Everyone is talking about AI, but what does the future hold? In a series of interviews we examine unexpected perspectives on the space.<\/em><\/p>\n One of the biggest questions in martech is how artificial intelligence will affect it. Not in five or 10 years, but right now. To try and find out, we are doing a series of interviews with experts in the field. Our first is with Chris Penn, co-founder and chief data scientist at TrustInsights.ai.<\/p>\n <\/p>\n Q: <\/strong>Because many, many marketers are still figuring out generative AI, what is an essential thing marketers need to understand about it?<\/p>\n A: <\/strong>These are language models. They\u2019re good at language, but, by default, then they\u2019re not good at things that are not language, like they can\u2019t count. They are terrible at math. But it turns out that language is the underpinning for pretty much everything. So even though it can\u2019t do math, it can write code because code is a language and code can run math.<\/p>\n What this means practically is that every software package and every software company out there that has either an internal scripting language or an API is or should be putting together a language model within their products.<\/p>\n Look at Adobe. It has its scripting language inside its products. And what has Adobe done? They\u2019ve integrated generative AI prompting in Firefly and their software. So when you interact with it, it is essentially taking your prompt and rewriting it to its own scripting language and then executing commands. So it\u2019s operationally better.\u00a0<\/p>\n Dig deeper: <\/em><\/strong>Decoding generative AI: How to build a basic genAI strategy for your marketing organization<\/em><\/strong><\/a><\/p>\n That\u2019s what Microsoft has done with everything. If you look at how Bing works, Bing does not ask the GPT4 model for knowledge. Bing asks us to translate into Bing queries that then go into Bing and then the results come back and has it rewrite those.<\/p>\n And so the big transition that\u2019s happening, and has to happen in the martech space now, is that if you\u2019ve got an API, you should have a language model talking to that API and that output should be exposed to the customer.<\/p>\n One of the first folks to do this was Dharmesh Shah over at HubSpot. I remember the day that GPT3 Turbo came out he was like, \u201cWe\u2019re putting this out, I\u2019m making a chatbot.\u201d And he demoed the alpha and he was like, \u201cYeah, it sucks. It\u2019s broken eight ways to Sunday. But this is where we know this is where it\u2019s going.\u201d<\/p>\n So if you are a martech company and you are not putting a generative prompting layer inside your software, you\u2019re done. Just sell the company now.<\/p>\n Q: <\/strong>OK, now that I know that, what should I know when using AI?<\/p>\n A: <\/strong>So there are two things that everybody needs to have to make the most of generative AI.\u00a0No. 1 is data because these tools work best with the data you give them. They\u2019re not as good at generating as they are at comparing \u2014 comparing and analyzing and stuff like that.\u00a0<\/p>\n Two is the quality and quantity of ideas that you have and you have to have both.\u00a0That is what is different. The skill doesn\u2019t matter anymore, right? If you have an idea for a song, but you can\u2019t play an instrument, fine, the machine will help you. It has the skill; you have to bring the idea when it comes to code.<\/p>\n I can say just from personal experience, I am coding things, coding things today at a pace that I would never have been able to do even six months ago. I wrote a recommendation engine in an hour and a half in Python, a language that I don\u2019t know how to code in and it works really well.<\/p>\n Now, here\u2019s the thing, I know what questions to ask because I have a domain understanding of the domain of how coding works. Even if I don\u2019t know the syntax, I know what this data structure should look like and please don\u2019t rerun this vector routine every single time. That\u2019s stupid, run it once, make a library store it.<\/p>\n Q: <\/strong>Many of us don\u2019t know that.<\/p>\n A: <\/strong>Yes. No one is teaching this. So this is one of the big issues right now. And it\u2019s going to contribute substantially to the problems that generative AI causes.\u00a0<\/p>\n Our society\u2019s education systems are already not preparing students for any of modern reality. And it\u2019s now made worse by the fact that many of the tasks that we associate with academic rigor are essentially moot, like writing term papers. A machine can write a better term paper than you can. Period. End of discussion.<\/p>\n And so critical thinking is one of those things that is just not taught. In fact \u2014 and this gets into tinfoil hat territory \u2014 the design of our education system is from the 1920s. Rockefeller<\/a>, Carnegie<\/a> and Mellon<\/a> basically helped to design the modern education system to make smart factory workers. And we never have evolved past that. And we are now seeing the limitations of that exposed with generative AI. It turns out that the factory worker mindset is also what AI is really good at.<\/p>\n So companies need to be thinking about how do we train employees to think critically? How do we train employees to be rapid idea generators and then partner with AI tools to bring those ideas to life quickly?<\/p>\n The tools give us agility, they give us speed, but they don\u2019t necessarily give us creative ideas because they\u2019re always a mathematical average of whatever we put into them. So that\u2019s where the big gaps are.<\/p>\n And the companies that are doing best with this right now are people who have a good bench of forward-thinking, gray-haired people. People who have hair that\u2019s colored like ours, but are not afraid of the technology and are willing to embrace the technology. So we bring our experience to the table combined with the power of the tools to generate incredible results that a junior person doesn\u2019t have the experience for, even if they have the technological savvy. That\u2019s the gap.\u00a0<\/p>\n Q: <\/strong>I have the right hair color and I\u2019m definitely a technophile: Do I need to learn coding?<\/p>\n A: <\/strong>Even though it\u2019s laborious, I actually think learning how to code is not a bad thing. There\u2019s one book in particular that I recommend that people read. It\u2019s called \u201cAutomate the Boring Stuff with Python.\u201d It\u2019s one of those books where you can read it, you don\u2019t need to actually do the coding examples because again, ChatGPT can do that, but it will introduce you to control structures, loops, data storage, file transformation stuff.<\/p>\n A: <\/strong>What new capabilities can we expect to see very soon?<\/p>\n Q: <\/strong>There are a few things that are happening right now. One is that the current multimodal models really are hack jobs. They\u2019re like essentially a bad ensemble kind of hooked together things. You can see this if you use ChatGPT with the DALL.E image generator. You can talk to it, but it clearly does not understand what it\u2019s looking at. There\u2019s no return path for it to look at the image it created and go, \u201cOh yeah, there actually are five people and you requested four in this image.\u201d So it\u2019s really stupid.<\/p>\n
![\"2024](\"https:\/\/i0.wp.com\/martech.org\/wp-content\/uploads\/2023\/12\/2024-car-sal-survey-v1-800x450_edited.jpg.webp?resize=800%2C450&ssl=1\"\/)
![\"2024](\"https:\/\/i0.wp.com\/martech.org\/wp-content\/uploads\/2023\/12\/2024-car-sal-survey-v1-800x450_edited.jpg.webp?resize=800%2C450&ssl=1\")
<\/figure>\n