AiThority Interview with Marc Carrel-Billiard, Senior Managing Director at Accenture Labs and Extended Reality
Know My Company
Tell us about your interaction with AI, ML and Quantum Computing?
These are all technologies on the research agenda at Accenture Labs. As the R&D organization within Accenture, Accenture Labs is focused on applying enterprise relevant emerging technologies in new and innovative ways to address key business challenges facing Accenture clients today, and those we expect them to face in the next few years. We harness the best innovation across the industry including top academic institutions, start-ups, and corporate R&D programs—to create cutting-edge prototypes and pioneering client engagements.
Accenture Labs works closely with Accenture’s dedicated business group focused on artificial intelligence, called Accenture Applied Intelligence, as well as our Quantum Computing practice.
How and why did you start working in this space?
I started at Accenture 22 years ago and have worked across all five industry groups that Accenture serves. I’ve led global Application Portfolio Optimization and SOA/Integration Architecture groups, along with many other roles, but I always kept my eye on Accenture Labs as they were driving some of the most exciting and innovative projects at the company.
How is Quantum Computing different from Cloud Computing? How are these two inter-related to each other?
A quantum computer is a type of computer whereas Cloud Computing is an architecture model for using computers remotely. Quantum computers and many other types of computers are available to use through cloud computing services. Accenture has been working to determine which of the available quantum, quantum-inspired, and classical computers in the cloud can be used to solve complex problems in the most cost-effective way for our enterprise clients.
What is the state of AI-related to IT service optimization in 2019? How much has it evolved around Quantum Computing?
Quantum computing has shown promise in solving complex optimization problems. AI is being used for autonomous decision making and optimization across all facets of IT, including IT infrastructure such as network, security, and application runtime, as well as IT planning such as resource availability, operations scheduling, and support. Mapping these complex problems to quantum methods is currently a work in progress. As the sophistication of the problems that quantum computers are able to solve continues to increase, many of these challenges could become viable to solve in a cost-efficient way.
Tell us more about your Quantum Computing patent. How will it bolster your market position?
We just received our second US patent for a “quantum computing Machine Learning module” that trains AI models to determine when computational tasks would be best handled by quantum computing versus classical computing methods, and route them to the best option. Deciding when to use quantum, as opposed to, or in tandem with classical computing, is critical for performing computational tasks in the most efficient and cost-effective way possible.
This adds to a patent we received last year for a “multi-state quantum optimization engine” that describes a solution that leverages the best aspects of both classical and quantum computing techniques to identify a broader range of solutions to business challenges. By running multiple simulations at the same time, the optimal outcome can be identified, improving business decision-making and operational efficiency.
These patents build on years of our quantum investments, partnerships and R&D efforts.
How much does IT cost to adopt and manage Quantum Computing infrastructure compare against Cloud/IaaS? What are the evident benefits of adopting Quantum?
Quantum computing cost per unit of performance is an important consideration, although this will change as quantum computers become easier to access and cheaper to build. Currently, due to the abundance of classical computing in the cloud and scarcity of quantum computers, it is estimated to be between 1,000 and 10,000 times more expensive per query to use quantum computers over their classical alternatives. depending on the type of algorithm you want to run. This makes quantum impractical for bulk commodity workloads for now. But problems that can’t be solved on classical computers but can potentially be solved on quantum computers are often worth the expense in the near term.
What is the biggest challenge for businesses related to digital transformation in 2019? How does Accenture’s quantum work contribute to digital transformation efforts?
I think the challenge is that simply doing digital is no longer enough. Digital technologies, like social, mobile, analytics and cloud, are now just the table stakes for doing business. Accenture believes we’re now entering a post-digital world. It doesn’t mean that companies have completed their digital transformation, it means that companies need to be preparing for what’s next and how they can leverage their digital capabilities to build unique and distinctive market advantages. We explore this in detail in the Accenture Technology Vision 2019 report, of which a key trend is what we call DARQ Power. DARQ is a term we coined for a Distributed ledger, Artificial intelligence, extended Reality, and Quantum computing. These are the next wave of technologies that businesses need to master to be successful in the future. While quantum is still in its early days, it’s advancing rapidly, and we’re committed to exploring how it can be used, in the right ways and at the right times for our clients. Organizations should be doing the same; they should be exploring quantum and other DARQ technologies so that that they’re prepared to combine and exploit them as the technologies reach enterprise-level maturity, putting them well ahead of more short-sighted competitors.
Where do you see AI/Machine Learning and other smart technologies heading beyond 2020?
We believe that AI’s greatest power lies in augmenting people and enabling humans and machines to leverage and amplify each other’s strengths. So, the focus going forward for these technologies really needs to be all about people. Current and future developments must be human-centric, they need to be purposeful and they need to be responsible for the outcomes they deliver.
What’s the good, bad and ugly of AI that you have heard or predict?
As AI takes a more central role in our lives, there will continue to be discussions about the consequences of the technology, and rightly so. At Accenture, we believe that there must be a responsible approach to AI and that it can be achieved if we “raise” the technology right. We don’t expect our children to act ethically without guidance, so we educate and nurture them. This is exactly the approach we should take with AI. Raising AI to be responsible means addressing many of the challenges we tackle through human education, such as fostering an understanding of right and wrong; imparting knowledge without bias; and building self-reliance while emphasizing the importance of collaborating with others.
There’s also been much discussion about AI’s impact on jobs and the speculation that it will reduce the need for human workers. But AI has the potential to create entirely new industries, new jobs, and new opportunities. It’s not a lack of new jobs that will be a problem, it’s the lack of skills. These topics are explored extensively in a book written by my colleagues Paul Daugherty and H. James Wilson called “Human + Machine: Reimaging Work in the Age of AI.” It’s a great guidebook for business leaders as they prepare their organizations and their workforces for the impact of AI.
The Crystal Gaze
What Cloud, Quantum Computing and Data Analytics SaaS start-ups and labs are you keenly following?
We have a group called Accenture Ventures that are focused on bringing our clients together with best-in-class emerging enterprise startups to accelerate their transformation. To do this, we conduct extensive research and collaborate with leading accelerators and venture capitalists around the world to identify new, innovative technology players to build collaborative business relationships with including making strategic equity investments. While I can’t share which companies are currently in our pipeline, I can point to a past example. In 2017, Accenture Ventures made a minority investment in 1QBit, a leading quantum computing firm based in Vancouver, British Columbia, which helped Accenture expand its capabilities in quantum computing analytics. Working together, Accenture and 1Qbit helped Biogen develop a first-of-its-kind quantum-enabled molecular comparison application that could significantly improve advanced molecular design to speed up drug discovery for complex neurological conditions such as multiple sclerosis, Alzheimer’s, Parkinson’s and Lou Gehrig’s Disease.
Another example is our participation in the IBM Q Network, which is one of the quantum platforms that has helped us to rapidly scale our quantum programs and better connect with organizations that are pushing the boundaries in this field.
What other technologies within AI/NLP and Cloud Analytics are you interested in?
I’m super excited by the work Accenture Labs is doing around Industry X.0. Industry X.0 is what we call the convergence of analytics, Artificial Intelligence, mixed reality and more that is enabling mass and hyper-personalization with smart, connected products, in real-time. Those products will provide totally new experiences to customers. Our R&D team at Accenture Labs is working to transform the manufacturing life cycle by applying AI- and IoT-driven intelligent automation and our research illustrate the enormous potential value waiting to be unleashed.
Which industries do you think will be fastest to adopt Analytics and AI/ML? What are the new emerging markets for these technologies?
Analytics and AI are already having a profound impact on every industry. From communications companies using AI in the front office for cross-selling effectiveness, and financial services companies using it in the back office for regulation, to pharmaceutical companies using AI and Deep Learning in R&D to accelerate time to market, it’s now pervasive and having a ripple effect across industries.
Tag the one person in the industry whose answers to these questions you would love to read:
Thank you, Marc! That was fun and hope to see you back on AiThority soon.
“As of 2015 Marc Carrel-Billard leads Accenture Labs globally. In his role Marc oversees all research and development activities of Accenture globally and leads the deliver of our yearly Technology Vision. Marc also leads our global practice on Extended Reality which covers immersive technologies such as VR, AR, …
Previously Marc Carrel-Billiard led our “Emerging Technology” practice globally. ET is an incubation organization which leverages the innovation from Accenture Technology Labs to drive them to mature solutions and transition them to wider delivery capabilities within our Technology Growth Platform.”
Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world’s largest delivery network—Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With more than 450,000 people serving clients in over 120 countries, Accenture drives innovation to improve the way the world works and lives.