Analysts laud SAS’ innovation in AI, marketing, risk and fraud solutions
Investment by SAS drives accolades in multiple reports from top analyst firms
CARY, N.C., July 30, 2024 /PRNewswire/ — When choosing new technologies like generative AI (GenAI) or selecting vendors for mission-critical functions like managing risk, improving marketing and customer loyalty, and fighting fraud and financial crimes, organizations often seek the advice of top industry analyst firms.
Top industry analyst firms have once again have recognized SAS as a leader in key business and technology areas.
And these top firms once again have recognized SAS and its technologies as leaders in important business and technology areas.
For more SAS rankings in analyst reports, see Analyst Viewpoints at SAS.com/analystviews.
Among the most recent analyst accolades for SAS are:
AI and Analytics
Customer Intelligence
Risk Management
Chartis RiskTech Quadrant® for Credit Risk Management – Trading Book – SAS named a Leader (June 2024)
Chartis RiskTech Quadrant for Credit Risk Management – Banking Book – SAS named a Leader (June 2024)
Chartis STORM50: Retail Finance Analytics50 – SAS earned the No. 1 overall ranking (June 2024)
Chartis STORM50: Quant Tech50 – SAS ranked No. 4 out of 50 vendors (June 2024)
Chartis STORM50: Insurance Analytics50 – SAS ranked No. 5 out of 50 vendors (June 2024)
Fraud and Financial Crimes
The Forrester Wave: Enterprise Fraud Management Solutions – SAS named a Leader (June 2024)
Chartis RiskTech Quadrant for Adverse Media Monitoring Solutions – SAS named a Leader (May 2024)
Chartis RiskTech Quadrant for Name and Transaction Screening Solutions – SAS named a Leader (May 2024)
SAS remains steadfast in its commitment to investing in the latest data and AI technologies to help its customers succeed. In April, for example, SAS announced new GenAI capabilities for SAS Viya, its cloud-native data and AI platform. And in June, SAS rolled out additional GenAI tools in its lead marketing technology solution, SAS Customer Intelligence 360.
“For decades, SAS has focused on helping our customers transform huge amounts of data into better business decisions and value,” said SAS CEO Jim Goodnight.
“And we’ve baked our passion for analytics, data and AI into SAS software solutions, which help our customers better serve their customers, fight fraud and manage risk. These latest analyst reports not only highlight SAS’ leadership in important business areas, but also show that choosing SAS is a very low-risk and high-reward move for any organization.”
Story continues
About SAS SAS is a global leader in data and AI. With SAS software and industry-specific solutions, organizations transform data into trusted decisions. SAS gives you THE POWER TO KNOW®.
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2024 SAS Institute Inc. All rights reserved.
Editorial Contact:Mike NemecekSASmike.nemecek@sas.com 919-531-5140sas.com/news
(PRNewsfoto/SAS)
Cision
View original content to download multimedia:https://www.prnewswire.com/news-releases/analysts-laud-sas-innovation-in-ai-marketing-risk-and-fraud-solutions-302209840.html
SOURCE SAS
Analysts laud SAS’ innovation in AI, marketing, risk and fraud solutions
Investment by SAS drives accolades in multiple reports from top analyst firms
CARY, N.C., July 30, 2024 /PRNewswire/ — When choosing new technologies like generative AI (GenAI) or selecting vendors for mission-critical functions like managing risk, improving marketing and customer loyalty, and fighting fraud and financial crimes, organizations often seek the advice of top industry analyst firms.
Top industry analyst firms have once again have recognized SAS as a leader in key business and technology areas.
And these top firms once again have recognized SAS and its technologies as leaders in important business and technology areas.
For more SAS rankings in analyst reports, see Analyst Viewpoints at SAS.com/analystviews.
Among the most recent analyst accolades for SAS are:
AI and Analytics
Customer Intelligence
Risk Management
Chartis RiskTech Quadrant® for Credit Risk Management – Trading Book – SAS named a Leader (June 2024)
Chartis RiskTech Quadrant for Credit Risk Management – Banking Book – SAS named a Leader (June 2024)
Chartis STORM50: Retail Finance Analytics50 – SAS earned the No. 1 overall ranking (June 2024)
Chartis STORM50: Quant Tech50 – SAS ranked No. 4 out of 50 vendors (June 2024)
Chartis STORM50: Insurance Analytics50 – SAS ranked No. 5 out of 50 vendors (June 2024)
Fraud and Financial Crimes
The Forrester Wave: Enterprise Fraud Management Solutions – SAS named a Leader (June 2024)
Chartis RiskTech Quadrant for Adverse Media Monitoring Solutions – SAS named a Leader (May 2024)
Chartis RiskTech Quadrant for Name and Transaction Screening Solutions – SAS named a Leader (May 2024)
SAS remains steadfast in its commitment to investing in the latest data and AI technologies to help its customers succeed. In April, for example, SAS announced new GenAI capabilities for SAS Viya, its cloud-native data and AI platform. And in June, SAS rolled out additional GenAI tools in its lead marketing technology solution, SAS Customer Intelligence 360.
“For decades, SAS has focused on helping our customers transform huge amounts of data into better business decisions and value,” said SAS CEO Jim Goodnight.
“And we’ve baked our passion for analytics, data and AI into SAS software solutions, which help our customers better serve their customers, fight fraud and manage risk. These latest analyst reports not only highlight SAS’ leadership in important business areas, but also show that choosing SAS is a very low-risk and high-reward move for any organization.”
Story continues
About SAS SAS is a global leader in data and AI. With SAS software and industry-specific solutions, organizations transform data into trusted decisions. SAS gives you THE POWER TO KNOW®.
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2024 SAS Institute Inc. All rights reserved.
Editorial Contact:Mike NemecekSASmike.nemecek@sas.com 919-531-5140sas.com/news
(PRNewsfoto/SAS)
Cision
View original content to download multimedia:https://www.prnewswire.com/news-releases/analysts-laud-sas-innovation-in-ai-marketing-risk-and-fraud-solutions-302209840.html
SOURCE SAS
The Commonwealth Secretariat and SAS join forces to secure an equitable digital future for young people
Thousands of people across the 56 Commonwealth countries will benefit from AI-driven initiatives meant to bridge the digital divide. One such initiative was launched recently, with the Commonwealth Secretariat joining forces with SAS, a global leader in data and artificial intelligence (AI).
The project aims to unlock the transformative potential of AI and advanced analytics to drive progress and innovation.
Focusing on digital literacy
The Commonwealth Secretary-General, the Rt Hon Patricia Scotland KC, reminded the audience that in June 2022, at the Commonwealth Heads of Government Meeting (CHOGM) in Rwanda, leaders acknowledged the transformative impact of technology on education and reaffirmed the critical importance of equipping citizens with the skills needed to thrive in a digital world. They resolved to address the digital skills gap in the 56 member countries – to build capacity, support development, and stimulate inclusive economic growth.
The Commonwealth Secretary-General, Rt Hon Patricia Scotland KC, said:
“Today’s launch is part of the implementation of that mandate. The SAS digital initiative, with its focus on digital literacy, access and building computational capacity, provides a unique opportunity for students and educators in our member states to be trained in the fundamentals of artificial intelligence and advanced analytics.
She added:
“Digital readiness is essential – and the cornerstone of this readiness is the digital capabilities of our young people. That is why our SAS Digital Literacy Initiative focuses on students and educators. This critical demographic has too often been overlooked or taken for granted in the drive to bridge the digital divide, but it is key to catalysing the spirit of innovation across our member states.”
Through this partnership, learners and educators in Commonwealth countries will develop AI and analytics capabilities, have access to educational resources, and have opportunities to participate in international AI competitions to foster practical experience and global recognition, whilst promoting responsible and ethical use of AI and data analytics.
Reggie Townsend, Vice President of Data Ethics at SAS, said:
“This collaboration will bring AI capacity to populations that haven’t always benefitted from the technological advances that power the world’s largest economies. These students will not only gain AI skills coveted by employers around the world, but they will also learn how to wield these powerful technologies ethically, in ways that benefit society.”
Creating new platforms
The first phase of the partnership includes a project with The University of the West Indies, located in four Caribbean countries, and serving 18 countries. Students from tertiary institutions and educators will have access to SAS Viya, a powerful data analytics tool. They will also benefit from the cloud platform on Microsoft Azure and 15 cutting-edge tools supporting visual analytics, open-source integration, model management, and more.
At the launch, Sir Hilary Beckles, Vice-Chancellor of The University of the West Indies, noted:
“Here we have a great moment in time. An opportunity where AI has the potential to create a global level field for everyone. It allows everyone to participate. It is undoubtedly a democratising technology. That is where it is going and that is why developing countries are very keen to embrace and participate.”
Guests at the launch were addressed by HE Saida Muna Tasneem, High Commissioner for Bangladesh, who shared insights about how technology and access to data have recently impacted on her country, leading to change. HE Janet Charles, Acting High Commissioner for the Commonwealth of Dominica to the United Kingdom, and HE Paul Andrew Gomez, High Commissioner of the Commonwealth of The Bahamas, also conveyed their appreciation for having this initiative piloted in the Caribbean.
Liz Moran, SAS Director of Global Academic Program and Certification, who is leading for SAS on the development of the collaboration package, provided more information and insight on what is on offer and the Secretariat’s Deputy Secretary-General, Dr Arjoon Suddhoo, delivered closing remarks that endorsed the initiative.
The Commonwealth Secretary-General has steadfastly advocated for the increased use of technology across the 56 member states. To advance this goal, the Commonwealth Artificial Intelligence Consortium (CAIC) was formed in 2023 and includes representatives from global tech firms, world-leading research institutions, and non-profit organisations. Ten Commonwealth member countries have also been included in the CAIC and will champion AI innovation in their own nations and throughout the union.
Further information about the partnership with SAS can be found here
The Commonwealth Secretariat and SAS join forces to secure an equitable digital future for young people
Thousands of people across the 56 Commonwealth countries will benefit from AI-driven initiatives meant to bridge the digital divide. One such initiative was launched recently, with the Commonwealth Secretariat joining forces with SAS, a global leader in data and artificial intelligence (AI).
The project aims to unlock the transformative potential of AI and advanced analytics to drive progress and innovation.
Focusing on digital literacy
The Commonwealth Secretary-General, the Rt Hon Patricia Scotland KC, reminded the audience that in June 2022, at the Commonwealth Heads of Government Meeting (CHOGM) in Rwanda, leaders acknowledged the transformative impact of technology on education and reaffirmed the critical importance of equipping citizens with the skills needed to thrive in a digital world. They resolved to address the digital skills gap in the 56 member countries – to build capacity, support development, and stimulate inclusive economic growth.
The Commonwealth Secretary-General, Rt Hon Patricia Scotland KC, said:
“Today’s launch is part of the implementation of that mandate. The SAS digital initiative, with its focus on digital literacy, access and building computational capacity, provides a unique opportunity for students and educators in our member states to be trained in the fundamentals of artificial intelligence and advanced analytics.
She added:
“Digital readiness is essential – and the cornerstone of this readiness is the digital capabilities of our young people. That is why our SAS Digital Literacy Initiative focuses on students and educators. This critical demographic has too often been overlooked or taken for granted in the drive to bridge the digital divide, but it is key to catalysing the spirit of innovation across our member states.”
Through this partnership, learners and educators in Commonwealth countries will develop AI and analytics capabilities, have access to educational resources, and have opportunities to participate in international AI competitions to foster practical experience and global recognition, whilst promoting responsible and ethical use of AI and data analytics.
Reggie Townsend, Vice President of Data Ethics at SAS, said:
“This collaboration will bring AI capacity to populations that haven’t always benefitted from the technological advances that power the world’s largest economies. These students will not only gain AI skills coveted by employers around the world, but they will also learn how to wield these powerful technologies ethically, in ways that benefit society.”
Creating new platforms
The first phase of the partnership includes a project with The University of the West Indies, located in four Caribbean countries, and serving 18 countries. Students from tertiary institutions and educators will have access to SAS Viya, a powerful data analytics tool. They will also benefit from the cloud platform on Microsoft Azure and 15 cutting-edge tools supporting visual analytics, open-source integration, model management, and more.
At the launch, Sir Hilary Beckles, Vice-Chancellor of The University of the West Indies, noted:
“Here we have a great moment in time. An opportunity where AI has the potential to create a global level field for everyone. It allows everyone to participate. It is undoubtedly a democratising technology. That is where it is going and that is why developing countries are very keen to embrace and participate.”
Guests at the launch were addressed by HE Saida Muna Tasneem, High Commissioner for Bangladesh, who shared insights about how technology and access to data have recently impacted on her country, leading to change. HE Janet Charles, Acting High Commissioner for the Commonwealth of Dominica to the United Kingdom, and HE Paul Andrew Gomez, High Commissioner of the Commonwealth of The Bahamas, also conveyed their appreciation for having this initiative piloted in the Caribbean.
Liz Moran, SAS Director of Global Academic Program and Certification, who is leading for SAS on the development of the collaboration package, provided more information and insight on what is on offer and the Secretariat’s Deputy Secretary-General, Dr Arjoon Suddhoo, delivered closing remarks that endorsed the initiative.
The Commonwealth Secretary-General has steadfastly advocated for the increased use of technology across the 56 member states. To advance this goal, the Commonwealth Artificial Intelligence Consortium (CAIC) was formed in 2023 and includes representatives from global tech firms, world-leading research institutions, and non-profit organisations. Ten Commonwealth member countries have also been included in the CAIC and will champion AI innovation in their own nations and throughout the union.
Further information about the partnership with SAS can be found here
SAS Defines Hybrid Reality For Quantum Computing
Development engineer Louise Hoppe checks a crystal wafer with light channels milled by a laser at … [+] German technology company Trumpf in Ditzingen near Stuttgart, southern Germany, on January 30, 2020. – The light channels are the heart in the construction of quantum sensors. (Photo by THOMAS KIENZLE / AFP) (Photo by THOMAS KIENZLE/AFP via Getty Images)
AFP via Getty Images
Quantum is huge. Because quantum computing allows us to step beyond the current limitations of digital systems, it paves the way for a new era of computing machines with previously unthinkable power. Without recounting another simplified explanation of how quantum gets its power at length, we can reference the double-slit experiment and perhaps the spinning coin explanation.
A coin sat on a desk is either heads or tails, rather like the 1s and 0s that express the on or off values in binary code. Quantum theorists would prefer we think of the coin above the desk, spinning in the air. In this state, the coin is both heads and tails at the same time. This is because, at the quantum level, both values exist until we make an observation of its state at any given point in time. We could further increase the number of positions possible (literally known as quantum superposition) by altering the angle of view we take on the coin, which is somewhat similar to how we work with qubits in quantum mechanics.
So then, Schrödinger’s cat is both alive and dead at the same time and the dummies guide to quantum entanglement is out there on the web if needed. What matters most now is how we will make practical use of quantum computing and where it will be applied for best advantage.
What Next For Quantum?
Across the universe of quantum entanglement, we’re at a point where quantum computing could redefine data analysis and model training in AI. This is the suggestion made by Bill Wisotsky, lead quantum architect and quantum computing researcher at SAS. In our near and immediate future, quantum computers could handle the complex calculations of AI algorithms much faster than classical computers and with less data, resulting in AI that can learn and adapt in ways we can’t currently imagine.
The main advancements Wisotsky and team are seeing inside SAS when speaking to customers includes work focused on fuelling the creation of a greater number of “good quality” qubits, which (in theory if not in practice) should get us to a point where we can tackle larger and more complex problems.
“Qubits are the smallest functional unit of QPU [quantam processing unit], analogous to classical bits. A larger number of computation qubits results in larger problems being solved on the QPU. Better quality qubits result in more reliable results that are less prone to ‘noise’ and instability,” said Wisotsky, in a company analysis blog.
As a quantum architect, Wisotsky explains quantum’s transformative potential to handle intricate computations and address detailed “combinatorial” analysis problems i.e. a mathematical term describing the number of elements that exist in a larger sum of values and the complexity of their arrangement. This is the type of analysis needed in all industries, but it has particular relevance for healthcare and life sciences and across finance and insurance.
Hope Lies In Hybrid
SAS underlines the fact that today, what has been most promising is the use of quantum-classical hybrid approaches, which aim at splitting computing processes and sending the pieces to quantum that quantum does best and the pieces to classical computing that classical does best. It’s slightly reminiscent of when cloud computing arrived and we were told that “cloud is for everyone, but not for every thing” – so therefore, similarly, it’s important to realize that not all problems will benefit from quantum computing.
“Problems need to be complex enough that classical systems struggle to solve them, only then will quantum properties be valuable,” explained Wisotsky. “For example, traditional computing might take days or months to run trial and error scenarios to find the best drug for a clinical trial, which impacts a hospital’s budget and personnel. Quantum computing offers the ability to search all solutions instantaneously, finding optimal drugs for trial much faster and more efficiently. By using both traditional computing and quantum computing in concert with one another, organizations can start to realize the benefits of quantum now.”
It is perhaps refreshing to hear enterprise tech firms talk realistically about the still-embryonic nature of an emerging technology in this way. With all the generative AI hype we’ve been working through for the last year or two, we need to handle this great power with really great responsibility. Extending and dovetailing with Wisotsky’s insight on this subject is Bryan Harris in his core capacity as CTO of SAS.
SAS R&D Factor
Harris talks about the quantum research work currently being carried out inside SAS R&D and, although the company is not building a quantum computer (it’s a discipline and skillset best left to specialized manufacturers and those tech behemoths with enough muscle to underpin development investment in this space such as IBM), it is actively exploring real-world applications and running actual use cases with third-party quantum computers.
In terms of practical tangible developments SAS researchers are investigating four opportunities for quantum computing:
Drug discovery: In the pharmaceutical industry, quantum computing is said to reduce the time and cost associated with discovering new drugs by simulating the behavior of molecules. This includes understanding the interactions between drugs and the complex biological systems they target. Financial modeling: As the world becomes more digitally connected, the complexity of modeling risk is beginning to overwhelm classical methods. In the banking industry, quantum algorithms have the ability to improve the modeling of financial markets, portfolio optimization and systemic risk associated with hyperconnectivity. Chemical simulations: Quantum computers can simulate the behavior of atoms and molecules at a quantum level with high accuracy. SAS researchers have noted that this is a challenge for classical computers because of the complex nature of quantum mechanics. In the science field, quantum computing can enable the discovery of new materials for improved sustainability to include much needed breakthroughs in batteries for electric vehicles. Optimization: Fourthly here, quantum computing could dramatically reduce computational time by finding near-optimal solutions through its ability to search an entire space instantaneously, leading to cost savings in cloud computing operations and tackling previously unsolvable problems.
For an example of the above-noted process of optimization, in traditional cloud computing, running trial and error scenarios to find the best solution could take days or months, which is expensive. Quantum computing offers the ability to search the space instantaneously, finding optimal solutions much faster and more efficiently.
Quantum In Data & Analytics
With these four cornerstones under development then, what is the future for of this technology in data and analytics, especially given new post-quantum cryptography standards guidance from NIST? To put the question another way, what are some possible pros and cons resulting from quantum’s introduction to modern enterprises?
“With every new technology, there are opportunities and risks,” advised SAS CTO Harris, speaking to press and analysts this week in London. “First, quantum presents many positive opportunities for businesses to solve challenging problems that were previously unsolvable. However, quantum computers have the potential to break many of the cryptographic systems we rely on today for secure communications and data protection. This reality has put it on national agendas with the recent announcement of NIST’s post-quantum cryptography standards.”
As a result he says, there are two important workstreams that must happen simultaneously.
“First, organizations must allocate research dollars into quantum computing to understand how it be leveraged to create a competitive advantage in products and services. Second, IT and product development organizations must plan for the integration of quantum-resilient encryption algorithms to maintain the security integrity of their infrastructure,” insisted Harris.
Which Verticals Will Adopt Quantum?
As we have noted, not every business or life problem can take advantage of quantum computing. We need to look for application scenarios that must be complex enough that classical computing systems struggle to solve them. The sectors most likely to benefit include life sciences, banking and materials science.
The big question is, no… the “first” and most important question we might ask here is just exactly how will quantum computing change the data and analytics industry, or indeed other industries?
“The first major impact that quantum computing will have on data and analytics is search space optimization for AI,” said SAS’ Harris. “In many AI problems, the training of a model or machine learning requires the exploration of a highly-dimensional data space for potential solutions. With classical computers, searching this space can be slow and expensive, especially in the cloud. With quantum computing, the entire space can be searched simultaneously to find the best solution that can be used as a starting point in classical computing.”
Our takeaways here are, like quantum theory itself, both simple and complex.
Put simply, quantum computing is as occasionally fragile as it is magnificently powerful and we’re still at a prototyping analysis stage with this technology, but we’re quickly coming out of that phase into real world applications. Put in slightly more complex terms, our quantum reality is likely to be a hybrid combination of traditional compute architectures made up of CPUs and GPU as also we now add QPUs into the mix.
As for Schrödinger’s cat, the lid isn’t off that box yet, thankfully.
The Commonwealth Secretariat and SAS join forces to secure an equitable digital future for young people
Thousands of people across the 56 Commonwealth countries will benefit from AI-driven initiatives meant to bridge the digital divide. One such initiative was launched recently, with the Commonwealth Secretariat joining forces with SAS, a global leader in data and artificial intelligence (AI).
The project aims to unlock the transformative potential of AI and advanced analytics to drive progress and innovation.
Focusing on digital literacy
The Commonwealth Secretary-General, the Rt Hon Patricia Scotland KC, reminded the audience that in June 2022, at the Commonwealth Heads of Government Meeting (CHOGM) in Rwanda, leaders acknowledged the transformative impact of technology on education and reaffirmed the critical importance of equipping citizens with the skills needed to thrive in a digital world. They resolved to address the digital skills gap in the 56 member countries – to build capacity, support development, and stimulate inclusive economic growth.
The Commonwealth Secretary-General, Rt Hon Patricia Scotland KC, said:
“Today’s launch is part of the implementation of that mandate. The SAS digital initiative, with its focus on digital literacy, access and building computational capacity, provides a unique opportunity for students and educators in our member states to be trained in the fundamentals of artificial intelligence and advanced analytics.
She added:
“Digital readiness is essential – and the cornerstone of this readiness is the digital capabilities of our young people. That is why our SAS Digital Literacy Initiative focuses on students and educators. This critical demographic has too often been overlooked or taken for granted in the drive to bridge the digital divide, but it is key to catalysing the spirit of innovation across our member states.”
Through this partnership, learners and educators in Commonwealth countries will develop AI and analytics capabilities, have access to educational resources, and have opportunities to participate in international AI competitions to foster practical experience and global recognition, whilst promoting responsible and ethical use of AI and data analytics.
Reggie Townsend, Vice President of Data Ethics at SAS, said:
“This collaboration will bring AI capacity to populations that haven’t always benefitted from the technological advances that power the world’s largest economies. These students will not only gain AI skills coveted by employers around the world, but they will also learn how to wield these powerful technologies ethically, in ways that benefit society.”
Creating new platforms
The first phase of the partnership includes a project with The University of the West Indies, located in four Caribbean countries, and serving 18 countries. Students from tertiary institutions and educators will have access to SAS Viya, a powerful data analytics tool. They will also benefit from the cloud platform on Microsoft Azure and 15 cutting-edge tools supporting visual analytics, open-source integration, model management, and more.
At the launch, Sir Hilary Beckles, Vice-Chancellor of The University of the West Indies, noted:
“Here we have a great moment in time. An opportunity where AI has the potential to create a global level field for everyone. It allows everyone to participate. It is undoubtedly a democratising technology. That is where it is going and that is why developing countries are very keen to embrace and participate.”
Guests at the launch were addressed by HE Saida Muna Tasneem, High Commissioner for Bangladesh, who shared insights about how technology and access to data have recently impacted on her country, leading to change. HE Janet Charles, Acting High Commissioner for the Commonwealth of Dominica to the United Kingdom, and HE Paul Andrew Gomez, High Commissioner of the Commonwealth of The Bahamas, also conveyed their appreciation for having this initiative piloted in the Caribbean.
Liz Moran, SAS Director of Global Academic Program and Certification, who is leading for SAS on the development of the collaboration package, provided more information and insight on what is on offer and the Secretariat’s Deputy Secretary-General, Dr Arjoon Suddhoo, delivered closing remarks that endorsed the initiative.
The Commonwealth Secretary-General has steadfastly advocated for the increased use of technology across the 56 member states. To advance this goal, the Commonwealth Artificial Intelligence Consortium (CAIC) was formed in 2023 and includes representatives from global tech firms, world-leading research institutions, and non-profit organisations. Ten Commonwealth member countries have also been included in the CAIC and will champion AI innovation in their own nations and throughout the union.
Further information about the partnership with SAS can be found here
SAS Defines Hybrid Reality For Quantum Computing
Development engineer Louise Hoppe checks a crystal wafer with light channels milled by a laser at … [+] German technology company Trumpf in Ditzingen near Stuttgart, southern Germany, on January 30, 2020. – The light channels are the heart in the construction of quantum sensors. (Photo by THOMAS KIENZLE / AFP) (Photo by THOMAS KIENZLE/AFP via Getty Images)
AFP via Getty Images
Quantum is huge. Because quantum computing allows us to step beyond the current limitations of digital systems, it paves the way for a new era of computing machines with previously unthinkable power. Without recounting another simplified explanation of how quantum gets its power at length, we can reference the double-slit experiment and perhaps the spinning coin explanation.
A coin sat on a desk is either heads or tails, rather like the 1s and 0s that express the on or off values in binary code. Quantum theorists would prefer we think of the coin above the desk, spinning in the air. In this state, the coin is both heads and tails at the same time. This is because, at the quantum level, both values exist until we make an observation of its state at any given point in time. We could further increase the number of positions possible (literally known as quantum superposition) by altering the angle of view we take on the coin, which is somewhat similar to how we work with qubits in quantum mechanics.
So then, Schrödinger’s cat is both alive and dead at the same time and the dummies guide to quantum entanglement is out there on the web if needed. What matters most now is how we will make practical use of quantum computing and where it will be applied for best advantage.
What Next For Quantum?
Across the universe of quantum entanglement, we’re at a point where quantum computing could redefine data analysis and model training in AI. This is the suggestion made by Bill Wisotsky, lead quantum architect and quantum computing researcher at SAS. In our near and immediate future, quantum computers could handle the complex calculations of AI algorithms much faster than classical computers and with less data, resulting in AI that can learn and adapt in ways we can’t currently imagine.
The main advancements Wisotsky and team are seeing inside SAS when speaking to customers includes work focused on fuelling the creation of a greater number of “good quality” qubits, which (in theory if not in practice) should get us to a point where we can tackle larger and more complex problems.
“Qubits are the smallest functional unit of QPU [quantam processing unit], analogous to classical bits. A larger number of computation qubits results in larger problems being solved on the QPU. Better quality qubits result in more reliable results that are less prone to ‘noise’ and instability,” said Wisotsky, in a company analysis blog.
As a quantum architect, Wisotsky explains quantum’s transformative potential to handle intricate computations and address detailed “combinatorial” analysis problems i.e. a mathematical term describing the number of elements that exist in a larger sum of values and the complexity of their arrangement. This is the type of analysis needed in all industries, but it has particular relevance for healthcare and life sciences and across finance and insurance.
Hope Lies In Hybrid
SAS underlines the fact that today, what has been most promising is the use of quantum-classical hybrid approaches, which aim at splitting computing processes and sending the pieces to quantum that quantum does best and the pieces to classical computing that classical does best. It’s slightly reminiscent of when cloud computing arrived and we were told that “cloud is for everyone, but not for every thing” – so therefore, similarly, it’s important to realize that not all problems will benefit from quantum computing.
“Problems need to be complex enough that classical systems struggle to solve them, only then will quantum properties be valuable,” explained Wisotsky. “For example, traditional computing might take days or months to run trial and error scenarios to find the best drug for a clinical trial, which impacts a hospital’s budget and personnel. Quantum computing offers the ability to search all solutions instantaneously, finding optimal drugs for trial much faster and more efficiently. By using both traditional computing and quantum computing in concert with one another, organizations can start to realize the benefits of quantum now.”
It is perhaps refreshing to hear enterprise tech firms talk realistically about the still-embryonic nature of an emerging technology in this way. With all the generative AI hype we’ve been working through for the last year or two, we need to handle this great power with really great responsibility. Extending and dovetailing with Wisotsky’s insight on this subject is Bryan Harris in his core capacity as CTO of SAS.
SAS R&D Factor
Harris talks about the quantum research work currently being carried out inside SAS R&D and, although the company is not building a quantum computer (it’s a discipline and skillset best left to specialized manufacturers and those tech behemoths with enough muscle to underpin development investment in this space such as IBM), it is actively exploring real-world applications and running actual use cases with third-party quantum computers.
In terms of practical tangible developments SAS researchers are investigating four opportunities for quantum computing:
Drug discovery: In the pharmaceutical industry, quantum computing is said to reduce the time and cost associated with discovering new drugs by simulating the behavior of molecules. This includes understanding the interactions between drugs and the complex biological systems they target. Financial modeling: As the world becomes more digitally connected, the complexity of modeling risk is beginning to overwhelm classical methods. In the banking industry, quantum algorithms have the ability to improve the modeling of financial markets, portfolio optimization and systemic risk associated with hyperconnectivity. Chemical simulations: Quantum computers can simulate the behavior of atoms and molecules at a quantum level with high accuracy. SAS researchers have noted that this is a challenge for classical computers because of the complex nature of quantum mechanics. In the science field, quantum computing can enable the discovery of new materials for improved sustainability to include much needed breakthroughs in batteries for electric vehicles. Optimization: Fourthly here, quantum computing could dramatically reduce computational time by finding near-optimal solutions through its ability to search an entire space instantaneously, leading to cost savings in cloud computing operations and tackling previously unsolvable problems.
For an example of the above-noted process of optimization, in traditional cloud computing, running trial and error scenarios to find the best solution could take days or months, which is expensive. Quantum computing offers the ability to search the space instantaneously, finding optimal solutions much faster and more efficiently.
Quantum In Data & Analytics
With these four cornerstones under development then, what is the future for of this technology in data and analytics, especially given new post-quantum cryptography standards guidance from NIST? To put the question another way, what are some possible pros and cons resulting from quantum’s introduction to modern enterprises?
“With every new technology, there are opportunities and risks,” advised SAS CTO Harris, speaking to press and analysts this week in London. “First, quantum presents many positive opportunities for businesses to solve challenging problems that were previously unsolvable. However, quantum computers have the potential to break many of the cryptographic systems we rely on today for secure communications and data protection. This reality has put it on national agendas with the recent announcement of NIST’s post-quantum cryptography standards.”
As a result he says, there are two important workstreams that must happen simultaneously.
“First, organizations must allocate research dollars into quantum computing to understand how it be leveraged to create a competitive advantage in products and services. Second, IT and product development organizations must plan for the integration of quantum-resilient encryption algorithms to maintain the security integrity of their infrastructure,” insisted Harris.
Which Verticals Will Adopt Quantum?
As we have noted, not every business or life problem can take advantage of quantum computing. We need to look for application scenarios that must be complex enough that classical computing systems struggle to solve them. The sectors most likely to benefit include life sciences, banking and materials science.
The big question is, no… the “first” and most important question we might ask here is just exactly how will quantum computing change the data and analytics industry, or indeed other industries?
“The first major impact that quantum computing will have on data and analytics is search space optimization for AI,” said SAS’ Harris. “In many AI problems, the training of a model or machine learning requires the exploration of a highly-dimensional data space for potential solutions. With classical computers, searching this space can be slow and expensive, especially in the cloud. With quantum computing, the entire space can be searched simultaneously to find the best solution that can be used as a starting point in classical computing.”
Our takeaways here are, like quantum theory itself, both simple and complex.
Put simply, quantum computing is as occasionally fragile as it is magnificently powerful and we’re still at a prototyping analysis stage with this technology, but we’re quickly coming out of that phase into real world applications. Put in slightly more complex terms, our quantum reality is likely to be a hybrid combination of traditional compute architectures made up of CPUs and GPU as also we now add QPUs into the mix.
As for Schrödinger’s cat, the lid isn’t off that box yet, thankfully.
SAS Defines Hybrid Reality For Quantum Computing
Development engineer Louise Hoppe checks a crystal wafer with light channels milled by a laser at … [+] German technology company Trumpf in Ditzingen near Stuttgart, southern Germany, on January 30, 2020. – The light channels are the heart in the construction of quantum sensors. (Photo by THOMAS KIENZLE / AFP) (Photo by THOMAS KIENZLE/AFP via Getty Images)
AFP via Getty Images
Quantum is huge. Because quantum computing allows us to step beyond the current limitations of digital systems, it paves the way for a new era of computing machines with previously unthinkable power. Without recounting another simplified explanation of how quantum gets its power at length, we can reference the double-slit experiment and perhaps the spinning coin explanation.
A coin sat on a desk is either heads or tails, rather like the 1s and 0s that express the on or off values in binary code. Quantum theorists would prefer we think of the coin above the desk, spinning in the air. In this state, the coin is both heads and tails at the same time. This is because, at the quantum level, both values exist until we make an observation of its state at any given point in time. We could further increase the number of positions possible (literally known as quantum superposition) by altering the angle of view we take on the coin, which is somewhat similar to how we work with qubits in quantum mechanics.
So then, Schrödinger’s cat is both alive and dead at the same time and the dummies guide to quantum entanglement is out there on the web if needed. What matters most now is how we will make practical use of quantum computing and where it will be applied for best advantage.
What Next For Quantum?
Across the universe of quantum entanglement, we’re at a point where quantum computing could redefine data analysis and model training in AI. This is the suggestion made by Bill Wisotsky, lead quantum architect and quantum computing researcher at SAS. In our near and immediate future, quantum computers could handle the complex calculations of AI algorithms much faster than classical computers and with less data, resulting in AI that can learn and adapt in ways we can’t currently imagine.
The main advancements Wisotsky and team are seeing inside SAS when speaking to customers includes work focused on fuelling the creation of a greater number of “good quality” qubits, which (in theory if not in practice) should get us to a point where we can tackle larger and more complex problems.
“Qubits are the smallest functional unit of QPU [quantam processing unit], analogous to classical bits. A larger number of computation qubits results in larger problems being solved on the QPU. Better quality qubits result in more reliable results that are less prone to ‘noise’ and instability,” said Wisotsky, in a company analysis blog.
As a quantum architect, Wisotsky explains quantum’s transformative potential to handle intricate computations and address detailed “combinatorial” analysis problems i.e. a mathematical term describing the number of elements that exist in a larger sum of values and the complexity of their arrangement. This is the type of analysis needed in all industries, but it has particular relevance for healthcare and life sciences and across finance and insurance.
Hope Lies In Hybrid
SAS underlines the fact that today, what has been most promising is the use of quantum-classical hybrid approaches, which aim at splitting computing processes and sending the pieces to quantum that quantum does best and the pieces to classical computing that classical does best. It’s slightly reminiscent of when cloud computing arrived and we were told that “cloud is for everyone, but not for every thing” – so therefore, similarly, it’s important to realize that not all problems will benefit from quantum computing.
“Problems need to be complex enough that classical systems struggle to solve them, only then will quantum properties be valuable,” explained Wisotsky. “For example, traditional computing might take days or months to run trial and error scenarios to find the best drug for a clinical trial, which impacts a hospital’s budget and personnel. Quantum computing offers the ability to search all solutions instantaneously, finding optimal drugs for trial much faster and more efficiently. By using both traditional computing and quantum computing in concert with one another, organizations can start to realize the benefits of quantum now.”
It is perhaps refreshing to hear enterprise tech firms talk realistically about the still-embryonic nature of an emerging technology in this way. With all the generative AI hype we’ve been working through for the last year or two, we need to handle this great power with really great responsibility. Extending and dovetailing with Wisotsky’s insight on this subject is Bryan Harris in his core capacity as CTO of SAS.
SAS R&D Factor
Harris talks about the quantum research work currently being carried out inside SAS R&D and, although the company is not building a quantum computer (it’s a discipline and skillset best left to specialized manufacturers and those tech behemoths with enough muscle to underpin development investment in this space such as IBM), it is actively exploring real-world applications and running actual use cases with third-party quantum computers.
In terms of practical tangible developments SAS researchers are investigating four opportunities for quantum computing:
Drug discovery: In the pharmaceutical industry, quantum computing is said to reduce the time and cost associated with discovering new drugs by simulating the behavior of molecules. This includes understanding the interactions between drugs and the complex biological systems they target. Financial modeling: As the world becomes more digitally connected, the complexity of modeling risk is beginning to overwhelm classical methods. In the banking industry, quantum algorithms have the ability to improve the modeling of financial markets, portfolio optimization and systemic risk associated with hyperconnectivity. Chemical simulations: Quantum computers can simulate the behavior of atoms and molecules at a quantum level with high accuracy. SAS researchers have noted that this is a challenge for classical computers because of the complex nature of quantum mechanics. In the science field, quantum computing can enable the discovery of new materials for improved sustainability to include much needed breakthroughs in batteries for electric vehicles. Optimization: Fourthly here, quantum computing could dramatically reduce computational time by finding near-optimal solutions through its ability to search an entire space instantaneously, leading to cost savings in cloud computing operations and tackling previously unsolvable problems.
For an example of the above-noted process of optimization, in traditional cloud computing, running trial and error scenarios to find the best solution could take days or months, which is expensive. Quantum computing offers the ability to search the space instantaneously, finding optimal solutions much faster and more efficiently.
Quantum In Data & Analytics
With these four cornerstones under development then, what is the future for of this technology in data and analytics, especially given new post-quantum cryptography standards guidance from NIST? To put the question another way, what are some possible pros and cons resulting from quantum’s introduction to modern enterprises?
“With every new technology, there are opportunities and risks,” advised SAS CTO Harris, speaking to press and analysts this week in London. “First, quantum presents many positive opportunities for businesses to solve challenging problems that were previously unsolvable. However, quantum computers have the potential to break many of the cryptographic systems we rely on today for secure communications and data protection. This reality has put it on national agendas with the recent announcement of NIST’s post-quantum cryptography standards.”
As a result he says, there are two important workstreams that must happen simultaneously.
“First, organizations must allocate research dollars into quantum computing to understand how it be leveraged to create a competitive advantage in products and services. Second, IT and product development organizations must plan for the integration of quantum-resilient encryption algorithms to maintain the security integrity of their infrastructure,” insisted Harris.
Which Verticals Will Adopt Quantum?
As we have noted, not every business or life problem can take advantage of quantum computing. We need to look for application scenarios that must be complex enough that classical computing systems struggle to solve them. The sectors most likely to benefit include life sciences, banking and materials science.
The big question is, no… the “first” and most important question we might ask here is just exactly how will quantum computing change the data and analytics industry, or indeed other industries?
“The first major impact that quantum computing will have on data and analytics is search space optimization for AI,” said SAS’ Harris. “In many AI problems, the training of a model or machine learning requires the exploration of a highly-dimensional data space for potential solutions. With classical computers, searching this space can be slow and expensive, especially in the cloud. With quantum computing, the entire space can be searched simultaneously to find the best solution that can be used as a starting point in classical computing.”
Our takeaways here are, like quantum theory itself, both simple and complex.
Put simply, quantum computing is as occasionally fragile as it is magnificently powerful and we’re still at a prototyping analysis stage with this technology, but we’re quickly coming out of that phase into real world applications. Put in slightly more complex terms, our quantum reality is likely to be a hybrid combination of traditional compute architectures made up of CPUs and GPU as also we now add QPUs into the mix.
As for Schrödinger’s cat, the lid isn’t off that box yet, thankfully.