Microsoft Copilot is like Tesla’s early car manufacturing, with top-notch production speed but hard-to-explain quality control

The biggest advantage of the Copilot tool is "quantity", which means that the time to complete the task will be greatly shortened, and employment, performance, and work processes may all be changed by it. Of course, Copilot can also improve "quality", but currently generative AI is not mature enough and is far from outstanding in terms of quality improvement.

By analogy, Microsoft Copilot is like Tesla, which built cars in the early days. It produced cars very quickly but of average quality. For employees pursuing “speed,” generative AI tools are attractive, but at the same time, quality must not be neglected.

Looking at generative AI from Tesla

We can actually make an analogy to Tesla. When Tesla entered the car market, it carried the aura of a "technology company" and attached great importance to automation and robotics. At the time, Tesla didn't have a deep understanding of how to make cars, but in the end Tesla built an electric car that was cheap enough.

Despite the popularity of Tesla cars, quality problems have frequently arisen. Because Tesla pays close attention to speed and cost, the robots and automation technologies it uses increase production speed, but do not improve quality. This is the same as the current performance of generative AI.

Look at Jaguar. It originally produced the F-Type in a new self-chemical factory, and the factory professionals were hired from Mercedes-Benz. The F-Type's production volume was not high, but its quality was outstanding. Because the professionals who ran the factory brought high-quality management experience, the cars produced had few problems.

Robots and AI technology can undoubtedly greatly increase the speed of production. When the good parts of production speed up, the bad parts also speed up, because the technology itself cannot distinguish between good and bad. Sure, you can train an AI to tell it the difference between "good" and "bad," but the AI ​​still won't understand how to achieve high quality.

AI also has no creative ability. The same goes for content-generating AI. Only when users know how to create "high quality" can AI work and truly help humans create high-quality products. If users sacrifice quality for quantity, AI will still only help produce products of poor quality.

As time goes by, the quality of Tesla’s cars continues to improve, but the advantages it gained initially are eroding. Early buyers of Tesla electric cars may be Porsche owners, who are very concerned about the quality of their cars. Tesla's poor early reputation will affect car buyers' attitudes.

Copilot for PowerPoint

When we use Copilot, we should pay attention to how Copilot improves productivity on the one hand, and how it improves "quality" on the other. Using Copilot in PowerPoint gives us an interesting experience that is worth exploring carefully.

Many people use PowerPoint for lecture notes, but never consider using PowerPoint to convey visual information. Copilot has brought changes, it can help us create more visual media content. In the past, when using PowerPoint, users may have been pursuing better “presentations”, but now they can add rich “visual elements”.

If you are good at telling stories, Copilot can make you even more powerful. Copilot can create pictures for documents and books, and use visual elements to describe various concepts to make communication more intuitive. If you don't know how to tell a story, you'll still get into trouble even with Copilot.

Mastering generative AI takes time and requires learning. When you deeply learn and master generative automated AI tools, your work speed will be greatly improved. As with any automation tool, if you work to eliminate defects from the beginning, future defects will be better controlled. If you indulge at the beginning and don't pay attention to eliminating defects, you will have to spend more time making adjustments in the future.

Generative AI tools are still in the early stages of evolution, and there is no doubt that in the future those who master this technology will eliminate those who do not, just as those who master computers will eliminate those who use typewriters and calculators.

We don’t know exactly what kind of changes generative AI will bring. However, the United States continues to optimize production tools and improve productivity. This research and development direction is worth learning from our companies. (Knife)

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