La Generative AI It is perhaps the best known of all that exist due, probably, to the famous macro chatbot of Open AI, Chat GPT. It is a kind of IA capable of creating new content. It bases its operation on the Deep learning (deep machine learning). But what is generative artificial intelligence, what it is and how it works.
What is Deep Learning exactly?
This type of learning has been used since 2006 and since its inception, it has tried to "emulate" the natural learning of a brain. Nowadays it is essential for the development of systems IA personalized. It continues to have significant advances in each of its fields of application. One of them (we return to the main topic) is the IAG.
From the beginning as a research project, until now, which is a company specialized in robotic products for rehabilitation, Inrobics has had a constant in the development of technology, and the use of the Artificial Intelligence (AI). Our developers bring the robots through it. But now, we have expanded the depth of interaction thanks to the Generative Artificial Intelligence (IAG), the protagonist of this post. We will tell you more about this at the end…
If you want to know more about IAG, how it works y what utilities has, keep reading…
What is Generative Artificial Intelligence? How does it work?
The operation of the IAG It involves collecting thousands and thousands of data/information that the system (through algorithms) uses to generate ideas, also adding all the information that users provide to the system. This helps the machine to be more precise. This is how it is achieved imitate human thought. Generate ideas as a brain would do and that is why, currently, it has so many Ethical and safety implications. It enriches any field (personal or professional) and helps to give depth and personality to machines like ours. robots.
Models IA corresponding to this category manage to generate new content because they learn and analyze the patterns or structure of previously entered data and create content with a similar structure. Therefore, the way of expressing oneself in a Chat GPT or the images created from instructions that we send (these texts that we introduce are called promps) seem so realistic to us.
One of the peculiarities of this type of IA is the level of customization that we seek with its use. The developers introduce different data layers specific for each case of IAGTo find an experience adapted to our needs we only have to correctly indicate what we want, the programs IAG respond to our requirements.
Adversarial generative networks or generative antagonistic networks, what are they?
Another of the peculiarities in the functioning of IAG is the use of algorithms called generative adversarial networks, also known as GANs (it sounds like a technical jargon, but we promise it's easy to understand). Currently, most of the applications we use in our daily lives belong to generative artificial intelligences of unsupervised learning. The GANs They are, neither more nor less, than two neural networks opposites competing in a zero-sum game.
But what are they? zero sum games?
They are a category of games in which the winnings of one player are balanced by the losses of another. That is, the total losses and winnings of the game will always be equal to zero, building a perfect balance.
So, back to the GANs, the first network, the generative, produces the first data as requested, while the second network, the discriminative identifies and analyses the material produced by the first and decides whether it conforms to what was indicated or whether it belongs to the set of data that was previously entered. These networks are the key to the customization and the adequacy that the applications of IAG They give the instructions we ask of them, whether in text, video, audio or image format, and they are able to do so instantly and without any human supervision.
This process, although in our eyes it is instantaneous, has thousands of clashes between generative network y discriminative networkOne provides material, the other indicates the degree of correctness of this material (with respect to the data stored from previous training), generating a new attempt by the first, and so on repeatedly. Each time, the generative network is learning from its mistakes, becoming more precise and faster at getting it right.
These are some sectors where the use of this technology is most relevant:
The media noise surrounding the Artificial Intelligence in general, and more specifically, around the IAG It is impressive, directly proportional to the growing use of tools that apply this technology in thousands of areas, both in the personal and professional environment.
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Technology and Software:
La IAG is used for generate code, facilitate the user interface design and improve efficiency in the Development of autonomous algorithmsIt is an excellent resource to speed up the creation processes of programmers, as well as correct their work.
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Health:
This is a sector that we have talked about at length in our blog, as well as the most common applications of the IA and the use that they give it clinical professionals. Some of the most notable utilities are the assistance in medical diagnosis, generate medical reports automatically, help in the biomedical research Through the creation of predictive models, comparison and image contrast, personalized medicine (The IA It analyses the specific data of each patient, such as genetics, medical history and lifestyle, providing a new vision for the specialist to interpret at his/her discretion. virtual health assistants o augmented reality in surgery. Among many other uses.
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Art and creativity:
In this area, it is used for the music generation, graphic design, visual art y Creative writing, offering new perspectives and endless artistic possibilities. This is an area that generates much controversy because, with the advance in precision of the IA, it is almost impossible to distinguish works and writings created by human hand, or those that have been created artificially. In this regard, the responsibility of professionals to use these applications as work tools to generate ideas and not have to start from scratch. An idea, a text or a musical piece created by IA It can be infinitely improved or adaptable, and can even inspire the creation of a work 100% produced, composed or written by a human author.
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Advertising and marketing:
In this case, the IAG It is used for personalize advertising content. FOR analyze market data and predict trends. Create ads more effective and, in general, to speed up the entire creation and analysis process.
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Human Resources:
You may have heard it before and some may think it is a myth, but the IAG It is applied in the profile selection for vacancies in companies. Again, under the supervision of professionals or for the automated evaluation of candidates, at least initially, where a series of filters are applied to discard profiles and reduce the candidates that are subsequently reviewed by the selection teams.
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Data Science:
This is where the training data we talked about previously comes from. The data that is provided to the generative artificial intelligence to make them more precise. It may sound a bit convoluted, but on many occasions, IAG already developed help to generate synthetic data that are used in training machine learning models, facilitating the development and testing of algorithms.
Applications of IAG
Among the most common applications of IAG are: deed (in all its variants, styles and intonations), generation of images, generation of music y video, sound pieces, generation of audio o synthetic voice (as in the case of narrations and automatic readings), simulation y Virtual Reality (VR), data translation and interpretation, among others.
The BOMBSHELL, Generative Artificial Intelligence arrives Inrobics
Our robots have their own voice
This is where we drop the bomb of this article on you. The intention of specifying what the IAG, it was not just about informing, we also want to advance that these months, our development team has been working on the introduction of this technology in our products (in our robots!). This implies robots with greater complexity and a more developed personality, if possible.
With this integration, Inrobics takes a step towards adapting the most coveted technologies. Towards a robotics infinitely more personalized y Engineering to human relations. This evolution allows us to bring the human-robot interaction to a whole new level. All this, taking into account that our robots already have an acquired personality and are now capable of interacting on a verbal level.
La vision of Inrobics is about creating products that impact people's quality of life, building a more inclusive future. This update brings us closer to that goal.
We invite you to learn more about us. You can meet our team or get in touch for any comments, interests or suggestions through our formOf course, if you want to know our solutions first hand, you can request a demo, It's free!
