Why The Best Model Can Be The Simplest

AI does not need to be in everything

Right now I’m making a project that should produce areas that have high risk of flooding in the future. To do that I had to create a model that would complete a time series analysis that would forecast into the future. Instead of using a deep learning model like LSTMs. I went with a tried and tested model for time series analysis called ARIMA. (this is because I was following a tutorial.) This made me think about how all the bells and whistles are not needed.

 As long as you're solving the problem the tool your using does not matter. I think this is the problem that people with engineering backgrounds have. They fall in love with the tool. Not solving the problem. Don’t get me wrong I do this all the time. But I think it’s important to solve the problem first. Rather than having a tool and finding a problem to solve it with. Granted I do this a lot.

I have been doing a lot of this recently, as a bid to improve my machine learning skills. I have been finding problems that will require me to make models. So, there is a time and place for all this. One of the benefits of having a simple model. Is stuff are less likely to break down. As you have fewer dependencies and connections between different bits of your code. It makes it easier to maintain. As your not getting a headache trying to comb through your model. The more stuff you add, the harder it is to troubleshoot the model. For example, if your model is overfitting. And you're trying to fix it with 10 layers. It will be harder as you need to tweak the parameters of all the 10 layers. Compared to a simpler model with only 3 layers. Also, this will take fewer resources so if you're running the model on the local computer. Then your computer is less likely to kneel over. Which saves you from buying a new computer, which is great.

Making Useful Projects

From Seth Goldin, This is Marketing:

It doesn’t make any sense to make a key and then run around looking for a lock to open. The only productive solution is to find a lock and then fashion a key. It easier to make products and services for the customer you seek to serve than it is to find customers for your products and services.

While he was talking about making products. It relates to this blog post. As solving problems is making products and services even if we don’t call it that.

In my applied technology blog post. I talked about how people can make an effective solution using simple tools. The example I gave in the article was a radiologist that made an ML model to find fractures in X-rays. Using Google’s no-code machine learning tool. This shows we can create useful products with simple tools. I think we should not be too nerdy about tools. Granted being nerdy is great, but we should always be thinking about the end-user first and foremost.

I think lots of developers get stuck into the “build it they will come” mindset. I’m only recently shedding this mentality right now. Putting my focus on people’s needs and wants. Granted I still want to build cool things, but if we want people to use our products then they need to be useful. The reason why machine learning is popular now, is that it helps solve problems that we could not do before. And we have the elements to make it more effective. Like powerful computing power and lots and I mean lots of data. This helped deep learning go mainstream.

I think I mentioned this in another blog post, but this is why I choose projects that I could see a person using. Not working out handwritten numbers from the MNIST dataset. The whole point of having tools is to allow us to solve a problem that we couldn’t without the tool. We have a hammer to punch in nails which we couldn’t do before. We have paddles to help us travel by boat quicker. And we have a computer to help us compute things ridiculously fast. So we should not get distracted by the next shiny toy (tool). This does not mean you should not change and stick the tools you already know. If that was the case, we still will be using sticks and rocks.

The Tool does not matter, it’s the solution that matters

From Patrick McKenzie (Patio11)

Software solves business problems.  Software often solves business problems despite being soul-crushingly boring and of minimal technical complexity.

…

It does not matter to the company that the reporting form is the world’s simplest CRUD app, it only matters that it either saves the company costs or generates additional revenue.

Even when companies are using advanced technology and techniques. Sometimes the goal is still very simple. Netflix has a great recommendation system, so you watch more movies. Facebook has PhDs in Psychology and Artificial intelligence so you can spend more time on Facebook. And look at more ads. Google has crawled the entire internet. So when you use search you get the information you want.

Again, it all comes back to the end-user. I'm a Nerd, so all this stuff interests me, I can spend all day tinkering with new technology. But we must remember that when building something it should help somebody else. It does not matter how small the audience is. Many people say the audience can just be yourself. This is helpful because if its useful for one person then is probably useful to other people.

While I'm writing this, a lot of content here can be applied to myself. Which is partly why I’m writing this blog post. To say, don’t make things complicated if they don’t need to be. Don’t create a rocket ship when you can just get a boat. Don’t get me wrong. Building things is fun. Which is why I have a hobby like this. But it's important not to get too distracted.