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One of the in person interviews was at a company, somewhat well known, in Connecticut. They had a room with long tables and vertical walls about three feet high set on the tables with about enough space between each partition for a PC and a chair -- these were for 'developers' they wanted to hire.

Near the end of the visit, a nice girl in their HR office walked me to a bulletin board they had with their legal announcement of their job openings and their claim that they had to hire H1Bs because no qualified US citizens were available. We didn't say anything to each other, but the scam was clear, Hope they didn't fire her.

A friend, who worked with me at Yorktown Heights, recently went on an interview for a programmer slot. Apparently all the programmers were on H1Bs from Taiwan, India, and Russia. My friend didn't get hired. He's terrific at C, C++, C#, Visual Basic, .NET, FoxPro, T-SQL, and system management and administration of Windows Server, SQL Server, and Exchange. And he's an expert in AI with an applied math Ph.D. from one of the world's best math departments. Yup, guess those guys from India, etc. were 'better qualified'.

The early part of my career was greatly helped by the Cold War and the Space Race. That's why in two weeks I could go on seven interviews and get five offers. Yes, that was near DC. At one time I was making six times what a new Camaro cost. I still have the Camaro!

But as has been documented, about then some executives from industry and government got together to see if they could change that 'horrible' situation. The result was that the NSF set up a team of economists that did some supply-demand calculations and estimated how many more 'tech workers' would be needed to 'solve the problem'.

Then to get the 'tech workers', the NSF wrote into academic research grant contracts that so many students had to be supported. And, hint, hint, hint, such students are available from Taiwan and India.

So, for some years freshman calculus classes were taught by graduate students with good understanding of Chinese but poor understanding of English. Of course, if are going to study a subject in English but don't know much English, then about the easiest subject to study is math since the vocabulary is very small and the terms are very well defined.

Soon US citizens in college walked into computer science classes and, on the first day, saw only a minority of US citizens, sensed something wrong, and walked out. So for some years during rapid growth of computing in the US, academic computer science was very short on US citizens.

Really, the H1B program was designed and intended to flood the US labor market for tech workers, and basically the program worked.

Congress was getting pushed from two sides on the H1B situation. But 9/11 provided an excuse to throttle all immigration (except from Mexico!), and the permitted H1B slots were shrunk.

Now some tech industry executives are back at claims that the US needs more immigrant entrepreneurs to get 'skills' in 'short supply' in the US. So, amazing situation: In the US families commonly have one heck of a time paying for college. Even in the US, a good computer, printer, Internet connection, work space, etc. for learning computing is somewhat expensive. A lot of bandwidth to US servers is needed for downloads. Yet somehow in countries with average family incomes 10% of those in the US and 10,000 miles farther away from US servers people are 'better trained' in 'technical skills'. Amazing.

No, it's just an old story: Economic activity needs land, labor, raw materials, capital, etc. Anyone with one of these likes to believe that their part is the most valuable. So, the people in the US with the capital, and who never wrote 100 lines of software or invented an algorithm, tend to believe that they have the most brains, the most valuable part, and should have the most power and that labor should be like workers on a factory floor 100 years ago. They wrap themselves in notions like "The US is a nation of immigrants". Yes, Mayor Bloomberg, you are one of those people.

To me these are now very old issues and there are some larger issues:

First, Moore's law and related 'laws' for other hardware have been charging along so fast that what can be assembled for a development computer or a first server for $1000 in parts is astounding.

Second, common US Internet bandwidth is beyond belief, even for a server. Just do some arithmetic assuming a Web page that sends for 200,000 bits, with three ads, with some reasonable 'charge per thousand ads displayed' (CPM), and an Internet connection with 15 Mbps upload bandwidth for less than $100 a month, assume half fill that bandwidth 24 x 7, and estimate the monthly revenue. THen can join the supercharged Corvette of the month club or the 50 foot yacht of the year club. Multiply it out and see.

Third, US technical graduate education still totally knocks the socks off nearly all the rest of the world. If have some such education and some research and also a good application, then get a computer, type in the code, go live on the Internet, get users, ads, ad revenue, a Corvette and a passenger about 5-4, 110 pounds, good figure, natural blond, cute, sweet, majored in art history, good at cooking, sewing, playing piano or violin, singing, wants to be a wife and mommy, ...!

Yes, I've published in mathematical statistics, that is, the more serious version of 'machine learning'. And I've published in optimization, that is, the more serious version of 'planning' in AI. And my Ph.D. research was in stochastic optimal control, that is, the more serious version of the AI 'planning over time under uncertainty'. And I've done some applied math research for my project. I recommend this path instead of 'computer science'.

That is, if going to grad school, I believe that there are some serious advantages in a carefully selected collection of topics in applied math instead of 'computer science'. Start with an undergraduate major in pure math. Sure, somewhere learn to write some code and then get, say, three hours of lectures on 'algorithms and data structures'. In graduate school, take seriously measure theory, functional analysis, probability based on these two, stochastic processes, optimization, and mathematical statistics, at least. My guess is that you will have the best tools for the future of computing and 'information technology' entrepreneurship and won't have much competition from outside the US or even inside. And those math classes are NOT crowded!

I need to get back to it!

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