What are some example of borrowings from specifically _Iberian_ Romances? Not having looked into it beyond reading a bit about Esperanto's history, I'd always believed what the likes of https://en.wikipedia.org/wiki/Esperanto_etymology#Source_lan... said that French and Italian were sources. Of course there would be many Iberian cognates. Even estas which looks very Iberian has a different source https://en.wiktionary.org/wiki/esti#Esperanto
Let me interject with a related issue I've seen in HN and its "Who's hiring" posts. I'm tired of having to waddle through the crypto/blockchain/web3 offers that are seemingly and permanently 6 months away from solving most of humanities issues. Most of them are grifters and they should not be rewarded with visibility in this forum.
The cross became a symbol of Christianity because Jesus was crucified, not the other way around.
Moreover, crucifixion is just a pragmatic approach to traditional public executions. Many societies have used trees and walls to hang, kill and display the executed their necks broken, beaten to death, lashed, lynched, asfixiated, left to die of thirst or exposure... the method doesn't really matter, the point is they are there for everyone to see.
> It might change parts of the world where redundancy and integrity are threats to very powerful people who want to control transactions and corresponding data.
The dermatologists make small dots/arrow markings on the positively identified lesions. What the Nature paper apparently didn't do was remove the small markings in their training. It is probably an innocuous flaw since gradient-based investigation/ interpretation only took off later than their publication (2017).
As a result, instead of positively identifying the lesion based on disease pathology, it identified overwhelmingly based on presence or absence of medical marks. There was following up discussion in a certain paper of this experimental design (I can't remember the exact name), but they did gradient based activation mapping and those pointed to the marks as the identifying feature. It felt quite a revelation of why this worked so well.
Greg probably also knows SAS and AMPL, and has a good knowledge of ops research, which is within stone-tossing distance of whatever ML is pretending to be this week.
After 15 years of experience with SAS this sounds to me like saying "knowing how to write and having a pen makes you to a poet". But it depends on how far you can toss a stone...
OR is perfect when you can describe explicitly what the decision space is and what the restrictions are.
ML is great fit when you want to identify and use patterns. Quality control with machine vision is a good application for ML. NLP for PDF documents is a huge field for manufacturing as well. Companies have so much data in email attachments that they do not currently take advantage of.
> OR is perfect when you can describe explicitly what the decision space is and what the restrictions are.
As opposed to having to figure it out later from the outputs of a black box?
> Quality control with machine vision is a good application for ML.
I can't imagine CV could be an actual replacement for actual SPC in many industries. There's a reason we need to take samples and stress test, analyze composition, etc.
> NLP for PDF documents is a huge field for manufacturing as well.
NPL could be big everywhere... if it provides actual value, which is not a given. ML has a lot of tangential applications (you could also say, better forecasting), but how will directly improve manufacturing processes?
I apologize for being abrasive, but I'm so tired of cs people descending upon all industries, plugging shit data into pytorch and doing shitty ML like it will automatically add value. Even more so in industrial engineering, which in my experience is full of people way better at math than computer scientists and requires a deep understanding of the product and the manufacturing process.
> As opposed to having to figure it out later from the outputs of a black box?
Not all problems can be formulated as a set of explicit equalities, constraints and variables (e.g. machine vision). If explicit modeling is an option, of course you should do it. I am seeing efforts to try reinforcement learning on systems that we know how to describe with equations, and of course the results are laughable compared to the traditional methods.
> I can't imagine CV could be an actual replacement for actual SPC in many industries. There's a reason we need to take samples and stress test, analyze composition, etc.
In one big manufacturing company they were using Machine vision and a cheap web camera to control flaring. Could they do it with fancy sensors instead? Of course, but it would be more expensive, and they never did in the past.
Another manufacturing company is using machine vision to raise an alarm if the door of a cargo car of a train is not closed after loading. Could they install sensors in all of the doors of the train instead? Sure, but it would be cost prohibitive.
>NPL could be big everywhere... if it provides actual value, which is not a given. ML has a lot of tangential applications (you could also say, better forecasting), but how will directly improve manufacturing processes?
In manufacturing we have multiple people opening pdfs from emails to copy contract numbers to excel spreadsheets. Others are getting orders in emails and then type them in SAP manually. I think that these tasks can be automated specially with the recent versions of NLP networks.
>I apologize for being abrasive, but I'm so tired of cs people descending upon all industries, plugging shit data into pytorch and doing shitty ML like it will automatically add value. Even more so in industrial engineering, which in my experience is full of people way better at math than computer scientists and requires a deep understanding of the product and the manufacturing process.
All is good :) There has been a lot of unsubstantiated hype in ML, made even worse by big consulting companies and cloud providers who just sell the hype.
There is a significant amount of research from the field of computer vision before ML even existed. It was quite robust as well within certain constraints. Those techniques simply did not generalize anywhere even close to as well as deep learning.
However, that said, in a tightly controlled environment such as a manufacturing line trying to spot defects I would imagine they would have a good chance at performing a lot better than deep learning.
A lot of the advancements in deep learning have also come out of ideas from that research. While they didn't use the techniques directly, there is a lot of knowledge that we'd be lost without.
This is one thing that scares me about ML. We are losing research into the fundamental physics/science to deeply understand these things and instead just throwing models at them.
I work in this space: most "cool" ML is useless, and stakeholder are very skeptical of new modelling techniques. It is a long slog of EDA and finding actionable causality. Deep learning, modern reinforcement learning... are not the best fit here.
However I have seen CV and NLP useful here and there... but it is not the bread and butter.
A tangent, if you have time: where would I go for a primer on operations research and/or discrete event simulation?
My thought is that Goldratt's "The Goal" / theory of constraints is a useful way of thinking about optimizing throughput in a computer system. http://www.qdpma.com/Arch_files/RWT_Nehalem-5.gif plus an instruction latency table is something like a well modeled factory. (The Phoenix Project applies these principles to project management, which I think is a somewhat less useful analogy!)
I'm curious about applying existing tools to modeling things like: how will this multi-tiered application behave when it gets a thundering herd of requests? What if I tweak these timeouts, adjust this queue, make a particular system process requests on a last-in-first-out basis? Can I get a pretty visualization of what would happen?
The "if I had a penny" family of expressions dates back to a time when the monetary value of pennies was greater than the burden of carrying them around.
I might very well be mistaken, but this war and Russia's belligerence during the last 10 years never seemed to me a matter of ambition and territorial expansion, but rather desperation. Putin is 70, and his death will certainly plunge Russia into a period of turmoil. It doesn't matter if a successor is anointed by big P himself. The democratic opposition will see it as an opportunity for reform. The political and military elites will be fighting each other to advance their position. I'd be surprised if after Putin's death the Russian state could settle for a coherent agenda and foreign strategy within a decade.
The last time Russians found themselves in a similar position, NATO and the EU showed up at their doorstep. Baltic countries, Poland, Czech Republic, Hungary, Romania, Bulgaria... all of them joined NATO and/or EU in quick succession.
That's what I think Putin is trying to prevent. So the goal is to either have loyal buffer states (e.g. Belarus, Kazakhstan) or leave "unruly" buffer states (Georgia, Ukraine) in such state of destruction and disarray, that after Putin's death, Russia could get back on its feet before those states could focus again on entering international alliances. In other worlds, if I need 10 years to recover, I'll make sure you need 20 years, even if it adds a couple of years to my tally.
Of course this need of keeping NATO at bay exists only if the economic and political strategy of the state is to be an international gun for hire. It's a pity that the Russian elites decided to go for the easy buck with gas and military instead of developing the huge technical and artistic talent of the Russian people.
The irony is, after Iraq's invasion, NATO was incredibly unpopular in many European countries, and actions against Russia were seen as undesirable. I think fellow Europeans will agree that we saw Russia as an authoritarian state with old-fashioned values, but we were hopeful that one day we could have shared institutions and deeper political and economic cooperation. Now a lot of my fellow citizens perceive Russia as a direct enemy.
>The last time Russians found themselves in a similar position, NATO and the EU showed up at their doorstep. Baltic countries, Poland, Czech Republic, Hungary, Romania, Bulgaria... all of them joined NATO and/or EU in quick succession.
NATO and the EU did not show up at their doorsteps. Baltic and Eastern European states willingly joined NATO and the EU seeking better economic opportunities than what they had under Russian imposed communism and protection against future Russian aggression.
NATO didn't invade those countries under special military operations but those countries joined willingly since it was in their best interest and despite the EU's and NATO's faults, they're better alternatives than living in the fear of Russian aggression where the sate can imprison you for saying stuff against state approved propaganda and living in constant poverty and corruption.
Eastern Europe has ~50 years worth of scars to prove how vile such regimes were. That's why they were so eager to join NATO and the EU at the first chance they got and they flourished quiet well after that economically and socially. And Ukrainians wanted the same for their country since 2014, not living as Russia's puppet state forever.
The decision of those countries is perfectly legitimate (and in hindsight a very good one, seeing how Putin instrumentalizes Russian minorities).
But my point is, before the soviet collapse Russia didn't have a lot of shared borders with NATO countries. Now they do. If Ukraine, Moldova (who knows, maybe one day Belarus) end up joining NATO or the EU, this will considerably hinder their power projection capabilities. Expanding on McCain's analogy, Russia is a sketchy gas station where you can hire bruisers.
Well, now you're just being obtuse. Putin just got into an incredibly expensive war, and protests are marginal at best. This is achieved through repression and violence, but if you don't think that is stability, you're deluded.
No, it isn't
> it blended lots of words from Iberian languages
No, it didn't