AI and machine learning are getting more special treatment these days. In the future, the influence of artificial intelligence and machine learning is going to be unavoidable, especially in the business world. Like, earlier hefty typewriters are replaced with the word processor, soon the word processor will be replaced by some AI analysts tool.
So, this change is bound to happen at any cost, however, the real question here is that whether your company is ready for this change or not. Just as the companies who are prepared for e-commerce and web development are now the only fragment of our imagination. That’s why if you don’t want to get lost in the whirlpool of artificial intelligence and machine learning, then you have to be prepared for it.
To get yourself ready for this unavoidable change, you gotta understand the few prerequisites before beginning your journey of AI. You need to get your strategies ready before diving into the pool of artificial intelligence.
Prerequisite 1: Education
Well, you can’t everyone data scientist in your company. Plus, some of the math equations are too long and fast that its impossible for humans to understand them. However, some basic things are going to be performed in the same fashion, that’s why training your employees in artificial intelligence especially in the following segments will be required;
– Clustering things together
– Sorting things under particular heads
– If you can make a line graph, you can probably predict what that value will be
– The liquidity or vibration value prediction
– Sorting, ordering and prioritizing sales order
Prerequisite 2: Componentization
Well, one of the recent tools available for data scientists to componentization is notebooks. These are the awesome tools for the data scientists and their associates. The real problem is that it encourages bad practices when it’s come to production. The interface of all classification algorithms looks the same, so a particular classification algorithm doesn’t change the problem.
Just like a company has to make a different representation of a customer, similarly, this has to do with the algorithms. This isn’t to say you need to come up with the one true clustering algorithm, but that you componentize what is different.
Prerequisite 3: System
In spite of everything, all the system still looks the same. There is the same process for installing data into the algorithms and there is the same process to execute the algorithm. If you are customizing you every algorithm over and over, then you are just wasting your time and money, and creating a bigger problem for yourself. Such as SOA changed so many companies deploy application software similar to artificial intelligence deployed.
Prerequisite 4: AI Componentisation
Prerequisite 5: Instruments
None of the above will work without the data. However, it doesn’t mean that you gotta to create the big and far data. Instead, let’s just focus on the instruments of the data. If you are creating manufacturing business data, then anyone pulling out manual gauge is waste of time.
These are just a few basic prerequisites of artificial intelligence, to see the full picture you have to prepare yourself for the future.