AI - The Great Equalizer for Startups in DSM USA
For years, Silicon Valley leveraged their strength of proximity. Being near the tech companies and talent was critical. If you needed to test your software on beta hardware, it was likely you needed to go to that company’s lab. As cloud computing started to break down the walls of co-location, the ability to text and implement from afar eliminated the need to be next to the data center, or for those of us who are older, house our own servers, creating an opportunity for locations like Greater Des Moines (DSM).
Specifically, Artificial Intelligence (AI) is creating opportunities for startups regarding location. Much of AI talent is not located in the Valley. In fact, the top minds in AI are learning about it at schools and universities across the globe and via online resources. Startups in places like DSM have as much opportunity as those in the Valley when it comes to learning and building AI-based solutions.
So, how do we in DSM take advantage of this opportunity? The next step for local startups is to engage in AI as much as possible.
Ways to Utilize AI
Understand the Types of AI Available to You and Your Team
I recently attended an AI conference in New York, NY. One of the best sessions I attended was presented by Kristian Hammond titled, “Here and Now: Bringing AI into the Enterprise.” This presentation was mostly a tour through the various types of AI technologies with an overview of the terminology. Even though I have not programmed in 30+ years, I was able to clearly understand the content. You can access the slide deck here.
Learn About AI in Startups
One of the best resources I have found is the Andreessen Horowitz AI Playbook. This site has a wealth of information on AI as it relates to startups. I also believe it represents the bar that has been set by VCs looking to fund AI startups. You can assume that you need to be able to answer any questions that this material will pose. After all, this information is from the VCs. They are learning about AI as we speak.
Look Into How AI Will Fit Into Your Product Strategy
It's one thing to know the theory and tools, it is quite another to build out a product that makes valuable use of AI. Neil Lathia recently wrote a post that appeared on Hackernoon titled “Machine Learning for Product Managers." Starting with a non-mathematical overview of machine learning, Lathia provides a great overview of a variety of topics around building out products with machine learning. This information, while limited to machine learning, is useful when looking at any AI implementation into a product.
Building Your Own Network
Several people I know who are in the beginning stages of learning AI are finding more experienced contacts online who are open to sharing content, including relevant links. Accessibility is creating open communication, collaboration and innovation by utilizing talents across the country. By doing so, the once limited bubble of tech in Silicon Valley has expanded to include talent from all walks of life.
Before you build a product for the market, build something for the sake of building it. Not sure what to build? Start with finding a large dataset you can access. Googling “public data sets for machine learning” yielded a number of data set sources. One page I found fascinating, and inspiring, was the bigML page “List of Public Data Sources Fit for Machine Learning." Reading through these lists of data sets may inspire you to build something interesting.
These five steps will help you embrace AI tech right here in DSM. Utilize the tools and resources available to you. Create and innovate. This is the time to take advantage of all that is available to you.
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