The use of Artificial Intelligence is making a lot of noise thanks to conversational chatbots like ChatGPT and Bard, but it has been with us for a long time, more precisely, since 1950. Speaking about the medical sector, the use of generative AI has reduced discovery times of medications from 3 - 6 years to just a few months, not to mention reduced costs. We tell you more information and some cases that have happened recently.
The use of AI in everyday life has been around for some time. Some examples that you have surely used are:
These are just some examples of how artificial intelligence is used daily, but now let's discuss the following evolution: generative AI.
Generative AI is a branch of artificial intelligence that focuses on content generation. It can be used to create text, synthetic data, product images (or anything), sentiment analysis, product ideas, and many more things.
2023 started with a lot of boom in the topic of conversational chatbots, this AI that generates text but makes it conversational. That is, it understands the concept of conversation and can go deeper into it.
Since the launch of ChatGPT, a large number of companies have begun to emerge to develop AI, and their skills are going beyond what a conversational chat is:
Now that we understand this tool's scope, the main part of this blog comes.
OpenAI's ChatGPT and Microsoft are ahead in the AI race vs Google's Bard, discover their story here.
Generative AI in the Medical sector
According to Brian Burke of Gartner, we are starting from 0% in 2023, and by 2025, more than 30% of new medicines will be discovered with generative AI techniques. Emphasizing that the health sector is just one of its many uses in different industries.
Recently, Insilico Medicina, a multinational biotechnology company that uses AI in its processes, and the University of Toronto Acceleration Consortium designed a treatment for liver cancer in just one month!
This was thanks to Pharma.AI, a platform equipped with powerful biocomputational and generative chemistry engines that allow thousands of potential drug combinations to be tested in a very short time. Before the use of this tool, this process would have taken years and a lot of trial and error. But with the use of AI, success was achieved in just four weeks.
This is just beginning, but in a few years—really few—generative AI will achieve more accurate diagnoses and more efficient solutions.