Recent submissions

Comment · 8 months ago
Sufficient if all else were equal. But the human brain and artificial neural networks are clearly not equal. This is setting aside the whole question of whether we hope to equal human performance or exceed it.
Comment · 9 months ago
Isn't this a little bit of a category error? LLMs are not a language. But prompts to LLMs are written in a language, more or less a natural language such as English. Unfortunately, natural languages are not very precise and full of ambiguity. I suspect that different models would interpret wordings and phrases slightly differently, leading to behaviors in the resulting code that are difficult to predict.
Comment · 9 months ago
The irony here is that universities are struggling to teach writing skills, due to massive cheating with AI.
Comment · 1 year ago
Comment · 1 year ago
How are other kinds of engineers such as automotive engineers treated at companies like Ford, or aerospace engineers such as at Boeing?
Comment · 1 year ago
I agree that the goals are worthwhile, and also feel that requiring every proposal to include this is not efficient and/or very effective. They should take all the funds and time spent on this every year as part of every award, and just fund programs specifically designed to attract inner-city kids to science, or funnel talented, low-income, high school students to be mentored, taught advanced classes, etc.

I would be happy to spend time mentoring URM, etc. But it'd work a lot better if others managed such a program, thought about how to attract them, etc. Specialization is good.

Comment · 1 year ago
Add some extra information, and it gets confused. This is 4o.

https://chatgpt.com/share/67759723-f008-800e-b0f3-9c81e656d6...

One might argue that it's impossible to compress air using known engineering, but that would be a different kind of answer.

Comment · 1 year ago
Comment · 1 year ago
Comment · 1 year ago
My favorite MLE example: Suppose you walk into a bank and ask them to give you a quarter. You flip the quarter twice and get two heads. Given this experiment, what do you estimate to be the probability p of getting a heads when you flip this coin? Using MLE, you would get p = 1. In other words, this coin will always give you a heads when you flip it! (According to MLE.)
Comment · 2 years ago
Only if you let the mistake go unmentioned. I do a version of this where I glibly include a mistake, like:

    // Examples of dereference operator.
    int i, *ip = ..., **ipp = ...;
    i = *ip; // Assuming ip has been correctly initialized.
    i = **ipp; // Likewise.
    // The address-of operator is the opposite.
    ip = &i;
    ipp = &&i;
I actually talk through the last line. Almost no one ever questions it. I then ask students to look at that last line again, and ask them if an address has an address, and if so, what does that mean, could it ever be useful?
Comment · 2 years ago
Yes, used in the past. I don't currently use them, though I think they are cool mechanical marvels, especially IBM Selectrics. Those were way too expensive to own personally, but were common in offices. My personal typewriter was a much cheaper Smith Corona electric.
Comment · 2 years ago
Oh, I personally don't currently use them. This was in the past, starting from playing around with my Dad's manual typewriter. Took typing course in 8th grade on a manual. Owned a Smith Corona electric in high school. Used IBM Selectrics for school newspaper, etc. I'm old. :-)
Comment · 2 years ago
Comment · 2 years ago
Bemused (https://www.merriam-webster.com/grammar/can-bemuse-mean-amus...) is another word that is often understood "incorrectly".

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