Great Expectations and great razzmatazz: a brief look at what the near future of AI holds for us.

Artificial Intelligence in 2023: a new hope of efficiency for companies?

We are witnessing a real flashback for the theme of Artificial Intelligence: after a long “AI winter” today we find ourselves in the blossoming of a luxuriant spring.

In the last decade AI has been considered pure avant-garde and retained within the R&D departments of companies, often as a mere exercise in style. However, between the end of 2022 and the beginning of 2023 a new vision is catching on: AI is emerging as a powerful yet multifaceted tool.

In fact, 2022 was a year of incredible growth for Artificial Intelligence.

A recent Gartner survey reveals that 80% of executives believe automation can be applied to any business decision, and a third of companies already apply AI to their business units.

This means a significant transformation of processes: one out of two experimental AI projects (54% of the total) becomes operational.

Therefore, organizations of any sector and size have begun to budget for AI-based activities, turning to partners specialized in the use of Artificial Intelligence.

In a scenario where innovation and the desire to apply new technologies are a big hype, where companies need to make savings more than ever, AI is actually one of the biggest hopes  of efficiency we have.

AI for efficiency

So, if everyone is talking about Artificial Intelligence today, what is it really for? To ensure that AI is truly functional to the needs of a company, first of all we need to understand and interpret its very context.

Whether it’s industrial or managerial problems faced by any company, the complexity of phenomena is the field in which AI can – and should – test and measure itself.

Applications to the world of manufacturing and production industry are constantly growing and spreading. However, to take us into the world of Industry 5.0 – an increasingly collaborative space between men and machines – technologies should be up to this change of pace, with safer and more sustainable solutions, focusing on the environment and the well-being of the people.

In this sense, Machine Learning and Model Serving technologies are the most powerful tools at our disposal to give us a more complete, precise and simultaneous view of the phenomena, analyzing the available data and adding the missing ones.

From this point of view, the ability of AI Models to process an ever-increasing amount of information, data and images is essential, especially when they are related to the processes and systems underlying the manufacture of products and the provision of services in general.

In these years, while we undergo so many transformations and transitions – ecological, economic, social – saving resources, time and space is an imperative that unites companies of all sizes and sectors.

Datrix has always dealt with sustainable AI approaches for business growth, and with Aramix – the new tech player born in February from the combined experiences of 3rdPlace and Aramis – it takes one step further towards efficiency, the real keystone in every area of ​​the current scenario.

AI for sustainability

While ESG criteria are becoming more and more stringent for all companies, investors are also much more sensitive to sustainability issues related to the companies they choose to invest in.  More sophisticated financial instruments are rising, such as thematic investing, for example.

Climate-conscious companies, well-managed diversity and inclusion, LGBTQ+ rights activists: these are just a few examples of the type of companies people prefer to invest in nowadays, in a current financial scenario where the impact of individual choices is increasingly pervasive.

The ability to monitor ESG-themed news and exposures in real time is one of the most irreplaceable advantages of Artificial Intelligence applied in Finance.

In turn, companies are now able to fully evaluate their corporate sustainability commitments, combining traditional internal data with alternative external data, measuring the effective perception of stakeholders on these complex, crucial issues.

AI for everyone?

In these first months of 2023 there has been a lot of talk about generative models: those technologies capable of generating original texts and images starting from discursive instructions. The ChatGPT case which quickly gained popularity for its versatility and unsettling ease of use.

ChatGPT is a large language model developed by OpenAI that plays an important role in advancing the field of artificial intelligence (AI). As a natural language processing (NLP) model, ChatGPT is trained to understand and respond to natural language inputs in a way that simulates human-like conversation.

The main role of ChatGPT and similar AI models is to improve our ability to communicate with machines.

However, the use of AI models like ChatGPT also raises important ethical questions. As these models become more advanced, there is a risk that they could be used to create fake news or manipulate public opinion. Additionally, there are concerns about the potential impact of AI on jobs and the economy, as machines become increasingly capable of performing tasks that were previously done by humans.

Despite these challenges, the development of AI models like ChatGPT is an important step forward in our quest to create more intelligent machines. As we continue to develop and refine these models, we have the potential to create new technologies and systems that will transform our world in ways we can only imagine.

This paragraph that you have just read, for example, was written by ChatGPT.

In terms of formal rendering, an essay like this one – generic enough but  fairly well constructed – is in fact indistinguishable from a text written by a human being. This is impressive, and intriguing in its implications.

After all, any visual or verbal language can be traced back to a combinatorial calculation of its elements, and who can do it faster than a machine?

Yet the relevance and quality of the output depends proportionally on the quality of the input. If Artificial Intelligence becomes open source, within everyone’s reach, it is crucial to carry out a specific education on how to interrogate it, to bring out its best potential.

AI will be able to provide us with ever more accurate and relevant answers, there is no doubt about it, but the right questions always belong to human beings.

So here then is the last hope for 2023: a real democratization of Artificial Intelligence.

For a use of AI that is forward-looking today and will be essential in the years to come, for companies of any size, and which starts from training, shared skills, ethics, attention to privacy and transparency .