Mesh Digital LLC's - Insights: AI Small Language Models (SLMs)

[00:00:00] Okay, so picture this. You're diving headfirst into this whole world of AI, right? And bam, you're hit with these massive supercomputer level setups. Impressive. Absolutely. But what if I told you that you could get those same crazy good results with something way smaller? Well, nimbler, you know, something that just fits your needs perfectly. And that's what we're digging into today. Small language models or SLMs for short. They're really shaking things up in the AI world and for good reason.

[00:00:30] We've got these two awesome articles from Mesh Digital Insights by Michael D. Kleinberg. Oh, and one's co-authored with John Gugliotti. They'll be our guides for this deep dive. And get this, turns out bigger isn't always better when it comes to AI. Who knew, right? But seriously, all those giant models everyone's going on about, well, they're starting to show some cracks.

[00:00:45] Yeah, you're right. You see, we keep building these bigger and bigger models. And don't get me wrong, it's impressive stuff. But we're kind of hitting this point of diminishing returns. You know, there's some wild research on this. Like there was this 2021 study by Patterson and their team.

[00:00:59] That found that treating these huge AI models, it just eats up way more energy. Way more than their smaller laser focused counterparts. So that's where these SLMs come in. Efficiency, that's their game. And trust me, in a world obsessed with AI giants, that's a breath of fresh air.

[00:01:16] Right. It's like, why use a sledgehammer when you need a scalpel? You know, sometimes you just need that focus power, not just brute force. And let's be real for a second. Efficiency isn't just about saving energy. It's about saving cash too, which let's face it, any business loves to hear.

[00:01:32] Absolutely. SLMs, they're just built to be easier on the budget when it comes to computing power. Less data to learn, fewer parameters. Think of those as like the settings inside the AI. And they just need less overall processing power. What's that mean for you? Lower development costs, faster results. Even smaller businesses can jump into AI without, you know, breaking the bank.

[00:01:54] This reminds me of something Andrew Rang said. You know, he's a big name in AI back in 2020. Actually, Kleinberg and Gugliotti. They quote him in The Power of Going Small. He said, it's not about the size of the model. It's about the size of the data. And that's huge. It's not about just throwing everything at the AI. It's about using the data that actually matters. The stuff that gets you where you need to go.

[00:02:15] You got it. Work smarter, not harder, right? But hold on. There's this other big advantage Kleinberg and Gugliotti talk about that's got me pumped. Speed. These SLMs, they're not just lean. They are lightning fast.

[00:02:26] They are. Less complexity means you can train them and deploy them way faster than those bulky LLMs. Yeah. And in the business world where everything's moving at warp speed. Yeah. That agility is priceless.

[00:02:37] It's like having a race car versus, I don't know, a freight train. I mean, they can both get you there, but when it's a tight market, sometimes you need that speed.

[00:02:46] Exactly. That whole time to market advantage, that can be a game changer, whether you're just starting out or you're already established and want to stay ahead of the curve.

[00:02:54] Now, speed's great and all, but it's only good if you're actually, you know, solving problems with it. And that's where things get interesting with SLMs.

[00:03:02] Absolutely. One of the coolest things about SLMs is how adaptable they are. Train them on smaller, specific data sets. Perfect for tackling those really specific tasks.

[00:03:13] Like having a whole team of specialists instead of just one general doctor. Right. And in their article, The Power of Going Small, Kleinberg and Gugliotti give some really neat examples.

[00:03:23] They were talking about SLMs being used for like, you know, going through legal documents, figuring out what's what in health care.

[00:03:29] Even something as nuanced as, well, figuring out what customers really think from online reviews and stuff.

[00:03:35] It all comes down to that laser focus. SLMs let businesses build AI that actually fits their needs, gives them a real leg up on the competition, still using those generic approaches.

[00:03:47] Work smarter, not harder. It can make all the difference.

[00:03:50] Exactly. Think about it. Everyone's trying to figure out AI, right? But SLMs, they let you stand out. They let you create something powerful, something really unique.

[00:04:00] It's not just about keeping up. It's about, you know, blowing past everyone else. But before we get ahead of ourselves, we got to talk about the elephant in the room, especially these days. And that's privacy. This is where SLMs, they really have an edge.

[00:04:13] You're telling me. Data privacy, it's a big deal for everyone these days, right? And as Kleinberg and Gugliotti point out, because SLMs use these smaller, more, well, curated data sets, it means more control over all that sensitive information.

[00:04:26] And they've got research to back it up. In The Power of Going Small, they talk about this 2021 study by Bomasani and a few others.

[00:04:33] And it really highlights how SLMs offer the safer, more responsible way of handling data, especially when things are, you know, sensitive.

[00:04:41] It's about finding that balance, innovation and responsibility. That's what we should all be aiming for, wouldn't you say?

[00:04:47] Absolutely. But there's another thing Kleinberg and Gugliotti bring up, the commoditization of LLMs. Sounds kind of intimidating, doesn't it?

[00:04:57] Don't worry. It's not as bad as it sounds. Basically, more companies are getting into AI, which means those big language models are easier to get a hold of through APIs and platforms, stuff like that.

[00:05:07] Imagine if like a really popular brand of tools was suddenly available everywhere. Great for getting your hands on them, right?

[00:05:14] But it also means it's trickier to stand out from the crowd, you know, with what you build.

[00:05:19] So it's like everyone having the same ingredients, right? But how do you make your dish special? How do you stand out?

[00:05:25] Now that is a great analogy. And that's SLMs for you. They're that secret ingredient, you know, they let you build something truly unique.

[00:05:33] Instead of using the same tools as everyone else, you build something special, something that gives you an edge.

[00:05:38] Exactly. You're not just following a recipe anymore. You're like a culinary artist.

[00:05:42] Now that is a thought I can get behind. But what about the future? Do Kleinberg and Gugliotti think SLMs are going to like take over completely? Or is it more complicated than that?

[00:05:53] It's hardly ever a case of one thing winning out, you know, the future of AI. It's going to be a mix of everything, different tools for different jobs.

[00:06:01] So it's less about picking sides and more about like building a killer toolkit.

[00:06:05] Exactly. I mean, there are always times where you just need the raw power of a big LLM.

[00:06:10] But for a lot of stuff, especially if you need precision, efficiency, and you want to be careful with GATA, SLMs are going to be key.

[00:06:16] It really comes down to this, you know, the right tool for the job. That's what it's all about.

[00:06:22] We're not talking about picking teams here, team LLM versus team SLM.

[00:06:26] It's about, well, understanding what each one does best and then, you know, using them together to get the best results.

[00:06:32] Like having a whole toolkit instead of just like one wrench you try to use for everything, right?

[00:06:37] Exactly. So picture this. You're using a big, powerful LLM like say GPT-4 or even Gemini to brainstorm a marketing campaign.

[00:06:45] You've got all this consumer data, right? You feed it in.

[00:06:47] But then you bring in one of these smaller specialized SLMs, one that's laser focused on your specific audience to really polish things up.

[00:06:56] The language, the tone, all that.

[00:06:58] So you've got the LLM for the big ideas and then the SLM to make it sing. I like it.

[00:07:02] Exactly. And think about this. This goes way beyond just marketing, right?

[00:07:06] Imagine analyzing tons of legal documents with an LLM, spotting all the important stuff, the risks, the opportunities.

[00:07:12] But then you bring in these SLMs trained specifically for that kind of work, maybe on contract law, maybe intellectual property to really dig deep.

[00:07:20] So it's like having a whole team of expert lawyers, each one with their own specialty, but they're all working together to crack this case.

[00:07:27] Exactly. Or even in health care. Imagine an LLM that's going through all this patient data, right?

[00:07:32] Trying to find early signs of problems. And then bam, SLMs trained on specific conditions.

[00:07:36] They step in, give more precise diagnoses, treatment recommendations, and they keep all that data safe and sound.

[00:07:43] This hybrid approach, it's like opening up a whole new world for AI, don't you think?

[00:07:47] It's not just about doing things faster. It's about like doing them better, way better.

[00:07:51] You hit it right on the head. We got to remember, this isn't about replacing us.

[00:07:55] You know, it's about giving us the tools to make smarter, faster decisions with more confidence.

[00:08:01] Work smarter, not harder, right? That's what AI is all about.

[00:08:04] Now, for our listeners out there who are thinking, okay, this SLM thing sounds cool, but where do I even start?

[00:08:10] What should they be thinking about?

[00:08:11] That is the question, isn't it? I think the first thing is, you got to know what you want.

[00:08:16] What are you trying to solve? What's the problem that AI can help you with?

[00:08:21] So start with the problem, not the tech.

[00:08:23] Exactly. Once you know what you're aiming for, then you can start looking at what's out there.

[00:08:29] There are a bunch of open source SLMs.

[00:08:31] Kleinberg mentioned some in his other article, small language models, SLMs, big impact.

[00:08:37] They're a great place to begin.

[00:08:38] And in that article, he really breaks down all those open source options.

[00:08:43] Distilbert, Tinybert, even Albert.

[00:08:46] It's a lot, but he makes it really easy to understand.

[00:08:48] That's the beauty of open source, you know?

[00:08:50] You can test things out, see what works without having to like remortgage your house.

[00:08:55] It's like a test drive before you buy the car.

[00:08:57] Perfect analogy.

[00:08:58] And don't forget about data. What do you have? What can you get? That's key for any SLM project.

[00:09:04] Size of the data, right? That's what matters.

[00:09:06] You got it. And, you know, having the right people on board, that's important too.

[00:09:10] Building this stuff, it takes know-how.

[00:09:12] So maybe build a team or find some experts who can, you know, show you the ropes.

[00:09:17] Okay, so let's say you've got all that figured out.

[00:09:19] How do you actually use SLMs?

[00:09:21] Like in the real world, not just playing around.

[00:09:23] That's where things get interesting.

[00:09:25] The good news is, because SLMs are smaller, you can often use them in more places.

[00:09:31] Your own servers, even those little edge devices.

[00:09:34] More control, more privacy, music to my ears.

[00:09:38] Got it.

[00:09:38] And depending on what you're doing, you might be able to slip those SLMs right into your existing setup.

[00:09:45] Use an API, something like that.

[00:09:47] I don't need to reinvent the wheel, right? Use what you've got.

[00:09:49] Exactly. But remember, just because you set it up doesn't mean you can forget about it, you know?

[00:09:54] You got to keep an eye on things. How's it performing? Does it need retraining? Maybe treat things as you go.

[00:09:59] That agility we talked about, being able to adapt, that's not just a bonus, it's essential.

[00:10:04] 100%.

[00:10:05] Right.

[00:10:05] And as you get more comfortable, you can start looking at even cooler stuff, like federated learning.

[00:10:10] Okay, now you're just showing off federated learning. Tell me more.

[00:10:12] Oh, it's fascinating. Basically, you can have a bunch of SLMs all learning from each other, but get this. They never actually share their data.

[00:10:22] Whoa. Talk about privacy. And collaboration. That's next level.

[00:10:27] It really is. It means even competitors could potentially work together, share insights without, you know, giving away the farm. Think of the possibility.

[00:10:36] It's like this whole world of collaborative AI, but it's still secure. Mind-blowing.

[00:10:41] And that's what gets me excited about SLMs. It's not just about building something bigger. It's about building something smarter, something that lets us work together in new ways safely.

[00:10:50] Okay, so we've talked about SLMs and how they can shake things up, but let's get real. How are businesses actually using these things to get ahead?

[00:10:59] Well, customer service is a big one. Kleinberg and Gugliotti, they talk about companies using SLMs to build, like, super-powered chatbots, the kind that actually know what they're talking about.

[00:11:09] Makes sense. Instead of some generic bot that tries to do it all, you've got one that's laser-focused on, you know, what you actually sell, what your customers actually ask about.

[00:11:18] Right. And because you can train SLMs so quickly on smaller data sets, you can keep those chatbots up to date.

[00:11:25] Customer needs change. Market shifts. No problem. Adapt on the fly.

[00:11:29] So faster responses, but also, like, way better responses. Customers are happy. Everybody wins.

[00:11:34] Exactly. And think about it. All those easy questions the bot handles. That means you're human agents. They can focus on the tough stuff. The stuff where they really shine.

[00:11:44] Yeah, that's what I call a win-win. Now, what about other fields? Any cool, unexpected places where SLMs are showing up?

[00:11:51] Kleinberg and Gugliotti, they had this really interesting bid about law. Apparently, some firms are using SLMs to go through contracts, legal documents, all that, to find risks, opportunities, you name it.

[00:12:02] Wait, so AI that can actually understand legal mumbo-jumbo? That's got to be tough to pull off.

[00:12:06] It is, but that's where specialization comes in. These SLMs are trained on tons and tons of legal text.

[00:12:12] They learn to see the patterns, the weird stuff, things even a seasoned lawyer might miss.

[00:12:17] So not replacing lawyers, but giving them, like, a superpower.

[00:12:20] Exactly. And they can do it way faster than us mere mortals. Speed up those big deals, contract stuff, even just routine reviews. Huge time saver.

[00:12:29] And we all know time is money, especially in the legal world.

[00:12:32] Tell me about it. And then there's healthcare. We talked about it before, but there's so much potential there.

[00:12:37] Yeah, let's dig in a little deeper. What are we talking about specifically? What are they doing with SLMs in healthcare right now?

[00:12:43] One of the most exciting things is medical imaging. Imagine.

[00:12:47] SLMs, they're trained to analyze x-rays, MRIs, all that, looking for those subtle signs of disease, any abnormalities.

[00:12:54] So it's like having this expert second opinion right there with the doctor, helping make sure nothing gets missed.

[00:13:01] You got it. And they're so much faster than humans. For some conditions, getting that diagnosis quickly, that can make all the difference.

[00:13:07] Not just speed, but you're also hopefully, you know, reducing the chance of human error, which in healthcare, that's huge.

[00:13:14] No doubt. And it goes beyond just diagnostics.

[00:13:16] SLMs are helping personalize treatment plans, speed up research for new drugs, even predict how patients are going to respond to treatments.

[00:13:25] It's incredible to think about. These technologies are already making a difference, and we're just getting started.

[00:13:30] It's just the beginning. And one of the big takeaways from Kleinberg and Gugliotti, it's this.

[00:13:36] SLMs, they're not just for the big guys anymore.

[00:13:39] Right. Democratization. That's what we were talking about before.

[00:13:42] Exactly. SLMs are becoming more affordable, easier to use. So now startups, small businesses, even just individuals with a good idea, they can get in on the action.

[00:13:52] It's like suddenly everyone can have access to this powerful tech. Imagine what people will come up with.

[00:13:57] That's what I'm talking about. It's this whole new world of possibilities for every industry everywhere.

[00:14:02] So much potential. And that's why it's so important to stay curious, you know.

[00:14:07] Yeah.

[00:14:07] Stay informed. This stuff is going to affect all of us.

[00:14:10] I couldn't agree more. The future of AI, it's not set in stone. We're building it right now with every choice we make.

[00:14:18] Absolutely. Well, folks, we've covered a lot of ground today, diving deep into the world of small language models.

[00:14:24] Big thanks to all of you for listening in. If you're hungry for more, we'll have links to those articles by Michael D. Kleinberg and John Gugliotti in the show notes.

[00:14:31] And until next time, keep exploring, keep learning, and keep asking those big questions.