This is a perfect lesson in why strong communication skills are important in engineering organizations. It's leaderships responsibility to learn from engineering what is technically feasible but its also engineering's responsibility to communicate well enough to convince their organization on the right path forward.
It's likely you haven't come across these use cases in your professional career, but I assure you its very common. My entire career has only seen projects where you need dozen to hundreds of CPU's in order to have a short feedback loop to verify the system works. I saw this in simple algorithms in automotive, to Advanced Driver Assistance Systems and machine learning applications.
When you are working on a software project that has 1,000 active developers checking in code daily and require a stable system build you need lots of compute.
There's a lot of folks in startups who think 100 devs is a large org and can't comprehend the scale at which '100% tests pass' stops being a build blocker. I've migrated from such an org to a late stage startup and 'tests must pass' even if fifty engineers are blocked with their PRs and the release train is fully halted. 'But our pipelines must be green' no they don't, at least not all of them.
because there is no information transmitted once you've measured one of the entangled particles.
The other particle never knows the first one was measured.
Consider the analogy that in a box there are two apples. A Red delicious and a green apple. You and a friend close your eyes and take one and go home. You know look at your apple -- its red. Now you know your friend as a Green one without asking them. Was information magically transmitted? No. Was that faster than light communication? No. Could you keep taking apples out of boxes to transmit data? no
Your analogy with the apples is an oversimplification of what is going on that misses an important aspect of the system: the measurements aren't independent. The type of measurement you do effect the result of the measurement your friend does.
Yes but all analogies of physics are oversimplifications; d_sem's analogy still conveys "why it's not FTL communication", even though it suggests a hidden variable that doesn't actually exist — that the colour genuinely isn't determined until one of you measures it, is only something you can verify by talking about it with each other afterwards (and even then as a statistical artefact of many such measurements not just one).
> only those that leave out parts that are essential to the discussion.
I have yet to see a single physics analogy that covers every single aspect of the physics without being misleading. If the maths is easy enough to follow without needing an analogy, you just get the maths.
They don’t have to cover every single aspect, only those that are relevant to the discussion. The analogy with water in tubes for electricity is not an oversimplification when you explain relationships between voltage and current in a resistance. It only becomes an oversimplification when you try to explain, say, electromagnets.
"Just" partial differential equations of complex fields for Schrodinger; the fourier transform to shift between, what was it, momentum and position?; matricies and/or quaternions for the Bloch sphere; bra-ket notation; and the Hermitian, Hamiltonian, and Laplacian operators.
Of these, the only one I did in my double maths A-level was matricies and partial differential equations of single dimensional real functions, and the absolute basics of what complex numbers are.
Seems like it needs a degree to me, having tried to teach myself using brilliant.org
Reminds me of the late Neil Postman, who gave space to consider that technological trends have secondary effects that can potential make life worse.
As an avid user of wireless headphones I think its worth briefly entertaining the side effects. Increased expectation of isolation in classically social settings, possible long term ear damage, increased baseline cost to consumer.
And yet I can provide modern LLMs unique never before asked scenarios that require the ability to reason about real world phenomenon and they can respond in ways more thoughtful than the average person.
Much of human education is feeding books of information about things we will never experience in our day-to-day lives, and convincing ourselves it reflects reality. When in fact most of us have not personally experienced any evidences that what we learned is true.
That vast majority of what a person "knows" is a biological statistical pattern matching on steroids.
What you're describing is no different than a linear regression describing the predicted value between two data points. Sometimes the regression is close if enough data exists, other times you get wild hallucinations, with the model none the wiser whether it's correct. All this tells us is that there is a lot of data out there on the internet that can still have useful information extracted from it.
Take someone like Ramanujan, who with a couple math books on his own, could derive brilliant and novel discoveries in mathematics, instead of needing millions of man hours worth reading material to replicate what is mostly a replacement for googling.
Don’t be hoodwinked by a plausibility engine. The central dogma of oracle-type LLMs is that plausibility converges towards accuracy as scale increases. This hypothesis remains very far from proven.
> And yet I can provide modern LLMs unique never before asked scenarios that require the ability to reason about real world phenomenon and they can respond in ways more thoughtful than the average person.
One example is to provide it a list of objects and ask it what would be the most plausible way to stack them without damaging the objects while also being stable. Optionally, you can ask the model to generate a rational for the solution provided.
You can even invent a fictious object that has never existed, define it's properties, and ask the model to include it in the list.
you have a lot of resources about similar problems on the internet. so LLMs will have some patterns to leverage even if it is not even sure if you will get correct answers.
Some data retention requirements are mandated by law and it is necessary to develop robust systems that can stand the test of time. I've seen 15 and 25 year retention periods for data in safety related applications.
Things my interns learned in the first month as part of new hire training.
My quip above is to illustrate that in a dynamic and complex field its important we don't over index on experience.
What is happening in the Bay Area is large corporations are using 3rd party exchanges that make following the price guidelines a requirement to participate. The 3rd party is paid to set the regional prices. And they all win through fee's and higher rent prices.
Its old fashion collusion. Using the word algorithm obfuscates the simplicity in the criminal activity.
I feel this is right up the late Professor Neil Postman's ally. There are many interesting talks of his. Notably, a talk in 1993 hosted by Alan Kay, where Neil playfully gave an argument against computers in front of Apple computer engineers [1].
I find the value of momentarily taking Neil's critical view of technology seriously because it opens up the questions about the true value we bring to users. It challenges the bias companies impose on their engineers in pursuit of money over social value.
Typically for every argument Neil makes you can find a counter-factual and dismiss the point of view. However, the more I age and learn about history, the less I hold the religious belief that we are always doing good by adding abstract layers of information complexity over the human experience.
The recent data on smartphone/social media impacts on young children are a startling example that path we take towards technological progress is not always the optimal path.
It was a common theme in Apple WWDC conferences in the late 80's. Alan Kay has an interesting talk about agents.
I think it could be argued that the low hanging fruit aspect of agents where fulfilled by microservices and web based businesses. The concept of webpages populated with relevant data like google search pages, or Amazon populating products you'd like, could be called agent based. Netflix could be an example of an agent based service.
Car dominated societies inevitably will expose their inhabitants to micro plastics through synthetic tire rubber dust. There is basically no possible way to avoid them without regulation.
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