Perhaps one of the most frequent scientific terms in recent times is the term artificial intelligence, after the emergence of the latest version of the "ChatGPT" program, which specializes in creating written texts that simulate human texts with an unprecedented degree of accuracy and at high speed as well.

In just one month, the Internet covered texts written through this program, which led to the issuance of entire books written or co-authored by the program, and it was also added as a co-author in one of the published scientific researches.

This drew everyone's attention to the amazing progress achieved by artificial intelligence and simulation techniques and models and their applications in various fields.

In fact, artificial intelligence works effectively in various fields around us, including many applications in data science, self-driving cars, diagnosis and treatment of diseases, and many research areas in biology, chemistry, pharmacology, oncology, computer games, design programs, and others.

Artificial intelligence models carry out their tasks without prior instructions, but based on their understanding of the situation and their analysis of the data (Shutterstock)

artificial intelligence models

Computer programs usually operate according to pre-instructed instructions fed to them by their programmers.

Based on these instructions, the programs make their decisions and carry out the tasks assigned to them.

Most of the programs used since the invention of the computer until today work in this way.

On the other hand, attempts began in the middle of the last century to develop computer intelligence that allows the programs that use it to carry out tasks and make decisions without prior instructions, but based on their understanding of the situation and their analysis of the available data, which is called artificial intelligence models.

These models have evolved slowly and their development is directly proportional to the superior capabilities of modern computers and the steady increase in the ability of humans to produce and collect data and make it available in central places (such as Internet servers and cloud computers), where it can be accessed and analyzed using new artificial intelligence models.

This is because creating new AI models depends on using a sufficient amount of data in two primary phases: training and testing.

Using artificial intelligence, the three-dimensional structure of more than 200 million proteins was derived (Shutterstock)

Create artificial intelligence models

In the training phase, the bulk of the data (usually 70-80%) is used to train the model to understand the structure and nature of the data so that it alone can distinguish it and know its components.

In the testing phase, the remaining part of the data is used to test the performance of the new model, and will it be able to analyze the data correctly based on the previous training?

For example, in the case of creating a model that helps diagnose tumors from diagnostic radiographs, the model is trained by feeding it a large amount of radiographs of healthy and sick people to learn how the x-ray of a healthy person looks compared to a patient.

In the next stage, the model is tested by giving it a number of x-rays and measuring the percentage of its recognition of x-rays of healthy people compared to patients correctly.

The main advantage of artificial intelligence models compared to regular computer programs is their ability to improve their performance by themselves or through increased training and data diversification.

In the previous example, if the performance of the model is not sufficient for a reliable diagnosis, the efficiency of the model can be raised by increasing training and increasing and diversifying the data used in training, thus obtaining better performance.

Biomimetic models based on artificial intelligence also help in agriculture and improve food quality (Shutterstock)

simulation models

Another section of computer programs is concerned with making models that simulate reality to study various phenomena.

These models were widely used in engineering, physical and astronomical applications.

However, with the widespread spread of computers, simulation models began to be developed in all fields.

During the Corona epidemic, we all followed expectations of the spread or recession of the epidemic based on the results of epidemiological models. Models were also created that simulate virus proteins and vaccines and how they relate together in the original virus and in its mutants to measure the effectiveness of vaccines with new mutants.

Simulation models rely on mathematical equations and statistical tests to perform simulations and verify the validity of model results, respectively.

The computer is used to create such models, feed them with the necessary data, test their outputs, and draw the results in easy-to-understand ways that are able to convey the meaning of the results to the users of the form.

Artificial intelligence based simulation models

Artificial intelligence and simulation models are among the latest and most useful technologies that are being used today.

Hence, it was only natural that they were combined together to create complementary frameworks that utilize the advantages of both technologies.

Recently, a group of applications have emerged that integrate the two technologies together to achieve exceptional performance, and thus achieve new unprecedented results.

In 2021, DeepMind, a subsidiary of Google, presented a simulation model for predicting the 3D structure of proteins, based on an artificial intelligence technology called AlphaFold.

The model has shown unprecedented accuracy in predicting the three-dimensional structure of the protein, close to the accuracy of laboratory experiments, which made it the most used model in studying the structure of proteins from the time of its publication until now.

Artificial intelligence and simulation models are among the latest and most useful and used technologies at the present time (websites)

The Google Scholar database for research shows that the research on “Alpha Go” published in the journal “Nature” has been used as a reference for more than 8,100 research in various fields since it was published in 2021.

Because of its high accuracy, many research agencies have used it extensively to achieve results that were previously considered impossible or very difficult.

For example, the European Bioinformatics Institute (EBI) of the European Molecular Biology Laboratory (EMBL) collaborated with DeepMind, the owner of the Alphafold model, to predict and infer the three-dimensional structure of more than 200 million known proteins in various organisms. Available to everyone in the AlphaFold Protein Synthesis Database.

One of the most recent applications is the use of "Alphafold" in finding a new drug for the treatment of liver cancer.

Where a research group from China, Canada and the United States has created a complete platform for drug design called Pharma.AI and is based on the "Alphafold" model along with some other artificial intelligence models.

The group was able to find the new drug using this platform.

Recent research also shows the tendency to use artificial intelligence models such as "Alphafold" and others to create biomimetic models that are used in agriculture, improve food quality, and find alternative sources of proteins that are more abundant and provide more healthy options.

Artificial intelligence and biomimicry, then, are two promising technologies that can be relied upon to solve major problems in the fields of health, medicine, and food. The world has made remarkable progress with them in recent years, but they are still in development stages, and it is expected that they will become more mature in the next few years.