For context, I recently heard having a breadth of knowledge (along with depth in chosen areas) is really helpful in problem solving and I'm looking for concrete examples for the same.
- amount of data can vary from small to large - error correction
They don't have to just hold URLs and can contain raw information that custom programs can read. I love their use in it for virtual currencies as public/private addresses b/c it simplifies them for users. Venmo also picked it up not too long ago to easily pay/request to people you may not have friended which is useful for street vendors.
Someone posted an example here about contact tracing and how it just leads to a web form to fill details in. Ideally, if we had our shit together, there can be some standard contact tracing format for QR and use programs to scan the data in to auto fill and submit your details to.
I said "In what context?" because really, I didn't know either. "I have to scan this QR code if I go to my office. It's apparently posted at the door, and will let them know I've been there, for contact tracing."
After a lot of playing around, we finally found out her phone's camera could automatically read QR codes. When we did, the QR code in question was a URL to a website with a form, requiring her to enter all her information.
Not a fan of QR codes.
I went to a restaurant the other day and it had one of those Coke Freestyle soda machines. There was a QR code on the screen which I scanned with my phone. This opened a website with drink choices. I put my cup under the dispenser and pushed the Barq's Root Beer button on the website on my phone which dispensed the drink from the machine.
I was impressed.
Also Japan, being one of the earliest adopters, is still big on QR codes.
And of course anything involving mobile and cryptocurrency transactions. And mobile payments in most of South and South East Asia.
https://www.macrumors.com/2020/05/18/ios-14-leak-apple-qr-co...
[1] https://apple.stackexchange.com/questions/301563/what-is-the...
Since then the assumptions present in Black-Scholes and similar pricing models have caused considerable chaos elsewhere in finance. One of those things that perhaps it would have been better that they had not invented. Professionally it was great for the inventors though: they won the Nobel Prize at the time.
I am not sure it's better if that was not invented - the question of option pricing doesn't go away, it's a fundamental need for real businesses producing commodities that need to hedge real risk around the weather, or selling into cyclical industries etc.
LTCM (& it's failure) has as much to do with getting so big as to present a systemic risk to the entire financial sector, and over-leverage. No matter what formula they use to price their options, those two factors make for a dangerous combination. There is a perverse incentive to become "too big to fail", because if you truly reach that, the gains stay private whereas the losses are inevitably socialized to prevent taking down the whole system.
For about a decade, as I flew a lot, I met a lot of mid level executives at all sorts of companies. I routinely asked them to describe if their company used any derivative products, and which, and why. I was astounded to learn pretty much everyone did, from pricing plastics, to dealing with international trade variations, to getting financing for projects.
There is a reason the derivatives market has a notional value of ~1 quadrillion, and it's not because the people using them are all idiots. Quite the contrary, this value is there because it adds value across every sector of the world economy, and business the world over voluntarily use these products because they deem it in their best interests, which almost universally is because it lowers costs and/or volatility.
This [1] claimed 94% of the world's biggest companies used derivatives, and this was in 2009. I'd expect more and more of them to use derivatives over time as more products get priced.
All this followed from the ideas in Black-Scholes, for pricing certain contracts, ideas which were later developed to handle all sorts of products. Before this, people did a lot of the pricing mostly by guesswork, making it much harder to design and use all these volatility reducing products.
[1] https://derivsource.com/2009/04/23/over-94-of-the-worlds-lar...
I think you're off base on this. The ensuing financial mishaps just made the model better, but the creation of Black-Scholes brought us from 0% to 90% of the way to where we are today, where modern derivatives insure product price swings for almost everything across the world. Since then, a patch-work of model changes have brought us closer to perfect pricing through the realization that many markets have higher kurtosis.
ISO 9001 was implemented in manufacturing, and is quite popular in many circles of hell.
Shigeo Shingo's book (https://www.amazon.co.uk/dp/0915299178/) is particularly emphatic that Kanban was a was for repeatable industrial processes and not, for example, for knowledge work.
Automotive Kanban is not a "Todo"/"doing"/"done" board, by his account anyway. The tickets sat on individual work items and moved around the factory. It was about limiting the number of unfinished work items (which take up space and can be a sign that something is out of control).
But more generally to the poster's question - like the example above, I think there is a lot in the project management space that was already solved by computer scientists. :-)
As it happens, limiting unfinished work items (aka WIP) boosts software development productivity as well. The space being taken up is mental, but is also a bad sign of things spinning out of control.
Also, not an industry, but I think that some mathematicians use category theory to translate insights from one domain to other.
(Trying the recipe itself here to find a meta-recipe) I think an insight itself from category theory to a more general recipe could be: don't try to move "laterally" to other industry, but go first "up" from a specific solution to a more general interpretation, and see what more you can solve "down" from there.
One of my first projects out of school was a web app where our engineers could document the assembly steps for a given sub-assenbly, then string those sub-assemblies together into a manual for a specific product. The sub-assembly instructions would be revision controlled, and products would be revision controlled. The model was conceptually similar to git submodules.
I suspect a big one is "regular" engineering vs software engineering. Regular engineering has schedules and (apart from the apple campus) can put up a building in a predictable amount of time. Also testing and maintenance and more.
Was simulated annealing inspired by actual annealing (heating and slowly cooling metal/glass to toughen it)? Or did they just name it annealing after discovering it?
What is the relationship between thermodynamic/statistical entropy and Shannon's information theory entropy (E = -p lg(p))?
FRANCES H. ARNOLD Nobel Prize in Chemistry 2018
https://www.nobelprize.org/womenwhochangedscience/stories/fr...
Exploring protein fitness landscapes by directed evolution
https://scholar.google.com/scholar?cluster=18129095207210817...
https://academia.stackexchange.com/questions/9602/rediscover...
One of the most prolific scientists Albert Einstein had his single most productive year while working as a patent officer (Annus Mirabilis). I strongly suspect that he learned quite a lot from many patent applications, journal papers and books that he was required to read during his daily job, thus getting excellent and novel ideas from seemingly unrelated patents and discoveries.
The classic modern example (sorry for the oxymoron terminology) is how a patented signal processing technique of radio astronomy research by CSIRO solved the wireless multi-path propagation problem that enabled wireless revolution from WiFi to 4G/5G.
CSIRO's patent leads to the wireless OFDM invention that allows for much higher communication bandwidth especially on wireless environment where unmitigated multi-path interference is a deal breaker. But of course wireless people just hate to admit it [1].
[1]https://arstechnica.com/tech-policy/2012/04/how-the-aussie-g...
https://www.wsj.com/articles/SB116346916169622261
Knowledge from pit stop procedures improves speed and decreases accidents in hospital settings.
https://www.irenebrination.com/irenebrination_notes_on_a/201...
Many filters in Robotics (Kalman Filter, Particle Filter) and many concepts in digital communication (Modulation Schemes, Filters, ...) are firmly rooted in statistics and require a decent applied understanding of the area.
We sometimes refer to software systems as held together with spit and baling wire, but it's never literally true.
Others have noted the general influence in the opposite direction of the Toyota Production System on software engineering methodologies (most notably in that family of processes labeled "Lean"), but it is pretty clear Tesla could have stood to take a bit more direct influence from TPS on their assembly line.
We haven't seen anything like that at SpaceX (despite much armchair prognostication), but then, even as they ramp up production and launches, each rocket is still somewhat a bespoke product, and no one is going to get in trouble for holding up the production schedule when a problem is noted. Each rocket is still very much a pet, rather than cattle. It remains to be seen if the pace of iteration will slack off (or start conforming to a more regular punctuated cadence) as SpaceX continues to ramp up their capacity.
There have been a few efforts recently to try and apply aviation safety lessons to healthcare.
Interesting story on it here https://www.bbc.co.uk/programmes/p02x3vwh
Beyond that, I think cross breeding some insights from other fields could bring some efficiency improvements to problems that are squarely in the domain of computer science. OS scheduling, for example, has plenty of related people/materials scheduling parallels in the Operations Research field, and possibly some in Auction Theory as well. Same for load balancing (e.g. The Min Cost Multi-Commodity Flow problem).
https://armaghplanet.com/astronomy-magnetic-resonance-imagin...
The concept of bootstrapping. How to start something from nothing that eventually becomes self sustaining.
Compound interest and exponential growth. Particularly relevant to investing as well as the personal ‘growth’ mentality. The natural exponent that was discovered from compound interest is everywhere in mathematics and physics.
Originally came from the thought that seals on ammo boxes would cost soldiers precious time on the battlefield.
Today it's used for seal and repair in everyday life.
Seeing With The Tongue – Paul Bach-Y-Rita –
http://antonyhall.net/blog/seeing-with-the-tongue-paul-bach-...
https://www.wired.com/2011/08/0811hedy-lamar-george-antheil-...
Some of the "top" hospitals in the US are downright miserable to go to as a patient.
https://www.discovermagazine.com/planet-earth/quantum-honeyb...
Is the breadth of knowledge related to cross domain discoveries?
I would say bringing narrow skills like management or IT or marketing to a company is what you want to aim for.
I'm not convinced cross domain issues exist at rates higher than internal domain issues. I think they are orders of magnitude lower.
