Global Journal of Computer Science and Technology, D: Neural & Artificial Intelligence, Volume 23 Issue 2

AI can automatically code workers' compensation claims. Virtual reality systems with AI capabilities can improve danger recognition training. Accident near-misses, which are crucial in lowering accident rates but frequently go unreported, can be detected by AI more effectively. 24. Biochemistry : It was used to provide the likely structures of all proteins in the human body and all proteins known to science (more than 200 million). AlphaFold two can determine the 3D structure of a (folded) protein in hours as opposed to the months required by older automated approaches. 25. Chemistry and Biology: Drug design has made use of machine learning. Additionally, it has been used to investigate huge chemical/reaction spaces and predict molecular attributes. The origins of life on Earth, drug syntheses, and developing pathways for recycling 200 industrial waste chemicals into effective drugs and agrochemicals (chemical synthesis design) have all been investigated using computer-planned syntheses via computational reaction networks. This platform combines "computational synthesis with AI algorithms to predict molecular properties." The subject of the investigation has been which forms of computer-aided chemistry would benefit from machine learning. "Drug discovery and development, drug repurposing, improving pharmaceutical productivity, and clinical trials" are possible uses. Proteins with predetermined functional locations have been designed using it. In a 46-day process, a medication that inhibits the enzymes of the DDR1 gene has been designed, synthesized, and tested using databases. One explanation for the high-quality datasets that made it possible for these results is the role of DDR1 in fibrosis and cancer. Machine learning has a variety of uses in deciphering human biology, such as assisting the mang of gene expression patterns to functional activation patterns or locating functional DNA motifs. In genetic research, it is frequently employed. Machine learning is also used in materials science, disease biology, nanotechnology (including bio nanotechnology and nanostructured materials), and synthetic biology. 26. Digital Ghosts: Roboticist Hans Moravec suggested that a future supercomputer could revive long-dead minds using the knowledge that still existed in his book 1988 Mind Children. Examples of this kind of data include recollections, film clips, social media interactions, personality traits that have been modeled, personal favorites, lists of tasks and notes, medical records, and genetic data. The dead will be able to be digitally recreated when Ray Kurzweil's theory of singularity is realized, according to the American inventor and futurist. This is one method for implementing the idea of digital immortality, also known as the resurrection of the dead as "digital ghosts" or "digital avatars." Virtual personas could "assist in knowledge capture, retention, distribution, access, and use" in knowledge management. Post-mortem privacy is a concern, as is the possible use of individualized digital twins and related systems by big data companies and marketers. 27. Astronomy, space activities, and ufology : Artificial intelligence is used in astronomy to analyze the ever- growing amounts of available data and applications, primarily for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights," such as finding exoplanets, predicting solar activity, and differentiating between signals and instrumental effects in gravitational wave astronomy. It could also be utilized for space operations like exploration, which includes data processing from space missions, real-time scientific decision-making for spacecraft, avoiding space junk, and more autonomous operations. Machine learning has been applied in the search for extraterrestrial intelligence (SETI) to find artificially created electromagnetic waves in data sources, including real-time observations and other techno signatures, such as via anomaly detection. Machine learning is used in ufology by the SkyCAM-5 projects, led by Prof. HakanKayal, and the Galileo Project, led by Prof. Avi Loeb, to identify and categorize unusual types of UFOs. 'Oumuamua-like interstellar objects and naturally occurring artificial satellites are potential extraterrestrial technology indicators that the Galileo Project hopes to find using AI. 28. Astrochemistry : Additionally, it can be used to create datasets of the spectral signatures of molecules involved in the atmospheric production or consumption of specific chemicals, such as the phosphine that may have been detected on Venus. This could prevent missed assignments and, if accuracy is improved, be used in the future detection and identification of molecules on other planets. 29. Archaeology, history, and imaging of sites: Ancient manuscripts can be attributed and restored with the aid of machine learning. For example, texts can benefit from indexing to make searching and categorizing fragments better and more accessible Geneticgenetic history can be uncovered by using artificial intelligence to analyze genomes. For example, interbreeding between ancient and modern humans has led researchers to deduce that a population that is not Neanderthal or Denisovan once existed. Additionally, "non-invasive and non-destructive access to internal structures of archaeological remains" can be accomplished with its help. 30. Physics: An emerging field of physics research is devoted to using classical machine-learning techniques in investigating quantum systems. Quantum state tomography, which learns a quantum state from © 2023 Global Journals Global Journal of Computer Science and Technology Volume XXIII Issue II Version I 25 ( )D Year 2023 Journey of Artificial Intelligence Frontier: A Comprehensive Overview