First, prices per se are irrelevant. The ratio of labor price to goods&services price is relevant.
Second, the labor / goods&services price ratio itself is irrelevant, as measured in the short term. What is relevant is the long term outlook of this ratio. See eg the Dutch Disease.
Third, even the long term labor / goods&services price ratio is irrelevant. Not everything in this world is, or should be, reducible to simplistic financial value.
One way to approach the underlying intuition is in terms of homeostasis, at nation state level.
I'm confused, are you asking we close our eyes and only operate on internal bias? Where does the world matter if no single metric is relevant? Regardless of number metrics, what do you think matters? I think a family that can no longer afford a laptop for their child's education matters. I think 10,000 or 100,000 such families matter a lot. How do we tell that story? What options have we but the numbers?
Long term median purchasing power, especially of essentials eg housing / food / energy / education, matters more to the health of a nation than the price of hitech on open global markets at a specific time instant. Furthermore, while the health and wealth of a nation are correlated, they are not the same. I wonder if there is a sensible way to prioritize health over wealth.
"How do you make sure that a hotel room cannot be booked by more than one person at a time" Excellent question! You don't. Instead, assuming a globally consistent transaction ordering, eg Spanner's TrueTime, but any uuid scheme suffices, it becomes a tradeoff between reconciliation latency and perceived unreliability. A room may be booked by several persons at a time, but eventually only one of them will win the reconciliation process.
A: T.uuid3712[X] = reserve X
...
B: T.uuid6214[X] = reserve X // eventually loses to A because of uuid ordering
...
A<-T.uuid6214[X]: discard T.uuid6214[X]
...
B<-T.uuid3712[X]: discard T.uuid6214[X], B.notify(cancel T.uuid6214[X])
-----
A wins, B discards
The engineering challenge becomes to reduce the reconciliation latency window to something tolerable to users. If the reconciliation latency is small enough, then a blocking API can completely hide the unreliability from users.
On the core observation "there are too many implementation choices", that is not quite right. True, the author mentions 4, and there are further variations. In practice, a library can:
1. Implement all suitable graph representations.
2. Implement algorithms tailored to the representation(s) that offer the highest performance.
3. Provide transformations from one representation to another. This is O(#representations), trivial to implement and trivial to use. Quite fair workload for both maintainers and users.
4. Bonus, provide import / export transformations from / to common standard library datatypes and idioms.
Memory and transformations are cheap, 99% of use-cases would likely find the overhead of transforming data, both in RAM and CPU, negligible.
Sounds like the makings of a huge library that I’m not sure I’d even use in my work. I use graphs heavily in my work, and my experience matches the people the author interviewed.
We always end up reimplementing graphs because:
- Performance matters, and no off the shelf graph library I’ve seen can take advantage of many of the regularities in our particular data set. (We have an append-only DAG which we can internally run-length encode because almost all nodes just have an edge pointing to the last added item).
- I haven’t seen any generic graph library which supports the specific queries I need to make on my graphs. The big one is a subgraph diffing function.
- Writing something custom just isn’t much work anyway! Graphs are way simpler to reimplement than btrees. You can have a simple graph implementation in tens of lines. Our highly optimised library - with all the supporting algorithms - is still only a few hundred lines of code.
I think it would be handy to have ways to export the data into some standard format. But eh. I think pulling a library in for our use case would add more problems than it would solve.
What do you mean by “subgraph diffing”? I work with graphs a lot and use SQL almost all the time. Sometimes I need to compute connected components with python.
I have DAG. I can then define a proper subgraph from some set of nodes {A, B, C, ...} such that the subgraph contains all transitive dependencies of that set of nodes. Given two sets of nodes X and Y, I want the set difference between the subgraphs of nodes defined by X and Y (and all of their transitive dependencies). So, what nodes exist in the subgraph of X but not in Y, and vice versa?
Ie, if we have the graph { A -> B, A -> C } then the diff between {A} and {C} is ({}, {C}). And the diff between {B} and {C} is... well, ({B}, {C}).
BigTech, which critically depends on hyper-targeted ads for the lion share of its revenue, is incapable of offering AI model outputs that are plausible given the location / language of the request. The irony.
- request from Ljubljana using Slovenian => white people with high probability
- request from Nairobi using Swahili => black people with high probability
- request from Shenzhen using Mandarin => asian people with high probability
If a specific user is unhappy with the prevailing demographics of the city where they live, give them a few settings to customize their personal output to their heart's content.
The rationalization for injecting bias rests on two core ideas:
A. It is claimed that all perspectives are 'inherently biased'. There is no objective truth. The bias the actor injects is just as valid as another.
B. It is claimed that some perspectives carry an inherent 'harmful bias'. It is the mission of the actor to protect the world from this harm. There is no open definition of what the harm is and how to measure it.
I don't see how we can build a stable democratic society based on these ideas. It is placing too much power in too few hands. He who wields the levers of power, gets to define what biases to underpin the very basis of the social perception of reality, including but not limited to rewriting history to fit his agenda. There are no checks and balances.
Arguably there were never checks and balances, other than market competition. The trouble is that information technology and globalization have produced a hyper-scale society, in which, by Pareto's law, the power is concentrated in the hands of very few, at the helm of a handful global scale behemoths.
The only conclusion I've been able to come to is that "placing too much power in too few hands" is actually the goal. You have a lot of power if you're the one who gets to decide what's biased and what's not.
...and if any individual room isn't profitable in any quarter of the year, I need the ability to detach it from the building and dump it. I don't care about any furniture inside, dump it too.
the attitude of those that do it: "what are you going to do about it?". escalatory power games, not an ounce of caring for your fellow man, barely a veneer of. we have entered very dark waters. unclear where the exit is.
The financial few have created a battle against the very world that have put them there. It might not be clear where the exit is, but it's clear the incentives are fundamentally opposite. Something, something Emperor's new clothes
Preventing or slowing the development of AI is just a startling contempt for human life. Every day millions of people die unnecessarily. Willingness to let that happen because you think your family (or, most likely, a giant corporation) deserves to be paid for a century after you die is sheer selfishness and ignorance.
Well, for one, you can't read a lot of scientific journals without paying massive fees.
That arguably slows down the pace of medical advance.
One might note that those massive fees do not go to the "creatives", in this case the scientists. The scientist do the research, write the papers, peer-review the papers of others, edit the journals... and the publisher pockets the money. That's the case with most "intellectual property" -- the person who actually gets paid the lion's share is not the "creative".
Or just a parody of accelerationist logic. There are so many fools on the internet that you often can't tell the fake fools from the real ones unless they give themselves away.
Currently the weapons against bullshit is trying to talk to it. Engage and you'll find only 5% of the time there is depth, or earnest.
The rest is just airing itself like dirty laundry by the second response and ultimately just serves in contributing to a humans ability to quickly adapt to new environments. Which means bullshit just smells more nuanced today.
If this was all done in the open as hoped, as promised and the worlds scientists were in pursuit of the same goal, I'd accept these arguments all day and keep my ignorant mouth shut. But to lie and say otherwise goes against the timeline of history we're all a part of. OpenAI lied about its openness. It then aligned militarily. It didn't offer to remove your data before this came into effect, did it? Source me if I'm wrong.
A private company securing the worlds resources physically, financially and informationally and selling it to anyone of its choosing or not -- is the true startling contempt for human life, especially those that follow along without an ounce of critical thinking.
It would obviously be better if everything were done in the open. But you can't simply say "corporations will corrupt AI with copyright regime X" and compare it to a hypothetical universe "copyright regime Y will result in corporations acting with altruism." Regardless, corporations are going to be rent-seeking parasites trying to maximize their profits at all costs.
The world you're arguing for isn't one where small-time artists are adequately compensated for their work. It's one where Disney and Elsevier collect a bunch of rents and hold back development of tools that would radically improve human well-being. Even in the best case, your copyright suggestion will privilege the giant corporations who have the capability to navigate copyright rules against a bunch of other giant corporations, at the expense of smaller researchers and hobbyists.
I'd be more than happy to sign into something saying "a small artist has a right to prevent training on their work without permission for a decade after it's released." But that is not in the cards, unfortunately.
> Even in the best case, your copyright suggestion will privilege the giant corporations who have the capability to navigate copyright rules against a bunch of other giant corporations, at the expense of smaller researchers and hobbyists.
Copyright doesn't really privilege giant corporations. In a world without it, they can just use their market power and immense resources (e.g., SaaS) to protect their interests.
Copyright is one of the few tools the little guy can use to protect their interests against giant corporations. Abolish it, and one of the first things that will happen is the RIAA will stop paying artists anything and become the biggest "pirate" in the world.
It's mind boggling how some people have that so backwards. I'm guessing it stems from only thinking about copyright in the context of "RIAA sues..." articles and complaints about Elsevier, without thinking about it from any other angles.
It's cognitive dissonance to such an arrogant and ignorant degree it's turning out to be the best sunlight we've ever needed on the situation. No one is arguing a balanced or logical alternative. Every argument ignores the entire landscape of issues and reduces it to 'what's yours is mine but what's mine is not yours'..... They're arguing to keep the toys in their playground. Even if it's not their toy. It's 'in the world' so we're free to take it.
Ok! I appreciate this insight. At this point I'll be 'scraping' everything from tech and fight this in court with their own words.
"have scientific journals disappeared" -- ironically, in the AI field most of the action is on arxiv / github / twitter. journals have been obsolete for decades, and the '10s obsoleted conferences too. the only function journals / conferences still serve in the AI field is to stack rank researchers and provide signal for hiring / funding decisions.
Second, the labor / goods&services price ratio itself is irrelevant, as measured in the short term. What is relevant is the long term outlook of this ratio. See eg the Dutch Disease.
Third, even the long term labor / goods&services price ratio is irrelevant. Not everything in this world is, or should be, reducible to simplistic financial value.
One way to approach the underlying intuition is in terms of homeostasis, at nation state level.