Understanding Artificial Intelligence - A Guide for Small Business Owners

What is Artificial Intelligence?

Artificial Intelligence (AI) stands for the science of mimicking human logic with computers. AI advancements are enabling machines to automate tasks traditionally performed by humans, making processes more efficient and effective.

There is a huge amount of buzz right now around AI. With that much noise, it can be hard to understand exactly what people mean when they say “AI” and how AI in its current form can benefit you as a small business owner.

On top of that, you’re already pretty time scarce because of how many hats you have to wear as a small business owner, so taking the time to find the best information can feel daunting.

With this article, we hope to pull together our best understanding of AI in a way that can benefit the total beginner who also happens to be a business owner.

Understanding these concepts does not require any computer science knowledge or previous knowledge at all. We’ll start from the ground and build our way up.

With that said, let’s start with the types of AI.

Types of AI

There are two main categories of AI: Narrow AI and General AI.

Narrow AI

Currently, all AI systems fall under Narrow AI. This type of AI focuses on executing specific tasks with high accuracy and efficiency. Examples include:

• Virtual Assistants: Apple’s Siri, Amazon’s Alexa, and Google Assistant use natural language processing to respond to voice commands.
• Email Spam Filters: These algorithms automatically identify and filter out spam emails.
• Recommendation Systems: Platforms like Netflix, YouTube, and Spotify use AI to recommend content based on user preferences.
• Social Media Feeds: AI curates personalized feeds on platforms like Facebook, Instagram, and X.
• Navigation Apps: Google Maps and Waze use AI to provide real-time traffic updates and route optimization.

Narrow AI systems are designed to perform well within their programmed domains but lack the flexibility and understanding of broader contexts.

In Plain English, this means that the AI you are usually exposed to is not the AI you may imagine. These are essentially smart processes that can look like intelligence but aren’t able to make creative leaps or innovations. They can only operate within the scope of a decision tree that applies to its own context.

For example, Apple’s Siri seems very intelligent because you can ask it questions in natural language and it is able to do a variety of tasks.

If you ask it to come up with a new business idea for a coffee entrepreneur, though, it will struggle. Its context is helping you accomplish tasks in the Apple software ecosystem. It doesn’t have the ability to brainstorm in a way that seems human.

It also can’t learn and adapt to new situations like the need to brainstorm without a human specifically programming it to do so.

Let’s now move on to the AI you usually think of when you think of AI.

General AI

General AI, or Artificial General Intelligence (AGI), refers to machines with human-level intelligence, creativity, and adaptability. While General AI remains a hypothetical concept, it aims to perform any intellectual task a human can.

Unlike Narrow AI, General AI would have the ability to learn and adapt to new situations without human intervention.

It is important to mention here that General AI does not yet exist. It may be close at hand, but truly intelligent machines have yet to be seen. We would know General AI exists when you are able to interact with a machine that is capable of responding to a novel situation and figure out a way to learn skills it needs to navigate that situation without a human telling it to do so.

For example, you could have a robot that sees that you are struggling with having a dining room table big enough for your next dinner party. Without you prompting it to, it decides to learn woodworking and build you a table.

Now you have entered the complexity of dealing with another intelligence - this is a solution to the problem, but is it the right solution? Did it build you a table you like? Is it able to understand your emotional context? This is the type of conversation we would be having if General AI existed.

Why is everyone talking about AI now?

AI has been around since the 1950s, but significant breakthroughs in natural language processing and generative models like GPT-4 and DALL-E have recently brought AI into the spotlight. These advancements have unlocked new applications and capabilities, making AI an interesting tool for businesses.

Even though these technologies are powerful and fascinating, they are still Narrow AI. It’s a partial step in the right direction for General AI but not even close to the kind of technical engineering capability one would need to harness in order to realize General AI.

That said, there is a lot of fear around AI because there is a lack of understanding around how limited these tools still are. There’s also a tremendous market incentive around these newly profitable companies for other businesses to push AI solutions and ride the wave of the new trend.

Let’s dive a bit deeper into Generative AI to understand how it fits into this map of AI that we’re building.

Generative AI

Generative AI focuses on creating new content, such as text, images, audio, and video. Despite being part of Narrow AI, generative models like GPT-4 have demonstrated remarkable potential in various applications.

When you hear about ChatGPT, CoPilot, and other AI these days, you’re usually hearing about Generative AI.

Applications with Large Language Models (LLM)

Large Language Models (LLMs) can generate coherent human-like text based on user prompts. They are deep learning algorithms that are capable of natural language tasks like classification, outlining, and image generation.

Keep in mind that since they are algorithms, they are still Narrow AI technically.

Here are some examples of what LLMs can generate:

• Text for conversations and interactive dialogues
• Short stories, novels, and poems
• Technical documentation
• Business reports and documents
• Advertisements and marketing copy
• Emails and letters
• Legal documents

These capabilities can significantly enhance productivity and efficiency in small businesses if applied correctly.

The Power and Limitations of LLMs

LLMs generate text by predicting the most likely sequence of words based on patterns learned from vast amounts of data. While they can produce impressive results, LLMs do not understand the meaning or context of the text they generate. They excel at pattern recognition but lack true understanding and reasoning capabilities.

Custom AI Models for Small Businesses

Small businesses can train custom AI LLM models using their own data, creating proprietary AI solutions tailored to their specific needs. These custom models can enhance industry-specific intelligence and provide unique value.

AI in Action: Enhancing Small Business Operations

Imagine a small business looking to gain insights from its data, which includes sales, financial, inventory, and operational data. By implementing an application with an LLM agent as the central intelligence component, the business can analyze its data, identify patterns and trends, and generate actionable insights more quickly and effectively.

How It Works

1. Data Integration: The application connects to various data sources, such as databases and spreadsheets.
2. Data Analysis: The LLM analyzes the data, identifying key metrics and calculating statistical measures.
3. Natural Language Interaction: Users can ask questions in natural language, and the LLM generates clear and concise answers.
4. Interactive Dashboards: The application provides visualizations of key insights and metrics.
5. Actionable Recommendations: Based on the insights, the LLM suggests strategies to optimize operations.

By continuously being trained on business data, the application becomes an invaluable tool for making data-driven decisions and driving business growth.

AI in Action: An Analogy

One way to think of using Generative AI for knowledge work tasks is by an analogy: digging ditches.

Before the invention of heavy equipment, you used to have to dig ditches using shovels.

It would take many people, each with a shovel, to dig a ditch of significant width, length, and depth.

However, with the invention of heavy equipment, a single person can now dig that same ditch in a fraction of the time with a fraction of the effort.

Now the same task takes less people. That may mean that those people never get hired in the first place, or it may mean that they are freed to pursue other tasks that create greater impact for their business.

Generative AI is similar. A software application that would normally take multiple developers many months to build “by hand” can come together much faster and with fewer people with the right AI systems in place.

For a small business owner, this is great news. It means that you can afford to invest in digital transformation initiatives that may have never been accessible before. It allows you to be more competitive with larger companies that have more resources available but take longer to innovate due to increased bureaucratic overhead.

Conclusion

Here are some key takeaways from this article:

• Artificial Intelligence is the science of mimicking human behavior with computers.
• There are two main types of AI - narrow AI and general AI
• Narrow AI executes specific tasks with high accuracy, but lacks the ability to learn and adapt independently
• General AI is the theoretical possibility of truly adaptive and self-driven machines, but does not exist yet
• ChatGPT and other Generative AI technologies, while powerful, fall under the Narrow AI category
• Generative AI is AI that focuses on generating new content based on previously created content
• Large Language Models (LLMs) are advanced algorithms that power Generative AI technologies
• Using Generative AI has the potential to allow typical knowledge work tasks like data analysis to be completed by fewer people, in less time, with better results when leveraged properly.
• This is of interest to small businesses that are used to having to do more with fewer resources and represents a potential competitive advantage in comparison to larger companies that are slower to innovate.

You will hear many people saying, “you have to get on board with AI right now”.

It’s important to understand that much of this is hype. Generative AI is powerful, but still requires human understanding and intelligence to be applied correctly to business processes.

That said, we’re on the beginning of a new frontier in technology. What’s ahead, we can only guess. Now is the perfect time to arm yourself with knowledge and consider the options when determining the type of digital transformation involving AI that is right for you and your business.

If you need conversation partners in that process, we’re only a message away. Reach out and let us know if you’d like to schedule a call. We would be happy to talk through your aspirations and concerns for free in a discovery call, as well as put together a proposal for digital transformation options tailored to your business.