If you don't have a TPM, you can get one of these usb sticks: http://www.entropykey.co.uk/ and it will also feed /dev/random with large amounts of real random data.
Many naive hardware based random number generators suffer from being not as random as one might think - thanks to quantising levels in A/D converters, to supposedly random physical processes having "spectra" where measurable signal occurs more in some bands than others, and to a multitude of other odd little effects just making a hardware based RNG is as simple as it seems.
The entropy key cited above has multiple noise sources and PRNG processes that mix them up and running checks to see that things are working as expected. That level of paranoid checking is more or less the minimum level required in a RNG to be confident about it.
Hardware RNGs sometimes rely on thermal noise (which is really random) but there are sometimes flaws with how that noise is sampled and de-skewed. Also, they need to be monitored to cope with hardware failure. Be aware, especially if you're using them for cryptography, that they might be a poor fit for your purpose.
Testing Hardware RNGs
(http://www.robertnz.net/true_rng.html)
EDIT:
Descriptions of various forms of noise:
(http://www.eie.polyu.edu.hk/~ensurya/lect_notes/commun_cir/C...)
And surely everyone on HN knows that part of the "snow" noise displayed on an untuned TV is cosmic background radiation, ie "afterglow" of the big bang. I still find that amazing.
When something is deterministic, it is reproducible and therefore not good for creating crypto keys.
Most /dev/random implementations use data from the ethernet driver, the keyboard, mouse etc to get some input which isn't easy to reproduce.
And truly random string is such string, that there's no possible program producing this string as output, that is shorter than the string.
On deterministic computers you can only produce pseudorandom numbers, with varying quality of randomness, depending on generator program you use, but it's sometimes not enough (esp. in cryptography).
The typical thing people do to get large amounts of randomness is to first generate some "real" random noise from some source (hardware thingamajigs, network timings, user interactions) and extrapolate these into longer sequences of random-looking numbers. The extrapolation can be fast and simple (in which case the randomness is not so good), or it can be slow and complex (to get decent looking randomness).
The laptop was relatively idle when the test was being run.
It's worth noting that when you do a --gen-key it does output the message:
"We need to generate a lot of random bytes. It is a good idea to perform some other action (type on the keyboard, move the mouse, utilise the disks) during the prime generation; this gives the random number generator a better chance to gain enough entropy."
I can't imagine it would state that if "5 seconds" was anything like normal. Perhaps you have some sort of additional source of entropy which you don't know about.
How do you determine that on Linux?
It is possible to provide true randomness from a chip, but it's probably cheaper not to.
http://spectrum.ieee.org/semiconductors/processors/behind-in...
http://en.wikipedia.orghwiki/RdRand
I suspect they just didn't consider RNG quality as a big factor in the usefulness of the design. TPM pre-dates the recent advances in on-die TRNG design. Plus the chip tends to live on a low-speed bus on the system which makes it inherently a bit crappy as a place to keep a high-bandwidth application like an RNG.
Personally I'd trust the random data supplied by a third party web service less than the pseudo-random data that the software on my local machine produces. Especially if you mix in data from a TPM, especially if you mix in data from an Entropy Key as well.