The AI Factory - Everything you need to know

Artificial intelligence (AI) is the wheel driving today’s times. From a basic electric kettle to the human robots, AI is the soul of every machine and technique. It covers almost every section of mankind from healthcare to wonder Tesla cars. 

 

More or less, everything around us is a blessing of AI. In recent times of the pandemic, AI’s sector has evolved with major advanced challenges. In this blog we will shed light on AI Factory, an organizational operating model and learn more about its approaches. 

 

(Read to learn more about artificial intelligence)

 

Before jumping into the main section, let us clear a few important related terms.

 

 

What is an AI Factory?

 

AI factory is defined as a well-organized model, which works on basic principles to deliver success and excellence in AI deployment. The AI factory combines basic factors such as people, data, platform, and process to deliver the goals. 

 

For example, a pharmaceutical factory creates medicines for patients, similarly, an AI factory also creates solutions for its clients. From a simple android of your hand to a complex weather report developer, a million services are the products of an AI factory. AI is in all from providing support services to risk management. 

 

(Recommended blog - AI in Risk Management)

 

It is the process of combining machine and mind in a systemized and sequenced manner.

 

Inhibitors of AI factory

 

Even so, AI is a name in itself. Still, the technology often crashes with casual challenges. What are these challenges and how do they inhibit the growth of an AI factory? Well, here is the list of main inhibitors that crash with AI factory success.

 

1. Inability to understand the goals of AI factory

 

2. Inability to understand and execute advanced AI technologies

 

3. Insecurity in data and its outcomes

 

4. More emphasis on men than machines.

 

5. Time period of implementation

 

These five points together are inhibiting factors of the AI factory. And, in the last few years 2018-20, a huge declination in trend has been noted because of them.

 

 

What is an AI factory approach?

 

AI factory approach is the set of basic and fundamental principles of AI factory. AI works on logistics, and it is important to crack logic before cracking it.  

 

In common man's words, the AI approach may be defined as a method of investigating AI algorithms and logic, in which a problem is first identified by experiments and observations. 

 

The problems identified are then solved. And hypotheses and statistics are then developed according to the situation. The developed hypotheses often served as fundamental principles. And are important for mechanism and functioning.

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Four major AI factory approaches

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The AI factory has a different approach which is the combination of technology and mental power. The four AI factory approaches have been highlighted below:

 

1. Suitable Data Leaders 

 

For any AI factory board, a high-level and dedicated team of data leaders is really important. Data depends on data leaders, and factories depend on data. Data being a prime source serves as raw material for an AI industry. 

 

Thus, it is essential to gather or produce authentic data. The data leaders help in providing direction and control to an AI factory. 

 

They also play a key role in reviewing and validating the progress of data collection. They work collectively to achieve a single role. And, are responsible to ensure real-time information flow and transparency of a project.

 

2. Organized Expert Team

 

Just like any other task, the AI factory needs an expert team of experts to show efficiency. This team serves as a platform for the approach. And, just as a platform, an organized team is important for performance. 

 

The team should carry at least one person of each skill including business, data, software, and digital technology. Together they work as a hybrid structure. While one gathers raw data, others search for suitable technology as a way to implement it. 

 

These teams work on agile methods. Agile methods refer to the process of developing a project in short cycles of work. The agile method ensures the stability and flexibility of any technical project. The team should be provided with a healthy, developing, and honest environment to work in. 

 

 

3. AI Technologies

 

For the delivery of a successful AI project, obviously, AI technologies play a vital role. Or in other words, advanced AI technology is the final step of the AI factory. 

 

(Suggested blog - AI Project ideas)

 

The chosen or resulting technology should be advanced and standardized. It must be based on the principle of good practices. 

 

To serve the purpose, the AI factory can use a combination of proprietary, cloud, and open-source solutions. Sometimes, existing AI technologies are used to develop the latest and advanced AI service. 

 

 

4. Proven Methodologies

 

Methodologies are the final step of any process. The data collected by data leaders are fed into an AI process to develop an AI service. Proven methodologies should be used to accelerate the success of AI deployment. 

 

These methods should be induced with specification and systematization. Each selected method should be assigned its own goals and objectives. This approach will give consistency and structure to the AI factory.

 

How can one set up an AI business?

 

You can own a successful AI business by strengthening the above-mentioned four approaches for your organization. 

 

There is always a vast scope of AI, but you have to analyze your job again after a particular time. You need to reconstruct the structure and reimplement the algorithms in this field. Once you are done with the structure, the building is entirely yours. 
 

The AI factory is a blend of a single 'd' and four 'p's. As explained above, an AI factory combines 5 factors that are data, product, process, platform, and people. 

 

Data is the raw material, products are AI services or final AI technologies, process is the blend of AI methodologies and intermediate technologies, platform dedicates the team of experts, and people here are the persons such as data engineers, digital marketers, or anyone who is utilizing or producing AI services. 

 

By implying an AI factory approach success could be achieved in deployment of AI. With minor modifications and optimization success rate can be increased. The AI factory approach is also known as pillars of the AI factory. 

 

Just as pillar supports a building, AI factory approach strengthens the organization. Implementation of the AI factory approach means you are all set up to turn your mind into a machine, your idea into an industry and your concept into a company.