GPU Education: Assessing the Risks

Will AI and GPUs improve education? The answer is likely yes. We've seen how predicting job openings based on upcoming retirements can inform curriculum development. These people can write books, and students can pay extra in Ivy League schools for less risk to get into one of them. It is a tradition that this job is filled by a Harvard graduate from a prestigious society, right?

However, this spending used to align to human distortions and errors. Professors chose the students they promote from a class. It is not known in advance, who will perform, and if it is known, who is interested. Finding a traditional job is a risky endeavor with an Apprentice like game incurring an inherent risk.

AI may disrupt these traditional pathways. Assess the risk by comparing the number of available positions to the number of students. LinkedIn is a good source.

The traditional path of internal promotion is also risky. Compare the number of long-tenured managers to the number of more recently hired employees to gauge churn and the likelihood of advancement.

If you were admitted to university being in the top 1% of the score as the author, you may need to think ahead. Your advantage is aligning well with the curriculum; teaching is a viable option. However, if others catch up with good education, founding a business may leverage the top 1% knowledge with lower risks.

AI will be invaluable in assessing these risks by providing accurate data how to choose.

Link of the day.
Englang scripts to generate an ERP with generative agentic AIs. Here.