The result is significant among the research community that work with quantum problems, but is insignificant and will not be considered as something interesting by the crypto community. When it comes to employment of methods for generation of uniformly distributed random numbers (both deterministic or ones that come from physical sources) - there are broadly accepted standards defined by NIST. So far those standards have served well both the crypto and information-security scientific community as well as the industry.
See Nathan O. Sokal, "Optimum choice of noise frequency band and sampling rate for generating random binary digits from clipped white noise," IEEE Transactions on Computers, vol. C-21, no. 6, June 1972, pp. 614-615. Random-digit generators based on the method described in the referenced article were manufactured in quantity in the late 1960s/early 1970s, and met exacting requirements for near-zero autocorrelation functions of the present digit to previous digits 1, 2, 3 ... digits prior to the present digit. Reprints, and assistance in applying the theory to actual hardware, are available from email@example.com .
What's so special about this? Surely a well-constructed analog circuit designed to generate a white noise spectrum, and free of other noise artifacts, followed by an ADC can be arranged to create a Gaussian-normal number stream.
Of course, this method fails when a coding application requires either algorithmic replication at a reciving site, or some other method of seeding the remote generator with a certain starting sequence. The latter can be achieved using the synchronization of specially-designed (analog) chaotic circuits.
"Today these applications have to depend on pseudo-random methods based on deterministic calculations of a physical system, usually based on a "seed" starting value."
No they don't. The usual source is quantum noise, usually from a reverse biased Zener diode.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.