Technology is a double-edged sword

The standardization plan for the food delivery industry has finally been released.

Although Lin Yuan's current identity is inextricably linked with overseas capital, this is the good thing about Longguo—they know how to use people wisely.

In the food delivery standardization plan he introduced, Lin Yuan restricted the AI Administrator Algorithm, preventing the algorithm from extending its branches unchecked.

He introduced the concept of 'algorithm tax.'

Because algorithms bring standardization, which clears the way for mass production, and mass production means economies of scale. Economies of scale are inherently suited to integration with large capital.

Therefore, after the food delivery industry was empowered by algorithms, it was inevitable that a situation would arise similar to how, after the Industrial Revolution, the agricultural revolution became vulnerable under the influence of standardization and mass production.

Applied to real life, this means the crushing dominance of large catering chain enterprises over small and medium-sized catering businesses.

Originally, small and medium-sized businesses could compete on different tracks from large catering enterprises by leveraging differentiation in taste and specialty. Small and medium-sized businesses could more easily innovate in dish specialties and flavors, while large catering chain enterprises, constrained by their size, had to follow a standardized, easily replicable path.

Just like KFC, it's impossible for it to produce a bunch of different flavored items in one city.

Because this would severely hinder its product development and procurement and stocking.

If the variety of dishes and production steps increase, then it's impossible to lower costs through large-scale procurement and standardized mass production, and the economies of scale that large catering chain enterprises rely on for survival would cease to exist.

Imagine if KFC gave customers walking in a menu with hundreds of items on it. Would every KFC store then need to be equipped with a master chef, and would every store need to independently procure ingredients based on its own operating conditions?

Ultimately, everyone would realize, why even bother with chain restaurants? The result of this way of operating would just be a bunch of small restaurants.

However, the AI Manager Algorithm makes these problems easy to solve.

First, employee training.

Even for hundreds of dishes, or even thousands of dishes, the chain restaurant headquarters only needs to complete a one-time development. The remaining employee cooking training process, as well as the corresponding assessment process, can be fully managed by the algorithm.

No one needs to master the cooking process of all those dishes; as long as the AI knows, that's enough.

The AI will be responsible for each employee's training and assessment, and the AI can even be detailed enough to remind the operator of each step. For example: how many grams of sugar to add at this time, or that the dish is ready to be served.

The cost of personnel training in traditional industries increases linearly with the increase in categories, but after the introduction of the AI algorithm, personnel training costs are almost zero. Because this has completely become the AI's job, the AI can check the employee's actions in real-time through monitoring footage to ensure compliance.

Another example is the procurement process. The biggest fear in procurement is small quantities and many categories.

If there are too many categories, it's troublesome for suppliers to stock. If the quantity is also small, the price cannot be driven down.

Therefore, large catering enterprises cannot have a huge menu like small restaurants; they prefer the model of selling milk tea. Because milk tea ingredients can be atomized. The main ingredients of milk tea are milk, milk powder, tea powder, and various flavorings.

But dishes can't be played this way; after all, the meat used for braised pork and shredded pork with green peppers is different.

So the algorithm made its debut.

Another most powerful aspect of the AI Manager Algorithm is that it also atomizes the raw materials of dishes.

Why can't a piece of pork belly used for braised pork be cut into shredded pork? It's not that no one has thought of this, but it breaks the general operational flow. For large enterprises, everything needs to be process-oriented. The biggest fear is too many and too complex processes.

A piece of pork belly can be broken down into lean meat, fatty meat, and pork skin, each having its own use. But the cost generated by this process would certainly be much higher than directly purchasing lean meat, fatty meat, and pork skin.

So large catering enterprises wouldn't do this.

But if they don't, for every portion of braised pork, they need to prepare a corresponding piece of pork belly, and for every portion of shredded pork with green peppers, they need a corresponding piece of pork loin.

The internal processes of large catering enterprises would only state how to make shredded pork for stir-fried shredded pork with green peppers from pork loin, and would not include a note that, if necessary, lean meat from pork belly could be used as an emergency substitute.

Of course, the above is just an inappropriate example. Its main purpose is to illustrate the contradiction between standardization and customization.

This is very common in industrial settings.

Every enterprise in the industrial sector likes to produce standardized products, even if the profit is slightly lower. Because standardization can reduce the costs of production, processes, and quality control, and it also facilitates large-volume procurement to drive down costs. Then, they profit through volume.

In short, customized products seem to have high single-piece profits, but too many management costs are sunk into them. So, general manufacturing enterprises universally dislike customized products and will charge high prices for them.

Similarly, the catering industry is actually the same. Because when the catering industry develops to a certain extent, it also becomes an industrial production industry.

And the most powerful aspect of the AI Manager Algorithm is that it automatically analyzes the material composition of each dish.

That's right, Lin Yuan felt that using the concept of 'material composition of dishes' was more appropriate.

'Ingredients' is a culinary term, while 'materials' is an industrial term.

If a dish is viewed from an industrial perspective, it is naturally appropriate to use the description of materials.

And what is the biggest characteristic of materials? They can be substituted.

In the industrial field, the concept of material substitution has always existed, because you cannot predict in advance and perfectly prepare all the materials needed for future production.

If you have residual resistors with 5% precision, and production requires 10% precision, would you then leave the 5% precision resistors unused and specifically procure 10% precision ones?

Not to mention the time wasted in the procurement process, material backlog would cause cash flow problems.

Which company would accept such recklessness?

So Lin Yuan applied this industrial production thinking to AI training.

The AI Manager Algorithm also lived up to expectations, quickly finding substitute solutions for various dishes.

The role of the algorithm in procurement is actually to provide a greatest common divisor guideline during procurement, based on the operating conditions of each business.

This greatest common divisor guideline is similar to breaking down the preparation of dish ingredients into the raw materials of milk tea, thereby combining fewer ingredients to create more dishes.

If this process were done by humans, it would be a terrible thing, greatly increasing management costs.

After adopting the AI Manager Algorithm, major catering companies found that they could truly manage the material flow of various chain stores using the concept of material management.

As a result, the advantages of small and medium-sized businesses over large catering enterprises in terms of variety, taste, and specialty were gradually eroded.

Especially the taste advantage.

Taste completely depends on cooking heat and seasonings, which is too easy for AI. It's like learning it after seeing it once.

So much so that large catering chain stores can even offer customized tastes for each customer, because it's simply a matter of listening to the AI's prompts through headphones while cooking, such as, "Please fill small seasoning container number 3 with chili powder number 9 and pour it into the pot."

In other words, achieving different tastes does not require the operator to think; they just need to follow the AI's instructions. If the operator even makes a mistake, the AI will issue an alert.

Then the unique cooking advantage of small restaurants would also disappear.

Technology once again showed its double-edged nature.

This is naturally something Lin Yuan did not want to see; he did not want the streets in the future to be filled with various catering chain stores, with no more 'fly restaurants' to be found.