Like everyone else, I’ve been talking a lot about A.I. over the past few months. In fact, just yesterday I co-hosted a webinar on this topic. Yet many people still don’t understand how this is any different than the “article spinners” of old, or how exactly it works.

Artificial Intelligence is very different than an article spinner. It uses what is called natural language generation techniques, using deep learning to create human-like readable text. With this technology a unique article is created based on a language prediction model. Article spinner tools on the other hand take an original article and produce one or more variations by replacing specific words, phrases, or sentences with alternate versions. Article spinners are essentially plagiarized content re-written from a single source.

Unlike article rewriting, natural language generation doesn’t require an original piece of content. It creates brand new content instead of rewriting existing articles.

No matter how advanced article spinners may claim to be, they cannot generate text but only change it. This type of tool requires an existing blog post from which it can only produce a derivative. They do not create, they merely modify. Therefore, article spinners are not a good fit for writing original works.

Think of it this way

If you were to assign a topic that was unfamiliar to a writer, they would first read up on the subject. They would likely research multiple articles, and possibly conduct a survey or conduct an interview with an expert. LLMs (Large Language Models) or Natural Language Models are no different. They have been “trained” on huge amounts of data including websites such as Wikipedia, books, news articles, and scientific journals.  Instead of researching a handful of documents, the AI analyzes massive amounts of data, then generates entirely new content based on what it knows.

This is how the AI generated images work as well. Whether you are using Dall-E or MidJourney or some other AI image generation tool, the images it creates do not exist somewhere else. They are not a modified graphic, rather the AI looks at various amounts of data and creates an entirely new image based on the input given.

Music too can be generated by AI using the same techniques. For example, SoundDraw and Aiva combine groups of notes or chords to generate new music based on the input you provide.

A Deep Dive into Natural Language Processing and How it Powers A.I.

Natural language processing (NLP) is a branch of artificial intelligence (AI) that enables machines to understand and interpret human language. It is a complex field of study that combines linguistics, computer science, and information engineering to enable machines to process and interpret natural language.

NLP is based on the idea that language is composed of a set of rules and patterns that can be used to interpret and understand it. To do this, NLP algorithms use a variety of techniques, such as natural language understanding, natural language generation, and natural language processing. Natural language understanding involves the use of algorithms to identify the meaning of words and phrases in a sentence and then uses that information to analyze and interpret text.

This almost sounds like science fiction, right?

Late last year, in November of 2022, AI broke free from the sci-fi speculations and research labs and onto the desktops and phones of the general public.  ChatGPT has subsequently grown faster than any other technology in history with 100 million users in less than 2 months. It’s what’s known as a “generative AI.” And now, a cleverly worded prompt can produce an essay or put together a recipe and shopping list, or even an entire book, like my “Written by a Robot” novel.

Although AI may not yet possess the type of living consciousness or theory of mind often portrayed in science fiction films and books, it is rapidly advancing and disrupting our preconceived notions of what AI systems are capable of. It is a remarkable tool for creating written and image content and is useful for providing you with a strong initial draft.

ChatGPT’s ubiquitous presence can be attributed to its multifaceted nature. Beyond its capabilities as an AI-powered chatbot, the company behind ChatGPT, OpenAI, offers an API (application programming interface) that enables other organizations to develop customized applications using its technology. Microsoft’s integration of ChatGPT into its Bing search engine is a prime example of this.

Try This Experiment

You need to try this! Go to ChatGPT (https://chat.openai.com) and tell it ‘Act as if you are Greg Jameson and introduce yourself.’ Now do the exact same thing, but put in your name, and see if you like the results.

If you don’t like the results, or it looks like it just made something up because it doesn’t know what you do, you have some serious work to do on your branding. Having an online store isn’t just about the technology – it’s about marketing! WebStores can help – start by registering (for free) to join our 5-Star Mastermind program.

Join our Marketing Mastermind Today!

WordPress Plugins

Since both ChatGPT and WordPress are open source programs, one would only expect that a plugin would be available for write new blog posts using the tool. Here is an example of how this can be done, using the ChatGPT API mentioned earlier.

With this you can create your own AI (using the GPT engine). For a limited time (because it costs me money), you can try out the WebStores AI (no credit card or email required).

Try Out the WebStores AI

While it is not necessary to use a plugin like this (as you can just use ChatGPT and copy and paste the information), it does make creating a first draft of a blog post very easy, with H2 heading tags already done, and images already created and uploaded.

Want to learn more about using the power of AI in your business?

Join us on March 14 at 4:00pm Mountain time as I co-host a webinar. Register here: https://bit.ly/AIRevolutionWebinar.