Artificial Intelligence (AI) in everyday language
at everyday studio our mission is to make the power of artificial intelligence accessible and practical for small businesses, empowering them to thrive and excel in an ever-changing world.
When I say artificial intelligence (AI) I bet the first thing most people would think of is ChatGPT…
While ChatGPT is an incredible tool, it is only one of many surface-level applications of AI. Let me explain.
The Structure of Artificial Intelligence (AI)
You are walking around a major city and look up at the big tall skyscrapers. They are a marvel of engineering but what did it actually take to build?
First, you have the solid foundation on which everything is built, in AI this is the data layer. This layer is made up of tons of information, often in the form of text, images, or audio, which the AI uses to learn. The quality and quantity of this data are critical; just as a strong foundation can support a larger, more complex building, rich and diverse data allow AI to learn more effectively and handle a wider range of tasks.
Now, think of the actual structure of the skyscraper, the part that takes the most time and effort to build. In AI this would be the learning layer. Through a process called ‘machine learning’, AI takes all the raw data it’s been given and starts to understand it. It follows a set of rules or formulas, which we call ‘algorithms’, to identify patterns or relationships in the data — much like following an architectural plan. As the construction progresses, decisions have to be made. Maybe the design needs to be tweaked to account for wind loads or the view from certain windows. In the world of AI, after learning from the data, the AI can make predictions or decisions, just like an architect adjusting the design.
Finally, you have the outside of the skyscraper, a beautiful building that everyone can see. This is the application layer and is the part of AI that’s tangible to us. It’s the sleek, user-friendly interface on your favorite apps, the smart recommendations you get when you shop online, or the surprisingly human-like responses from a chatbot like ChatGPT. When you ask your virtual assistant to play your favorite song or to set a reminder, it’s the application layer you’re interacting with. In reality, AI is a lot more complex, with even more layers working together behind the scenes but having a general understanding of how it all works together should help you as the models and applications become more and more developed.
America’s next top (AI) Model
Many companies are fighting for supremacy over who can produce the best learning layer model upon which applications can build. You can think of this battle as choosing between using iOS or Android (or another operating system).
OpenAI, the entity that created ChatGPT, has developed some significant models that are shaping the AI landscape. One of these is GPT-4, a Generative Pretrained Transformer. This model is essentially a natural language processing wizard, capable of understanding and generating human-like text with astonishing accuracy. However, OpenAI’s innovations don’t stop at text. They’ve also engineered a multimodel blend of GPT and Generative Adversarial Networks (GANs), resulting in DALL·E — a program that can generate specific images from textual descriptions. It’s like having an artist who can bring to life any scene you can describe with words.
Meanwhile, tech giants like Google aren’t sitting idle. They’ve launched their own contender in the AI chat interface arena, known as BARD which is powered by Google’s Pathways Language Model 2 (PaLM 2). Just like each skyscraper in a city skyline has its own unique architectural style and engineering, each of these AI models operates in its unique way.
I won’t delve into the technicalities of how these models operate in this piece but the important takeaway is that each AI model is unique, and designed to excel in its specific function. Much like the way operating systems have evolved to offer a variety of options catering to diverse needs, AI models are becoming more specialized, nuanced, and powerful to meet the growing demands of our technologically advanced world.
The talk of AI has been bustling recently, largely due to the incredible advancements made in the area of generative models. These models, in essence, are like digital artists — they can produce content that seems creative, even innovative. Whether it’s a painting, a piece of music, or a piece of writing, these models can generate it. This capacity of a machine to mimic creativity — something once thought to be uniquely human — is truly a significant leap forward, and it has ignited a flurry of excitement around the possibilities of AI.
Despite these big advancements, chances are high that you’ve been engaging with different forms of AI for years, often without even realizing it.
As the number of these models grows, it’s important to note that each comes with its own unique set of capabilities and constraints. Just as a hammer isn’t useful for every task, neither is each model suitable for every application. Every model has been designed and refined to perform specific tasks incredibly well. For example, a Natural Language Processing (NLP) model like ChatGPT might be excellent at understanding and generating text, but it wouldn’t be the right choice for analyzing images or video (yet) — that’s a job for a Computer Vision model.
As we step into the future, one of the key challenges will be navigating this increasingly diverse landscape of AI models. For individuals and businesses alike, understanding these models is only part of the equation. The bigger challenge will be discerning which model — and thus which applications — will provide the most value for their specific needs and contexts. Whether it’s improving customer service with a chatbot, gaining insights from data with a predictive model, or creating eye-catching visuals with a generative model, the goal is to identify and leverage the most effective AI solutions to meet unique needs and drive success.
Don’t stop at ChatGPT
As you can see, the world of AI is much bigger and more diverse than ChatGPT and its Natural Language Process (NLP) capabilities. Yes, the ability of AI to generate human-like text is impressive, but it’s just the tip of the iceberg. From visualizing the world to predicting the future, automating tasks, and even generating new content, AI has a multitude of applications.
AI should also not be some scary concept to fear or think that you can’t understand. At everyday studio, we are working to bridge the gap between complex AI models and practical business solutions. Our aim is to help businesses tap into the power of AI, and not just ChatGPT, in ways that truly matter to them.
So next time when someone says AI, don’t just think of ChatGPT. Remember the vast world of AI models that are at our disposal.
Share your thoughts or ask any questions in the comments below. If you want to know more about AI, everyday studio can help your business understand the power of AI, so don’t hesitate to get in touch with us.
