5 Things to Know Before Starting an AI Project
Before you start an AI project, you need to focus on five key stages. You will get the desired result just by focusing on the right approach.
Join the DZone community and get the full member experience.Join For Free
Suppose you have an opportunity to create a project on AI. Consider these five stages before starting. These five are learning, programming language, knowledge representation, problem solving, and hardware.
1. Learning Process
Learning means adding new knowledge to the knowledge base and improving or refining previous knowledge.
The success of an AI program is based on the extent of knowledge it has and how frequently it acquires knowledge. Learning agents consists of four main components. They are the:
- Learning element — The part of the agent responsible for improving its performance.
- Performance element —The part that chooses the actions to take.
- Critics — They tell the learning element how the agent is doing.
- Problem generator — It suggests actions that could lead to new information experiences.
2. Programming Language
LISP and Prolog are two of the primary languages used in AI programming.
LISP (List Processing) — LISP is an AI programming language developed by John McCarthy in 1950. LISP is a symbolic processing language that represents information in lists and manipulates lists to derive information.
PROLOG (Programming in Logic) — Prolog was developed by Alain Colmeraver and P. Roussel at Marseilles University in France in the early 1970s. Prolog uses the syntax of predicate logic to perform symbolic, logical computations.
3. Knowledge Representation
The quality of the result depends on how much knowledge the system possesses. The available knowledge must be represented in an efficient way. Hence, knowledge representation is a vital component of the system. The best-known representations schemes are:
- Associative Networks or Semantic Networks
- Conceptual Dependencies and
4. Problem Solving
The objective of this particular area of research is how to implement the procedures on AI systems to solve problems as humans do. The inference process should also be equally good to obtain satisfactory results. The inference process is broadly divided into the brute and heuristic search procedures.
Most of the AI programs are implemented on Von Neumann machines only. However, dedicated workstations have emerged for AI programming. Computers are classified into one of the following four categories:
- Single Instruction Single Data (SISD) Machines
- Single Instruction Multiple Data (SIMD) Machines
- Multiple Instruction Single Data (MISD) Machines
- Multiple Instruction Multiple Data (MIMD) Machines
Published at DZone with permission of Srini Pesala. See the original article here.
Opinions expressed by DZone contributors are their own.