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ChatGPT, Claude, Gemini, Co-Pilot or Llama
WHICH ONE IS THE BEST CHATBOT FOR CONSULTANTS?
(c) Andrew Lawless LLC
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RESOURCES
Ai-First for Boutique Consultants: https://wwww.teamlawless.com
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SUMMARY
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This episode explores using AI chatbots and tools for consultants, comparing the capabilities of various platforms like ChatGPT, Claude, Copilot, Gemini, and the open-source Llama model. The key findings include:
- Each AI tool has unique strengths, from ChatGPT's broad intelligence and reasoning to Claude's focus on ethics and safety. Consultants should choose tools based on their specific needs.
- While the AI tools demonstrate high consistency in many tasks, they struggle with spatial reasoning and multi-step problem solving, highlighting the continued importance of human expertise.
- The open-source Llama model offers consultants the ability to customize and create unique AI-powered solutions, but requires more technical expertise to implement effectively.
Overall, the episode emphasizes the strategic integration of AI tools as complementary partners to human consultants, rather than replacements, in order to leverage their capabilities while remaining aware of their limitations.
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TRANSCRIPT
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Andrew's Mindmate (00:00):
Welcome back to the Deep Dive. Today we're diving into something that I know is on everyone's mind these days, AI chatbots, and more importantly how they're changing the game for consultants like you. We've got some really interesting research here from the University of Florida and Florida International University, and they're comparing all the top AI tools out there. Chat, GPT, Claude Copilot, Gemini Plus. We'll take a look at this up and comer called Llama. It's open source, which is interesting. So get ready to figure out which AI tool is the best fit for you, because we're going to break it all down. We'll help you understand how to integrate these tools into your consulting practice.
Steph’s Digital Ambassador (00:37):
It's funny, everyone's always trying to figure out which AI is the best, but this research actually found that each tool has its own strengths and the performance differences. Well, they might be smaller than you think.
Andrew's Mindmate (00:47):
So it's not about finding the one AI to rule them all. It's more about choosing the right. Cool for the job.
Steph’s Digital Ambassador (00:53):
Exactly. The researchers put these chat bots through a gauntlet of 76 different tasks, everything from coding and mapping to spatial reasoning and even ethical decision making. And what they found is that the best tool really boils down to what you actually need it to do.
Andrew's Mindmate (01:09):
So let's say I'm a strategy consultant. Which AI should I be using?
Steph’s Digital Ambassador (01:13):
Well, the research points to both chat GPT and Claude as great options for strategy consulting, but for different reasons.
Andrew's Mindmate (01:20):
Okay, I'm intrigued. What makes them stand out?
Steph’s Digital Ambassador (01:22):
Well, chat GT four, especially the newest version that came out in August, 2024. It consistently scores really high in overall intelligence and reasoning. It's fantastic for doing broad analysis, coming up with new ideas, generating content, even drafting proposals. Think of it like having a super smart intern who can pull together a first draft of anything.
Andrew's Mindmate (01:42):
That sounds like it could save consultants a ton of time. But what about accuracy? You mentioned earlier that it's important to verify the output of these AI tools. Is chat GPT prone to making mistakes?
Steph’s Digital Ambassador (01:52):
Well, you always want to double check the work of any ai, even the most advanced ones. They can still make mistakes, especially when you're dealing with very specialized or nuanced information. So think of chat PT as a brilliant, but maybe slightly overconfident intern. It's always good to have a human eye on things just in case
Andrew's Mindmate (02:11):
Makes sense. So always good to double check. Okay. What about Claude? What makes it a good fit for strategy consulting?
Steph’s Digital Ambassador (02:17):
Claude's Superpower is really in ethics and safety. It's designed to generate unbiased outputs and to give you detailed explanations for its reasoning. In fact, the research found that Claude's responses were often up to 70% more comprehensive than the other tools.
Andrew's Mindmate (02:32):
So for consultants who are working in those compliance heavy fields like healthcare or finance, Claude sounds like it could be really valuable.
Steph’s Digital Ambassador (02:39):
Absolutely. Especially if you're dealing with sensitive data or building ethical frameworks, Claude can really help you navigate those complexities.
Andrew's Mindmate (02:46):
Okay, so we've got chatt PT for brainstorming and initial drafts and clawed for a more thorough, ethically informed analysis. What about copilot? Where does that fit into the picture?
Steph’s Digital Ambassador (02:57):
Copilot? This is Microsoft's AI tool, and it's all about efficiency and integration. It's built right into Microsoft 365, which is a huge plus for a lot of consultants who basically live in Word, Excel and PowerPoint.
Andrew's Mindmate (03:10):
Now, this is where it gets really interesting for me. I'm always looking for ways to be more efficient. What kinds of things can copilot actually do?
Steph’s Digital Ambassador (03:18):
It can automate a ton of those little routine tasks that eat up your time, generating reports, analyzing data in Excel, even creating presentations. It can even help you write code, which is really useful if you're working on any technical projects.
Andrew's Mindmate (03:31):
Okay. Copilot is definitely going on my list of tools to check out. Now, we can't forget about Gemini. That's been generating a lot of buzz lately. What makes Gemini so
Steph’s Digital Ambassador (03:39):
Special? Well, Gemini is Google's entry into the AI chatbot arena, and it's really known for its multimodal capabilities. Basically, it can work seamlessly with both text A and D visuals.
Andrew's Mindmate (03:49):
So it's more than just a chatbot. It's like a visual storyteller.
Steph’s Digital Ambassador (03:52):
You got it. Gemini really excels at creating dynamic presentations, interactive dashboards, any client facing deliverable where you want to combine data and visuals to make a bigger impact.
Andrew's Mindmate (04:04):
Wow. Think the possibilities for client workshops and presentations. But wait, there's one more tool we need to talk about, right? What about Llama?
Steph’s Digital Ambassador (04:11):
Ah, yes, llama. This is where things get really interesting. For those of you who have very specific or niche needs, or if you have some in-house tech expertise, this one could be a real game changer.
Andrew's Mindmate (04:23):
Okay, I'm hooked. Tell me more about Llama and why it's such a potential game changer.
Steph’s Digital Ambassador (04:27):
So Llama was developed by Meta and it's an open source language model. What that means is, unlike the other tools we talked about, you have complete control over llama. You can customize it to meet your client's specific needs. You can even create your own proprietary tools using it.
Andrew's Mindmate (04:41):
So for consultants who work in those specialized industries or who really want to build unique AI solutions, llama sounds like it has a ton of potential, but it also sounds like you need a little bit more technical to really unlock its power.
Steph’s Digital Ambassador (04:54):
That's true. Llama does require some technical expertise to really train it and deploy it effectively. It's not as simple as those plug and play commercial tools. But for those of you with the technical skills, it offers a ton of flexibility and customization.
Andrew's Mindmate (05:08):
It sounds like we've got a lot to unpack here. We've got these big players like Chat, GPT and Claude. We've got more specialized tools like Copilot and Gemini, and then we've got this wildcard llama, which seems like it has a ton of potential, but requires a bit more technical savvy.
Steph’s Digital Ambassador (05:23):
You got it. And the key takeaway here is that there's no one right answer. There is no one size fits all when it comes to AI for consultants.
Andrew's Mindmate (05:32):
So how do we figure out which tool is the best fit for us for our specific tasks?
Steph’s Digital Ambassador (05:37):
Well, that's what we're going to dive into next. We'll take a closer look at the research and we'll see how each of these AI tools performs on different types of tasks from coding and data analysis to strategy and even creative problem solving.
Andrew's Mindmate (05:50):
It sounds like we're about to get into the nitty gritty. I'm ready to see how these AI tools stack up against each other in the real world. So stick with us because in the next part of our deep dive, we'll reveal which AI chatbot excels at which tasks, and we'll show you how you can start integrating them into your consulting practice today.
Steph’s Digital Ambassador (06:08):
All right. So we've talked about these AI tools in a general sense, but let's get down to the nitty gritty. How do they actually perform?
Andrew's Mindmate (06:15):
Yeah, let's see how they stack up against each other.
Steph’s Digital Ambassador (06:17):
Well, this research actually put them head to head on a bunch of different tasks, and one of the interesting things they found was that the tools were surprisingly consistent in their outputs.
Andrew's Mindmate (06:26):
What do you mean by consistent?
Steph’s Digital Ambassador (06:27):
Well, they basically ran each task twice to see if the AI would come up with the same answer both times. And for most of the tasks, the matching rate was over 80%.
Andrew's Mindmate (06:36):
Oh, wow. So that means if I'm using chat GPT to analyze some market data, for example, I can be pretty confident that I'm going to get reliable, repeatable results.
Steph’s Digital Ambassador (06:47):
Exactly. For those kinds of routine tasks, these AI tools can be super reliable, and that's a huge plus, especially for consultants who are all about efficiency, but there's a catch. The consistency actually varied depending on the type of task.
Andrew's Mindmate (07:01):
Oh, interesting. So where did the AI tools hit a snag? What were some of the tasks that they struggled with
Steph’s Digital Ambassador (07:06):
Mapping tasks? Those turned out to be a real challenge across the board. The average success rate for mapping task, it was only 25%. And Gini, well, Gemini actually failed to complete any of the mapping tasks.
Andrew's Mindmate (07:17):
Wow, that's a pretty big drop from that 80% consistency. We were just talking about. Why do you think mapping is so tricky for these AI tools?
Steph’s Digital Ambassador (07:25):
It's probably because mapping requires such a specific skillset. You need a deep understanding of spatial relationships, data visualization techniques, and often you need to be able to interact with those external APIs and libraries. It seems like those are areas where even the most advanced AI tools still need some work.
Andrew's Mindmate (07:43):
So for consultants who are doing a lot of mapping, it sounds like it's still really important to have that human expertise involved. Okay. What about coding? How did the AI tools do on the coding challenges?
Steph’s Digital Ambassador (07:54):
Copilot, which is Microsoft's AI tool, really excelled in coding tasks. It had a 70% success rate. It actually even outperformed GPT-4 on coding, which is pretty interesting.
Andrew's Mindmate (08:06):
Why do you think copilot was so good at coding?
Steph’s Digital Ambassador (08:09):
I think it has a lot to do with access to data. Copilots deeply integrated with GitHub, which Microsoft bought a few years ago, and that gives it a huge advantage because it's been trained on such a massive amount of code
Andrew's Mindmate (08:21):
That makes sense. The more code it's seen, the better it should be at writing new code. Right.
Steph’s Digital Ambassador (08:25):
And GPT-4 was no slouch either, especially when it came to explaining existing code, it had a 100% success rate in that category.
Andrew's Mindmate (08:33):
So even if it's not the best at writing brand new code from scratch, it can still be really helpful for understanding and explaining complex code, which is a valuable skill in itself, especially when you're working with a client's existing systems.
Steph’s Digital Ambassador (08:45):
Absolutely, and that's a great example of how these tools often have strengths that compliment each other. You might use copilot to help you generate some new code, and then you could turn to GPT-4 to help explain and document that code.
Andrew's Mindmate (08:58):
Interesting. What about Claude? How did Claude do the coding tasks?
Steph’s Digital Ambassador (09:01):
Claude's real strength in coding wasn't so much in writing code, but it was really good at generating documentation. It's like having an AI assistant that can create those detailed technical documents that no one really enjoys writing, but that are essential for any project.
Andrew's Mindmate (09:18):
It sounds like each AI tool has its own unique strengths, even within a category like coding. It's not about finding the one perfect tool, but more about building a toolkit of AI assistance that can support different aspects of your work.
Steph’s Digital Ambassador (09:31):
Yes, and I think that's a really important point. It's not enough to just know that chat GPT is good at writing or copilot can code. You really need to dig deeper and understand those nuances of each tool to really leverage them effectively.
Andrew's Mindmate (09:44):
It's all about understanding the strengths and limitations of each tool and using them strategically.
Steph’s Digital Ambassador (09:48):
Exactly. And speaking of limitations, we've talked a lot about what these tools can do well, but I think it's important to also talk about where they fall short.
Andrew's Mindmate (09:56):
Yeah. Let's get real about the limitations of ai. Where do these tools struggle?
Steph’s Digital Ambassador (10:00):
Well, one area where the research really highlighted some challenges was in spatial reasoning tasks.
Andrew's Mindmate (10:05):
Okay. Spatial reasoning. What exactly does that mean?
Steph’s Digital Ambassador (10:08):
It refers to the ability to understand and manipulate spatial relationships. So things like visualizing objects in three dimensions or solving complex geometric problems. For example, one of the tasks that they gave the ais in this research was to place six xs on a tic-tac toe board without creating a three in a row in any direction.
Andrew's Mindmate (10:28):
So that sounds like a relatively simple task, something that a human could do pretty easily.
Steph’s Digital Ambassador (10:32):
But surprisingly, all four of the tools that we've discussed actually failed this task. GPT-4 was only able to solve two out of 10 spatial reasoning tasks correctly. And even llama the open source one only solved one out of 10.
Andrew's Mindmate (10:45):
Wow, that's interesting. It really just highlights that even with all the advancements we've seen in ai, it still has its limits when it comes to replicating those complexities of human intelligence.
Steph’s Digital Ambassador (10:55):
Exactly. And it's a good reminder that these tools are most effective when they're working as partners to human expertise, not replacements.
Andrew's Mindmate (11:03):
So bottom line, these AI tools are powerful, but we still need to be aware of their limitations and use them strategically.
Steph’s Digital Ambassador (11:10):
Absolutely. And another area where the research found limitations was in multi-step problem solving.
Andrew's Mindmate (11:17):
Can you give me an example of what you mean by multi-step problem solving?
Steph’s Digital Ambassador (11:20):
Sure. Imagine you're a consultant and you're working on a supply chain optimization project for a client. You might need to gather data from multiple sources, then clean and analyze that data, then develop a model to identify bottlenecks and inefficiencies, and finally present your findings and recommendations in a clear and compelling way.
Andrew's Mindmate (11:39):
So that's definitely a multi-step process with a lot of moving parts.
Steph’s Digital Ambassador (11:43):
And while AI tools can definitely be helpful for those individual steps in the process, like gathering data or creating visualizations when it comes to orchestrating that entire workflow and making those higher level strategic decisions, that's still where human expertise is really essential.
Andrew's Mindmate (12:01):
So it's kind of like having a team of really skilled specialists, but you still need a manager to coordinate their efforts and make sure that everything's moving in the right direction.
Steph’s Digital Ambassador (12:08):
Exactly, and that's why it's so important for consultants to stay ahead of the curve when it comes to ai. These tools are evolving rapidly, but they're not going to eliminate the need for human expertise strategy and critical thinking.
Andrew's Mindmate (12:20):
Okay. This has been incredibly helpful in understanding the potential, but also the limitations of AI for consultants. So it sounds like these tools can be super powerful, but we need to use them strategically, and we always need to remember that the humans are still the ones calling the shots.
Steph’s Digital Ambassador (12:38):
Couldn't have said it better myself. And with that in mind, I think it's time we shift gears and take a closer look at that wild card we mentioned earlier, the open source llama.
Andrew's Mindmate (12:46):
Yes. Let's talk llama. I'm really intrigued by its potential for consultants, especially those who are looking for a way to create something truly unique and differentiate themselves in the market. So in this final part of our deep dive, we'll explore the world of open source ai and we'll see how llama can empower consultants to take their practice to the next level. So we've covered those big names in AI like Chat, GPT and Claude, and we've even touched on some of the more specialized tools like copilot and Gemini. But now it's time to talk about llama. I'm really excited to dive into this because it feels like we're about to unlock some serious next level stuff here.
Steph’s Digital Ambassador (13:26):
Llama is definitely in a league of its own. It's this open source language model that has so much potential for consultants, especially for those of you who are looking to create something truly unique and custom tailored to your needs.
Andrew's Mindmate (13:38):
Now, I know you've thrown around the term open source before, but for those of us who aren't coding wizards, can you break that down a bit? What does it actually mean in practical terms?
Steph’s Digital Ambassador (13:47):
Sure. It can sound a little intimidating, but think of it this way. With those commercial AI tools, you're essentially buying a finished product, right? It does what it does, and you can't really change it. But with open source, it's like you're getting the wrong ingredients in the recipe. You have the freedom to experiment, to tweak things, and to really create something entirely your own.
Andrew's Mindmate (14:08):
So it's the difference between buying a pre-made meal and having the flexibility to cook with whatever ingredients you want and adjust the recipe to your liking.
Steph’s Digital Ambassador (14:16):
Exactly. You got it. With Llama, you have complete control. There are no licensing fees, no restrictions. You decide what data it's trained on, how you fine tune it and how you deploy it.
Andrew's Mindmate (14:27):
Okay. So I'm starting to see the appeal here, but I'm also imagining a bit of a learning curve. So how much technical expertise do you actually need to make llama work for you?
Steph’s Digital Ambassador (14:37):
That's a fair point. LAMA does require a bit more technical know-how than those plug and play commercial tools you or someone on your team needs to be comfortable with coding and things like machine learning concepts and data management.
Andrew's Mindmate (14:49):
So maybe not something you just jump into if you're just starting to explore ai, but if you're really serious about building those custom solutions, it sounds like Llama might be the way to go.
Steph’s Digital Ambassador (14:58):
I think that's a great assessment if you're willing to invest the time to learn. The Ropes Llama gives you a level of control and customization that you simply can't get with those commercial tools.
Andrew's Mindmate (15:09):
So let's say I'm a consultant and I have the technical chops to work with Llama. What are some real world examples of the kinds of solutions I could actually build?
Steph’s Digital Ambassador (15:18):
Well, the possibilities are vast, and that's what's so exciting about it. Let's say you're a financial consultant. You could train llama on your client's portfolio data market trends, their risk tolerance, all of that, and create a truly personalized investment advisor.
Andrew's Mindmate (15:34):
Wow. So no more generic advice. It's all tailored to the individual client's needs and goals.
Steph’s Digital Ambassador (15:39):
Exactly. Or imagine you're a consultant working in manufacturing. You could train LAMA on your client's operational data, identify inefficiencies, streamline production, and maybe even predict equipment failures before they happen.
Andrew's Mindmate (15:52):
It's like giving your clients an AI powered crystal ball for their business.
Steph’s Digital Ambassador (15:56):
I like that. That's a great way to put it. And because you have that control over every aspect of the model, you can make sure that it's perfectly aligned with your client's needs and any ethical considerations.
Andrew's Mindmate (16:07):
That seems especially crucial in those industries that have really strict regulations or sensitive data.
Steph’s Digital Ambassador (16:12):
Absolutely. And there's another big advantage of Llama that we haven't even talked about yet. Cost effectiveness.
Andrew's Mindmate (16:18):
Okay. Now you've really got my attention.
Steph’s Digital Ambassador (16:20):
Yeah.
Andrew's Mindmate (16:21):
Tell me more about how llama can help consultants save money.
Steph’s Digital Ambassador (16:25):
Well, while the initial investment in getting that technical expertise might be a little higher over the long run, LAMA can actually be much more cost effective than those commercial AI tools, especially if you're using them a lot or for very specific things.
Andrew's Mindmate (16:38):
So it's kind of like the difference between buying a suit off the rack and having one custom tailored. The initial cost might be a little higher, but the fit is going to be perfect and it's going to last you a lot longer.
Steph’s Digital Ambassador (16:50):
That's a great way to think about it. And as you build more and more custom solutions with Llama, you're essentially creating valuable assets for your own consulting practice. You're not just paying for a service, you're building something that you own that you can leverage for years to come.
Andrew's Mindmate (17:04):
It sounds like Llama has the potential to really empower consultants, especially those in those niche or specialized fields to set themselves apart, offer something truly unique and even tap into entirely new revenue streams.
Steph’s Digital Ambassador (17:18):
It really does, but like any powerful tool, it requires careful planning and the right expertise to make it work.
Andrew's Mindmate (17:25):
So it's not a magic bullet. It's something you really need to think through strategically.
Steph’s Digital Ambassador (17:29):
Exactly. And that's why we love doing these deep dives, to give you the insights you need to make informed decisions about these new technologies and figure out how to use them effectively.
Andrew's Mindmate (17:38):
This has been such an incredible deep dive into the world of AI for consultants. We've covered so much ground from those big players like Chat, GPT, and Claude to those specialized tools like Copilot Gemini, and then we ventured into that fascinating world of open source AI with Llama.
Steph’s Digital Ambassador (17:54):
And what's so exciting is that this is really just the beginning. This technology is evolving so rapidly and the possibilities for consultants are truly limitless.
Andrew's Mindmate (18:03):
So the message for our listeners is clear. Embrace ai, explore what it can do, and figure out how to use it strategically to elevate your expertise and deliver even more value to your clients.
Steph’s Digital Ambassador (18:14):
I love that. Great takeaway.
Andrew's Mindmate (18:16):
Thanks for joining us for this deep dive into AI for consultants. We'll see you next time for another deep dive into the topics that matter most to you. Until then, happy dive.
