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Beyond the Hype: Radix Insights on the Future of AI

Take a simple test: type "Artificial Intelligence" into any internet search engine. At the time of writing, the term already amassed 133 million results, an impressive number for a technology that only recently reached the mainstream. Despite the recent boom, driven by tools like OpenAI's ChatGPT and Google's Bard (Gemini), AI's history dates back years. Its roots lie in advances in deep learning, a field familiar to scientists and researchers for quite some time. Few may recall, but as early as the early 2000s, the topic was already being discussed, including with the release of the movie A.I. - Artificial Intelligence, directed by Steven Spielberg in 2001.

Though the boundaries of this technology and its potential remain uncertain, unlike other recent innovations such as the metaverse, AI has quickly gained popularity in its use and concepts.


The first known Artificial Intelligence program dates back to the distant year of 1966 when a computer scientist at MIT, Joseph Weizenbaum, of German-American origin, created a chatbot he named Eliza. Even then, the program could engage in relatively simple conversations with humans.

More recently, the uses and applications of AI have multiplied in all fields of personal and professional life. Some sectors have quickly learned to make the most of this technology, such as the entertainment industry, with the use of AI in special effects in cinema; in advertising, with the possibility of creating personalized ads; in virtual games; fashion; healthcare; finance, among many others.

In heavy industry, AI has been used to optimize production processes and develop new products. In agriculture, it helps monitor crop health and optimize resource use. And in the education sector, it creates personalized teaching materials and assists in student evaluation, among many other applications.


The potential of AI to drive growth and reduce costs cannot be underestimated, especially in the energy and materials sector, where data dependence and analysis are crucial for innovation. This sector is built on increasingly complex and subtle processes.

Essentially, AI brings intelligence to any data, empowering decision-making and enabling workers to acquire previously unknown knowledge and skills. In the case of heavy industries, the sector generates an enormous amount of data. From sensor logs and engineering reports to work orders and maintenance records, this data represents a gold mine of information that can be explored to optimize operations and make smarter decisions.

In Radix's view, to achieve the best results, the use of this data must be strategic and customized. Companies often prioritize technology and engineering, postponing the critical discussion of how to use data for business impact. The belief is that creating a "data lake" in the cloud with tons of data sets is the first step in the journey. Practice shows that modern architectures are instrumental to success, but knowing the problem to be solved and defining an operational model connected to business areas should come first. It is essential to design and validate the target architecture first. Implementation should be driven by business needs. The same thinking applies to governance. Value streams prioritize specific tasks and details after establishing the first set of guidelines and security boundaries.


[We can lay out as a thermometer]
•    According to a recent study by EY, 92% of energy companies are already investing in AI or planning to do so in the next two years.
•    Nearly 9 in 10 CEOs (87%) of global energy companies say Generative AI has already had a significant impact on their business.
•    And 41% say AI is inspiring their long-term strategy.

The countries leading this race are already benefiting from a significant increase in productivity in their activities. We can highlight: the United States, which also stands as a superpower in the AI world, leading various fields of development and research; China, which follows closely with ambitious plans in the area; as well as Japan, Canada, and the United Kingdom, which are part of this elite group.

In Brazil, some technology companies also stand out, such as Radix, which already operates in many of these countries, with custom AI projects and solutions for various sectors and applications.


The trend is for the digital transformation of the industry to continue at an accelerated pace. But, if the plans for the future are grand, the challenges are no smaller: companies that want to stand out must create differentiation by leveraging their own data to create unique solutions, as well as bridging the gap between technology and business to ensure that data and AI improve performance.

It is essential that industry players carefully analyze how AI fits into their current digital strategies and be prepared to leverage its potential to the fullest.

To get an idea of the size of this impact, although it is difficult to quantify the potential of AI accurately, studies by major institutes and consultancies point to some statistics:

"A 16% increase in global GDP, generating up to $13 trillion for the economy by 2030" - McKinsey Global Institute
"AI can generate $2.4 trillion in value for the energy sector by 2035, representing an 11% increase in sector revenue" - GlobalData

The potential seems limitless, doesn't it?

By making intelligent and strategic use of this technology, Radix already offers advanced AI solutions for companies worldwide. Our deliveries optimize asset integrity, improve maintenance efficiency, accelerate new product discovery, create virtual consultants, and assist and optimize production.
If you want to learn more about this groundbreaking technology and how it can leverage your business results, follow the lead of some of the world's largest companies: talk to Radix and turn your challenges into competitive advantages.


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