Keywords: digital transformation; chat gpt；ai
The birth of Chat GPT has caused heated discussions among the whole people, and until now, this craze is still unabated. All walks of life are scrambling to explore the application of GPT, some to catch up with the trend and play with the concept, and some are trying to connect it with their own business at the technical level. Individuals or enterprises' understanding of GPT is also gradually changing, from the initial fanatical worship to rational view, and more attention is paid to its application effect in practical scenarios. So, what impact will GPT technology have on the digital transformation of enterprises? What are the practical application scenarios of GPT technology in the digital transformation of enterprises?
The essence behind artificial intelligence
It is undeniable that the function of GPT is indeed very eye-catching, but it is essentially a deep machine learning process, and it is best to think of it as a super baby who learns to imitate the sky. For example, a smart park project introduces an intelligent robot to receive visitors. The robot does a great job of presenting, has a smooth conversation, and can even lead guests upstairs. Behind this, training robots is extremely difficult: the newly purchased robots are like a blank sheet of paper at the beginning, and they need to use millimeter-wave radar to scan the entire campus environment, including every floor, every office area and even each office, and establish maps and markers. When workers leave work, they also need to check the questions that the bot failed to answer, and then supplement the answers. The reason why GPT can make the world amazing is the result of its continuous learning and growth.
Those drawbacks of AI technology
In life, AI technology is currently widely used in Internet services, mostly playing the role of search engines. Everyone usually uses a large public model, which is very convenient and has no worries, even if there is an information cocoon, it will not miss any major events. However, when this technology is applied to enterprise-level scenarios, it may bring new security issues, and data security is the first and foremost.
Samsung has had a serious chip secret leak. In less than three weeks after using ChatGPT, they discovered that important information such as the company's key measurement data of semiconductor equipment and product qualification rates had been stolen and stored in the ChatGPT database in the United States. Because the core model and computing power of GPT are in the United States, when running GPT internally, the data of the internal server must be called, which naturally creates data security risks.
Now we are facing a contradiction: if enterprises do not adopt public large models and computing power, but choose to deploy privately, this means high costs, not all enterprises can afford it, and at the same time, it also means a longer learning and training cycle, after all, the specific work scenarios of enterprises can provide limited learning samples. However, if you continue to use public interfaces, there is a risk of data breaches. Because in the process of optimizing the work effect, GPT needs to learn in actual work scenarios, which inevitably collects employees' work behaviors, business data and information in various systems, which will eventually be transmitted to GPT's server through the network, resulting in the leakage of internal data of the enterprise.
In addition to the data security risks, if you want to know what are the thunder points and pitfalls of GPT technology applied to the digital construction of enterprises, please subscribe to the next issue of Wuque Technology!