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Thursday, October 10, 2019

6 Critical Questions to Help Businesses is cutting through AI application

It is always satisfactory when a specialist confirms that you are suspicious. Research firm Gartner conducted a critical analysis that Artificial Intelligence (AI) reached "extended peaks in expectations" and put a real shot at coffee in the morning last summer. .

If Elon Musk expects an AI to worry about, call back to the business software level. It's actually not as common as it seems. AI has already changed the way data is used to understand the world.

It has also become corporate fashion. For each AlphaGo Zero, there are 1000 companies (startups and long established companies) that have AI labels attached to their products, such as the bread strips of the 1980 machines.

There is no doubt that AI has made significant and rapid progress in the past few years. My challenge is hype aggression, which reflects the tech bubble of the late 1990s and early 2000s. Risk: Buy an overfilled commitment rather than a product with a proven return on investment (ROI).

Hype advertising sometimes clouds our judgment on purpose.

If you share my doubts, but feel equally important and want to avoid too much attention, there are six questions that can help you tune your BS detector.

What business problems are you trying to solve?

This is the most important question and has nothing to do with AI. Certainly, some companies find value in experience, but open-end projects should be handled with great care. We recommend that you clearly define the business problem you want to solve.

Business investment needs to be evaluated against three criteria: increased revenue, reduced costs, and reduced risk?

Pinning new technology into at least one of these fundamentals establishes its value. Then ranking ownership and accountability is the best way to get the technology initiative on track.

 Why do we need AI to solve this problem?

Maybe you don't. True to the AI ​​and apply knowledge and skills. Suitable for situations where variation and novelty exist, but difficult to build and therefore requires a premium. Consider the complexity of self-driving car surfing on busy city streets. Does your business problem involve ongoing issues?

Machines that improve on a step-by-step basis are compelling, but you need to focus on the results, not the technology used to achieve them.

Do you find a margin for improvement that makes AI costs worthwhile? Comes with a test that evaluates the size of the margin. Run on paper and run again in a proof-of-concept project. Make sure AI won the award.

Do you have enough data to use AI?

The best AI solutions outperform those in certain tasks, such as cancer cell recognition analysis and false trader determination at investment banks.

But machine learning to understand for dirty and consistent information requires a lot of training. AI uses models to understand and generalize the world. It is difficult to find enough examples to build a good model.

Lots of historical data is available from the healthcare system or from banks. Can you? Finding a relevant example to find a relevant example, if possible, is time consuming and expensive.

To overcome this hurdle, some companies have started developing AI modeling software that makes the process faster and cheaper. Still, it's a difficult task whenever data is scarce.

Related: Big Data, Big Deal! Five ways to be revolutionized in 2018

 Do I need to build or buy an AI solution?

If you are incorporating AI into your company product or service, your internal functions can make sense. Still, do not underestimate the resources and expertise involved. A carefully chosen partner can provide a faster path to glory.

If you are working on a known business problem, it is best to work with an experienced trader. You must not be overwhelmed by technology.

Everything you buy must be customized or tailored to your environment and requirements. Focus on understanding the business domain and the type of data that consultants need to leverage.

How much does the seller know my domain?

Some vendors claim that AI is experienced in irrelevant domains. Don't Believe I Work with a consultant who doesn't need to learn business from scratch is faster and less stressful.

Review relevant experiences and partnerships with potential sellers. Can merchant leaders provide examples of equivalent problem-solving production for others?

If your problem is truly unique, look for experienced experts dealing with parallel challenges in different industries and similar types of data.

 Do you have a proven ROI?

In the Gartner report, "expanding expectations at peak" followed by the same "fascinating swallow of disillusionment".

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