Introduction to Artificial Intelligence(AI)

• Artificial intelligence (AI) broadly refers to the intelligence exhibited by machines or computer systems
• An AI system is software that mimics human thought processes in a computer

Common AI Systems

• Advanced search engines (e.g., Google Search)
• Recommendation systems (e.g., YouTube, Amazon, Netflix)
• Speech interaction (e.g., Google Assistant, Siri, Alexa)
• Autonomous vehicles (e.g., Waymo)
• Generative and creative tools (e.g., ChatGPT, Gemini, Apple Intelligence)
• Strategic games and analysis (e.g., chess, Go)

History

• The term "Artificial Intelligence" (AI) was introduced by John McCarthy at the 1956 Dartmouth Seminar
• The term itself wasn't directly tied to the understanding of human intelligence.
• John McCarthy defined AI as the challenge of determining which computational procedures should be called "intelligent."
• He pointed out challenges in understanding some intelligence mechanisms.
• AI involves understanding "the computational component of the ability to achieve goals in the world"

Further definitions

• Following the Dartmouth seminar, in 1959, John McCarthy described "artificial intelligence" in his article "Programs with Common Sense."
• AI was described as a computational system capable of creating smaller programs
• John McCarthy later simplified AI as "the computational part of the ability to achieve goals in the world."
• All technical systems are goal-oriented, and this highlights its application in engineering
• The definition of "intelligence" included terms like, "understanding, capability, comprehension," and "information gathering"

Caveats regarding the translation of terms

• The meaning of "artificial intelligence" is somewhat distorted and causes confusion and unrealistic expectations
• The term "intelligence" as opposed to "intellect" was specifically used.
• Artificial intelligence is defined as systems that imitate cognitive functions with comparable results to solve problems
• Crucial system features in AI include self-learning and decision-making (often without pre-set algorithms).

Accurate Interpretation

• Artificial intelligence begins with the definition involving "processing, recognition, and understanding"
• Systems showcase "analysis and prediction," and "comprehension and understanding"
• Algorithms must be founded on current scientific laws, methods, and principles, especially as it pertains to mathematics, physics, and informatics.
• This definition enables a wide range of applications automating human intellect.

Other definitions of AI

• A scientific field focused on creating hardware or software that can perform tasks that require human intelligence.
• A field in informatics and information technology focused on recreating rational thought and actions using various hardware and software. Systems understand external data, learn from it, and adapt accordingly to achieve specific goals and objectives.

Other definitions in Informatics

• AI aims to develop intelligent software systems capable of performing tasks that require human intellect
• AI allows computers to communicate with humans in natural language
• AI works to enable computers to fulfill different tasks upon request (e.g., speech recognition, translation, creative arts, or driving).

Consistent Ideas

• Underlying the definition of AI lies the modeling of human intellect
• Developing intellectual software systems capable of performing tasks traditionally performed by humans, such as
• Solving problems by finding effective solutions during issues
• Learning from experience to obtain new skills and knowledge.
• Identifying objects and patterns in data
• Understanding and communicating in a natural language
• Selecting the most optimal course of action in given circumstances
• Automating routine and manual intellectual tasks with aim to increase process efficiency

AI construction and qualities

• AI system, comprised of a data base, solve and smart interface with programming languages, establish contact with computer
• AI qualities enables systems to learn, adapt to altering requirements and become autonomous
• AI systems able to apply knowledge they obtained and process large sets of data to scale function

Dealing with uncertainty in AI

• Systems can still operate effectively in total or incomplete information scenarios
• Knowing the properties as well as structures of AI helps to properly gauge capabilities to resolve problems
• Helps choose the applicable tech to resolve such, and encourages development of new algorithms

Study direction

• It operates in several directions, such as symbolic development to mirror intellect, nature language to work, and use one's understanding and understanding of information

Symbolic modeling

• Modeling intellect sets groundwork to other directions and has since paved to ways to develop AI
• Entails coding of symbolic systems with assigning of a task that needs to be resolved
• Tasks are pre-designed, and translated via math and algorithms to offer the solution, for example game/decision theory or scheduling

Interacting with natural languages

• An imp 방향nnt direction, focusing on language processing that analyzes the synthesis to establish convenient types of communication
• In theory, natural language is a solid goal for computers that requires large vocabulary and ability to function, which makes the definition fundamental in AI

Machine Reception

• Present time looks to address the ability for a system that doesn't just observe the content but interpret data and its syntax, to fix and pinpoint exact, relevant errors.
• Being able to address what the machine cannot understand, and its the key to the issue

Knowledge

• From retrieving to organizing data via retrieving, structuring and use its key
• Its tied to create systems for complex issues, and with aid of programs, it can offer a set of answers

Extract unstructured content

• A machine's ability to automatically create frameworks in documents, which is a task linked to natural language in itself in identifying information
• All such tasks related to extracting relevant details by skimming subjects and documents.

Cognitive understanding

• Focuses how intellect is archived, and edited as it is linked to informatics in its manner of condensing all knowledge and what's gained. It uses this to create programs.

The term "knowledge providing" itself

• It pertains to how the info is handled, especially thoughts coming from distinct elements from pre-archived content to deduct.

Bioengineering

• Practiced today in USA, used in banking sectors that assess data from retail lenders by nearly 90% using AI
• Is key in finding new forms to create by reducing labor that still maintains high professionalism and accuracy
• It helps create the framework, to make it fit into a system

Machine acquisition

• Can be approached various ways through system such as neutral nets that help reduce network info
• Can reduce the data that the networking portrays and minimize network functionality

Machine learning

• The means through its system understands its function and can analyze info itself
• Solved issues over time. With an individual's account on it being the "inductive machine" to work
• Works by using information not just to identify issues. Math tools are used to determine all elements

Approaches it

• The inductive method: Looks to determine data by what's set

Deductive

• Employs the specialists info, edits it, and sets it. Limited to expert system, the terms the machine and pre-set are one in the same

Formulating

• Set of answers that showcase an interaction and some type of linkage occurs

This knowledge helps for the generation to be the product and function more optimally

• Has a special capability. Data is then stored in a form that's accessible to use
• When something is not known, it can be accessed and the overall learning, and response can be applied by function analysis
• A general set of knowledge now exist. Specific aspects have some limits numerically
• Entry data isn't complete, not exact, number or non-numerical for those various traits
• The automated process reduces the complex tasks that need professional understanding The environment's scale of info is also applied throughout science, industry in health etc
• It needs to be resolved, from taking on risk to now needing precedent

Model biological properties

• AI that mirrors natural ways of operating and functioning, such as reading abilities
• Looks for the biological structure. Its what is related. Ability to learn is how something functions

Technologies that have come to be

• neural networks that resolve unclear issues or that cluster items together
• Genetically inclined patterns that make algorithms that seem more effective, and by comparison, it stands out

Biologically intended

• An agent has to interact on its side. Quasi models are based through it. Living cells are the root

Bio-computing

• Helps organize complex tasks and tissue cells that require complex counting, and these molecules are used
• Acid helps in the way its formed with some computer parts. Other proteins as bios, as it also has film to do function

Robots, AI

• One another's work is linked. Science is another aspect that helps build further
• Manipulate the objects and do task with navigation, which also determines its intellect

The automation works by making robots with it, but still is very manual

• Human creative is still not studied or explored as much compared to AI, but it still has areas. Al's roles are writing music, stories (often poems or tales)- creative in nature.

By making it actually look real it helps industries

Technical innovation is another key, and its starting in 1246. Other factors like computing and linear controls are there

• Al's quality that is close, is the one that helps
• Can apply in the present.

Applied Intel Information system

(AIS)

• Is based to help with problems in solving tasks and by what high expertness is, and use it Tasks are defined by how well its not having concrete methods
• It enables experts to think
• Images
• This is what helps build the pattern and works to describe class

Speech editing system

• Info is pushed at faster rates, taking a look in the area
• 4 visual aids is used, and in all its means works to give access
• Gaming's creation also occurs
• Has many forms and a lot of aspects to it and helps to apply the tools to the function now.

Automatic delivery

• Helps the flow of data by letting systems access data quicker
• The speed, large size and steady aspects of flow help

New gathering system

• All the procedure enables collecting, and organizing itself. Such as: sym network and evolution.

Symbolic

• Direct info in data and the laws to get the equation that helps the AI reach and determine which action to go to by reasoning factors. New AI helps do this

Biology

• Elements can alter one another to determine patterns and can decide
• Evolutions are a set to handle it, from the natural and genetics of natural items

Tools in programming

• To build an AI program, its advised to select some aids like IPP, Python

Plane aid, with robots

• Some robotics start by taking what needs to be fulfilled and using that with its ability by what its told
• Due to factors this is where there is the important element. As plane parts start up, you can see how simple ways the task operates from place to place in all that exists. The correct track is then used now

Robot integration

• Creating, in all what is robotics greatest height

The tech aids to be

• Its sight, hearing, feel for situation and what should be. 1 gen are then applied now to all such tasks. Very autonomous.

21st century

• Health is the most.
• All those areas show the increase in need with AI for daily means and has a very real function

Create solution to address this by testing to do and what's need

To address this means some type of likenesses that some have followed. And has tried building all this

The framework is, as is made. Al'S

• Ray was a medieval time expert that built an idea that machines must mimic mind of person in order to build systems that work

Later versions followed such as

• Leibniz and Dekart the language that is all knowing and helped and the basis here is seeing its key aspects in such jobs From this point scientist tried to replace many jobs, and with Pascal (French mathematician) he made number-calculating tool
• 1957 Turing built a machine with aspects.

WWII, and even though tough programming had

• From the 50s all fields started using it as mind mapping helped. Neural nets were then used and built up. Tuling thought people can learn the systems and its function. An assessment to make that known (whether AI could fool people)

First successful program was built, and another made the ability to predict moves

Turing stated he would show all that

• Mcarthy in 1956 was one who stated all the tools and he then launched an idea to test all this as its own item now