Revisiting The Early Innings of AI in Marketing
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As discussed in last week’s episode of the pod, ChatGPT and Bing AI are putting some pressure on Google, but they still represent just a meager share of the monthly searches your customers conduct. They likely represent an infinitesimal share of the traffic your brand and business receive every day. Yes, they represent an amazing breakthrough and will have enormous effects on your business. You should use these tools right now to make your business better.
At the same time, we’re still in the early innings of AI in marketing. They’re immensely important. But they’re not yet the end-all, be-all, Alpha and Omega of digital marketing.
We need to think about the “ships and shipwrecks” that AI in marketing will invent. We need to think of how we can get the greatest benefit, while also thinking about the downsides &mdash the shipwrecks — sure to come with our use of artificial intelligence. Most importantly, we need to think about our role and how we can use our passion, our intellect, and our humanity to create and connect… and not just turn everything over to the machines.
You might also enjoy this webinar I recently participated in with Miles Partnership that looked at "The Power of Generative AI and ChatGPT: What It Means for Tourism & Hospitality" here:
Want to learn more? Then give a listen, review the transcript, and check out all of today’s show notes. Enjoy!
Revisiting The Early Innings of AI in Marketing — Headlines and Show Notes
Show Notes and Links
- [Meta unveils a new large language model that can run on a single GPU [Updated] | Ars Technica](https://arstechnica.com/information-technology/2023/02/chatgpt-on-your-pc-meta-unveils-new-ai-model-that-can-run-on-a-single-gpu/)
- AI experts suggest 39% of time currently spent on chores could be automated within the next decade
- Nvidia predicts AI models one million times more powerful than ChatGPT within 10 years | PC Gamer
- Google announces major breakthrough that represents ‘significant shift’ in quantum computers | The Independent
- Microsoft tests ChatGPT for controlling robots • The Register
- Limitless Possibilities – AI Technology Generates Original Proteins From Scratch
- The Rise of AI Content Generation Stirs Brand Reputation Fears
- AI-created images lose U.S. copyrights in test for new technology | Reuters
- Some companies are already replacing workers with ChatGPT, despite warnings it shouldn’t be relied on for ‘anything important’
- Is ChatGPT Going to Steal Your Job? (Thinks Out Loud Episode 371)
- The End of Google? (Thinks Out Loud Episode 372)
- Will ChatGPT Kill Google? (Thinks Out Loud Episode 367)
- The Future of Content Marketing is Already Here (Thinks Out Loud Episode 350)
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Transcript: Revisiting The Early Innings of AI in Marketing
Well, hello again everyone, and welcome back to Thinks Out Loud, your source for all the digital expertise, your business. My name is Tim Peter. This is episode 374 of the Big Show, and I think we have a really cool episode for you today.
We Live in a World of Constant Change
First, can I just tell you how much I love what I get to do for a living?We continually see change in what we do. It is an amazing thing to work in digital and have the opportunity to learn and to grow, day after day, week after week, year after year. It’s just so much fun. I talked about this earlier this year in an episode called The Future is Already Here, and in another episode called The Most Important Trends in Marketing in 2023, and to a lesser extent a couple of weeks ago when identifying what we learned from Big Tech’s earnings so far this year.
AI and ChatGPT: Early Innings in Marketing
And of course, the thing that everybody’s talking about and learning about right now are artificial intelligence and large language models and tools like ChatGPT and how big a trend they are and how big a trend that they will be this year and next year and the year beyond. And I think that’s right.
I think that this is one of the most important trends that we’re going to have to deal with. The other thing that’s true, the reality is that we are in the earliest days of artificial intelligence, large language models and tools like ChatGPT in the workplace. We’re in the early innings of the game.
AI Ain’t New. But…
Yes, I know AI has been around a while. I know it’s embedded in a wide array of tools. What’s also true though is that unlike a laptop or a mobile phone, AI hasn’t been in the hands of most people in their day-to-day work for very long at all. Sure, some developers and data scientists use it every day, and it is very much available to people under the covers in tools from Google or Facebook or Microsoft or Salesforce.com or any of those folks, you know, Adobe. So there are some cool things out there.
But we’re beginning to see what it might look like when AI and large language models and tools like these are in everyone’s hands. Your entire team is learning ways to apply these tools in real time every day. and we have yet to begin to scratch the surface of all of the amazing and creative ways that people are going to put these tools to work.
We’re seeing some cool ideas, but to think that we’ve seen how people are going to use them every single day, you know, two years from now or five years from now, or 10 years from now, we just don’t know.
Ships and Shipwrecks
It reminds me then of the Paul Vaio quote that you have heard me use many, many times that when you build the ship, when you invent the ship, you invent the shipwreck.
First, the Ship…
There’s no two ways about it. When you get the good side, the bad side comes with it. And I want to talk about the ship a little bit first and how much room there is to grow. I’m going to share with you a handful of headlines just from the last few weeks to give you a sense of how much room for growth there still is.
How Meta Plans to Get in the Game
So obviously we’ve heard a lot about ChatGPT and “the new Bing” from Microsoft and OpenAI. Of course, we’ve heard about LaMDA and BART from Google. Well, as you might figure, many other members of Big Tech, many other members of the AGFAM, want to get in on this as well. So Meta unveiled a new large language model that can run on a single graphics processing unit, a single GPU. A GPU is the, is the underlying hardware that these systems all run on. And on Ars Technica, they write that quote, meta announced a new AI powered large language model called Llama-13B, that it claims can outperform OpenAI’s GPT-3 model, despite being 10 times smaller. The article goes on to say that “smaller sized AI models could lead to running ChatGPT style language assistance locally on devices such as PCs and smartphones.”
So think about how sophisticated and how cool we see something like ChatGPT are already. Now imagine you could just run it on your mobile phone locally with no connection to the internet. That’s crazy. That’s kind of like Moore’s Law in Action where we see, you know, either the power double every 18 months, or in this case you get the same power for half the cost. I’m going to say in this, in this specific case, half the computing power in, you know, a very short period.
AI Will Be 1 Million Times More Powerful in Ten Years… Maybe
If you want to take it to the other side, Nvidia, who is a big maker of GPUs, predicts that AI models will grow dramatically over the next 10 years. Uh, in the recent earnings call, PC Gamer reported that CEO Jensen Huang, there’s a quote, claimed “that NVIDIA’s GPUs had boosted AI processing performance by a factor of no less than 1 million in the last 10 years.”
And Huang continued by stating, “Over the course of the next 10 years, I hope, through new chips, new interconnects, new systems, new operating systems, new distributed computing algorithms, and new AI algorithms, and working with developers coming up with new models. I believe it’s going to accelerate AI by another million times.”
What? Another million?!? Again, that’s insane. Now, let’s be fair. Let’s be fair. Maybe he’s wrong. Maybe it’s only 10th, a 10th of that, so it’s not a million times accelerated. It’s only a hundred thousand times accelerated. Can you imagined what that looks like? Well, let me give you a couple of examples.
AI Will Power Robots and Eliminate Domestic Chores… Maybe
There are people who asserts, according to TechXplorer, experts predicted that on average, 39% of the time that people currently spend on any given domestic work task could be automated within the next 10 years.
Well, how could they do that? Well, according to the register, Microsoft has a project that’s testing ChatGPT for Controlling Robots. This is again, a quote. “The project defines a high level API that ChatGPT can understand and map it to lower level robot functions. Thereafter, the users wrote text prompts for ChatGPT describing task goals, specifying available functions, and setting task constraint. ChatGPT then responded by generating device applicable code to accomplish whatever simulation goal had been set.”
The idea is that a person conversing with ChatGPT can bug test robot directives until they work properly simply by conversing with it. How fricking cool is that?
I will answer my own question. The answer is way cool.
AI Can Also Develop Proteins and Cure Illness… Maybe
Oh wait, that’s not cool enough for you? Fine. Here’s another one. There’s a site called Limitless Possibilities. I admit this is not my core area of expertise, so I might be wrong about this, but they said in laboratory experiments, some AI developed a whole bunch of original proteins from scratch. And this is the quote “In laboratory experiments, some of these enzymes demonstrated efficacy comparable to natural enzymes, even when their artificially created amino acid sequences greatly deviated from any known natural protein.” Wait, what? We’re using AI to actually engineer proteins? You know that can be used in medical treatments.
Science Fiction in Real Life
This is like, this is science fiction come to life. This is the kind of thing that were put in science fiction novels and science fiction stories and science fiction movies or TV shows, and now they’re talking about where we might be, where we might be down the road.
Last one, last part of the ship side of this story.
The Independent out of the UK reported that Google announced a major breakthrough that represents a significant shift in quantum computers. Here’s a quote from the article. It said, “Dr. Julian Kelly, who’s the director of Quantum Hardware at Google’s Quantum AI, ‘The engineering constraints of building a quantum computer certainly are feasible. It’s a big challenge. It’s something that we have to work on, but by no means that blocks us from, for example, making a large scale machine.’"
Now, I said a moment ago, some of this sounds like science fiction, but I know a physicist, I talked to a physicist, who said that when physicists say something is theoretically possible, what they’re actually saying is it is possible. The rest is simply an engineering challenge.
Overestimate the Change in the Next Two Years, Underestimate the Change in the Next Ten
I’ll give you a real world for instance. The Nyquist-Shannon Theorem, which essentially led to digital audio, to compact discs, to sampling in modern music like hip hop to MP3s, that theorem dates to 1928 or so. We didn’t get commercial compact discs for another 45 years, roughly. You know, it was the early eighties before we started to see sampling, and we started to see digital audio really come into any kind of mainstream use. So the tech is there, the, the concepts are there, the science is there for many of these. It also means that some of these big breakthroughs may not be all that commercially imminent.
This is another place where Bill Gates aphorism comes into play, “We always overestimate the change in the next two years and underestimate the change in the next 10.” I think all of these news stories I told you are incredibly cool. They might also take a decade, half a decade at least, before people actually can put them to work in a commercially viable sense.
I’ve spent a lot of time with the new Bing, the AI powered version of Bing. It is awesome. I don’t think it’s going to take 10 years before it’s commercially viable. I do think it’s not commercially viable today. It’s buggy. It’s weird. It’s subject to bias. It’s got all kinds of problems because when you invent the ship, you invent the shipwreck.
So let’s talk about the shipwreck for a second. You know, I mentioned this over a bunch of recent episodes in terms of, you know, “Will ChatGPT Kill Google,” and an episode from a few weeks ago called “The End of Google?” Well, we’re seeing some of these problems come to light in the real world every day.
Brand Reputation Issues
For instance, Adweek has a fantastic story about how the rise of AI content generation stirs brand reputation fears. Are we going to see people use our brands, use our businesses information in ways that are troubling or can make our brands look poor, you know, make them look bad.
There was a story in Reuters how AI created images lost their US copyright. This is a quote from a letter written by the US Copyright Office that said, “The fact that Midjourney specific output cannot be predicted by users makes Midjourney different for copyright purposes than other tools used by artists.”
If you, the artist, can’t say what it is you’re going to get at the output, you don’t own that output. I’ve talked in past shows about artists deliberately trying to get AI tools to include copyrighted material from folks like Disney in their information, in the outputs they create, to trigger lawsuits from folks like Disney, right? Because the artists want their information, want their work to have copyright protection and not be able to be reused by AI.
I’m kind of okay with that. I mean, I’m a content creator myself. You probably don’t want the content you create for your business to be used by other folks, either in whole or in part, if you can avoid it.
Which again, these large language models are trained on information that exists in the world. They’re not making things up from scratch. They’re borrowing from what they’ve learned. So that’s a very real risk that needs to be addressed. And if you use content created by these tools, it’s entirely possible that the content you create with them itself will have no copyright protection. You won’t have the ability to actually own that in a legal sense.
That’s a very real shipwreck that most companies haven’t quite figured out what they’re going to do yet or how they’re going to address that.
Then of course there’s what might happen on the labor front. Now, I have talked about this a lot. I have argued that ChatGPT and AI will not steal your job, but that smart people who use AI will.
Of course, what I should have realized is that dumb people could use these tools too. I should have remembered that if you build an idiot proof system, the world will simply find us a new supply of idiots.
There’s an article on Yahoo Finance that says some companies, this is a quote, “Are already replacing workers with ChatGPT despite warnings, it shouldn’t be relied on for ‘anything important.’”
I mean… seriously. This is such a foolish idea at this point. Even if you’re getting sometimes good results, the risks that you are exposing your company to are really, really big. Remember, these tools have built in biases against people of color, against women, against all kinds of folks, because the underlying data so often does.
And as I just talked about, they’re not subject to copyright protection and they can hurt your brand. So this is not smart use of these tools. This is dumb.
You want to look at ways to incorporate AI alongside your team rather than replacing them all together. You want to look at ways to increase your team’s skills, to recognize, for instance, the bias and the other issues that could arise before you expose yourself to the risks of the shipwreck.
Pilots (Process and People)
So if we’ve got a ship and there’s the potential for a shipwreck, then we need to talk about one last thing and that one last thing is “the pilot.” Now you know this, you’ve done this many times. You do a test and learn exercise and you call it a pilot. “We’re conducting a pilot. We’re testing to see what works.”
But a pilot is also the person who comes on a ship and steers it into the harbor past rocky shores. You want to conduct tests, you want to conduct pilots to see what works for your business. But increasingly, I believe a pilot, as in the role, is key to your long-term success. Here, the people who can look ahead to see where the rocks and the reefs are, who can spot where you might run aground, are going to be so valuable over the near to midterm.
Sure, AI will improve over time as it learns from its mistakes. But it would be really good if you could minimize the downsides of those mistakes, or, I don’t know, avoid making them all together with proper planning, with a good pilot. That’s an enormous opportunity that we’re going to see that we are seeing emerged as companies start to look for ways to put these tools to use.
So the pilot in terms of the event, but the pilot in terms of the person. That’s what you want to be right now. Because we are in the early innings, we’ve got a lot of time ahead of us before we see how these are going to be used day to day.
Revisiting The Early Innings of AI in Marketing Conclusion
Yes, there are lots of opportunities for us to invent new ships.
That means as a consequence, we absolutely will invent new shipwrecks. So conduct tests, conduct pilots to see what works for your business and to minimize the risks that might exist of those shipwrecks, but also be a pilot. Look forward to see where the potential exists to run aground and think about how it is you can prevent that from happening in the first place.
Look ahead and keep thinking about where we’re going to end up two years from now, five years from now, 10 years from now. Because there’s a lot of opportunity here to really succeed, and there’s a lot of opportunity to run a ground. The key is to look forward, look ahead, plan well. And then you’ll be able to enjoy the ride.
Show Closing and Credits
Now looking at the clock on the wall, we are out of time for this week. I want to remind you that you can find the show notes for today’s episode, as well as an archive of all past episodes by going to timpeter.com/podcasts. Again, that’s timpeter.com/podcasts. Just look for episode 374.
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