Artificial Intelligence development: Should your startup go for it?

In case you haven’t noticed, AI is having its Internet moment. 70% of senior executives have now put AI at the top of their investment priorities, and tech is scrabbling to serve their needs. 

Is it time for your startup to join the fray? Maybe you ought to start developing a standalone AI app. Or you might want to add AI features to your existing tech tools. 

We’ll help you answer these questions by considering the work that goes into AI development. We’ll also look at just how costly and challenging it is. And, of course, we’ll explore the ways NERDZ LAB can help you find your way through the AI labyrinth.  

Article content:

• The work that goes into AI development
• AI app development cost
• Should you go for AI development?
• Just how challenging is AI development?
• How we can help
• Conclusion

The work that goes into AI development

Are you ready to take on an AI project? To answer that, let’s first take a look at the type and amount of work that goes into building an AI product.

When it comes to artificial intelligence development, you have three basic options.

Creating and training your own model

An AI model — like GPT, PaLM 2, or LLaMa — is a program or algorithm that’s been trained on a massive amount of data and can answer questions about that data.

The big daddy of AI development is training your own model from scratch. The work you put in will depend on the complexity and size of the model. You might train a smaller model on customer service conversations or health data. Bigger models, such as a large language model (LLM), will require more training. 

Uptraining existing models based on your needs

One step down from creating your own model, you can work with an existing model (like GPT-4) and uptrain it until it meets your specific needs. 

For instance, GPT-4 may not be well-versed in the details of certain business processes. Still, you can uptrain it with domain-specific knowledge to enhance the contextual relevance of its responses. You can feed it with examples of conversations and user intents that accurately reflect your customer base. 

Designing input queries with prompt engineering

​​Prompt engineering involves designing input queries to guide AI systems, which is the easiest way to add AI functionality to your product. For example, you can improve the responses you get from generative pre-trained transformers (GPT), the models that enable apps to craft human-like content, by providing clear instructions (or prompts).

For instance, you can use prompts to add GPT-based AI chat functionality to a document editor or provide text-to-image AI like DALL-E with instructions on how to create an interior design.

Just like uptraining, prompt engineering aims to improve the performance of AI models. But instead of retraining the model, it improves output by refining user input (the prompts). 

AI app development cost

Can your business afford AI development? Let’s run through the factors that can affect its cost.

Software development time

How does developing an app with AI features compare with the alternative? 

Manual software development involves writing separate code for every business logic or decision your user might make. A developer considers a problem or use case, cuts it into smaller tasks, and crafts code for each task. This means that developing a traditional program takes more time — and money — upfront. 

Using an AI model, on the other hand, requires limited user involvement and business logic. That’s because it makes all its decisions based on training data. Programmers only need to feed the algorithm a large amount of data, train it to perform certain tasks, and leave it to find patterns and learn or adapt. 

Infrastructure cost

Developing AI features may be faster, but because an AI model works on large data sets, it requires considerable computational resources. One simple action can take between 20 and 100 times more resources than a simple data query. 

Just how costly can it get? Meta’s AI model, Galactica, used 128 NVIDIA A100 80GB nodes. For context, a single A100 can set you back $15,000. And that’s only part of a system that includes high-performance CPUs, RAMs, and networks. Even if you don’t have Galactica-sized ambitions, it all adds up.

In short, AI development can be beneficial initially as you spend less on development time. However, because of the infrastructure costs, it will become more expensive in the long run. A good software development partner will help you find the sweet spot to use your budget in the wisest way. 

Should you go for AI development?

Your heart is probably set on developing something with AI features. But it’s still good to take a reality check.

Traditional programming involves telling a computer what decision to make based on a particular case. While these programs are powerful enough to carry out complex tasks such as solving advanced equations, they fall short when it comes to human-like functions (like understanding the intent of written messages or differentiating elements by images). Moreover, they can only perform tasks they’re programmed to do. 

If you need software that can understand incoming emails and make human-like responses, you’ll have to turn to AI development for a solution. AI is also your best option if you want a system that continues to learn as more information about your customers comes in. 

Just how challenging is AI development?

Short answer: It depends.

Some AI processes can be so complex that even the engineers who train them cannot explain or predict their results. You can think of AI as a black box with secret mechanisms that you can’t see or understand but that change as you train them. It adapts to your training data and delivers the desired output.  

This kind of AI development is complicated and expensive. But you can also get your hands on out-of-the-box solutions that only require some tweaking. You can also turn to a vendor who knows the landscape better.  

How we can help

At NERDZ LAB, our goal is to deliver the output you require with the least cost and complexity possible. If that means simply developing a predictable algorithm — say for text processing or database manipulation — that’s what we’ll recommend (and do). 

If AI development makes more sense, we minimize the cost and complexity of the process by retraining models or working on prompt engineering instead of creating a model from scratch. 

LLMs are always a great starting point, but as much as possible, we use task-specific AI models. For instance, say you need a tool that supports agricultural firms with their marketing and business processes. We’ll use a pre-trained model for that specific task and industry.  

Blank AI: An AI-driven personal assistant, coach, and companion

We helped a US-based innovator make their mark in ​​the AI development market with Blank AI. Our client, Global Digital, commissioned us to create an MVP for the app, which interacts with the GPT LLM. In just three months, we delivered a functional MVP capable of managing daily activities, providing resources for personal growth, identifying objects in images, understanding user intent, and responsive chat. 

Blank AI has evolved into an app with opportunities for monetization (subscription model and in-app purchases), user engagement (personalized scheduling and entertainment features), partnership (with tourism, education, and arts businesses), and user-generated growth. 

SCOPO: A smart business proposal tool

We can also integrate AI-powered features into your existing product, just as we did with SCOPO. The app utilizes AI to propose feature breakdowns for software projects and expedite the process of creating estimates.

Nearly any product can be extended with AI to make it more appealing and usable, and at NERDZ LAB, we’re happy to help you identify possible areas for improvement. 

One indicator can be user time spent on a functionality. Tasks requiring too much manual work, like a long registration process, may benefit from AI support. You can also think of what users could do on your app that they’re currently doing outside of it: if you have a family recipe planning app, could you add AI recommendations about where users could save on their grocery budget?

Conclusion

AI development can be complex and expensive, but that’s only one end of the market. Leveraging existing models through up training and prompt engineering are two much more affordable options for adding AI to your product. 

At NERDZ LAB, we can create an AI app from scratch that brings your idea to life. We can also add AI features to your existing app. We’ll even forego the use of AI in traditional programming makes more sense — and we’ll show you why it does. Our goal is to deliver results in the most cost-effective way possible. 

Reach out, and let’s explore your options together!