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For this assignment you will be researching and presenting information about 1 type of AI listed below. This can be a group project with up to 3 members, or you can work alone. The requirements are:
A title slide with you group members on it.
At least 1 slide introducing the type of AI you're researching and how it works. Example: Explain how Reactive AI functions and makes decisions.
Information about how the AI was trained. Example: Explain what Laion 5B is and how it was used to train AI image generators.
A minimum of 2 examples of where that AI is used, and how those things use it. Example: how does a self driving car use AI to drive? How does generative AI work (include some AI generated images).
At least 1 slide about the benefits of the AI you chose.
At least 1 slide about the problems with the AI you chose.
Explain you or your group's feelings on AI - the good and the bad.
At least 1 slide about a new (within the last few months) innovation in AI.
And finally, answer this question; Do you think AI is actually "intelligent" explain why or why not.
ALSO - include links to the websites or videos where you found your information. Add the link in the actual text like this example: The Moon is about 238,855 miles from earth.
The three kinds of AI based on capabilities:
1. Artificial Narrow AI
Artificial Narrow Intelligence, also known as Weak AI, what we refer to as Narrow AI is the only type of AI that exists today. Any other form of AI is theoretical. It can be trained to perform a single or narrow task, often far faster and better than a human mind can. However, it can’t perform outside of its defined task. Instead, it targets a single subset of cognitive abilities and advances in that spectrum. Siri, Amazon’s Alexa and IBM Watson are examples of Narrow AI. Even OpenAI’s ChatGPT is considered a form of Narrow AI because it’s limited to the single task of text-based chat.
2. General AI
Artificial General Intelligence (AGI), also known as Strong AI, is today nothing more than a theoretical concept. AGI can use previous learnings and skills to accomplish new tasks in a different context without the need for human beings to train the underlying models. This ability allows AGI to learn and perform any intellectual task that a human being can.
3. Super AI
Super AI is commonly referred to as artificial superintelligence and, like AGI, is strictly theoretical. If ever realized, Super AI would think, reason, learn, make judgements and possess cognitive abilities that surpass those of human beings. The applications possessing Super AI capabilities will have evolved beyond the point of understanding human sentiments and experiences to feel emotions, have needs and possess beliefs and desires of their own.
Your presentation will be about one of the types of AI below.
Your presentation will be about one of the types of AI below.
IBM's Deep Blue
Reactive AI
The most basic type of AI, reactive AI is programmed to provide a predictable output based on input. Reactive machines respond to identical situations in the same way every time, and they are not able to learn actions or conceive of past or future.
Deep Blue: IBM's chess-playing AI that defeated chess grandmaster Garry Kasparov by identifying possible moves without incorporating past mistakes
Spam filters: An example of reactive AI
Netflix recommendation engine: Analyzes viewing history to suggest personalized content
Automated teller machines (ATMs): An example of reactive machines
Traffic light systems: An example of reactive machine
Limited memory AI
The most used AI technology today, limited memory AI learns from the past by storing historical data and using it to make better predictions.
Virtual voice assistant: Virtual voice assistants like Siri and Alexa are examples of limited memory AI.
Self-driving cars: Self-driving cars use limited memory AI to observe other cars on the road for their speed, direction, and proximity. They use this information to represent the world, such as knowing traffic lights, signs, curves, and bumps in the road.
Generative AI
Used to create AI art, generative AI analyzes data and renders new art based on references. Users give the AI commands to render new art, which are called "input prompts".
E-commerce: Generative AI can be used for personalized marketing, visual search, product description, and image generation.
Healthcare: Generative AI can help diagnose diseases, predict treatment outcomes, and generate personalized treatment plans by analyzing medical data and patient records.
Call centers: Generative AI can create new content without human input.
Code generation: Tools like ChatGPT can write accurate codes for specific programs.
Content generation: Large language models can process large amounts of text and generate new text based on the patterns it identifies. These models can be used to generate news articles, scientific papers, and improve natural-language processing systems.
Marketing: Generative AI can make creating personalized content easier and improve interactions with potential customers.
Natural language processing: Generative AI can use natural language processing to pull information from around the web to answer search queries and fulfill copy requests.
ChatGPT - LLM
A type of machine learning model called a large language model, it is usually trained on vast amounts of text data to generate language that is contextually appropriate and natural-sounding. ChatGPT is a LLM.
Marketing: can be used in chatbots and virtual assistants to provide customer service, answer questions, and make recommendations.
Legal services: can automate certain legal services, such as contract drafting and review. It can also analyze legal documents to ensure they are accurate and legally binding.
Educational support: can help students and learners get explanations and clarifications on academic topics, homework help, and tutoring.
Brainstorming: can help generate creative ideas, brainstorm solutions to problems, and help with creative writing projects.
Research: can be used for datasets for research, business intelligence, or even training a machine learning model.
Writing: can be used to automatically write emails.
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