AI in Biology, Chemistry, Physics, and Astronomy: The Rise of AI for Scientific Discovery. Introduction. Modern science faces a problem that previous generations of researchers rarely encountered at the same scale: there is simply too much information. Genomic databases contain enormous numbers of DNA sequences. Chemistry produces vast libraries of molecules and reactions. Physics experiments generate complex datasets from particle detectors, simulations, and instruments. Astronomy continuously produces observations containing billions of stars, galaxies, and other celestial objects. Human researchers cannot manually examine all of these possibilities. This is where artificial intelligence is becoming increasingly important. AI can process enormous datasets, identify patterns, estimate relationships, generate hypotheses, predict molecular or physical properties, and help researchers decide which experiments deserve further investigation. The transformation is already measurable. ...
What Is Agentic AI, and How Is It Changing the World? Introduction Imagine asking a digital system to conduct a research project, compare dozens of sources, organize the findings, identify missing information, prepare a report, and then revise the report after checking its own work. A conventional software program normally requires each step to be explicitly designed. A chatbot can explain how the work might be done, but it may stop after producing an answer. Agentic AI represents a different approach. Instead of merely responding to individual instructions, an agentic system can pursue a defined objective through a sequence of actions. Depending on its design, it can plan tasks, use external tools, retrieve information, interact with software, evaluate intermediate results, and continue working toward a goal. This shift is important because it changes the role of AI from an information interface in...