Technological startups with AI advantage

Artificial Intelligence startups with strong competitive advantages

Building strong economic moats appears to be a great challenge 

for a modern startup. Today's full-scale shift to cloud and open 

source questions yesterday's competitive advantages. The rise of 

artificial intelligence itself puts an entrepreneur in a difficult 

position: You can't ignore it since so many use it, and yet you 

can't get competitive advantages from it since so many use it. As 

a result, nurturing a defensible business seems hardly possible.
User data is one of the strongest means that can provide modern 

digital businesses with a lasting competitive advantage. But to 

benefit from it, the company has to shift from technological to 

data tenure, learning how to collect information and how to use it 

in their favor. The most convincing way to do so, I believe, is to 

exploit two machine-learning-oriented concepts — systems of 

intelligence and coaching networks.

But to achieve it, we need to find out what sort of information 

we're looking for. There's no shortage of user data around the 

web; stocks of it are on the market, open for everyone who has a 

wallet and, therefore, rendering it absolutely useless as business 

leverage. The data that we need is the one that possesses three 

important qualities.

To make smart decisions, your algorithms must be intellectual, so feeding them with stale data models stashed on the market wouldn't be enough. Your machine learning solution must get data from real humans (your clients and employees) directly so it can learn from their actions, give them intelligent advice based on this knowledge and ask for feedback to correct itself. The goal is to establish a dialogue between your clients and the machine — or, in other words, create a feedback loop.

Google has already adopted the idea. It's asking its users how crowded their train rides are — first, to predict how crowded they will be and, second, to learn from the feedback and correct its own predictions.

Another problem with data on sale on the market is that they'rewell, they're on sale. Everyone who has money has the same data.

Today, only proprietary data creates real value. Exclusive insights that only you possess. So, again, you'll be advantaged using the golden source of information — your clients — to make them happy.

The cheerfulness of your users can help attract new users. In the best-case scenario, you achieve a so-called network effect; the bigger you get, the faster you grow.

Data is a perishable product. What is actual today won't match reality tomorrow. Those who continually harvest data and use it here and now will win the race for the client's happiness and thus gain a competitive advantage.

And here we return to the network effect: The happier your clients are, the more clients you have, the fresher data you gain, the smarter your machine becomes, the happier your clients are...

The three principles point us to a pretty simple idea: To flourish, you need the constant flow of unique signals from your customers, and your AI system should know how to learn from them and how to use it to help them in return. I think the best way to build such a system is to combine two brilliant business concepts.

1. System Of Intelligence: The concept of a system of intelligence (SoI) is laid out by Jerry Chen, a partner at Greylock. Roughly speaking, SoI is a layer in your SaaS application that bridges all the data sources from your systems of records (like CRM or HR) and the interfaces that engage users (like email or fancy social network). Geared with artificial intelligence and machine learning, systems of intelligence feed on insights from your users and your staff, returning helpful tips. The more valuable data it gets, the more useful hints it returns, deepening your economic moats.

2. Coaching Network: Venture capitalist Gordon Ritter coined the concept of coaching networks. In his idea, the best intelligent system is a symbiosis of humans and machines. They work together through a constant feedback loop — no longer adversaries but partners. While learning from your clients, guiding your clients and asking them for feedback, the system grows into their best helper.

Melding the two concepts, we replace separated AI/ML solutions that cover isolated business processes with a powerful client-oriented system. It connects all the users of your SaaS and grows smarter by a continuous partnership with them.

In a docket-like way, it goes like this:

• Creating aggregated profiles.

• Collecting user input data.

• Collecting model validation data from users.

• Feeding this data to shared data storage for all the models to use.

The future of business, as I believe, lies within the system of intelligence and coaching network. Those who can set up a close unity between their customers and the machine will hold this future. Such a system will be a deep moat alone in the world where moats seem to become impossible.

I hope you like this article " "

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