Ai and Data: what lies ahead

Even if last year- and hopefully not-so-much the current one-will be defined in the annals by the slow recovery from the Covid pandemic, it is very likely that in the far future, people will look back at the second decade of 2000 as a pivotal moment for Data Science and AI. There is indeed a lot of expectation around the possibilities offered by AI, both in business development as much as in everyday life. Kebula is ready to ride this wave and forge new avenues for growth and innovation using Data as a game-changer for business. We have asked ourselves which are the new trends to look for in the race for data-centered value extraction? Here we propose a concise, and not exhaustive, list of four areas of interest to close attention in 2022:

hyper-automation

The process of automating everything that can be automated, basically.

It is the driving force of the digital transformation taking place in the EU. It is crystal clear that hyper-automation, to be consistent, needs to harvest and process big data continuously. Specifically, most AI models, which are the backbones of automation, are hungry for massive amounts of data, and flexible data pipelines are needed for incorporating structured and unstructured data.

In this regard, Kebula is setting its course of excellence. We can realize streamlines of processes that concur to increase the efficiency and the accuracy of the output. To perform such a complex task, multidisciplinary approaches are required, ranging from mathematical modeling to software engineering. Our team is ready to face the challenge, as it continues to expand its potential, both numerically and in terms of competencies.

Language-driven Intelligence

The voice and speech recognition market is growing. It is projected to reach $26 billion by 2025.

The Covid pandemic, in particular, drove the surge of smart speaker usage and con-tactless technologies. In 2022, we will see large language models becoming the foundation for next-generation conversational AI tools and for automated text generation and classification. Voice assistants in particular will be tailored, in the years to come, on specific business challenges, both for internal use (such as voice meetings) and for customer services (smart chatbots). For instance, according to recent reports, AI will save 8 billion USD per annum for the Customer Service Sector.

Kebula is building growing expertise on NLP. Together with the previous experiences in the field, we have ongoing projects related to automatic code generation and speaker recognition for Media. We are on it, read to sky-rocket.

AIoT

The artificial intelligence of things will emerge in the next year as the big thing, merging AI and the Internet of Things in sophisticated ways.

AI’s ability to propose real-time action and/or operating decisions will drive the IoT to new heights, empowering smart devices with data-oriented decision-making processes. A major driving factor to this technology is the roll-out of 5G which will enable faster transfer of large volumes of data across IoT devices. Hence, a proliferation of smart homes, offices, and cities is expected to come, again as prospected in the investment plan of the EU.

Kebula and Kineton are moving decisive steps in this direction. Starting from the Internet of Cars, we want to integrate the data acquisition process and analytics to directly impact the driving experience. This will create a bridge between different industrial stakeholders, opening up potential new markets: Telco, Automotive, and Entertainment industries are directly involved in this process.

AI4Green

The race for a sustainable industry is just started.

More and more organizations are pledging to “go green”, by choice or political pressure, hence there is an increasing need for companies to implement technologies that allow them to decrease their environmental footprint while retaining or increasing their revenues. AI is already being used to combat environmental challenges like reducing energy waste, spotting fire hazards, marine pollution, and optimizing pollutants management policies. This trend is set to increase.

In particular, Kebula wants to exploit data from different sources to tackle complex problems related to sustainability. We will make use of images from satellites, sensory data, traffic information, industrial product data, and so on to realize smart models and solutions that will reduce the overall footprint of many businesses, empowering a sustainable decision-making process. Still, our proposals aim to be business-friendly too, hence designed to have a positive impact on the revenues and the entire value extraction process.

  • Data and AI Scientist at Kebula Postdoc in quantum mechanics at the University of Tübingen in Germany. Previous he was a Research Fellow at the University of Nottingham (UK). He obtained a Ph.D. in Theoretical and Computational Physics at the University of Sheffield (UK).

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