Don't pivot into AI research

🌈 Abstract

The article discusses the future of the machine learning field, drawing a parallel to the past trajectory of the chip design industry. It cautions against the blind pursuit of machine learning or AI research careers driven by status-seeking, and encourages students and new graduates to carefully consider their personal goals and the trade-offs of different career paths.

🙋 Q&A

[01] The Reality of the Future of the Machine Learning Field

1. What is the parallel drawn between the machine learning field and the past trajectory of the chip design industry?

• The article suggests that a similar story played out in the past with chip designers, where chip design was a high-profile role with famous chip designers being viewed similarly to how famous ML researchers are viewed today.
• However, as the market dynamics changed, the supply of hardware engineers grew too high and the number of significant employers decreased to a handful of major chip makers, leading to chip design losing status amongst students and new graduates, and becoming a less lucrative and high-status profession.

2. What is the key driver behind this parallel between chip design and machine learning?

• The high capital cost required for chip manufacturing is cited as a key driver, which is similar to the high cost of LLM (Large Language Model) training in the machine learning field.

3. What is the advice given to engineers and students regarding pursuing machine learning or AI research careers?

• The article suggests that for some engineers, machine learning or AI research may be a genuine passion, and they should pursue it while understanding the trade-offs compared to other careers such as software engineering.
• However, the article cautions that many more students and new graduates are driven by the inertia of their university and a blind status-seeking, and they would be better off thinking through their personal goals and what paths are best for them, rather than blindly pursuing "AI research".

[02] Advice for Students and New Graduates

1. What is the key advice given to students and new graduates regarding their career choices?

• The article encourages students and new graduates to carefully consider their personal goals and what paths are best for them, rather than being driven by the inertia of their university or a blind status-seeking.
• The article suggests that the same will be true for "AI research" as it was for chip design, where the field lost status and became less lucrative over time.

2. What is the underlying message regarding the pursuit of "machine learning or AI research" careers?

• The article cautions against the blind pursuit of "machine learning or AI research" careers, which is described as a vaguely defined field that includes everything from data engineering, infrastructure, and model architecture.
• The article suggests that students and new graduates should think critically about their personal goals and the trade-offs of different career paths, rather than being driven by the perceived status or excitement of the field.