When Biotechnology adopts Artificial Intelligence | Adamas University

Artificial Intelligence, Biotechnology

When Biotechnology adopts Artificial Intelligence

Artificial Intelligence (AI) in Biotechnology adding great values as it explores more applications, broadening its field in a more transformative way. Famous stories regarding the use of Artificial Intelligence goes like this that after the creation of one of the first autonomous robots it was asked a question “Do you know God” and it promptly replied “I am God” and this goes on to show the world how powerful and revolutionary it’s role will be in reshaping the upcoming future of this entire planet.

Introduction of AI and Machine Learning – these two rather synonymous technologies have could change our view towards the use of modern technologies. Even the greatest minds, like Stephen Hawking and Elon Musk, used to acknowledge its unlimited power beyond anyone’s imagination and feared that it could have proven dangerous if misused. There is a possibility that it may come into the picture in the upcoming decades, but today we are not anywhere close to that yet. The AI which is making headlines these days is a “Narrow Artificial Intelligence”, a rather limited functioning machine “intelligence” which can solve only a few specific assignments or a group of tasks. Already AI showed its efficiency in providing meaningful real-world solutions on those narrow tasks, like language processing, image recognition of various images, developing self-driving cars, and in drug developments more specifically in the field of biotechnology.

The usefulness of AI and machine learning proved its ability to find and analyses hidden and unintuitive patterns from big data sets in quick time, which proves impossible in ways that human achieve. AI represents a significant potential to have a transformative impact on many industries, especially the pharma and biotech companies.

AI’s adoption of machine learning (ML) helps it to solve complex problems through its systematic testing. Instead of coding what it needs to know, developers create AI to use the ability to learn and analyze data – resulting in innovative solutions that are virtually impossible to reach through human ability alone.

With the amount of data available to the biotechnology scientists worldwide, we may still find ourselves while asking the big questions, but AI programs are finding the solutions already. Nowadays most of the biotechnology companies are comprehending the value that AI can bring to their entire field in the form of – · Expanding accessibility · Crucial predictions · Effective & efficient decision-making · Cost-effectiveness Biotechnology can be categorized into a few types like · Medical biotechnology, · Agricultural biotechnology · Animal biotechnology, · Industrial biotechnology · Bioinformatics.

Now we see the functions of AI in different domains of Biotechnology: Medical biotechnology Medical biotechnology uses living cells for the improvement of human health by producing various drugs and antibiotics. It also engages in the study of DNA and genetical manipulation of the cells to increase the production of desirable characteristics.

AI & Machine Learning are extensively applied in drug discovery. Machine Learning is widely used in diagnosing diseases because it uses the actual results to improve the diagnostic tests, that is to say, the more diagnostic test runs, the more accurate results can be obtained. Apart from the above-mentioned applications, these technologies are widely used in radiology gene editing, etc.

Machine learning and AI are significantly used in the diagnosis of cancer. With powerful companies like Quest Diagnostics, machine learning makes the identification of cancer more accurate. Agricultural biotechnology It helps to develop genetically modified plants to increase crop yields or introduce new characteristics to the existing plants.

It involves conventional plant breeding, molecular breeding, genetic engineering of plants, micro-propagation, and tissue culture, which forces the biotechnology companies to accept AI & Machine Learning methods to develop autonomous robots that can improve agricultural tasks like crops harvesting at a much faster rate.

Machine Learning algorithms help in tracking and predicting various environmental changes like the weather changes that impact the crop yield. Animal biotechnology applies various techniques of molecular biology to produce genetically modified animal species with improved sustainability for the sake of pharmaceutical, agricultural, and industrial use. Artificial Breeding of animals is another domain where AI models offer valuable insights. Artificial breeding of animals gives the advantage of inserting the selective genes in them, which provides the leverage of developing animals with the most desirable characteristics and becomes a very prevalent practice in food biotech industries such as milk industries, meat industries, etc. This practice is applied to the molecular level where desired genetic characteristics of the animals were selected & inserted in breeding such animals by using AI.

Machine Learning and AI aids in understanding the genomics and helps the experts in predicting the genetic expression. Industrial biotechnology hovers around making biopolymer substitutes, inventions in areas like vehicle accessories, fibers, fuels, chemicals, and their production process.

Machine Learning and AI analyzes the machines, enhance the efficiency of equipment, etc. to improve production and produce a better quality product. Bioinformatics helps the acquisition, storage, processing, distribution, analysis, and interpretation of and biological and biochemical information with the help of mathematical, computer science tools to understand the biological significance of a variety of data.

Artificial Intelligence and Biotechnology are by themselves two of the most promising and profitable fields in the future economy. This makes financial analysts believe that the economic impact will increase exponentially if these two sectors are combined. Artificial intelligence (AI) and biotechnology have the potential to improve and extend our lifestyles and life expectancy in a cost-effectiveness way.

Biotechnology has improved 10 times more every year in terms of cost-benefit. And one cannot deny the efficient involvement of AI in this. The cost of decoding the human genome has reduced from $3 billion in 2002 to around $1,000 recently; a painstaking process that took more than a month, little more than a decade ago and now it can be finished in less than sixty minutes.

 

Based on current developments, it is estimated that the contribution of Artificial Intelligence globally will reach $15.8 trillion by 2030 – more than the shared yield of China and India in today’s world. So, it is the absolute need to this time that more and more importance is given to this domain where the culmination of AI & Biotechnology is given utmost priority.

In Adamas University, students of BSc and B.Tech Biotech courses at the school of Life Science and Biotechnology, get to know both the subjects: Artificial Intelligence and modern technological developments in the field of Biology in a perfect ratio, which further broadens their knowledge base and increase their chances of getting jobs in various biotech industries. With a huge panel of experts both from Engineering fraternity and Biotechnology, Microbiology and Biochemistry fields, and modern and sophisticated Engineering and Biology laboratories, students from this course will surely start a leap ahead in their future career opportunities. Several professional clubs like Adamas Robotics club, Adamas Biotechnology club provide them to test their theoretical knowledge on hand and also to showcase their talents at the global stages through various competitions under the banner of Adamas University. Biotechnology courses at the school of Life Science and Biotechnology at Adamas University help the young and inquisitive minds from all around the world to groom, induce job-preparedness, and motivates them to become leaders for the Biotech industries in the future post-COVID era.

 

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