In today’s world, artificial intelligence technology has become a game-changer when it comes to its immense applications in the field of science. Scientists are relying on machine learning algorithms to process data and gain valuable insights from a massive volume of data sets.
They are designing neural networks, which is a subset of machine learning that uses a structure inspired by the human brain to find patterns in the data to suggest new hypotheses rather than relying on human assumptions. This has led to the immense speed up of scientific processes, ultimately accelerating scientific research and discoveries.
Therefore, if the field of artificial intelligence intrigues you, then enrolling in an AI and ML course can help you learn the basic and advanced concepts such as machine learning, deep learning, NLP, computer vision, reinforcement learning, generative AI, prompt engineering, etc., which can expedite your journey into the AI realm.
1. Processing information faster
AI’s machine learning algorithms and deep learning techniques are becoming indispensable tools for scientists to collect, process, and analyze data to determine patterns in massive volumes of data sets. Scientists are using AI to spot patterns and connections in data sets that humans would overlook.
In fact, AI has already generated hypotheses that human scientists have not considered. Going by the trend, AI will soon be used to find answers to never-before-answered questions like how life first evolved, the expansion of our universe, and the true nature of chaos.
Many of these questions remain unanswered due to their complexity or lack of data. The ability of AI to analyze massive amounts of data, find patterns, and make connections will be critical to answering these profound questions.
2. Learning about the universe with AI
Astronomers have to swift through massive volumes of data produced by radio telescopes to learn about the universe, which is a mammoth task. However, with the help of AI, Astronomers are now able to process enormous data sets and uncover new information about the universe. Identifying the multitude of faint galaxies hidden in the background of images was one of the first applications of AI in astronomy.
Earlier, in an astronomical image, background radiation, light from other sources, or the blackness of space make up about 99% of the pixels, and the faint shapes of galaxies are present in just 1% of them. By the 2010s, with the advancement in deep learning techniques and neural networks, astronomers started classifying galaxies using neural networks. Nowadays, the algorithms can classify galaxies with 98 percent accuracy.
AI has also been used significantly in the discovery of exoplanets. There is a decrease in the star’s light when a planet passes in front of it. Astronomers have found most of the 5300 known exoplanets by measuring this dip, and AI systems have detected exoplanet signals with 96% accuracy. This method has been used by teams to find new exoplanets, understand more about the parent stars that shaped the Milky Way’s formation and expansion, and identify potential gravitational wave signatures.
3. AI-enabled drug development
AI has the potential to revolutionize the process of drug development and expedite the discovery of life-saving drugs. With the help of AI, researchers and scientists are able to make the process of drug development efficient and faster. For example, AlphaFold, a DeepMind AI predicted the shape of every known protein with utmost accuracy, which included protein structures of 330,000 proteins. This included all 20,000 proteins found in the human genome.
This was considered a milestone in the drug development domain as it was a process that took years of lab work. Since then, the AlphaFold Protein Structure Database has expanded to encompass over 200 million proteins, almost all of which have been cataloged and are known to science. DeepMind AI was also used by researchers to create synthetic syringes that inject tumor-killing compounds directly into cells. The process, which normally takes years, was completed in 46 days.
Exscientia, a global pharma tech company, uses AI to develop precision-engineered drugs that are aimed at reaching human clinical trials faster, which ultimately benefits the patients.
Another significant breakthrough occurred in January 2023, when AbSci used zero-shot generative AI to be the first organization to create and validate de novo antibodies in silico. The milestone achievement can reduce the time it takes to develop new drugs, thus lowering the costs of developing drugs, which ultimately leads to lower treatment costs for patients.
Antibodies are traditionally created using pre-existing antibodies or templates, which can be time-consuming. AI-designed antibodies can reduce drug-discovery times by 50%, from up to 6 years to just 18 to 24 months.
We can expect AI to play a larger role in drug development as it becomes more sophisticated. With the help of AI, the traditional drug discovery process, which was time-consuming and expensive, can have shortened development cycles and can reach clinical trials much more quickly. Also, to determine efficacy and toxicity, clinical trials could be shortened, and molecular simulations could reduce the need for animal testing. This could be useful in identifying cancer targets and developing new drugs.
4. Be anywhere, anytime
Consider being present in a science lab without being physically present. This could become a reality thanks to virtual reality and artificial intelligence. In virtual reality, scientists could conduct experiments and manipulate digital models of molecules or materials, all while monitoring the results in real-time.
On July 27th, researchers from The Western Institute for Space Exploration (Western Space) in Ontario, Canada, completed the world’s first international holographic teleportation. The holographic teleportation, or Holoport, is a combination of hologram and teleport, which is essentially a technology where a hologram of a person or an object is transmitted instantaneously to another location.
The technology creates a hologram of a subject using a special camera, which is then received by another person in a distant location using a HoloLens, or essentially a VR set. With the help of the HoloLens, both parties can then virtually interact with each other.
Holoport-like technologies might gain immense application in the future, leading to many scientific discoveries by facilitating instantaneous global collaboration between scientists. According to NASA, Holoport technology can greatly improve future missions into deep space, where it can be used to provide better and more personal communication between astronauts and people on Earth.
Also, this technology is being explored in remote healthcare, where it can be used to provide long-distance healthcare solutions. This will be a groundbreaking application, especially in the wake of the pandemic. Scientists can watch an experiment in real-time from across the globe, or they could beam in holographic images of lab apparatus.
This might result in increased cross-border cooperation, quicker scientific discoveries, and a scientific community that uses less carbon.
In conclusion, AI can pave the way for many exciting scientific discoveries and alter the course of history by addressing issues related to vaccines, drugs, climate change, and even the discovery of new compounds that can degrade plastics.