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# Madeleine's AI Presentation 

## AI TOOL LIST

* across all these areas, the Adobe Creative Suite is excellent, incorporating multiple AI tools into your usual workflow. But I'll focus on other, individual tools, in this list. However, I expect many of these tools will evolve rapidly-- some may disappear as they are bought up by larger compoanies, or different tools might merge. 


1. Video Essays:
    * Vidnami: Vidnami is an AI-based video creation tool that can automatically generate video content from text. It can convert written content into engaging videos by adding visuals, animations, and voiceovers. This can make creating video essays more efficient, as it eliminates the need for extensive video editing skills.
    * Lumen5: Lumen5 is an AI-powered video creation platform that can transform articles and blog posts into video content. It suggests relevant visuals, adds text overlays, and even generates voiceovers. It's a great tool for turning written content into visually appealing video essays.
    * Magisto: Magisto uses AI to turn raw footage into polished videos. It can analyze the input content and apply appropriate editing techniques, transitions, and effects, streamlining the video creation process for video essays.
    * Rocketium: Rocketium is an AI tool that lets you create videos by simply inputting text, images, and videos. It offers templates, music, and other customization options, making it easier to craft engaging video essays without extensive video production knowledge.
    * Animoto: Animoto is an AI-driven tool that helps users create professional-looking videos by offering customizable templates, music, and animations. It's suitable for crafting visually appealing video essays without a steep learning curve.

2. Podcasts:
    * Descript: Descript employs AI to transcribe audio content and provides a text-based audio editor. This allows podcast creators to edit their podcasts by editing the written transcript, which in turn edits the audio. It streamlines the podcast editing process.
    * Repurpose.io: This tool uses AI to automatically convert video content into podcast episodes. It can extract the audio from video files, making it a time-saving solution for repurposing video content for podcasting.
    * Audiate: Audiate is an AI tool that can transcribe and edit spoken content. It's particularly useful for refining podcast scripts and ensuring a polished final product.
    * Temi: Temi is an AI-powered transcription service that quickly and accurately transcribes audio content. This can be valuable for generating accurate podcast transcripts or repurposing podcast content into written formats.
    * Otter.ai: Otter.ai is another transcription tool that can transcribe audio content in real-time. It offers collaboration features and can help podcast creators maintain accurate transcripts.

3. Posters and Infographics:

    * Visme: Visme uses AI to suggest design elements and templates based on the content you input. It's suitable for creating visually appealing posters and infographics without extensive design skills.
    * Canva: Canva employs AI to offer design suggestions and automate design processes. It's user-friendly and can help create eye-catching posters and infographics.
    * Infogram: Infogram is an AI-driven infographic tool that assists in creating data visualizations and infographics. It can automatically generate charts and graphs from your data.
    * Venngage: Venngage provides AI-powered templates and design recommendations for creating infographics. It's a helpful tool for students who want to create informative visuals.
    * Crello: Crello uses AI to suggest design elements and animations, making it easier to create engaging posters and infographics. It's suitable for students who may not have extensive design expertise.

4. Coding for Web Design:
    * Sketch2React: Sketch2React utilizes AI to transform design sketches into responsive web components. It streamlines the process of turning design concepts into functional web elements.
    * Zeplin: Zeplin uses AI to facilitate collaboration between designers and developers. It generates code snippets and style guides directly from design files, making the handoff process smoother.
    * Framer X: Framer X is a design and prototyping tool that incorporates AI-driven animations and interactions. It's useful for students aiming to enhance the interactivity of their web design projects.
    * Wix ADI (Artificial Design Intelligence): Wix ADI uses AI to automatically design a website based on user preferences and content. It's an efficient tool for quickly creating functional web designs.
    * Bootstrap Shuffle: While not strictly AI-based, Bootstrap Shuffle helps users create custom Bootstrap themes and layouts with ease. It simplifies the process of designing responsive websites.

5. Performances:
    * AI Music: AI-generated music tools like AIVA or Amper Music can compose original music compositions based on specified moods, genres, and themes. These compositions can be used as background music for performances.
    * AI Choreography: AI tools like Choregraphe can help in generating and fine-tuning dance routines. This can be beneficial for students preparing choreography for performances.
    * AI Script Analysis: AI tools like IBM Watson's Tone Analyzer can analyze written scripts or text and provide insights into emotional tone and sentiment. This can assist performers in understanding the emotional nuances of their performances.
    * AI Vocal Analysis: Tools like VoCo can analyze vocal performances, providing feedback on pitch, tone, and expression. This can aid singers and vocal performers in refining their techniques.
    * AI Video Analysis: AI tools like IBM Watson Video Analytics can analyze video footage to detect emotions, facial expressions, and movement patterns. This can help performers fine-tune their expressions and movements for impactful performances.

6. Virtual Galleries:
    * Artland: Artland offers an AI-powered virtual gallery platform that allows artists to showcase their work in a digital space. It provides a virtual gallery experience for visitors.
    * Artivive: Artivive combines physical artwork with augmented reality (AR) technology. Artists can use it to add digital, interactive layers to their physical pieces, enhancing the virtual gallery experience.
    * SketchAR: SketchAR uses AI to assist artists in creating accurate sketches by overlaying digital lines onto the physical canvas. This can help artists prepare artwork for virtual galleries.
    * Augment: Augment is an AR platform that allows artists to place their 3D models or artwork in virtual spaces. It's useful for creating immersive experiences in virtual galleries.
    * VRChat: While not strictly AI-driven, VRChat is a virtual reality platform where artists can create and exhibit their work in 3D virtual spaces, offering an interactive and immersive virtual gallery experience.




## AI TERMINOLOGY

Artificial Intelligence (AI) terminology encompasses a diverse array of formal and informal terms. Here's a compilation with a particular focus on Large Language Models (LLMs) and related concepts. While this list includes both formal terms and slang, remember that AI terminology continues to evolve alongside technology advancements and online communities. 


AI Foundations:
* Artificial Intelligence (AI): The simulation of human intelligence processes by machines, especially computer systems.
* Artificial General Intelligence (AGI): AGI, also called strong AI, is a type of AI that possesses advanced intelligence capabilities similar to human beings. While artificial general intelligence was once primarily a theoretical concept and a rich playground for research, many AI developers now believe humanity will reach AGI sometime in the next decade.
* Cognitive Computing: Cognitive computing is an AI field focusing on developing systems that imitate human cognitive abilities, such as perception, learning, reasoning, and problem-solving.

Machine Learning and Learning Types:

* Machine Learning: Machine learning is a way for machines to learn and make predictions without being explicitly programmed. It's like feeding a computer with data and empowering it to make decisions or predictions by identifying patterns within the data.
* Deep Learning: Deep learning is a branch of AI that uses artificial neural networks with multiple layers to learn from vast amounts of data. It enables machines to perform complex tasks, such as natural language processing, image, and speech recognition.
* Neural Network: A computational model inspired by the human brain, used in machine learning models to excel in various tasks.
* Recurrent Neural Network (RNN): A type of neural network that can process sequential data using feedback connections. RNNs can retain the memory of previous inputs and are suitable for sequence-based tasks.
* Generative Pre-trained Transformer (GPT): A specific architecture for LLMs, capable of generating coherent text based on prompts.
* Large Language Model (LLM): A machine learning model trained on vast amounts of data for meaningful, contextual responses.
* Computational Learning Theory: A branch of artificial intelligence that studies algorithms and mathematical models of machine learning.
* Computer Vision: Enabling computers to interpret visual information from the world.

Natural Language Processing:

* Natural Language Processing (NLP): The ability of machines to interpret, understand, and respond to human-readable text or speech.
* Natural Language Generation (NLG): Creating human-readable text from structured data.
* BERT (Bidirectional Encoder Representations from Transformers): A transformer-based model for NLP tasks.

Data Handling and Analysis:

* Data Science: Extracting insights from data using scientific methods, algorithms, and systems.
* Data Mining: Acquiring valuable knowledge from large datasets using statistical analysis and machine learning techniques.
* Data Augmentation: Techniques to increase diversity in training data.
* Dataset: A collection of data used for analysis or training models.
* Pattern Recognition: Identifying and interpreting patterns in data.
* Pushshift: A platform for Reddit data collection and archiving.
* Reddit Scraper: A tool to extract data from Reddit for analysis or ML projects.
* OpenAI: An AI research laboratory developing tools that can appear as smart as humans.

Programming and Tools:

* Python: A popular programming language for AI and ML.
* Hackathon: An intensive coding event to solve challenges using technology.

Development Concepts:

* Commit: A saved change in a repo with a description.
* Fork: Creating a copy of a repo to work on independently.
* Pull Request: Proposed changes to a repo that can be reviewed and merged.
* Push: Uploading local commits to a remote repo.

Bias and Limitations:

* Bias: AI bias refers to the tendency of a model to make certain predictions more often than others. Bias can be caused due to the training data of a model or its inherent assumptions.
* Hallucination: AI hallucination refers to the instances where a model produces factually incorrect, irrelevant, or nonsensical results. This can happen for several reasons, including lack of context, limitations in training data, or architecture.

AI Communication:

* Chatbot: AI-based conversational agent for human-like interactions.
* ChatGPT: A chatbot built on LLMs, like GPT-3, designed for interactive conversations.

Tools and Version Control:

* Push: Uploading local commits to a remote repo.
* Pull Request: Proposed changes to a repo that can be reviewed and merged.
* Commit: A saved change in a repo with a description.
* Fork: Creating a copy of a repo to work on independently.
* Remember that some terms might have relevance to multiple groups based on their context and usage in AI.

Other Concepts:

* Fine-tuning: The process of refining a pre-trained LLM on a specific task or domain.
* Inference: Using a trained model to make predictions on new data.
* Hyperparameters: Settings that define how an algorithm or a machine learning model learns and behaves.
