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Killexams : IBM Technical information source - BingNews Search results Killexams : IBM Technical information source - BingNews Killexams : Axiado to Demo New Smart Secure Control Module Technology at OCP Global Summit No result found, try new keyword!Executive leadership from Axiado will be available at the OpenPOWER Foundation (OPF) booth #C32 at the OCP Global Summit in San Jose, Calif., October 18-20, to demo their Smart SCM security hardware ... Mon, 17 Oct 2022 02:36:00 -0500 en-US text/html Killexams : View from India: Quantum computing’s amazing potential

There is growing interest and investment in quantum computing, but we’ve just about touched the tip of the proverbial iceberg. It could take a while before the potential of this technology is fully harnessed for new drug discoveries, scientific explorations and more.

An image of the penicillin molecule may be difficult to analyse, let alone molecules with over 100 components. This is where quantum computing fits in. It has a unique ability to calculate structures at atomic and subatomic scales and does so with precision. That’s just one of its attributes. No surprise that the technology could find applications in communication satellites that can be beamed to receivers on Earth. This may be used for scientific studies. That’s not all. Quantum computing may be used in healthcare, communication and large-scale optimisation like traffic flow, goods delivery and task simulation. It could probably help to sift through large chunks of data related to climate or population.

Given this diversity, the government and private companies are investing in this technology for research and commercial applications. Start-ups too can scout for opportunities in software, hardware and manufacturing of smaller parts. The 2020 Union Budget earmarked 8,000 crore (80 billion) rupees (£860m) for quantum technology research over the next five years.

The Ministry of Electronics and Information Technology (MeitY) had also announced a collaboration with Amazon Web Services (AWS) to develop a Quantum Computing Applications Lab. A quantum computing laboratory and an AI centre at a military engineering institute at Mhow, Madhya Pradesh has been established by the Indian Army. Last year, the Indian government launched Quantum Simulator (QSim) devices that are meant for studying quantum effects, which may be difficult to pursue in a lab. This is for developers, scientists and students to research on quantum computing. The platform has been built by Indian Institute of Sciences (IISc), Bangalore, Indian Institute of Technology (IIT), Roorkee, and the Centre for Development of Advanced Computing (C-DAC). Browsers can sign in from anywhere through Google too has announced a similar QSim last year. IBM has come up with initiatives such as IBM Quantum Challenge, IBM Quantum Summer School and Qiskit Challenge-India. Qiskit is IBM’s open-source software development kit. Honeywell and Boeing offer cloud simulations of quantum computing.

Hopefully these efforts will trigger off new studies in the technology. The next thing that comes to mind is quantum computers, which are far removed from the regular classical computers. Standard computers store information as binary 0 and 1states. The quantum computing analogue of classical computer bits is qubit or quantum bits. A qubit can be in a combination of states. This differentiator gives it an extra mileage which can be utilised for deducing large calculations.

Quantum computers may not replace the classical ones. They could collaborate with classical computers to solve computational problems. The algorithms from quantum computers could be used to measure and understand the gaps in the classical computers.

An intrinsic feature of quantum computers is that they need to be kept cold, much colder than the surrounding area. It would take a lot of engineering and tweaking to Improve the technology and build large-scale quantum computers and implement themto understand the structure of molecules and new materials. “The real challenge today is not to build a quantum computer and show that it can work (it does)…however, to scale up the technology and build large-scale, super quantum computers,” said Shohini Ghose, Wilfrid Laurier University, speaking at the Keysight World Innovate event held virtually. 

Not just that, quantum computers are based on quantum mechanics and quantum uncertainty, which can be used functionally. To provide an example, it may not be possible to know about every single property, movement and location of an electron or atom. Quantum uncertainty by its very nature can be applied to create a computing model for getting insights into the electron or atom. By doing so, the landscape of computing expands and may be used to tackle security threats. “If you wish to hide information from eavesdroppers, quantum computing can be used to encode information on the quantum data. When one particulate and quantum bits interact, they can get locked together. Jointly they have a connection and their co-relation may be tapped to develop a new kind of compute protocols and calculations,” added Ghose, an award-winning quantum physicist who threw light on the basics of quantum computing, its promise, its dangers, and what to expect from it in the future.

The process of quantum computing involves teleportation. In simple terms, quantum teleportation happens when quantum information is transferred from source to destination through entangled states. “Quantum teleporting is mind-boggling. The teleport qubits may open up avenues in quantum internet, networking and matters related to privacy and confidentiality,” reasoned Jeff Harris, vice president, portfolio and corporate marketing at Keysight Technologies.

Quantum computing can impact various sections of the society, it can be a social impact revolution. But then, somewhere people could make a beginning and this may become a use case for others to emulate. As in the case of other technologies, there are bottlenecks here too. “Performance, scalability and up-time are among the three technical challenges of quantum computing. We design products based on the three parameters to solve various issues. We are in the process of creating the next-gen quantum engineers by grooming them on YouTube and through partnership initiatives,” explained Giampaolo Tardioli, vice president, communications solutions group, Keysight Technologies. 

Decades-long hype around quantum systems probably still exists. Yet it could offer near and far-term potential. But then technical challenges may have to be overcome for quantum systems to realise their promise in fields spanning cyber-security, materials creation, financial analysis and military receivers.

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Sun, 16 Oct 2022 22:55:00 -0500 en-US text/html
Killexams : Red Hat Names Carolyn Nash as Senior Vice President and Chief Operating Officer

Open source leader also selects new senior vice president and chief financial officer and vice president and chief information officer.

Red Hat, Inc., the world's leading provider of open source solutions, today announced that Carolyn Nash has been named the company's senior vice president and chief operating officer, effective immediately. As part of this move, Red Hat is building out the Finance and Operations organization and has named Robert Leibrock senior vice president and chief financial officer and Jim Palermo as vice president and chief information officer. Nash will continue reporting to Red Hat's president and chief executive officer, Matt Hicks. Leibrock and Palermo will report directly to Nash.

This press release features multimedia. View the full release here:

Carolyn Nash, senior vice president and chief operating officer, Red Hat (Photo: Business Wire)

Nash most recently served as Red Hat's senior vice president and chief financial officer and was responsible for leading the company's global finance organization. Before assuming the CFO role in early 2022, Nash was vice president of Finance, overseeing the Global Finance Transformation and Operations (GTO) organization. She has played an integral part in strengthening and growing the company's finance operation. Before Red Hat, she served in leadership positions at Cisco, Hewlett Packard and KPMG in finance and operational roles.

Leibrock brings 20 years of experience in both the financial and operational space to Red Hat. He has spent much of his career at IBM, most recently serving as assistant controller, and was responsible for enterprise-wide financial management, including forecasts, measurements and IBM's operational management system. He also played a key role in IBM's $34 billion acquisition of Red Hat in 2019, responsible for the overall project office, finance and operations functions and driving offering synergies.

Palermo has nearly 30 years of experience in information technology spanning technical and leadership roles. He joined Red Hat in 2010 and most recently he served as vice president of Digital Solutions Delivery (DSD) where he was responsible for developing and driving the environment, tools and delivery for hosting internal workloads both in the hybrid cloud and in Red Hat's next-generation data centers.

Supporting Quotes
Matt Hicks, president and chief executive officer, Red Hat
"As Red Hat evolves to meet our customers wherever and however they operate across the open hybrid cloud, we need every aspect of our business, from engineering and product development to corporate functions like IT and finance, to perform at the highest possible level. Carolyn's proven track record shows that she is the right leader to oversee the expanded Finance and Operations organization, backed by the expertise and experience of Bobby and Jim. Together, I'm confident that these leaders can help accelerate Red Hat's mission to help our customers take advantage of open source innovation while helping us more readily adapt to dynamic market conditions."

Carolyn Nash, senior vice president and chief operating officer, Red Hat
"I am so grateful to be a part of Red Hat and have the ability to work alongside our incredibly talented and passionate associates every day. The Finance and Operations functions are the engine that fuels our growth and make it possible for all Red Hatters to be successful in their jobs. As Red Hat works toward its mission of being the defining company of the hybrid cloud era, our corporate functions need to be in lockstep. I am excited to work with Bobby, Jim and the rest of the organization as we enable customer success and support Red Hat into the future."

Robert Leibrock, senior vice president and chief financial officer, Red Hat
"I have been fortunate to work very closely with Red Hat leadership over the last few years so joining the team feels like a natural progression. Red Hat is the driver in the hybrid cloud industry and there is immense opportunity ahead. As CFO, I'm excited to make an impact on Red Hat's next chapter of success and honored to lead a highly talented group of associates. As more organizations look to open source and Red Hat to help them innovate, we are the right strategic partner to help them modernize their IT infrastructure and applications."

Jim Palermo, vice president and chief information officer, Red Hat
"Customer requirements must be the driver behind IT's future, especially as organizations transition to complex, multi-layered environments that use open hybrid cloud and automation technologies. IT's role within the Finance and Operations teams is not only to support broad business operations but also to serve as a reference architecture for Red Hat solutions in production. I am proud to take on this leadership role and help drive alignment within Red Hat's internal systems and environments as we work together to make hybrid cloud the default language for global IT."

Connect with Red Hat

About Red Hat, Inc.
Red Hat is the world's leading provider of enterprise open source software solutions, using a community-powered approach to deliver reliable and high-performing Linux, hybrid cloud, container, and Kubernetes technologies. Red Hat helps customers integrate new and existing IT applications, develop cloud-native applications, standardize on our industry-leading operating system, and automate, secure, and manage complex environments. Award-winning support, training, and consulting services make Red Hat a trusted adviser to the Fortune 500. As a strategic partner to cloud providers, system integrators, application vendors, customers, and open source communities, Red Hat can help organizations prepare for the digital future.

Forward-Looking Statements
Except for the historical information and discussions contained herein, statements contained in this press release may constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements are based on the company's current assumptions regarding future business and financial performance. These statements involve a number of risks, uncertainties and other factors that could cause actual results to differ materially. Any forward-looking statement in this press release speaks only as of the date on which it is made. Except as required by law, the company assumes no obligation to update or revise any forward-looking statements.

Red Hat and the Red Hat logo are trademarks or registered trademarks of Red Hat, Inc. or its subsidiaries in the U.S. and other countries. Linux® is the registered trademark of Linus Torvalds in the U.S. and other countries.

© 2022 Benzinga does not provide investment advice. All rights reserved.

Wed, 12 Oct 2022 01:01:00 -0500 text/html
Killexams : Utility Asset Management Market 2022 Global Trends, Share, Growth, Analysis, Opportunities And Forecast To 2027

The MarketWatch News Department was not involved in the creation of this content.

The Utility Asset Management Market report offers insights into the latest trends. Analysis and discussion of important industry trends, size, key players, current industry trend, market share estimates and profiles of the leading industry Players.

The global “utility asset management market” size stood atUSD 3.31 billionin 2019 and is anticipated to attainUSD 6.20 billionby 2027, exhibiting aCAGR of 8.5%during the forecast period.

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Major Utility Asset Management Market Manufacturers Covered In The Market Report Include:

  • GE
  • ABB
  • Eaton
  • Siemens
  • DNV GL
  • Aclara Technologies
  • IBM
  • Sentient Energy
  • Black and Veatch
  • Schneider Electric
  • IFS
  • Getac
  • Lindsey Manufacturing Company
  • Fujitsu

An Overview of the Impact of COVID-19 on this Market:

Latest Update: This has brought along several changes this report also covers the impact of CurrentCOVID-19 situation

The outbreak of COVID-19 has affected various industries, which affected the sales. The global lockdown and stringent restrictions imposed by governments created a long halt on the production operations of several companies. This affected the major key players' sales and revenue generation rate. To maintain social distancing norms imposed by governments, various companies have reduced the operating workforce that affected their production and supply chain.

Key Industry Development:

August 2020:Emerson Electric is planning to buy Open Systems International, Inc. (OSI Inc.) worth USD 1.6 billion. This development would help the former to include OSI’s product portfolio in its existing lines for accelerating digitization.

Growth Drivers:

Increasing Number of Residential and Commercial Infrastructures to Aid Growth

The rising consumption of energy backed by the increasing number of commercial and residential infrastructures worldwide is set to augment the utility asset management market growth in the coming years. Apart from that, there has been a rapid surge in the deployment of various novel power generation techniques that are capable of fulfilling the growing demand for energy. However, unavailability of skilled workers with the correct technical knowledge for installation of complicated hardware and equipment may lower the demand for utility asset management.

Key Region/Countries Are Classified As Follows:

The Regional Assessment Of The Utility Asset Management Market Has Been Carried Out In Six Key Regions Including North America, Asia Pacific, Europe, Latin America, Middle East, And Africa. Furthermore, The Report Also Provides Deep Insights Into The Ongoing RandD Activities, Revenue, Innovative Services, actual Status Of Supply And Demand, And Pricing Strategy. Further, This Report Also Provides Details On Consumption Figures, Export/Import Supply, And Gross Margin By Region.

Have Any Query?

Key Questions Answered In The Report:

  • What Will The Market Growth Rate Of Utility Asset Management Market In 2022?
  • What Are The Key Factors Driving The Global Market?
  • Who Are The Key Manufacturers In Space?
  • What Are The Market Opportunities, Market Risk And Market Overview Of The Global Market?
  • What Are Sales, Revenue, And Price Analysis Of Top Manufacturers Of Global Market?

The following are the study objectives for the Process Mining Software Market forecast report:

  • SWOT Analysis focuses on worldwide main manufacturers to define, assess, and analyze the market competition. By kind, application, and region, the market is defined, described, and forecasted.
  • Examine the global and main regional market potential and advantage, opportunity and challenge, constraints and risks.
  • Determine whether trends and factors are driving or limiting the market growth.
  • By identifying high-growth categories, stakeholders would be able to analyze market potential.
  • Conduct a strategic study of each submarket's growth trends and market contribution.
  • Expansions, agreements, new product launches, and acquisitions in the market are all examples of competitive developments.
  • To create a strategic profile of the main players and analyze their growth plans in depth.

Table Of Content:

Report Overview:It includes the Utility Asset Management Market Share study scope, players covered, key market segments, market analysis by application, market analysis by type, and other chapters that provide an overview of the research study.

Executive Summary:This section of the report gives information about trends and shares, market size analysis by region and analysis of global market size. Under market size analysis by region, analysis of market share and growth rate by region is provided.

Profiles of International Players:Here, key players of the Utility Asset Management Market are studied on the basis of gross margin, price, revenue, corporate sales, and production. This section gives a business overview of the players and shares their important company details.

Regional Study:All of the regions and countries analyzed in the report is studied on the basis of market size by application, the market size by product, key players, and market forecast.

Company Profiles:Almost all leading players of the global Utility Asset Management Market are profiled in this section. The analysts have provided information about their latest developments in the global Utility Asset Management Market, products, revenue, production, business, and company.

Market Forecast by Production:The production and production value forecasts included in this section are for the global as well as for key regional markets.

Market Forecast by Consumption:The consumption and consumption value forecasts included in this section are for the global Utility Asset Management Market as well as for key regional markets.

Value Chain and Sales Analysis:It deeply analyzes customers, distributors, sales channels, and the value chain of the global.

Key Findings:This section gives a quick look at the important findings of the research study.


If You Want More Insights Into The Utility Asset Management Market, Buy Now This Exclusive Report:

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To view the original version on The Express Wire visit Utility Asset Management Market 2022 Global Trends, Share, Growth, Analysis, Opportunities And Forecast To 2027


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The MarketWatch News Department was not involved in the creation of this content.

Sun, 16 Oct 2022 21:21:00 -0500 en-US text/html
Killexams : Universal vaccine advancement through AI and recombinant technology

In this interview, NewsMedical talks to Dr. Amy Sheng, a technical account manager at Sino Biological, and Dr. Lurong Pan, founder and CEO of next-generation biotech startup Ainnocence, about how artificial intelligence (AI) can be used in combination with high throughput production and screening to enhance the development process for potential universal vaccines.

Topics discussed include how AI can be used in combination with high throughput production and screening of proteins to expedite the development process for candidate universal vaccines – an ideal method for preventing and controlling future pandemics but also one of the major research challenges in biotechnology today.

Can you provide an overview of your background and your current role at Sino Biological and Ainnocence, respectively?

Dr. Amy Sheng: I am a technical account manager at Sino Biological. My background is in cell and molecular biology, antibody development, and production. Currently, I am in charge of the CRO program in Sino Biological in the United States.

Dr. Lurong Pan: I am the founder and CEO of Ainnocence, an AI drug discovery platform. I have a Ph.D. in computational biology and a background in computer science specializing in artificial intelligence. I have been in this industry doing drug design and leveraging different computational algorithms for about 14 years. I initially collaborated with Sino Biological, using them as one of the cell providers of our internal drug discovery program.

Can you define universal vaccines and why they are important to work on?

AS: Universal vaccines are vaccines that provide broad efficacy against various strains of a virus. From the case of SARS, we have experienced and understood how rapidly a virus can mutate and can escape immunity. Therefore, it is vital to develop the vaccine or therapeutics reagents that will continue to protect against any new versions of the virus that may emerge.

A universal vaccine has more potential compared to traditional ones in protecting vulnerable populations from various strains and even future variants. Before SARS and COVID, influenza has been a target for the development of a universal vaccine. The development of influenza vaccines with broader productions has been a goal for decades, and thanks to latest developments in vaccine targets and more efficient delivery platforms, this goal is believed to become more achievable.

What are some of the other advantages that universal vaccines have over traditional methods of vaccination with specific disease examples?

AS: With influenza, traditional vaccines do not produce durable, productive immunity and a cross-reactive immune response that can neutralize diverse influenza viral strengths. Traditional vaccine efficacy varies significantly in various age groups and against different viral strains. The strain mismatch is one of the main causes of vaccine failure. Very commonly, I hear friends say that oh vaccine does not work. Even I was knocked down for 1 week by flu even though I got the flu shot. In fact, just last year, the major strain of flu H3N2 mutated in a way that the designed vaccine could not efficiently provide immunity to the vulnerable population.

However, universal vaccines could potentially solve this issue and provide better production as quickly as possible. Besides the efficacy, universal vaccines would lower the cost of vaccine R&D, manufacturing, and stockpiling if we are faced with a rapidly mutating virus, which will greatly benefit the low-source country populations that are particularly vulnerable to pandemics. 

Can you break down some of the science behind how universal vaccines work and how they are able to provide immunity against a range of diseases?

AS: Universal vaccine development mainly focuses on the unchanged part of the virus or conserved region. However, this region might be shadowed by the ever-mutating domain of the virus, which is called immunodominance. In other words, the generated universal vaccine might have lower immune responses. Now, researchers are trying to make chimeric protein vaccines to make the conservative region more immunodominant and the immune response broader and more durable.

How the vaccine is packed can also greatly affect the strain and the quality of immune responses. For example, adenoviruses can be modified and used to deliver DNA sequences encoding the viral antigens we want to present. The benefit of this is that they can keep producing the antigen for weeks, which might help extend the response.

LP: Vaccines have two types of purposes: preventive and therapeutic. Preventive means you provide it ahead of time, and it is protective for a while. Those are normally the vaccines that generate B cell immunity that has a longer memory in our immune system and takes effect. From the current improvement in science, we are already observing certain antibodies or antibody cocktails that can target multiple viral infections. If we could find a universal antigen using those computational and experimental measures, the product would be a universal preventive vaccine that generates a cocktail of long-term protective B cell immunity.

Another part of our immunity is T cell immunity which normally gives a more distinct and harsh response to clear non-selective invaders of our body. We could control T cell behavior in a therapeutic way that stimulates its function when we get infected and, at the same time, customize it for different types of patients.

Some patients have compromised T cell immunity, and some have overexcited T cell immunity that causes an inflammatory effect. If we could have a modulator to stimulate our T cells to be able to protect us, clear out any invaders or pathogenic modules from outside, and at the same time not hurt us – that would also be classed as a universal vaccine used after infection to stimulate your immune system.

What are some of the challenges in finding candidates for universal vaccines, and how can AI technology help to address those challenges?

LP: Traditionally, we generate antibodies using a single antigen species. For example, with COVID, initially, we designed the vaccine using an animal model to generate antibodies to a strain that was currently happening. When the virus is mutant, we have to inject models multiple times in a timeline. We cannot chase the speed of the mutant using the conventional animal model method to develop universal vaccines.

Computational technology could be a great help in collaborative experiments where we have virtually computed all the strengths from the beginning of the pandemic to that current time point, resulting in over 1,000 different strengths. Within a few hours, you can generate antibodies that potentially target different strengths. In the opposite vein, we can also use the same algorithm to identify what is common among all those mutant strains to generate an antibody to prevent future strains. In using this model for antibody design, the antibody is also able to prevent a future strain.

There are patterns in the evolutionary trait of the viral species that we can learn from and be able to predict the future mutation trend of those species. If we can completely digitalize the virus, we could build an algorithm to find its evolutionary pattern and find a common immunogenetic sequence to contribute to the vaccine design process. Computational technology could speed up design and even help discover new phenomena in biology in the future.

How has the introduction of AI and working with companies like Ainnocence helped and changed your workflow when developing technologies like these?

AS: Ainnocence is a great platform to design proteins and antibodies and provide a guideline of what the ideal candidates look like. With Ainnocence, we can better understand and predict how the products will interact with the protein partners.

On the production side, if the vaccine is in protein form, the production of the predicted sequences can be challenging. The desired protein should have high stability, high yield, and purity for the later manufacturer and other aspects of the R&D. We have to do a lot of troubleshooting to standardize the production of that protein.

Can you talk about how you started working with Ainnocence, and how you developed the AI platform and integrated it with your development workflows to work on these new vaccine candidates?

AS: Ainnocence was one of our customers. We developed a lot of component antibody projects together. As we provide various platforms for recombinant production, especially the highest approved protein production and screening, we can produce up to 1,000 constructs in a turnaround time as short as four weeks.

Together with Ainnocence, we are able to provide quick answers to some basic information such as yield stability and purity and computational designs. We have extensive experience with viral protein production and the world’s largest viral protein bank. These antigens can be used to analyze vaccine-induced antibody responses.

Can you talk about the process of adapting your technology to what Sino needed in this project, and how does working with Sino compare to other projects that you have?

LP: We started by collaborating on the COVID project, and we found out a lot of customers not only wanted to produce a protein drug but also wanted to Improve the property of those protein drugs. In the past, you had to try different mutations to find a good quality one, and this would take a lot of time and cost a lot. Suppose we could involve AI and be able to shortlist all those unnecessary experiments. In that case, we can enrich all the high-probability positive species using our AI engine and thus only need to conduct a very limited number of experiments to save time. It would expedite the R&D process and, from the customer side, mean that less money is spent on failed experiments. The technology is a good solution for the industry, and if we combine it to have a design and a production capability simultaneously, we can have a quick turnaround for more customer modules to be made. It is a good business model for both companies.

How long until universal vaccines are common in therapeutic use around the world, and how much is AI affecting that?

LP: A lot of universities, commercial entities, and nonprofit organizations are working on a universal vaccine. From a scientific and technology readiness point of view, I think we are getting close. I cannot make an accurate prediction if it will be in five years or ten years, but I think we will be able to see good animal study results in the coming three years. A large human trial is another story because that would involve a long-term series of safety studies, a larger population, and collaboration globally in different regions. In the next five to ten years, I would hope to see a vaccine validated in human trials for a candidate able to cover most of the common pathogens.

AS: What we have seen recently for SARS-COVID is a unique case of vaccine development. The normal process of universal vaccine development, or any vaccine development, would take a long time, especially in the human trial, to ensure that the vaccine has a good safety record before the government finally approves it. We hope to see that coming out faster, but the most important thing is safety and keeping that on track.

There are all different kinds of viruses like influenza, SARS, etc. During vaccine development, do you see any similar evolution patterns between different kinds of viruses?

LP: We see common patterns for viral evolution: they evolve quickly and with their hosts. It is something we can learn digitally and computationally to either analyze understanding or even predict its trend. Everything is encoded in an RNA or a DNA strain that can be shared in a digitalized way for all species. In that case, these patterns are computable.

About Dr. Amy Sheng:

Amy Sheng, Ph.D., is a technical account manager in Sino Biological. Amy joined Sino Biological in 2021 supporting CRO services and project management in Eastern US region.

Prior to joining Sino Biological, she worked in Caprico Biotechnologies as production manager in charge of antibody development and production for flow cytometry. She has a PhD in Molecular and Cell Biology from Georgia Institute of Technology, and is ASCP-certified molecular biologist and ASQ-certified CSSGB.


About Dr. Lurong Pan

Dr. Lurong Pan is the founder and CEO of Ainnocence, an AI-powered, next-generation biotech startup. She has extensive drug design and precision medicine research experience using structural biology, computational chemistry, and artificial intelligence technologies. 

She was previously a senior investigator at Global Health Drug Discovery Institute and a research scientist in structural biology and computational biology at University of Alabama at Birmingham. 

Dr. Pan received her B.S. in Applied Chemistry from Nanjing University, M.S. in Computer Science from Georgia Tech, and Ph.D. in Chemistry from University of Alabama at Birmingham. She is also an IBM-certified big data architect.




Twitter: Ainnocence (@Ainnocence_Inc) / Twitter

About Sino Biological Inc.

Sino Biological is an international reagent supplier and service provider. The company specializes in recombinant protein production and antibody development. All of Sino Biological's products are independently developed and produced, including recombinant proteins, antibodies and cDNA clones. Sino Biological is the researchers' one-stop technical services shop for the advanced technology platforms they need to make advancements. In addition, Sino Biological offers pharmaceutical companies and biotechnology firms pre-clinical production technology services for hundreds of monoclonal antibody drug candidates.

Sino Biological's core business

Sino Biological is committed to providing high-quality recombinant protein and antibody reagents and to being a one-stop technical services shop for life science researchers around the world. All of our products are independently developed and produced. In addition, we offer pharmaceutical companies and biotechnology firms pre-clinical production technology services for hundreds of monoclonal antibody drug candidates. Our product quality control indicators meet rigorous requirements for clinical use samples. It takes only a few weeks for us to produce 1 to 30 grams of purified monoclonal antibody from gene sequencing.

Sun, 02 Oct 2022 19:54:00 -0500 en text/html
Killexams : How To Invest In Artificial Intelligence

Key takeaways

  • Tesla AI Day came and went, they delivered on the humanoid robot prototype announced last year and poised to hit the market long before the decade’s end.
  • Companies like Amazon are built around the power of artificial intelligence, with every aspect of the business using AI, from customer recommendations to their highly profitable cloud-based services.
  • AI is changing every industry, from health care to education to investing, so here’s a list of possible AI investments.

We absolutely can’t ignore that artificial intelligence is changing the way we do everything in every industry, from the possibility of self-driving cars to social media algorithms showing you customized content. You may have heard of some of AI's advances in text or image generation. You may have even heard about AI being used in health care, as the World Economic Forum just announced how AI could detect tuberculosis.

The hope is that machines will eventually replicate human intelligence without the need for human input or interference. This space is growing rapidly, and it seems likely that every industry will be impacted by it. Many major companies have invested heavily in AI, and it feels like if you don’t take it seriously, you could be left behind.

What’s happening with AI?

Basic forms of AI are currently being used across many industries. Colleges are using AI for admissions and financial aid decisions. E-commerce platforms use AI to help make product recommendations. Many businesses are using AI for fraud detection and budgetary oversights.

AI is now allowing computers to make decisions that historically required human beings. Issues are resolved within a company without humans ever interacting. AI is being used to solve complex problems, automating new tasks and business functions, minimizing errors, leading research and data analysis, and even - ahem - enhancing customer service.

According to findings from the Brookings Institute, the U.S. is significantly behind in AI developments compared to China, and the federal market for AI is still in its early stages.

How wide ranging is artificial intelligence?

AI covers everything from search engine algorithms to robotics and self-driving cars. There’s enormous potential for AI to Improve the health care industry. AI can help schedule staff, detect patient risks, and even discover patient conditions. Patient risk predictors can expedite the work of front-line staff and Improve the flow of hospitals. There’s even the possibility of using AI to create a robot taxi service, already in process at Tesla.

According to Zion Market Research, the global AI industry should grow to $422.37 billion by 2028. This would be up from $59.67 billion in 2021.

It’s worth noting that many tech giants sell AI analytical services to business clients, from cloud computing to software tools.

Leading companies in different fields of AI.

With so much emphasis on the future of AI, here are some leading companies utilizing this new technology.

Alphabet Inc.

Alphabet, the parent company of Google, is one of the leaders in AI research. We’ve all experienced the power of Google’s AI technology, from the accuracy of our daily searches to the often-incredible precision with which they organize our photos for us.

Google’s use of AI could fill a book, but suffice to say, it’s becoming more ubiquitous across their platforms. Google Assistant is an AI-powered voice assistant. Google Maps uses AI-powered updates to provide you a live view of where you’re going and autocorrecting for traffic changes along the way.

Alphabet also owns a company that uses AI for drug discovery, DeepMind, whose scientists were just awarded a $3 million prize for creating an AI system that predicts how almost every protein folds into its 3D shape. Researchers at DeepMind also recently taught digital humanoids how to play soccer from scratch. The team is investigating whether these AI training strategies can work beyond soccer.

Nvidia Corporation

This high-end chip maker is responsible for powering AI applications. The company offers AI solutions to various industries, ranging from health care to higher education. Nvidia offers solutions for speech recognition, medical imaging, gaming, and improving supply chain management.

While the company has suffered in 2022 with crypto mining changes (like the Ethereum merge) causing the GPU market to drop, analysts are now back to supporting Nvidia since the company announced new products, such as the Omniverse Cloud Services for industrial Metaverse applications.


It’s pretty astonishing how deeply integrated AI technology is throughout Amazon’s entire company. Amazon uses AI to customize the products that customers see and recommend. They also use AI at certain fulfillment centers, with small robots used to ferry packages around the warehouse to their human workers. Then there are many Amazon Fresh and Amazon Go stores that use the Just Walk Out payment system.

So, AI plays a role in most parts of its business, from targeting advertisements to the Amazon Web Services platform. Alexa is also in many households around the country, and AWS cloud customers have access to many AI tools.


Lemonade is the first insurance company to be fully powered by AI. The company uses an AI-powered bot, Maya, to handle everything for you, from finding a quote to handling claims. You can go through the website to see how efficient AI is when it comes to insurance.

The company offers insurance products for the following sectors: homeowners, renters, pets, life, and auto insurance. Lemonade has turned the insurance industry upside down by relying on AI for handling claims. If you were to claim property insurance, you wouldn’t have to worry about calling an insurance agent and being stuck on the line. You can handle everything online with Maya.


We can’t forget a company that has a dedicated annual AI Day. With a humanoid robot, self-driving cars, and the possibility of a robot taxi service envisioned as a mix of Airbnb and Uber, Tesla’s always working on innovations when it comes to AI. One can only imagine what the peak of AI’s technological advancement will look like when hearing about Tesla’s projects.. One of the main purposes of Tesla’s AI Day is to recruit the best talent in AI, as the company is investing heavily in this field.

These companies are worth looking into as an investment if you’re looking to purchase shares in the AI industry. We have you covered in the next section if you want some additional stock choices.

The best AI stocks to consider right now

Here are some AI stocks worth looking into long-term as the stock market continues to tumble.

Meta Platforms Inc. (META)

Chances are that you’ve seen how Meta uses AI in its news feeds and algorithms for ads on Facebook. That’s just scratching the surface regarding what Meta’s working on involving AI. The company owns the Meta AI lab that recently announced they’re trying to use AI to decode speech from brain activity from those who’ve suffered traumatic brain injuries. The research has yet to be peer-reviewed and is still in its early stages, but it goes to show the ambition Meta has for the future of AI technology. While it often feels like Meta can read your mind, it would truly be something else if they could literally read your brainwaves. (AI) is involved in enterprise AI, which offers done-for-you and customized AI applications to clients looking to go all digital and get their companies on the cloud. These AI algorithms can help with operations, reducing costs, detecting fraud, and even employee safety.

The company hasn’t reported a profit yet because expansion investments are still being made.

Salesforce (CRM)

Salesforce is a cloud-based customer relationship management platform that uses connected apps to bring companies and customers together. The company also offers AI-based information for sales, marketing, and service teams across all industries. The cloud-based software helps companies track customer analytics along with sales and spending. Salesforce Einstein is the official AI technology used in the customer success platform.

Other AI stocks worth investing in:

  • Adobe (ADBE) Creative Cloud products now all use Adobe's AI platform, Sensei.
  • International Business Machines Corp. (IBM) just announced that research is being done on how to train a customer service robot to sound more human.
  • Workday, Inc. (WDAY) is a cloud-based application provider focused on human resources.

We just scratched the surface here when it comes to investing in AI. Many companies specialize in AI, and many organizations are implementing AI-based technology. There is a lot of debate in technical circles about what actually qualifies as AI versus exceptional algorithms and machine learning, all impressive work but real AI is built around neural networks. You can expect more from us on this course in the future.

How uses artificial intelligence

If you’re looking to see the power of AI in action, you must learn more about, our company is built to leverage artificial intelligence to offer investment strategies. utilizes artificial intelligence in three key ways to help investors:

  1. Creating investment kits, which is to say selecting stocks, ETFs, etc. The power of AI is used assess every investment every week and to bundle them into kits that users can use to invest in key market sectors like Precious Metals, Tech Rally, Value Vault and Short Squeeze.
  2. Weighting the assets in each Investment Kit in order to manage downside risk within each sector.
  3. Portfolio Protection is a feature that uses AI predictions to forecast possible risks to adjust portfolio allocations.

If you’re hoping to make money in the AI space, you can invest in one of our Kits. AI-powered Investment Kits take the guesswork out of investing. Our artificial intelligence scours the markets for the best investments for all manners of risk tolerances and financial situations. Each asset is assessed on its technical merit, growth potential, momentum volatility and market sentiment data from news sources, search data, proprietary sources and more. .

Download today for access to AI-powered investment strategies. When you deposit $100, we’ll add an additional $100 to your account.

Wed, 05 Oct 2022 12:26:00 -0500 - Powering a Personal Wealth Movement en text/html
Killexams : Microsoft launches open-source AI models to optimize farm operations

Microsoft announced the release of FarmVibes.AI, a collection of different open-source AI models that work towards supporting farm operators in optimizing their tasks and efficiency.

FarmVibes.AI is one of the numerous technologies created by Microsoft as part of an initiative named Project FarmVibes. This initiative aims to incorporate software and connected devices such as sensors to achieve higher farming efficiency. All the innovations released as a part of this initiative will be open-source.

“At Microsoft, we are working to empower growers with data and AI to augment their knowledge about farming and help them grow nutritious food in a sustainable way”, said Ranveer Chandra, Microsoft’s managing director of research for industry.

FarmVibes.Connect includes a set of different software and hardware tools designed to deliver Internet connectivity to agricultural regions. Furthermore, this initiative leverages various unused elements of the radio spectrum to create wireless connectivity. FarmVibes.Edge, on the other hand, focuses on simplifying crop and farm data uploading to the cloud for analysis.

FarmVibes.AI comprises four artificial algorithms which are designed to help farmers optimize day-to-day work by collecting data on crops.

The first algorithm, Async Fusion, is responsible for combining information collected from sensors at a farm, drones, and satellite imageries. It aims to deliver an optimal map for carrying out farming errands.

The second algorithm, SpaceEye, streamlines satellite data assessment and processing methods implemented in the farming maps. In the case there isn’t any satellite image, the AI algorithm substitutes it with satellite-based radar measurements and instruments.

The third algorithm, DeepMC, is great for estimating wind speeds, temperatures and rainfall through internet-connected devices. It identifies the optimal time for performing different agricultural tasks in certain weather conditions.

The fourth algorithm included in FarmVibes.AI helps farmers in all matters related to sustainability and diverse agricultural practices affecting carbon amounts in their soil. Not only this, the algorithm helps identify different methods of enhancing crop yields.

Tip: Meta develops mind-reading AI model

Sun, 09 Oct 2022 22:04:00 -0500 en text/html
Killexams : Quantinuum Is On A Roll – 17 Significant Quantum Computing Achievements In 12 Months

On the heels of two major quantum computing achievements last month, Tony Uttley, President and COO of Quantinuum, made three more announcements at IEEE Quantum Week 2022. The company’s latest announcements include another quantum volume record, a new method to make two-qubit gates with higher fidelity and greater efficiency, and a milestone achievement of more than a half-million downloads of Quantinuum’s open-source software development kit (SDK) called TKET.

Before analyzing the latest announcements, it's important to review Quantinuum’s quantum hardware and architecture that made those announcements possible.

Quantum Charged Coupled Device

There are two common ion traps, linear traps and quantum charged-coupled device (QCCD). The linear trap is exactly what it sounds like – a long chain of ion qubits contained in a single trapping zone. Linear traps have some shortcomings such as the limited ability to scale qubits in large numbers; it also has some limitations with qubit addressability. QCCD has its limitations as well, but nearly all major problems have been solved.

In July, Quantinuum solved a technical QCCD problem that has baffled the quantum research community for years when its scientists developed a method to allow ions to make 90-degree turns when moving through ion trap intersections. This is covered in more detail later.

QCCD was first proposed in a research paper by Dr. David Wineland and his NIST group over twenty years ago. However, Quantinuum was the first company to implement and Improve it. Dr. Chris Monroe, co-founder and Chief Scientist for IonQ, also Professor of Physics and ECE at Duke University, was one of the authors of that paper.

Rather than storing and performing qubit operations in a single linear trapping zone, QCCD uses multiple zones for the arbitrary rearrangement of qubits and accommodation of various codes, including those with exotic geometries. Small chains of ions in multiple small zones provides greater precision and control compared to large ion chains within a single trapping zone.

Of the two architectures, QCCD is considered the most advanced and most flexible. Quantinuum’s H-Series quantum computer currently has 20 qubits spread across 5 gating zones where qubits are parked, and quantum operations are performed. Ions can be moved from one zone to the next and then recombined. The architecture provides high-fidelity interactions between distant qubits and low crosstalk between gates. All of Quantinuum’s recent advancements have been made possible by QCCD’s high fidelity and flexibility.

Tony Uttley is confident that QCCD will support Quantinuum’s quantum roadmap of future generations of H-Series processors. He feels that QCCD offers a superior menu of technical advantages and provides greater adaptability not only for technical reasons, but for future market needs as well.

While QCCD qubit control is precise, qubit control in a single linear trapping zone with 50 or more qubits can be problematic. Packing many ions together in single traps can adversely affect spacing between ions which makes it difficult to address individual ions and create unwanted interactions between them. Fiber optics and optical switches may allow interconnection of multiple linear traps in the future, allowing for greater control and scaling. However, there are no optical switches available today that are fast enough to stitch a multi-chip trapped-ion architecture together.

Dr. Jungsang Kim is Co-founder and Chief Technology Officer of IonQ. He is also Professor of Physics in the Department of Electrical and Computer Engineering at Duke University. While working for Bell Labs in the early 2000s, Dr. Kim built the world's largest optical switch with over a thousand ports. Dr. Kim is currently working on an optical switch for IonQ's future architecture.

Quantinuum announcements at IEEE Quantum Week

  • Arbitrary angle entangling gate capabilities: Single qubit gates and fully entangling two-qubit gates are routinely used to build quantum circuit operations. Because there are a lot of algorithms that don’t need fully entangling two-qubit gates, Quantinuum developed a method using arbitrary angle partially entangling gate that increases efficiency and reduces errors. Lower errors allow more complex problems to be run.

Dr. Brian Neyenhuis is the Director of Commercial Operations at Quantinuum. When asked if the method was proprietary, Dr. Neyenhuis explained that the technique was not proprietary to Quantinuum.

“Other companies may be able to implement arbitrary angle entangling gates at some point in the future,” he said. “However, we have an advantage with QCCD because when we do a two qubit gate, it's only those two specific qubits in the interaction zone with laser beams. That makes it very straight forward. If there are too many qubits, such as in a linear trap, you have to worry about crosstalk which occurs when many qubits interacting together; and you also have to be careful about what the other qubits are doing. You can do those things with longer chains but it’s a lot harder.”

Dr. Neyenhuis also pointed out there are algorithms where the arbitrary angle two-qubit gate act as a natural building block. In general, the arbitrary angle gate can run on many quantum circuit types. He gave the quantum Fourier Transform as an example.

The Fourier Transform has been called one of the most useful mathematical tools in modern science and engineering. Dr. Neyenhuis explained that use of arbitrary angle two-qubit gates in the quantum Fourier Transform can reduce the number of two-qubit gates needed for the transform by 2x, plus it can reduce overall errors by 2x as well. Greater circuit fidelity offers the advantage of running deeper and more complex circuits. More information about arbitrary angle entangling gates can be found here

  • Record quantum volume 8192 attained by using arbitrary angle entangling gates: Setting Quantum Volume (QV) records is nothing new for Quantinuum (or previously as Honeywell Quantum Solutions). However, there is something new about this record - Quantinuum used its new arbitrary angle partially entangling gate to help achieve it’s latest record quantum volume. The new QV record of 8192 (213) is double Quantinuum’s previous volume record of 4096 set only five months ago. In fact, it is the seventh time in two years that Quantinuum’s H-Series system has set the record for a measured QV. Quantinuum’s goal is to increase quantum volume by 10X annually.

IBM originally developed quantum volume in 2017 as a hardware-agnostic performance measurement for gate-based quantum computers such as the Quantinuum H-Series system. QV testing measures many aspects of a quantum computer. Although the number of qubits is important, there are also other system factors that affect a quantum computer’s performance such as qubit connectivity, gate fidelity, cross talk, circuit compiler efficiency, and more. A high quantum volume is an indicator of a quantum computer’s power.

QV score is determined by running specified algorithms and arbitrary circuits. For this QV record, Quantinuum ran 220 quantum volume circuits 90 times each.

Quantinuum scientists found that arbitrary angle two-qubit gates performed more efficiently and with less errors at each step of the algorithm. The cumulative effect of the arbitrary angle gates helped boost quantum volume to its current record value of 8192.

Quantinuum plans to continue the use of quantum volume until a better metric is created and endorsed by the ecosystem. More complete information about the new quantum volume record can be found here.

  • A big number for TKET downloads

Tony Uttley also announced that Quantinuum achieved a milestone of surpassing 500,000 downloads of TKET.

TKET is Quantinuum’s open source SDK used by developers writing quantum algorithms for gate-based quantum computers. It is universally accessible through the PyTKET Python package. Functionally, it optimizes quantum algorithms by reducing computational resources. The TKET SDK also integrates with Qiskit, Cirq and Q#.

Since the software is downloaded both by companies and academic institutions with multiple users, the user count is likely greater than 500,000. Quantinuum estimates that the TKET base is growing globally and now has close to a million users.

Quantinuum plans to continually evolve the TKET platform as updates and advancements occur to ensure it includes new hardware capabilities such as Quantinuum’s most latest development, arbitrary angle two-qubit gates.

Analyst comments

Over the past 12 months, Quantinuum scientists have performed a great deal of research. However, there are two previous pieces of standout research that should be highlighted:

  1. Highlighted research #1 - Shuttling ion pairs through intersections and negotiating 90 degree turns: In July, Quantinuum researchers discovered how to move two ions of different species - ytterbium and barium - simultaneously through an intersection of a microfabricated prototype trap with a grid-like structure. The research demonstrated that an ion pair could turn 90 degree corners with speed but without excessive motion.

It may not sound significant, but this research provides the capability to execute Quantinuum’s long term roadmap for future generations of H-series quantum computers. Quantinuum is following the pre-merger hardware strategy originally developed by Honeywell Quantum Solutions. That plan calls for the System Model H-2 to use a racetrack-like design shown in the above graphic. H-Series System Model H-3, H-4, and H-5 will use two-dimensional traps that resemble a city street grid with multiple railroad lines and intersections.

Limitations inherent in the QCCD grid design are what motivated Quantinuum scientists to pursue research needed to move ion pairs through grid intersections together and make sharp corner turns without excessive energy and motion.

Ion trap researchers have been working on this problem for years. Prior to Quantinuum’s research, it was believed that the only way for paired ions to move through zones was to first separate the pair, then move them through junctions one at a time. That solution would have significantly increased processing time.

2. Highlighted research #2 - Closing the gap on fault-tolerant quantum error correction: Fault tolerant quantum error correction will make it possible to build quantum computers with enough qubits to solve problems far beyond the computational reach of today’s largest and most powerful supercomputers.

Qubits are very sensitive to sources of noise in their environment which can result in random errors during quantum computation. Uncorrected errors can accumulate to the point that viable computation isn’t possible. It is currently not possible to build quantum computers with millions of qubits due to the lack of quantum error correction (QEC).

QEC is both a physics and engineering problem. In the quantum ecosystem, nearly every academic and commercial institution is performing some level of QEC research. The entire ecosystem has invested years of research into QEC and yet a complete fault tolerant QEC solution has yet to be developed, which illustrates its complexity and difficulty. Even so, much progress has been made.

A good example is the research paper Quantinuum published in August that illustrates two important error correction firsts.

These “firsts” were made possible by using physical qubits to form logical qubits. Each logical qubit is formed from groups of entangled physical qubits that perform computations while other qubits are tasked with error detection and correction.

Several years ago, it was thought that 1000 physical qubits would be needed for each logical qubit. Now that ratio is down to 10 to 1 or less.

For the first time, Quantinuum researchers were able to construct a logical entangling circuit that had a higher fidelity than its physical counterpart. The researchers also accomplished another QEC first by entangling two logical qubit gates in a fully fault-tolerant manner using real-time QEC.

Key to this demonstration is its repeatability, a necessity for any QEC solution. While the research does not provide a complete QEC solution, it is stil an important proof of concept that creates a new starting point for other researchers to build on.

More information on Quantinuum error correction research can be found here.

3. Quantinuum research performed over the past 12 months:

September 27, 2022

Quantinuum Sets New Record with Highest Ever Quantum Volume of 8192

August 4, 2022

Logical qubits start outperforming physical qubits

July 11, 2022

Quantum Milestone: Turning a Corner with Trapped Ions

June 14, 2022

Quantinuum Completes Hardware Upgrade; Achieves 20 Fully Connected Qubits

May 24, 2022

Quantinuum Introduces InQuantoTM to Explore Industrially Relevant Chemistry Problems on Today’s Quantum Computers

April 14, 2022

Quantinuum Announces Record Quantum Volume of 4096

March 29, 2022

On the ArXiv: Modeling Carbon Capture with Quantum Computing

March 29, 2022

Quantinuum Announces Updates to Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

March 3, 2022 Quantinuum announces a world record in fidelity for quantum computing qubits

December 29, 2021 Demonstrating Benefits of Quantum Upgradable Design Strategy: System Model H1-2 First to Prove 2,048 Quantum Volume

December 7, 2021

Introducing Quantum Origin, The world’s first quantum-enhanced cryptographic key generation platform to protect data from cybersecurity threats

(Note: On November 30, 2021, Quantinuum was formed by the merger beteen Honeywell Quantum Solutions and Cambridge Quantum)

November 27, 2021

Quantum Milestone: We Can Now Detect and Correct Quantum Errors in Real Time

November 29, 2021

LAMBEQ: A Toolkit for Quantum Natural Language Processing

November 29, 2021

How a New Quantum Algorithm Could Help Solve Real-world Problems Sooner

November 29, 2021

Quantum Milestone: 16-Fold Increase in Performance in a Year

October 15, 2021

Researchers ‘Hide’ Ions to Reduce Quantum Errors By Reducing Crosstalk Errors An Order of Magnitude

October 20, 2021

TKET: Quantum Software Tool Goes Open Source

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex,, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movandi.

Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movand

Thu, 06 Oct 2022 04:47:00 -0500 Paul Smith-Goodson en text/html
Killexams : Statistics Centre Abu Dhabi taps IBM Turbonomic to accelerate their digital footprint in the region

More than 3000 automated actions executed, saving over 500 hours of manual work.

Cairo, Egypt: Statistics Centre - Abu Dhabi (SCAD) and IBM discussed boosting cooperation to fuel SCAD’s growth, accelerate digital footprint and drive sustainable development across various operations. The collaboration enables SCAD to leverage IBM® Turbonomic® Application Resource Management (ARM) to automate processes, optimize digital infrastructure performance and minimize costs.

SCAD is responsible for building an information network and a unified channel that serves the statistical ecosystem in Abu Dhabi by organizing, unifying, and managing all aspects of the Emirate's statistical data. SCAD develops a leading statistical ecosystem to empower decision makers and users in the government, private sector, and society.

SCAD selected IBM Turbonomic to scale intelligent automation capabilities to run across any hybrid cloud environment. Over the duration of three months, IBM Turbonomic executed over 3,000 automated actions, including continuous placement for virtual machines, containers, and scaling infrastructure resource saving SCAD more than 500 hours of manual work with a projected expectation to save 2,000 hours over 2023.

The partnership between SCAD and IBM is aligned with efforts to reach a balance between carbon neutrality and application performance. Through leveraging IBM Turbonomic, SCAD will be able to minimize energy consumption and reduce carbon footprint by 17 tonnes.

Aziz Hmoud Saif Alkayyoomi, Acting Director of Information Technology at SCAD, said: “We are focused on leveraging the latest emerging technologies that provide reliable and high-quality statistics, analysis and research that support sustainable development processes and Improve user experience across Abu Dhabi. Our collaboration with IBM is an important step to create a leading statistical ecosystem that empowers decision-makers in both the public and private sectors.”

Wael Abdoush, General Manager, IBM Gulf, Levant, and Pakistan, said: “We are pleased to partner with SCAD to provide a one-stop shop of AI-powered automation capabilities, all built on Red Hat OpenShift to run anywhere. IBM designs, deploys, and manages energy efficient infrastructures and innovations with a hybrid cloud approach. Our collaboration with SCAD paves the way for SCAD to achieve sustainable development goals and deliver the most efficient use of computing, storage, and network resources,” he added.

About SCAD

The Statistics Centre – Abu Dhabi (SCAD) was established by Law No. (7) of 2008 to organize and develop statistical work in the Emirate of Abu Dhabi. The SCAD’s role has been reregulated in 2021 and started to report to the Abu Dhabi Executive Office. It adopted a decentralized methodology in statistical work, in order to support decision-makers and entrepreneurs to devise strategic plans and policies and advance Abu Dhabi’s comprehensive and sustainable development.

SCAD has an independent legal personality and full financial independence, as well as full legal capacity to work in line with the Emirate's directions towards achieving sustainable economic and social development goals and the Abu Dhabi Economic Vision 2030, under the supervision of the Abu Dhabi Executive Council.

Based on the law amendment, SCAD is now responsible for building a unified system for Abu Dhabi’s statistical information and unifying and managing all aspects of statistical work in the Emirate. This includes development and regulation of statistical frames for all activities and sectors and updating them periodically, as well as providing technical supervision of statistical work and data systems at government entities. That, in addition to collecting, classifying, storing, analyzing, processing, archiving, publishing, and protecting Abu Dhabi's statistical data obtained from various data sources.

SCAD is also responsible for making, developing, and disseminating estimates, projections, extrapolations, and forecasts. Additionally, the Centre is tasked with supporting government entities and transferring knowledge and expertise, thereby enabling them to provide reliable and accurate statistics. SCAD is also authorized to contract with any entity or company within or outside the Emirate to undertake data collection and other statistical activities.

About IBM

IBM is a leading global hybrid cloud and AI, and business services provider, helping clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,800 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently, and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM's legendary commitment to trust, transparency, responsibility, inclusivity, and service. For more information, visit

Thu, 13 Oct 2022 15:34:00 -0500 en text/html
Killexams : Be Part of History in the Design Automation Conference’s Diamond Anniversary Year No result found, try new keyword!In the 60 years since the Design Automation Conference (DAC) was founded, the world has evolved from highly specialized, building-sized computers to digital technologies that power every aspect of our ... Wed, 12 Oct 2022 08:39:00 -0500
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