The developments in the field of Artificial Intelligence (AI) are largely unprecedented, and have opened the doors towards a lot of new pathways. All the developments that were expected of AI, are finally proving to be true, and we have entered a stage of consistent development. Being associated with AI for much of the last decade, I have witnessed its growth over time. The technology has grown at a rate of knots, and it can safely be said that it now stands at a very crucial junction of time.

As part of my endeavors to keep myself up to date with the changing AI ecosystem and the developments made in it, I attended the Atos Technology days in Paris. The event was a nourishing experience for me, as I got to speak to and attended keynotes with different leaders from Atos such as Thierry Breton, who is Chairman and CEO Atos, Philippe Duluc, who is CTO for big data and security (BDS), Phillipe Vannier, who is group CTO, and Arnaud Bertrand, who is the Head of BDS Strategy and Innovation.

It felt great to be part of the conference and some interesting insights have been shared. Gartner has researched and found out that by 2021, we may have 40 percent of all consumers using smart technologies in applications. Not only this, but by 2020, it is expected that 50 percent of all BA software will be using prescriptive analytics. Keeping the bright future of AI, there was a lot to talk about.

How to Approach AI

The first step to approaching AI is to realize all the key ingredients of the process. AI is rapidly growing as an up and coming technology, and considering all that it has to offer, there are certainly no doubts regarding the benefits. However, before we talk about approaching AI, we will have a look at the three ingredients leading this change.

Data 

Data is the necessary fuel of all artificial intelligence. It is the explosion of data in the previous years that has helped us into this age of AI. Without the unprecedented wave of data dictating the way for us, we wouldn’t be able to implement so many Machine Learning (ML) techniques, get predictive analysis, and implement changes. Data hence provided the raw material that AI needed to develop.

Knowledge 

Knowledge or algorithms play an important part in AI as well. While data is extremely important in itself, it is the knowledge that we use to extract sense from it that dictates the way into the future. Going into the future requires the implementation of unprecedented changes and learning methods. Machine Learning and other methods have given data the platform it needed to become a source of artificial intelligence.

Computing Power 

Computing power is today at the heart of this revolution. Neural networks have existed since the 90s, but it is the power of computers in the world today that has led to a bigger change in AI. The fast pace of Quantum computing can be accredited with the change here, as it has made the smooth running of heavy Machine Learning systems possible.

The world is growing hybrid, combining traditional IT, private, managed and public clouds, and Atos Technology have truly captured the essence by creating a unique, hybrid experience. I spoke to Arnaud Bertrand from Atos about their endeavors in this regard, and he mentioned that the hybrid experience promised by Atos includes an amalgamation of on-site computing, private cloud, and edge computing. To ensure the security of data on the cloud, it is necessary that you incorporate the data with other solutions, to create a hybrid setting.

AI Use Cases

There are numerous use cases of how Atos has redefined the AI experience by creating the perfect mix of AI offerings for their clients. The following use cases will help explain their services in AI better:

Connected Cooler 

Atos has the honor of being Coca-Cola Hellenic Bottling Company’s official IoT partner. They recently went into an agreement over delivering more than 300,000 connected coolers to them by the end of 2018. These coolers are to be installed in nearly 30 countries across the globe, and the main goal they are supposed to achieve is to help customers out with their routine Coca-Cola vending machine/connected cooler experience.

What the connected cooler brings to the picture here for Coca-Cola is:

  • It achieves unprecedented efficiency for Coca-Cola by enhanced methods of predictive maintenance and placement.
  • It improves inventory, product placement, and stock optimization by following interactive AI methods to serve the purpose.
  • It increases sales by linking up targeted promotions with the connected consumers.

By promoting connectivity, the connected cooler will be giving Coca-Cola a chance to achieve brilliant success here.

Prescriptive Maintenance

The State Department of Virginia wants to protect the technology infrastructure within the state. They plan to do this through the next generation of AI powered cybersecurity solutions. The solution will be extremely helpful in identifying many future attacks and limiting them to an extent, where they don’t possess a potent threat anymore. The solution covers many different aspects, including threat detection to access point security and vulnerability management.

Cybersecurity has always been a tough task to manage, as isolated intrusions have been hard to detect for most systems. However, since these tasks have grown over the last few years, the need for a system that recognizes the attack and uses the information for further detection was felt. The prescriptive Security Operation Center detects all the signals left by such attacks and alerts security managers about possible risk areas, even before the attack happens. This not only gives insight into how cyber attacks are most often carried out, but also helps companies stop cyber attacks from hindering their services.

Digital Twin

Atos signed their global strategic partnership with Siemens in 2011. Ever since then, they have joined hands to market the MindSphere platform by Siemens. The platform is basically a cloud based operating system that gives customers the freedom to connect their physical infrastructure and legacy systems to the digital world.

By Digital Twin Technology, manufacturers can create a real-time digital replica of all physical assets for comparing and analyzing them in the future. This gives manufacturers the ability to find new ways for improving the production process. Automotive engineers could benefit from the twin technology by creating a prototype of the car inside the digital world, rather than in the physical world. Only when all testing has been done online, would they feel the need for physical testing.

Atos’s efforts to put AI in motion have helped their clients go a long way, and they endeavor to create such solutions going into the future as well. You can learn more about the possibilities of AI by watching videos of keynotes from the event.

Ronald

Ronald helps data driven companies generating business value with best of breed solutions and a hands-on approach. He has been recognized as one of the top 10 global influencers by DataConomy for predictive analytics, and by Klout for Data Science, Big Data, Business Intelligence and Data Mining and is guest author on leading Big Data sites, is speaker/chairman/panel member on national and international webinars and events and runs a successful series of webinar on Big Data and on Digital Transformation. He has been active in the data (process) management domain for more than 18 years, has founded multiple companies and is now director at a Data Consultancy company, leader in Big Data & data process management solutions. Broad interest in big data, data science, predictive analytics, business intelligence, customer experience and data mining. Feel free to connect on Twitter or LinkedIn to stay up to date on success stories.

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