Surely you know ChatGPT or DALL-E, but did you know that both work thanks to Generative Artificial Intelligence? Many people know the term Artificial Intelligence, but not so much when it is followed by the word “generative”. There are many types of Artificial Intelligences, and today we want to talk about this one, one of the most widespread, so that you know it in depth, know how it works and understand what are all its uses, so you can put it into practice in your company.
What is Generative Artificial Intelligence?
Generative Artificial Intelligence or Generative AI is a branch within AI capable of generating original content based on previously supplied existing data. It is based on machine learning and deep learning methods, as well as advanced neural networks and algorithms that can learn images, texts, videos and music and then generate new and original content, difficult to distinguish from that created by a person on most occasions.
How Generative AI works
Generative AI works through machine learning, with which it is able to process a large amount of data, both visual and textual, to internalize patterns and know which elements are more likely to appear near others.
In short, a generative AI is a system trained to respond to what is asked of it in the most human-like way possible, thanks to the fact that it has learned by probability which elements should go next to others.
However, there are different training techniques to create a generative AI:
- Transformational Training: this is the one that has been used to train ChatGPT and causes this AI to work in a certain way. This training consists of ChatGPT deducing the meaning of a text to understand how different semantic elements and words are related and thus being able to establish the probability of some appearing close to others. But this is actually a pre-training phase, as the AI is then trained by humans and must interact with them.
- GAN training: the generative adversarial network or GAN is a training technique that consists of two AIs facing each other. One (the generative AI), based on probabilities derived from a large amount of data, creates images or text. And the other (called discriminative AI) must analyze whether that result is generated by an AI or is human. To win, the generative AI will do its best to fool the discriminative AI, adapting as much as possible to the results created by humans. The training ends when the generative AI systematically beats the other.
As you can see, human involvement is present in the creation of generative AIs, but most of their learning and training takes place automatically.
Benefits of generative AI
The good thing about generative AI is that it can be very positive for different teams within the same company and for different industries:
- Supporting the content creation team: known to all are the text, video and image generative AI platforms. In fact, they are the most famous. ChatGPT, Midjourney, DALL-E… All of them can be great allies to eliminate creative blocks and provide ideas.
- Medical and scientific application: capable of analyzing large amounts of data, these AIs can detect patterns that are difficult for humans to locate and support professionals in making a diagnosis.
- Boost for marketing and advertising: for the same reason, it is very interesting to use AI tools in these two areas. Thanks to the fact that they can detect consumer patterns, brands will know what consumers need in order to give it to them and increase their conversions. Not only that, they can identify trends before they happen so brands can prepare and take advantage of sales opportunities.
- Free up time for teams: by being able to simulate human-like conversations, generative AI can do more basic tasks such as answering frequently asked questions from users so that professionals have more time to deal with more complex and creative tasks.
Limits of generative AI
It must be taken into account that AI is based on content already generated by humans, so if it is trained with content from the Internet, as happens with, for example, ChatGPT, it can give untruthful, poorly contrasted and subjective information. Therefore, we should not take the information it gives as true, but as what it is, information gathered from different sources that may have errors.
On the other hand, when using Generative Artificial Intelligence to create creative content, many times we are not going to find the final result in the first interaction with the tool. We will most likely need to give it our human review, so nowadays, generative AIs focused on creative aspects serve as inspiration and guidance, but do not usually deliver the result we are looking for at the click of a button.
Uses of Generative Artificial Intelligence in the company
- Translation of texts into different languages.
- Generation of informative and creative content.
- Summary and extension of content.
- Explanation of complex tasks.
- Creation of communicative bots to serve customers 24/7.
- Creation of images and video.
- Code generation.
In short, anyone who needs to generate content, whether textual or visual, can turn to Generative AI for support.
How to build Generative Artificial Intelligence
The truth is that few companies have managed to develop Generative Artificial Intelligence models. Those that have managed to do so have millions of funds that donate resources to the cause. For example, Elon Musk’s company OpenAI, creator of ChatGPT, DALL-E and previous ChatGPT models, has billions of donors. Creating these systems takes time and money. ChatGPT-3 is estimated to have cost several million dollars and had to be trained on around 45 terabytes of textual data.
And not only that, the companies capable of bringing this type of technology to light also have some of the best engineers and computer scientists in the world. As is the case of, for example, DeepMind, a subsidiary company of Alphabet (parent company of Meta and Google) that brought out its Generative AI called Make-A-Video, a tool capable of generating videos from text.
So, as you can imagine, most companies can’t afford to create a Generative AI on their own and have to rely on tools created by the type of companies named above. Fortunately, ChatGPT is an open-source platform that anyone can benefit from, although most of them require payment.
The near-term future of generative AI
The big question is, will generative AI replace the work of some professionals? That is something that cannot be known, but what is certain is that, little by little, Generative AI tools will become an indispensable tool within many sectors and many areas of the company.
In the event that the replacement takes place, there are tasks that AI cannot perform and that humans will have to continue to do, tasks that, by the way, are very important. In that sense, to deal with that replacement in the best possible way, as individuals and as companies, there are many things we can do:
- Do not stop learning about technology: technology is advancing by leaps and bounds and as a professional it is crucial to keep updated in order to be able to adequately face the different challenges that will arise. Learning about data science, AI and machine learning is going to be crucial, as this technology is going to be more and more present and you need to know how to work with it.
- Train soft skills: this encompasses all those social and communication skills that allow the person to move through the work environment in an adequate manner. An AI cannot replace them and will be the true value of a professional.
- Knowing the appropriate use of AI: it is important to be informed about the limits and risks involved in AI in order to know how to use them responsibly and ethically.
- Enhancing innovation and creativity: AIs are not yet capable of generating new concepts or ideas, as they copy existing ones. Therefore, these two aspects will also be great values that a person will be able to contribute as a professional.
If you have not yet done so, we encourage you to include Generative Artificial Intelligence in some areas of your company so that you are not left behind. You will see that they can be a great support for your team, being able to streamline processes and improve the final results. Don’t be reluctant to new technologies, the real challenge lies in knowing how to use them properly, but refusing to use them will only lead to your competitors taking advantage of them.