"AI is the new electricity." - Andrew Ng, AI pioneer
A breakthrough in problem solving
The startup Harmonic recently claimed victory by solving an Erdos problem with GPT-5.2 Pro. For decades, elite mathematicians have struggled with these thorny puzzles. This achievement suggests that artificial intelligence is reaching a point where it can conduct legitimate academic research through advanced computation.
The illusion of understanding
Experts like Terence Tao express caution regarding machine logic. He suggests these models possess so much background knowledge that they can fake a true grasp of complex concepts. The resulting solution may be a clever reorganization of human work rather than a genuine mathematical discovery.
Accelerating the scientific process
While the debate over original thought continues, AI is already a practical tool. Scientists use these systems to analyze vast amounts of data. It helps researchers deliver information that experts may have forgotten or never encountered in their specific fields of study.
Efficiency in the laboratory
Derya Unutmaz highlights how AI narrows research focus. Instead of performing fifty experiments, scientists can focus on the five most promising ones. This acceleration has a profound effect on fields like cancer research, saving significant time and resources for medical teams.
Discovery versus proposal
Kevin Weil of OpenAI celebrated the technology for answering problems. However, mathematicians maintain these outputs are proposals rather than discoveries. They provide hypotheses for humans to test, acting as a collaborator for scientists rather than a replacement for their unique creative intuition.
Summary
While AI solves complex puzzles, experts argue it may be mimicking patterns rather than understanding logic. Regardless, the technology accelerates research by helping experts narrow their focus and process vast datasets more efficiently than humanly possible, acting as a powerful assistant in the scientific community.
Food for thought
If a machine provides a correct answer without understanding the logic, should we still credit it with making a scientific discovery?
AI concept to learn: Pattern recognition
Pattern recognition is the ability of a computer system to identify regularities within large sets of data. It allows the model to predict outcomes by matching new information against examples it has seen before. This process is the foundation for how current machines appear to understand language.
[The Billion Hopes Research Team shares the latest AI updates for learning and awareness. Various sources are used. All copyrights acknowledged. This is not a professional, financial, personal or medical advice. Please consult domain experts before making decisions. Feedback welcome!]
