presented a prospective study for early diagnosis of AMD at the annual conference of AAO, 2020. The results presented during the prestigious Original Paper Session demonstrated 88.7% accuracy, compared to ophthalmologist gradings, on detecting referable AMD.

AMD, with no early signs or symptoms, is a leading cause of adult blindness in the developed world. Early detection can enable preventative measures in time and stop AMD incident. Currently, AMD diagnosis has been limited to retinal examination by an ophthalmologist. AMD cases in the U.S. are expected to grow from 2.1 million to 5.4 million in the next ten years, and there is an increasing need for large scale screening and identification of individuals who are at risk of developing late AMD. iHealthScreens AI based tool can facilitate this screening and help prevention of late AMD.

In an interview, Dr. Bhuiyan spoke about the study and the findings: We are encouraged by the results and believe that the new AI-based technology can diagnose early AMD in primary care settings, which enables the timely preventative measures by ophthalmologist and prevent this deterioration of vision. We want to express our sincerest thanks to the participants and professional staff who were involved in this clinical trial and gathered the data.

These results speak to the feasibility of this approach, said Theodore Smith, M.D., Ph.D., Trials Principal-investigator and Professor at Icahn School of Medicine at Mount Sinai. I believe that the ease of use of iHealthScreens AI tool will contribute to its adoption in the wider primary care community.

About iHealthScreen

iHealthScreen is a private, clinical-stage, medical diagnostic/device company. iHealthScreen has developed iPredict, an AI and telemedicine-based HIPAA compliant platform for automated screening and prediction of individuals at risk of developing late age-related AMD, diabetic retinopathy (DR), glaucoma, cardiovascular heart disease and stroke.

Read this article:
iHealthScreen's Artificial Intelligence (AI) Based Tool Can Accurately Diagnose Age-Related Macular Degeneration (AMD) and Help Prevent Blindness -...

When Professor Boaz Golany of the Technion gave a speech to visiting students from the Czech Technical University in Prague several years ago, he described the Golem of Prague as a metaphor for artificial intelligence (AI). The Golem is part of Jewish tradition and is well known to every Czech. The legend of the Golem and his 16th-century creator, Rabbi Loew Judah ben Bezalel, known as the Maharal, has been an integral part of popular culture in Czechia since the end of the 19th century. When people can share such complicated metaphors, it is no wonder there are currently a number of Czech-Israeli research projects using AI in different fields that assist communication between robots of different autonomous vehicles, find an optimal path for robots maneuvering with drones or improve robotic physiotherapy treatment.

Quite a few Czech intellectuals have been fascinated with the connection of the Golem to the development of science. This past September was the 100th anniversary of the publication of R.U.R., the dystopian play by the Czech author Karel apek that introduced the word robot into the English language and to the world of science. apek himself said that his robots were Golems in mass production.

Czech companies also bring high value to complicated construction projects. Dekonta, the leading Czech environmental services and technologies company, participated in a bioremediation project of contaminated soil at the Beersheva Railway Station. The JUTA company supplied high-density polyethylene (HDPE) geomembranes for the Habonim water reservoir project in the Carmel coastal area near Haifa.

Many more opportunities are on the way. The Czech ICT company Tesco SW is developing brain diagnostic software for Parkinsons disease that can be used in Israel. Last year the DLD Tel Aviv Innovation Festival brought together innovators, who announced the creation of the Czech-Israeli platform of FinTech companies in early November. They also want to support bilateral tourism and business financing.

Perhaps the Czech-Israeli collaboration in the sciences can be best epitomized by Jakub Abramson, an immunology professor at Weizmann Institute in Rehovot. Professor Abramson was born in Prague and made Aliyah ten years ago. He is very enthusiastic about Czech-Israeli collaboration. It is important for me to strengthen Czech and Israeli collaboration. In the Czech Republic, there is great potential for science. They have amazing potential that they dont use and exploit properly. Professor Abramson has done many collaborations with Czech scientists, including a description of a new auto-immune disease that attacks the teeth and combining Israeli expertise in immunology with Czech know-how in medicinal chemistry. He is looking forward to spending the next academic year on sabbatical in Prague.

The cooperation in science has been growing, thanks to joint financial support from the Israeli Ministry of Science and Technology and the Czech Ministry of Education. Currently, there are six Czech-Israeli projects examining the use of nanotechnologies in cleaning air or water, the use of AI in computer vision, the development of assistive devices for physiotherapy, planning for robotic laparoscopic surgery, and conflict-free movement of self-driven vehicles. The successful research project should be followed by commercial success. Private and public support for accelerating innovations, creating joint start-ups, or removing barriers for innovative companies to offer their products in the partner country could bring the Czech-Israeli innovative cooperation to another level.

Czech-Israeli Innovation Days

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From the Golem of Prague to artificial intelligence - The Jerusalem Post

A new report added by Big Market Research claims that the globalArtificial Intelligence (AI) in Drug Discovery marketgrowth is set to reach newer heights during the forecast period,2020-2026.

This report is meticulous research formulated by market professionals by deeply analyzing key driving and restraining factors, major regional market situations, major players, and size & scope of the market. The report also offers value chain analysis, Porters Five Forces model, and PEST analysis. Furthermore, the competitive landscape in different regions is elucidated in the report to assist top market players, new entrants, and investors determine investment opportunities.

Request for a sample copy of this report @https://www.bigmarketresearch.com/request-sample/3848349?utm_source=SHASHI&utm_medium=MC

The report also explains the factors boosting the market growth. The major drivers of the Artificial Intelligence (AI) in Drug Discovery market are:

Microsoft Corporation, NVIDIA Corporation, IBM Corporation, Google Inc., Atomwise, Inc., Deep Genomics, Cloud Pharmaceuticals, Inc., Insilico Medicine, Benevolentai, Exscientia,

In addition, the research report provides a comprehensive analysis of the key segments of the Artificial Intelligence (AI) in Drug Discovery market. An outline of each market segment such as type, application, and region are also provided in the report.

On the basis of region, the market is evaluated across:

North America (U.S., Canada, Mexico, etc.)

Asia-Pacific (China, Japan, India, Korea, Australia, Indonesia, Taiwan, Thailand, etc.)

Europe (Germany, UK, France, Italy, Russia, Spain, etc.)

Middle East & Africa (Turkey, Saudi Arabia, Iran, Egypt, Nigeria, UAE, Israel, South Africa, etc.)

South America (Brazil, Argentina, Colombia, Chile, Venezuela, Peru, etc.)

The report outlines company profiles, product specifications and capacity, production value, and 2020-2026 market shares of key players active in the market. Moreover, the research presents the performance and recent developments of the foremost players functioning in the market. The insights delivered in the report are valuable for individuals or companies interested in investing in the Artificial Intelligence (AI) in Drug Discovery industry. These insights might help market players in devising effective business strategies and taking the required steps to obtain a leadership position in the industry.

Shareholders, stakeholders, product managers, marketing officials, investors, and other professionals in search of detailed data on supply, demand, and future predictions of the Artificial Intelligence (AI) in Drug Discovery market would find the report beneficial. Furthermore, we endeavor to deliver a customized report to fulfill the special requirements of our clients, on-demand.

Research Objective

To analyze and forecast the market size of global Artificial Intelligence (AI) in Drug Discovery market.

To classify and forecast global Artificial Intelligence (AI) in Drug Discovery market based on product, sources, application.

To identify drivers and challenges for global Artificial Intelligence (AI) in Drug Discovery market.

To examine competitive developments such as mergers & acquisitions, agreements, collaborations and partnerships, etc., in global Artificial Intelligence (AI) in Drug Discovery market.

To conduct pricing analysis for global Artificial Intelligence (AI) in Drug Discovery market.

To identify and analyze the profile of leading players operating in global Artificial Intelligence (AI) in Drug Discovery market.

The report is useful in providing answers to several critical questions that are important for the industry stakeholders such as manufacturers and partners, end users, etc., besides allowing them in strategizing investments and capitalizing on market opportunities. Key target audience are:

Manufacturers of Artificial Intelligence (AI) in Drug Discovery

Raw material suppliers

Market research and consulting firms

Government bodies such as regulating authorities and policy makers

Organizations, forums and alliances related to Artificial Intelligence (AI) in Drug Discovery

Highlights following key factors:

:- Business description A detailed description of the companys operations and business divisions.:- Corporate strategy Analysts summarization of the companys business strategy.:- SWOT Analysis A detailed analysis of the companys strengths, weakness, opportunities and threats.:- Company history Progression of key events associated with the company.:- Major products and services A list of major products, services and brands of the company.:- Key competitors A list of key competitors to the company.:- Important locations and subsidiaries A list and contact details of key locations and subsidiaries of the company.:- Detailed financial ratios for the past five years The latest financial ratios derived from the annual financial statements published by the company with 5 years history.

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Table of Contents

Chapter 1. Executive Summary

Chapter 2. Global Artificial Intelligence (AI) in Drug Discovery Market Definition and Scope

Chapter 3. Global Artificial Intelligence (AI) in Drug Discovery Market Dynamics

Chapter 4. Global Artificial Intelligence (AI) in Drug Discovery Market: Industry Analysis

Chapter 5. Global Artificial Intelligence (AI) in Drug Discovery Market, by Method

Chapter 6. Global Artificial Intelligence (AI) in Drug Discovery Market, by Style

Chapter 7. Global Artificial Intelligence (AI) in Drug Discovery Market, by Application

Chapter 8. Global Artificial Intelligence (AI) in Drug Discovery Market, Regional Analysis

Chapter 9. Competitive Intelligence

Chapter 10. Research Process

Tending Report :

Global Healthcare Data Storage Market Size study, by Type (Flash & Solid-State Storage, Magnetic Storage), Storage System (Storage Area Network, Direct-Attached Storage, Network-Attached Storage), EJLN-User (Pharmaceutical & Biotechnology Companies, Hospitals & Clinics, Research Centers, Others) aJLN Regional Forecasts 2020-2026

https://www.bigmarketresearch.com/report/3848350/global-healthcare-data-storage-market?utm_source=SHASHI&utm_medium=RR

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Artificial Intelligence (AI) in Drug Discovery Market in Global : Current and the Future Trends : Microsoft Corporation, NVIDIA Corporation, IBM...

WEST LAFAYETTE, Ind. The COVID-19 pandemic is leading a Purdue University innovator to make changes as she works to provide new options for people with Parkinsons disease.

Jessica Huber, a professor of speech, language, and hearing sciences and associate dean for research in Purdues College of Health and Human Sciences, leads Purdues Motor Speech Lab. Huber and her team are now doing virtual studies to evaluate speech disorders related to Parkinsons using artificial intelligence technology platforms.

Huber and her team have been working to develop telepractice tools for the assessment and treatment of speech impairments like Parkinsons disease. They received a National Institutes of Health small business innovation and research grant to develop a telehealth platform to facilitate the provision of speech treatment with the SpeechVive device, which has received attention at the Annual Convention of the American Speech-Language-Hearing Association.

In the current study, Huber and her team are collaborating with a startup company, Modality AI, which developed the AI platform that will be used in the study.

The application of the technology we are evaluating may lead to far-reaching insights into more standardization in assessments, earlier diagnoses and possibly an easier way to track discrete changes over time to guide interventions, said Andrew Exner, a graduate research assistant in the Motor Speech Lab. My personal research passion, and the mission of our lab, is to find ways to improve the quality of life for people with Parkinsons and other related diseases.

Exner is leading the virtual study for participants across the country to evaluate an AI platform that can collect and automatically measure the speech skills of people with Parkinsons disease. The need for AI platforms is increasing as the use of telepractice explodes as a result of the COVID-19 pandemic.

My interest in speech-language pathology actually started during my training as an actor and opera singer, Exner said. I saw the effects of pathology on the voice and wanted to extend that interest into speech disorders.

SpeechVive Inc. is an Indiana startup company based on Hubers research. The company has developed a wearable medical device to improve the speech clarity of people with Parkinsons.

Anyone interested in learning more about the virtual studies or taking part can email Exner at exner@purdue.edu.

About SpeechVive

SpeechVive is a behind-the-ear smart device that helps people with Parkinsons disease speak more loudly and communicate more effectively. The SpeechVive device is based on the research of inventor and co-founder Jessica Huber at Purdue University. Clinical data over four years demonstrated SpeechVive to be effective in improving volume, articulation and speech rate in 90% of the people participating in four multi-site clinical trials. It is estimated that 1.5 million people in the U.S. and 10 million people worldwide suffer from Parkinsons disease. To learn more about SpeechVive, visit http://www.speechvive.com.

About Purdue Research Foundation

The Purdue Research Foundation is a private, nonprofit foundation created to advance the mission of Purdue University. Established in 1930, the foundation accepts gifts; administers trusts; funds scholarships and grants; acquires property; protects Purdue's intellectual property; and promotes entrepreneurial activities on behalf of Purdue. The foundation manages the Purdue Foundry, Purdue Office of Technology Commercialization, Purdue Research Park, Purdue Technology Centers and University Development Office. In 2020, the IPWatchdog Institute ranked Purdue third nationally in startup creation and in the top 20 for patents. The foundation received the 2019 Innovation and Economic Prosperity Universities Award for Place from the Association of Public and Land-grant Universities. For more information on licensing a Purdue innovation, contact the Purdue Office of Technology Commercialization at otcip@prf.org. For more information about involvement and investment opportunities in startups based on a Purdue innovation, contact the Purdue Foundry at foundry@prf.org.

About Purdue University

Purdue University is a top public research institution developing practical solutions to todays toughest challenges. Ranked the No. 5 Most Innovative University in the United States by U.S. News & World Report, Purdue delivers world-changing research and out-of-this-world discovery. Committed to hands-on and online, real-world learning, Purdue offers a transformative education to all. Committed to affordability and accessibility, Purdue has frozen tuition and most fees at 2012-13 levels, enabling more students than ever to graduate debt-free. See how Purdue never stops in the persistent pursuit of the next giant leap at purdue.edu.

Writer: Chris Adam, cladam@prf.orgSource: Andrew Exner, exner@purdue.edu

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Artificial intelligence taking role in developing technology to help Parkinson's patients during COVID-19 pandemic - Purdue News Service

COSTA MESA, Calif.--(BUSINESS WIRE)--Veritone, Inc., (Nasdaq: VERI), the creator of the worlds first operating system for artificial intelligence (AI), aiWARE, today announced it now supports the NVIDIA CUDA platform, enabling organizations across the public and private sectors to run intensive AI and machine learning (ML) tasks on NVIDIA GPUs, whether on-premises or in the Microsoft Azure and Amazon Web Services (AWS) clouds.

This Veritone innovation unlocks new performance levels for organizations using aiWARE, Veritones proprietary OS for AI, as they can now process massive amounts of video, audio and text dramatically faster and more accurately by using the parallel-processing computational power of the newest generation of NVIDIA GPUs.

The NVIDIA CUDA parallel computing platform and programming model enables dramatic increases in computing performance by harnessing the power of NVIDIA GPUs, which can process substantially more concurrent tasks than a central processing unit (CPU).

By taking advantage of the latest CUDA-compatible version of aiWARE running in the Azure and AWS clouds, organizations can leverage GPU auto-scaling to handle more demanding workloads than ever before, seamlessly scaling GPUs in the cloud, whenever faster results are needed.

The marriage of aiWARE and NVIDIA CUDA helps organizations realize artificial intelligence and machine learning solutions that can process vast amounts of data at unparalleled speeds, said Veritone Founder and CEO Chad Steelberg. We built aiWARE to uncover insights from video, audio and text data, at scale, in near real-time. Supporting the CUDA platform advances that mission.

NVIDIA AI technology enables dramatic increases in computing performance and provides the needed foundation for creating GPU-accelerated applications for a variety of business challenges, said Keith Strier, Vice President of Worldwide AI Initiatives at NVIDIA. NVIDIA CUDA offers Veritone aiWARE the power and ease of use required for todays complex GPU-based AI and machine learning workloads across a broad range of industries.

The combination of aiWARE and NVIDIA CUDA opens doors in time-critical AI applications such as:

Energy to optimize energy dispatch in real time and dynamically synchronize and control distributed energy resources such as solar, wind and battery power, down to the device level.

Security to securely and quickly authenticate into applications with multifactor SSO using face and voice biometrics.

Smart Cities to extract valuable insights from large quantities of smart city sensors, including street and municipal vehicle cameras, traffic and roadway sensors, green building and environmental sensors and more.

Media and Entertainment to automatically produce new, synthetic content from massive volumes of existing back catalog and other previously produced content.

Contact Centers to instantly transcribe, translate and voice-recognize customer calls, classify requests, gauge sentiment and intent, and route appropriately.

Industrial and Manufacturing to perform high-volume industrial inspection to efficiently manage the flow of products through fulfillment, distribution and receiving areas.

This new Veritone aiWARE capability is available on any on-prem or cloud GPU that supports NVIDIA CUDA, including AWS and Azure. aiWARE supports the latest GPUs offered by NVIDIA, including for network-isolated deployments of aiWARE. For cloud-based aiWARE deployments, Azure N-series VMs and AWS EC2 P2 and P3 instances are supported.

For more information about aiWARE and Veritones artificial intelligence solutions, visit veritone.com.

About Veritone

Veritone (Nasdaq: VERI) is a leading provider of artificial intelligence (AI) technology and solutions. The companys proprietary operating system, aiWARE powers a diverse set of AI applications and intelligent process automation solutions that are transforming both commercial and government organizations. aiWARE orchestrates an expanding ecosystem of machine learning models to transform audio, video, and other data sources into actionable intelligence. The company's AI developer tools enable its customers and partners to easily develop and deploy custom applications that leverage the power of AI to dramatically improve operational efficiency and unlock untapped opportunities. Veritone is headquartered in Costa Mesa, California, and has offices in Denver, London, New York and San Diego. To learn more, visit Veritone.com.

Safe Harbor Statement

This news release contains forward-looking statements, including without limitation statements regarding aiWAREs support of the NVIDIA CUDA platform, and the expected processing speed, use cases and other benefits to customers of the use of such chipsets with aiWARE. Without limiting the generality of the foregoing, words such as may, will, expect, believe, anticipate, intend, could, estimate or continue or the negative or other variations thereof or comparable terminology are intended to identify forward-looking statements. In addition, any statements that refer to expectations, projections or other characterizations of future events or circumstances are forward-looking statements. Assumptions relating to the foregoing involve judgments and risks with respect to various matters which are difficult or impossible to predict accurately and many of which are beyond the control of Veritone. Certain of such judgments and risks are discussed in Veritones SEC filings. Although Veritone believes that the assumptions underlying the forward-looking statements are reasonable, any of the assumptions could prove inaccurate and, therefore, there can be no assurance that the results contemplated in forward-looking statements will be realized. In light of the significant uncertainties inherent in the forward-looking information included herein, the inclusion of such information should not be regarded as a representation by Veritone or any other person that their objectives or plans will be achieved. Veritone undertakes no obligation to revise the forward-looking statements contained herein to reflect events or circumstances after the date hereof or to reflect the occurrence of unanticipated events.

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Veritone aiWARE Now Supports NVIDIA CUDA for GPU-based AI and Machine Learning - Business Wire