ML Engineer vs Applied AI Engineer

This is what I write my self my blog is polished by claude

ML ENGINEER VS APPLIED AI ENGINEERING AI when someone talk about AI in front of anybody their mind hit only one application ChatGPT , it's very famous Ai provider so do you know the meaning of chatGPT It's combination of two words chat + GPT means chat with GPT(Generative Pretrained Transformer), chatGPT devide the AI in to two border field first is Applied AI and another is Research AI . What is these two AI ,

Research Based AI : In this we create llm , trained the llm fine tune the llm on the large data set , and this needs a losts of maths and statistics probabilities. LLM large language model GPT Generative Pretrained Transformer Means  Pre Trained transformer Generative in nature. All the LLM that are generative in nature Pre Trained over large datasets and they structure is transformer are GPT You can thought LLL/GPT is a great chef who knows everything cusion because you trained it on large datasets , if you give him some vegis he make some disease because he has large datasets training

Applied AI Application: this is very interesting part in this we learn how to use llm in better way create application solve real-world problem create business

So there are two type of engineer one who works on the llm side and other on the use case size .take the example both and their complexity LLM. ML Engineer who created a multililentd chef who make foods good he takes input give output, take lots of data ,engineering, chemistry, biology, nutrient

Application Engineer: design a resturant design the flow of resturant, how the table are placed and use experience, in which structure take order in which structure give to chef then polish the chef output and serve this is also engineering but not as hard on data and chemistry we build application by using chef llm