AI products, we will provide some specific

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and I have tried various application scenarios of AI products on the company’s self-developed business platform. It is a pity that only a few succeed. It can be said that you sow but reap little. From a product success perspective, it is indeed lackluster. But from an engineering perspective, although our repeated failures cannot tell us what success is, it can at least tell us under what circumstances some products that appear to be very "correct" and "valuable" on the surface are unsuccessful. The

writing of this series is to break away from the abstract anxiety-mongering Afghanistan WhatsApp Number in the media, and also to break the knowledge bottleneck in understanding the underlying complex principles of AI. For ordinary people, or friends who are working in product manager positions but do not have knowledge of cases and stories about the implementation of AI products. Generally speaking, when people are making products, they always prefer to focus on what



is a successful product, or they are keen to analyze a certain hot product and want to tell everyone what is right. But in the face of AI, a new productivity and technology, its application is far from mature enough to support and guide future successful products through past success. At this stage, the most important thing is to understand and appreciate what AI is through continuous attempts. Under this concept, AI is what it cannot do and what it is not. Only by clearly understanding the