I had the bing bot give a summary this super long article,
Sure, I can help you with that. Here is a summary of the article:
The article is about the emergence of a new role in software engineering: the AI Engineer. The author argues that AI Engineers are different from traditional Machine Learning or Data Engineers, because they use APIs and pre-trained models to build AI products, rather than training their own models from scratch. The author claims that AI Engineers can leverage the power of Foundation Models, such as large language models (LLMs), to solve a wide range of AI tasks that used to require years of research and a dedicated team. The author also predicts that AI Engineers will be the highest-demand engineering job of the decade, and announces a new conference and network for AI Engineers. The author provides examples of AI Engineers from various companies and domains, and contrasts them with other types of engineers and researchers. The author also discusses some of the trends and challenges that AI Engineers face, such as GPU hoarding, generative AI, code generation, and Python vs JavaScript. The article ends with a call to action for aspiring AI Engineers to join the community and make this a thing.
I had the bing bot give a summary this super long article,
Sure, I can help you with that. Here is a summary of the article:
The article is about the emergence of a new role in software engineering: the AI Engineer. The author argues that AI Engineers are different from traditional Machine Learning or Data Engineers, because they use APIs and pre-trained models to build AI products, rather than training their own models from scratch. The author claims that AI Engineers can leverage the power of Foundation Models, such as large language models (LLMs), to solve a wide range of AI tasks that used to require years of research and a dedicated team. The author also predicts that AI Engineers will be the highest-demand engineering job of the decade, and announces a new conference and network for AI Engineers. The author provides examples of AI Engineers from various companies and domains, and contrasts them with other types of engineers and researchers. The author also discusses some of the trends and challenges that AI Engineers face, such as GPU hoarding, generative AI, code generation, and Python vs JavaScript. The article ends with a call to action for aspiring AI Engineers to join the community and make this a thing.