Reasoning encompasses two typical types: deductive reasoning and inductive reasoning. Despite extensive research into the reasoning capabilities of Large Language Models (LLMs), most studies have failed to rigorously differentiate between inductive and deductive reasoning, leading to a blending of the two. This raises an essential question: In LLM reasoning, which poses a greater challenge - deductive or inductive reasoning? While the deductive reasoning capabilities of LLMs, (i.e. their capacity to follow instructions in reasoning tasks), have received considerable attention, their abilities in true inductive reasoning remain largely unexplored. To investigate into the true inductive reasoning capabilities of LLMs, we propose a novel framework, SolverLearner. This framework enables LLMs to learn the underlying function (i.e., $y = f_w(x)$), that maps input data points $(x)$ to their corresponding output values $(y)$, using only in-context examples. By focusing on inductive reasoning and separating it from LLM-based deductive reasoning, we can isolate and investigate inductive reasoning of LLMs in its pure form via SolverLearner. Our observations reveal that LLMs demonstrate remarkable inductive reasoning capabilities through SolverLearner, achieving near-perfect performance with ACC of 1 in most cases. Surprisingly, despite their strong inductive reasoning abilities, LLMs tend to relatively lack deductive reasoning capabilities, particularly in tasks involving ``counterfactual'' reasoning.

Is Real AI Superintelligence the Fundamental Solution of Human Problems? RAIS is like a scientific modelling makes a particular part or feature of the world to automatically understand, define, quantify, visualize, or simulate by referencing to its encoded/programmed world's data/information/knowledge base. The RAIS is to run the Master Algorithm of Reality and Mentality as Descriptive, Deductive, Intuitive, Inductive, Exploratory, Explainable, Predictive and Prescriptive (DDIIEEPP) Platform. In all, the RAI program implies radically innovative approaches and paradigmatic shifts in fundamental knowledge fields and advanced technology domains, as reality and mentality, causality, science, technology and statistics, AI and ML, data and intelligence, information and knowledge, AI software and hardware, cyberspace and intelligent robotics. The RAIS Platform could compute the real world as a whole and in parts [e.g., the causal nexus of various human domains, such as fire technology and human civilizations; globalization and political power; climate change and consumption; economic growth and ecological destruction; future economy, unemployment and global pandemic; wealth and corruption, perspectives on the world's future, etc.].

How do I build an AI human-like machine from scratch? What are all the steps and skills that are required? To build full or Real AI (RAI) is much more important than "artificial sun", known as ITER, an international nuclear fusion research and engineering megaproject to create energy by replicating fusion processes of the Sun. The RAI is to run the Master Algorithm of Reality and Mentality as Descriptive, Deductive, Intuitive, Inductive, Exploratory, Explainable, Predictive and Prescriptive (DDIIEEPP) Platform. In all, the RAI program implies radically innovative approaches and paradigmatic shifts in fundamental knowledge fields and advanced technology domains, as reality and mentality, causality, science, technology and statistics, AI and ML, data and intelligence, information and knowledge, AI software and hardware, cyberspace and intelligent robotics.

How do I build an AI human-like machine from scratch? What are all the steps and skills that are required? To build full or Real AI (RAI) is much more important than "artificial sun", known as ITER, an international nuclear fusion research and engineering megaproject to create energy by replicating fusion processes of the Sun. The RAI is to run the Master Algorithm of Reality and Mentality as Descriptive, Deductive, Intuitive, Inductive, Exploratory, Explainable, Predictive and Prescriptive (DDIIEEPP) Platform. In all, the RAI program implies radically innovative approaches and paradigmatic shifts in fundamental knowledge fields and advanced technology domains, as reality and mentality, causality, science, technology and statistics, AI and ML, data and intelligence, information and knowledge, AI software and hardware, cyberspace and intelligent robotics.