© Mark Ollig
Decision-Making Neural Networks (DMNs) are artificial intelligence (AI) models using multiple learning methods to make decisions in solving complex problems.
AI models make decisions by processing different data types, including text, audio, images, video, sensor data, and code.
They also identify patterns in historical information and associations between different pieces of information and previously arrived at decisions.
AI models then apply this knowledge to quickly analyze and process large amounts of new information.
DMN AI models have been applied to the health industry for making decisions about patient care, logistics for managing shipping routes, various financial investment decisions, and for use with multiple applications on the Internet.
An AI inference model is a computer program trained on large datasets of labeled data, allowing them to make predictions on information they have not previously encountered.
These models learn from labeled datasets, such as photos of cats labeled as “cat” and dogs labeled as “dog,” to generalize and recognize similar images in the future.
This AI stuff sounds easy-peasy.
AI inference models learn to identify patterns in data and make projections on new data they have not seen before.
Certain AI models utilize rule-based logic that involves “if-then” statements to arrive at decisions. For instance, a rule-based AI system could have a rule that states: “If the temperature exceeds 90 degrees Fahrenheit, switch on the air conditioner.”
Machine learning algorithms allow AI models to learn from data and make decisions without requiring extensive programming.
An algorithm based on machine learning models can be trained using past weather data to forecast temperature for a specific day.
Machine learning algorithms are generally more powerful than rule-based logic, so most AI models rely on them to make decisions.
AI models assist in decision-making for self-driving cars, medical diagnoses, security, fraud detection, product recommendations, and more.
ChatGPT AI can assist with a vast range of topics. Its language model is designed to provide responses that resemble human-generated ones. It’s worth noting its data and code are current up until 2021.
ChatGPT is at https://chat.openai.com.
In February, Microsoft launched Bing Chat, using OpenAI’s Generative Pre-trained Transformer 4 (GPT-4), a large language model that supports multiple modes of communication.
GPT-4 is integrated with Microsoft’s Bing search engine, helping users to obtain current information from verified web pages.
OpenAI, founded in 2015, focuses on developing safe and beneficial AGI with a mission statement to “ensure that artificial general intelligence [AGI] benefits all of humanity.”
At present, AGI remains a theoretical form of artificial intelligence that may one day possess the ability to comprehend and rationalize like a human.
OpenAI developed the DALL-E 2 Generative AI-powered model that creates images based on text descriptions.
If given the instruction “a cat wearing a hat sitting on a skateboard,” DALL-E 2 can generate an image visually similar to what a human artist would create.
ChatGPT is a popular AI processing network that is still in development. It uses OpenAI’s advanced language model, GPT-4, to generate human-like written content through visual and textual input.
Bing AI chat uses the power of ChatGPT and GPT-4 in partnership with OpenAI and enhances it with real-time information and sources. It interacts with human users and provides additional example questions to initial requests.
Accessing Bing Chat from the Microsoft Edge web browser is recommended. I created this shortened link: https://tinyurl.com/BB-BingAI.
Google Bard is a large language model (LLM) generative AI chatbot developed by Google AI.
It is acknowledged that generative AI can produce content, images, audio, videos, and text almost identical to what humans create.
Google Bard is a tool that uses a large amount of text and code to create responses to various prompts and questions resembling human-like interactions.
It can assist with generating text, language translation, creating diverse types of content, coding in programming languages like Python, Java, and C++, and “answering your questions about the real world.”
Although still under development, the Google Bard AI chatbot can be accessed at https://bard.google.com.
Chatbots powered by AI can comprehend natural human language and deliver personalized replies.
When communicating with AI chatbots, it is important to use clear language that is easy for the chatbot to understand, use simple sentences, avoid jargon, and be specific.
When communicating with those AI chatbots, including appropriate keywords in your sentences is important.
Avoiding offensive or vulgar language is also good, as it sometimes restricts a chatbot’s ability to interact with you.
Learn how to create a personalized chatbot from the YouTube video “ChatGPT in Python for Beginners – Build A Chatbot” at https://tinyurl.com/ymcb3v5a.
Having a personal chatbot reminds me of owning a pet rock in the ’70s.
You do remember those pet rocks, right?
As AI continues its unstoppable advancements, we are witnessing its ongoing integration with our existing technology and us.
Is AI an “it” or a “they?”
Some contend it should be called “it” since it is a machine lacking human qualities.
Meanwhile, others suggest using “they” because AI is becoming more advanced and may eventually achieve consciousness.
Will it be AI that assimilates us, and not “The Borg?”
Folks, we won’t be putting the AI toothpaste back in the tube.
