In this article, we will not try to discuss technical issues, NLP, DNN, deep learning, etc. will not be involved, but simply discuss the product perspective, the core content of which mostly comes from my experience, observation and analysis.
Artificial intelligence has been on fire for quite a while. Many capitals, entrepreneurs, and large and small companies seem to be chasing this rare slogan. Especially after Li Kaifu’s concept of advocating artificial intelligence in many public places, it is all about artificial intelligence. Articles for reporting and analysis.
As the most dazzling jewel in the crown of computer science, artificial intelligence has attracted countless computer scientists and practitioners to climb in the past few decades, and countless people are constantly exploring the future technology of artificial intelligence . As a product manager who has worked in the field of artificial intelligence and has continued to pay attention to it, after reading a lot of articles, I have seen either artificial intelligence as a gimmick to discuss a vague industry topic, or deep Analyze the technology behind artificial intelligence. I deeply feel that these articles are not really helpful to the product manager, but it is easy to be confused.
Therefore, I decided to combine my experience, observation and analysis, and hope to provide a relatively comprehensive overview and discussion of artificial intelligence from the perspective of products. I also hope that in this process, I can improve my understanding of artificial intelligence and hope to attract More small partners are involved in the discussion.
First, what is the artificial intelligence product?
1. What is the so-called artificial intelligence product?
In the computer world, based on the accumulation of massive data, a set of statistical analysis based on massive data, which can guide and support the key decisions in some application scenarios, this product model has a common term, called large Data operation. And almost all of the scened products based on big data operations can be called artificial intelligence products.
Artificial intelligence products are different from artificial intelligence technology, technology is the core competitiveness, and the ultimate product is to be able to use.
For example, image recognition based on deep learning technology is an artificial intelligence technology, and products that can be used by users using this technology are artificial intelligence products, such as Microsoft Xiao Bing's "small Ice knows the dog.
2. What should product managers focus on in artificial intelligence products?
In artificial intelligence products, we focus on the problem of scenario, not technical or data. As a product manager, the core of our focus should be how to apply the shaped artificial intelligence technology to the right scene.
As we all know, the technology of artificial intelligence is still in the development stage until today, and no technology has been perfected. In the process of technology development, products often need to be considered to complement each other and be targeted.
For example, AlphaGo, the main developer of the DeepMind team, has been conducting in-depth research in a scenario over the past few years, and has made breakthrough progress. Another example is the artificial intelligence voice assistant Alexa in Amazon Echo Audio. Human-machine dialogue is a very complicated academic problem, but Alexa cleverly limits the scene (voice interaction + smart home), which makes the user experience very good.
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