Cloud Hosting

Bengaluru: Marc Carrel-Billiard, who recently visited India, serves as a senior managing director at Accenture. He heads Accenture Technology Innovation, the R&D Labs, Accenture Strategic Growth Initiatives, Accenture Studios and Accenture Ventures. In his 25-year tenure at the company, he has pioneered technology, particularly in voice recognition, knowledge-based systems, and neural networks. In an interview, Carrel-Billiard shared his views on how business leaders can harness scientific advancements and technologies such as artificial intelligence (AI), generative AI, quantum computing, blockchain, metaverse, and digital twins, and Indias role in these domains. Edited excerpts:

Bengaluru: Marc Carrel-Billiard, who recently visited India, serves as a senior managing director at Accenture. He heads Accenture Technology Innovation, the R&D Labs, Accenture Strategic Growth Initiatives, Accenture Studios and Accenture Ventures. In his 25-year tenure at the company, he has pioneered technology, particularly in voice recognition, knowledge-based systems, and neural networks. In an interview, Carrel-Billiard shared his views on how business leaders can harness scientific advancements and technologies such as artificial intelligence (AI), generative AI, quantum computing, blockchain, metaverse, and digital twins, and Indias role in these domains. Edited excerpts:

As we spelt out in our Technology Vision 2023 report, theres a revolution at every level. While companies already have a technology strategy to manage their information (IT) and operational technology (OT, which is about physical or hardware systems), the strategy needs to encompass science tech (ST), too, if enterprises want to leverage the new reality over the next 5-10 years.

Hi! You're reading a premium article

As we spelt out in our Technology Vision 2023 report, theres a revolution at every level. While companies already have a technology strategy to manage their information (IT) and operational technology (OT, which is about physical or hardware systems), the strategy needs to encompass science tech (ST), too, if enterprises want to leverage the new reality over the next 5-10 years.

Many companies are using tools such as RPA (robotic process automation) for automation work and claiming to do AI. But next generation of AI is about generalizing AI, which explores how a new category of AI, spurred on by foundation models and large language models (LLMs), is used by companies. We are also looking at multi-sensorial next-generation metaverse that is not just about vision and audio, but also haptics. One key focus area of the metaverse, will be industrial digital twins (digital replicas of physical systems).

Our technology vision report has a different theme every year. This year it is: When Atoms meet Bits: The foundations of our new reality. That is, while we may live in a physical world, we parallelly live in a digital world, too. We are going to see convergence of those two worlds in digital twins: everything you do will basically be replicated by a computer. For instance, instead of going to a doctor to get your heart (or any organ) examined, you will get an alert because of predictive monitoring of your digital twin whether you are on a plane, in a car, or anywhere. Besides, the value of the metaverse is not only to buy a house next to a big star, rather, it is a continuum of digitally-enhanced worlds, realities, and business models. Our life will be powered by digital twins, whether building digital twins of refineries or airplanes using 3D scanning to anticipate failures or monitoring. People at times do not appreciate the complex system modelling that goes into building a digital twinthey see only the user interface of a digital twin like the 3D model, or AR-VR (augmented and virtual reality) experiences. However, we need a very smart AI engine to simulate that stuff. At Accenture, we have made strategic investments in this complex system modelling to simulate organs, planes, refineries, and even climate change.

We have set up a generative AI and LLM Centre of Excellence (CoE) with 1,600 employees globally, a significant part of which is in India. We are working with Indian Institute of Science on collaborative research projects and developing intellectual properties in next generation computing technologies that enable AI at the edge, including cloud, edge, quantum, and neuromorphic computing and sustainable software engineering. People working at our Bengaluru lab also contribute to the lab in Dublin, which specializes in life sciences.

There are different types of clientsthose that are very innovative. They have the culture and mindset for innovation. There are the followers who had been innovating, but didnt know that they had the capacity to reinvent themselves. The third comprises laggards who are not much into digital transformation, and have migrated their services on the cloud to survive. We deliver our tech vision to clients by explaining our agenda and actions.

Yes. Thats one reason why we advise our leaders to think about the six pillars when considering generative AI, or any new tech tool. First, we advise them to dive in with a business-driven mindset, where you just need to think about the power of a technology and rethink how it can reinvent part of the business (not the company) so that you dont have to take a big risk. Basically to have your employees and, eventually, customers to experience it. For example, car makers put the whole document of a car in a book, or online with videos. Soon, it will be delivered with the help of Generative AI, using natural language processing or speech recognition, wherein you get to talk to the car or phone to get answers. The second is people-first approach. You need to demystify technology for employees, change their mindset to make them realize that these tools will make them powerful, rather than having their activities (jobs) taken away.

The third is getting your proprietary data ready, and connect it with a mesh-like technology. Four, choose the best green platform to run your system. Five, use Responsible AI to explain how your systems work. And last, but not the least, you need to figure out what youre doing with this data. Nothing can stop Generative AI. We must adopt it, understand it, and try to leverage it in the best possible way.

Generative AI is not new. Google was already working on transformers in 2017. So, weve been leveraging Generative AI for many years, its just that we didnt talk about it. For me, its just another tool like the cloud, etc. But (with ChatGPT), consumers lapped this up, which explains this (Generative AI) revolution.

As for our clients, we explain how they can leverage Generative AI the way we explain our approach to quantum computing. One thing we found is that Gen AI has the potential to transform 40% of all working hours. This doesnt mean that 40% of jobs will go away but it simply means that there will be a shift in the way we work. Basically, a specific task in any given job may become fully automated while some will be assisted by AI like a co-pilot. Other jobs will not be affected.

At Accenture, we are using Gen AI in our labs to deliver assets and solutions. And we announced a $3 billion investment over three years in its Data and AI practice this June to show the world that we are doubling down our efforts in this space. The important consideration for enterprises is how they will customise the system. The easiest stuff to do is what we call prompt engineering, but even this will be done by AI itself in the next 1-2 years.

While technology has accelerated scientific discovery, enterprises were largely content to leave science tech in the hands of researchers and specific industries like pharma or chemicals. Thats starting to change. More enterprises are widening their innovation efforts and discovering just how disruptive the intersection of science and technology can be.

When we launched our quantum computing practice six years ago, we wanted to talk to our industry leaders to understand what type of business or classification of problems were appropriate for quantum computers. We surveyed about 49 industries, and out of these, we found more than 150 use cases that we could use in sectors like manufacturing, finance, and pharma.

As an example, we started to engage with Biogen. One of the processes they wanted to change was to be able to compute the level of stability of medical compounds but classical computers, which allow drug companies to run hundreds of millions of comparisons, are limited only to molecules of up to a certain size. Quantum computers allow pharma companies to compare molecules that are much larger. Accenture Labs worked with D-Wave 1QBit (1QB Information Technologies, Inc.) to significantly improve the companys discovery process and eventually improve patient outcomes.

Another example is BBVA. Weve been working with them in three areas -- currency, credit scoring and optimization of trading trajectories (Accenture worked with D-Wave Systems and Spain-headquartered Banco Bilbao Vizcaya Argentaria (BBVA) to use quantum algorithms to address the opportunities in these areas).

A lot of people are cyborgs. They just dont know it. Youre a cyborg, for instance, if you have a pacemaker (sends electrical pulses to help your heart beat at a normal rate and rhythm) in you because it is powered by electronics. Theres are very smart AI algorithms that measure everything, which are making pacemakers more intelligent. Accenture also has a US patent for developing an algorithm to find the optimal donor-patient matches in a kidney exchange network using quantum computing, which can be used by hospital networks and government agencies nationwide.

For me, blockchain is the technology to power Web 3, but we need to rethink blockchains like making it greener. Accenture is one of the prominent players when it comes to making blockchain adoption in the world -- were all talking about making your identity card, driving permit, and everything into your E-wallet, powered by blockchain.

When I think sentient, for me its about two worlds. The first is emotional, and the second is, responsible. In our Dublin lab, we are also looking at how we can make these intelligent systems more emotional, so that they can interact with people better. On the emotional front, we have developed a tool which allows clients to change the recipe using suggested ingredients from generative AI, which comprises three categories: expected, surprising and novel. This is not something you would expect from a machine. And weve been testing the tool in partnership with a Michelin 3-Star restaurant. As for AI becoming sentient at any given point in time, I believe we will have to create machines we can connect with you. Thats going to be important in the future of adoption of these systems.

Continue reading here:
Everything you do will be replicated by a computer | Mint - Mint