From the agricultural to the interpretive AI, the technology that will put everything upside down

To the hatching of the generative AI approximately three years ago the “boom” of the agriculture has followedthat goes one step further and is not only capable of generating content with absolutely very pasty content based on simple “prompts” of text but also of executing tasks autonomously (and with little supervision by humans of flesh and blood).

However, and even the agricultural AI is undoubtedly a vast myriad opportunities for companies (and can, example, assume the construction of website page with a lot of speed), Bruces de Bruces (such as generative AI) with not a few limitations.

The workflows and the results placed on the table by the agricultural AI remain too much at the expense of the variations when they are executed in large organizations with a large volume of processes that must necessarily be anchored in predictability and reliability.

For this reason, The true revolution in the universe of artificial intelligence is not housed in the bowels of the agricultural AI but in those of the interpretive AIwhich will really bring a revolution (absolutely seismic) in companies.

Unlike agricultural AI, The interpretive AI is able to process complex and unstructured information and interpret it as predictable as defined with the same technological infrastructure. And not just that. The interpretive AI allows organizations to execute complex processes without being necessary human intervention in each of the steps that integrate such processes, explains John Lester in an article for Fast Company.

The interpretive the AI ​​promises to be much more useful for companies than the generative and agricultural AI

Although its development is still in a fairly embryonic phase, the interpretive AI is already applied in some areas. And some doctors are already using this technology to listen to the conversations held with their patients and automatically fill their clinical records to facilitate the monitoring of treatments and ultimately make billing.

In addition, in the near future the interpretive AI could help determine the cause of traffic accidents based on police reports written in multiple formats or process videos recorded from the screen of a laptop while someone makes a presentation to facilitate their teammates automatic updates on the projects in which they are involved.

The interpretive AI could lead to an increase in productivity between 20% and 40% in large companies. However, to get all their juice to this technology, organizations must necessarily involve the use of the interpretive AI to all their departments, fly the flag of experimentation and be willing to change roots and entrenched processes that could ultimately slow down their adoption. Even when the interpretive AI will undoubtedly overcome obstacles in any way negligible within companies, the benefits that it will bring under the arm will be absolutely colossal.

Economic growth is largely at the expense of standardization and the process scale to make them faster, cheaper and more reliable. This was done possible by assembly chains and a similar revolution will also be spoiled by the interpretive AI.

The generative AI has failure in general terms when giving Alas to automation. Many companies have supported, for example, in this technology to reduce the time that the Human Resources Department enshrines employees’ consultations in relation to internal policies. However, in this context the generative AI still needs human review, so it improves in terms of productivity remains quite modest and being largely weighed by unpredictability.

On the other hand, the agricultural AI constitutes an evolution with respect to the generative AI because it allows to develop and execute step by step plans, but it also needs the assistance of people of flesh and blood to be truly productive. AND Its results remain variable.

The interpretive AI promises to carry automation in organizations in volandas

Instead, The interpretive AI is able to process human language taking into account all its nuances And it is not limited only to tasks that are easy to quantify with data but also extend its “super powers” to many other activities.

With the aid of The interpretive AI, which will allow the number of average controls to coordinate activities within organizations ostensiblycompanies can evaluate, for example, as simple as reliably the tone and quality of the interactions of their employees with customers and also monitor the policies in force in the workplace.

The generative AI will also provide companies with the possibility of understanding aspects as opaque as operatively crucial in business terms such as codes and data inherited from decades that often constitute an important obstacle when implementing new technologies within organizations.

In any case, it should be noted that the interpretive AI, the agricultural and generative AI are not mutually exclusive and can perfectly be implemented simultaneously. The interpretive AI sounds perhaps on the less spectacular role than the agricultural and generative the AI, but It potentially has a seismic impact when it comes to getting economic revenue to artificial intelligence within companies.