AI. Artificial intelligence. ChatGPT. DALL-E. Skynet.
OK, we jest a little — that last one’s from the Terminator movies. Joking aside, AI tools have been all over the news and social media lately. It started with photo and art generating AIs that could create surprisingly good art or turn photos into surprisingly realistic “paintings.” And lately, the internet is geeking out over a new generation of chat AI tools, headlined by ChatGPT.
In some ways, it’s really impressive what these AI tools can do. Scary impressive, even.
In other ways, these tools are revealing the ongoing limitations of AI.
Whether these developments in AI are entirely a societal good, we’ll leave to the philosophers and ethicists.
For the rest of us, the point is this: these tools are here, and they’re going to keep getting better. So it’s time to start understanding what these tools can and can’t do, and how you might be using them in your business in the coming years — or months.
Why All the Buzz About AI?
We’ve been hearing about AI for decades in science fiction (and a little bit in science nonfiction). But all of a sudden, it’s everywhere. Why?
The simple answer is that technology continues to improve and evolve. We’re finally at a point where systems can process enough data at a large enough scale and cheap enough cost that “AI for regular people” is possible.
In some ways, “doing AI” requires a lot of processing power. As the models and technologies underlying it all get better, certain elements take less, like how your smartphone can (sometimes) understand what you’re asking it.
There’s also an aspect of learning or training going on here. These big AI applications train on absolutely massive data sets. They aren’t very good when they start, but they get better as they train. That’s part of a process called machine learning.
Machine Learning Explained with Chess
Think of the game of chess. It follows clear rules, and there are a theoretically finite number of moves and outcomes. A human could never memorize all sequences of moves (and doesn’t need to), but a computer can do this almost instantly.
Here’s where the differences between artificial and human intelligence become obvious. Once a human knows the basic rules of chess, creativity and planning come into the picture. From day one of playing the game, an adult of average intelligence already knows that some moves are really dumb and others are better.
Computers, on the other hand, have to be taught. They run through a seemingly impossible number of games and make every mistake imaginable. But every mistake is an opportunity to learn. Computers can store or remember these mistakes and avoid them in the future. So on day one, the human wins every time. But years later, the best human chess players compete with chess-trained AI—and sometimes the human loses.
That’s machine learning, basically. And it’s an underlying technology fueling growth throughout data analytics and artificial intelligence. It’s what has given rise to the biggest change in recent years: generative AI.
The latest round of AI tools are different. They don’t just memorize move sets or try to understand what you’re saying. They can respond to your text prompts in surprisingly human ways.
ChatGPT can answer all sorts of queries, not by listing a bunch of links, but by telling you the answer in plain, somewhat original language. It can also do things like write instructions on cleaning a chalkboard in the style of a Shakespearean sonnet. It can even write or check basic computer code.
The way this works is complicated, and the results aren’t always accurate. But for the right questions and use cases, ChatGPT can do very quickly what would take a human much longer.
Most people won’t want to start using ChatGPT as a copywriter, at least not with serious editing and fact-checking. But tools like this likely have a role to play in writing workflows in the coming years.
Similar generative AIs are generating art from text prompts. Same basic idea: these aren’t better than your graphic designer, but they may have a role to play in graphic design workflows.
What It Means for Your Business
It used to be that only the big enterprise businesses could gain value from AI. That’s beginning to change as AI gets baked into the apps and services we all use every day.
The landscape is changing quickly. Would you like more help understanding how AI might change the way you get stuff done? We’d love to help. Reach out today!