The tech's also been there to put cameras everywhere, and to wiretap every phone, etc. We put guardrails in place to control how that tech is deployed.
Not sarcastic, but I probably didn't convey the subtlety of what I was trying to say in a one line comment. I was objecting to the defeatist "oh the tech is there, so we can't do anything about it" attitude. I tried to choose the examples I chose that the tech being there definitely has some consequences and significant privacy implications, but some controls exist too (like, wiretaps are still applied very selectively, there's been a growing movement against Flock cameras and scaling back of their deployments in some places recently).
To pull the example of Discord since the ExHashRing was mentioned in the OP: Needing to hash a few hundred things instead of one thing adds up when you do it a lot of times. They went with consistent hash ring over rendezvous hash because of that; every message needs to do one of these hash ring lookups, also whenever someone connects, they need to do a lot of these hash ring lookups to find all of their servers and friends.
There's plenty of scale below FAANG where efficiency matters.
The hierarchical (log(n)) approach to bucketing here is fine for an "I just want to shard this N ways, N will never change" but is extremely intolerant of bucket mutations.
Part of the point of rendezvous hash and consistent hashing is that adding and removing elements minimizes the amount of things reassigned. That is, if you add nodes, the only items being reassigned are those that are moving to the new nodes. If you remove nodes, the only items being reassigned are those leaving the departing nodes.
If you know your set of nodes never changes, or you don't care about the cost of reassignment, you don't need a rendezvous hash or consistent hash, you just need a plain old hash function.
> Now, if someone searches for an espresso machine, Gemini will pull up your most relevant products and instantly write a custom explainer highlighting why your product may be the right choice for them.
This is like the essence of the evil of AI ads distilled down to one sentence. For an advertiser this is a dream. For a user this reads like getting bombarded with ads tailor made just for you based on the context of what would be most effective.
It's just plain fraud. LLMs are hallucinatory, this is a basic fact of their basic design. You can't have them write product descriptions especially in advertisements, without any human supervision.
If the LLM invents a product feature that doesn't exist, you have advertising fraud done fraud. And if the LLM un-invents a feature that does exist, you have done fraud and pissed off the advertiser.
To not have these risks, you need to play it incredibly safe. E.g.: The bottom half of the Vertuo Up's blurb is just off the website.
<meta name="description" content="Vertuo Up is our new fast coffee machine, ready to brew in just 3 seconds. Enjoy 6 cup sizes and app connectivity for effortless control. Shop Pearl White.">
This would've been on old-Google. If you're an advertiser, Google is going to charge you their premium rates for a sloppy first paragraph you could've put there yourself if you wanted.
Note how the search query in that example asks for a "compact machine" but the explainer doesn't say anything about the size of the machine. The dimensions are right on the product's webpage. This advertising product doesn't want to risk the LLM fucking up something like the dimensions, so it just does nothing at all.
And the kicker is that none of this has to be a problem. It's Google, they can just ask the advertisers to hand them over a standard-format datasheet, and put the LLM to work figuring out what parts of the data the user wants and include those verbatim. If the LLM hallucinates, it creates a perfectly truthful but slightly less effective ad. If the LLM doesn't hallucinate, you've created an ad product that is better than most product comparison sites, something users want to use.
Well. If you were a for profit company and were offered to get the most effective ads ever at the cost of 0.1% of advertisement containing falsehoods about your product, would you take it?
What about if you know your competitors are taking the offer?
Silver lining: Is there a chance the ads will be relevant? Enterprise targeted advertising sophistication level is currently at "He just bought shoes; wow he must like shoes" or "He's 34-45M; make the reels only boobs.
I listened to a song a few weeks ago... now that song is in almost every page on YouTube for me. Homepage, sidebar, search results. It's just everywhere.
I've already listened to it. I don't want to listen to it again every single day for the rest of time.
Can’t wait for the AI rated™ product reviews. “This coffee maker doubles as a coin bank for your collection of rare pennies. Why brew a boring cup of coffee? Start your day with the taste of copper.”
I do wonder if that sort of system would be responsive to feedback. I would have told it something like "because you advertised this espresso machine to me, I will explicitly never purchase it. It's effectively banned from my household. Never recommend a product again."
Before it was:
"Shop for balding pills",
Now it's going to be:
"Your calendar indicates your mother's birthday is tomorrow, your album photos of her living room seem to indicate she likes elephants. In a past LLM conversation you mentioned she has trouble with technology. A good gift idea is the new Google Geminibook with this animal laptop skin. Add to cart?"
More like, "Your mom's birthday is tomorrow and you forgot again, didn't you? I've gone ahead and added this perfect gift to your cart that will be delivered in time. I'll purchase and ship it now if you'd like?"
But intelligent beings are fundamentally fallible? That's kind of the nature of doing leaps of reasoning: sometimes those leaps are amazing, sometimes they're wrong. It's what's advertised.
Glyph binning looks for any chunks in the image that are similar to eachother, regardless of what they are. Letters, eyeballs, pennies, triangles, etc without caring what it is. OCR looks specifically to try and identify characters (i.e. it starts with a knowledge of an alphabet, then looks for things in the image that look like those.
If the image is actually text, both of them can end up finding things. Binning will identify "these things look almost the same", while OCR will identify "these look like the letter M"
In companies I've been in, insider trading windows close because there's been a certain amount of time since the last report. So less frequent reports = more time for insider to know things that aren't public yet = more time unable to trade, not less.
"only 8 cents of every dollar shows up as direct aid and grants"
That's an extremely misleading statement. For instance, a food bank giving away food to a pantry does not count as "direct aid and grants" (at least, if they're defining that as "Grants and other assistance to domestic individuals." from the I-990" ). The salary for the warehouse worker operating the food bank is also not counted in that 92%.
Other cherry-picked statements like "32% of donors trust charities less today than they did five years ago" (not giving the percentage that trust charities more, or any other way to contextualize) make it clear that this is just a hit piece.
I don’t even get the point of this site. They say:
> Most of this spending isn’t waste. Hospitals need staff. Universities need facilities. Even small charities need people to run programs. The problem isn’t intent. It’s that the reporting system was designed to satisfy the IRS, not to show donors where their money went.
The complaint seems to be that the form filed with the IRS has the information the IRS is interested in, not the information whoever made the site wants.
The reality is that I know how the places I donate my money and time to use their money because I’m not relying on their IRS filings to get that information. I would suggest others do the same and donate to places where they understand what the org is doing and where the money is going.
Having a detailed and auditable report of how money is being used is really helpful for creating the understanding you are talking about. That is what accounting is for and why it is so essential to modern life.
The site is obviously just an advertisement for a weird camera surveillance system, but the concern about incomplete accounting is very real. In many places one might want to contribute to non-profit efforts, IRS information isn't even available. In my work in Ecuador, I have seen a lot of fraud, and half-baked charities. Some rich NGOs sometimes walk in on some field trip that donors have paid for, make some statements about all they are going to do and disappear without follow-up. Basically they are just tourists on a free vacation taking publicity photos. There is a specific organization that comes down to build environmentally safe toilets. Not only are these built by young middle class volunteers that know nothing about building anything but their CVs, the communities they are helping don't even need new toilets. The building supplies tend to be repurposed after the volunteers are gone, every single year. I'd like to know if I paid for that. There are seeds of merit in the program, but also unnecessary waste.
Despite negative examples, there are many worthy things that are done, and could be done in the region. Northern money can go very far in the areas I work. It can do a lot to not just improve but transform people's lives. So you suggest that an answer to money misuse is to have personal experience with any organization you donate to. How many people who have the money are going to spend any real time in Amazonian Ecuador? They aren't there now. What is going to change? Since there are few people with money who can be personally involved, does that mean that no effort should be made to better people's lives there? Obviously, that is what accounting is for. I think the article is absolutely right about that. I find their solution to be creepy and invasive. Maybe just having better auditing and reporting standards makes more sense than pointing cameras at hospital patients, but what do I know?
In a similar vein if anyone thinks this is an incorrect viewpoint (it’s not):
For every combat soldier in the Pacific Theater in WWII there were roughly 4.3 support soldiers. I don’t think anyone questions the fact you needed all those people for support and not direct action.
Fair point. I updated the article. The 7.7% is the "Grants and other assistance" line on the 990, and it applies to the $500B charitable nonprofit portion, not the full $3T. A food bank distributing food shows up under program expenses, not grants. The original framing was too easy to misread.
The bigger issue is that even the program expenses line doesn't tell you whether the program worked. A food bank spending $2M on operations could be feeding 50,000 people or 5,000. The form doesn't say.
That’s not a misleading statement for what they’re trying to say.
They wouldn’t disagree with what you say. The point they’re making is we don’t know. Maybe 92% of the remaining money is being spent usefully towards programs and 0% as overhead. Or maybe 0% usefully and 92% as overhead.
The IRS disclosure requirements are not sufficient to know. And yet we will give those donating to both organizations the same tax breaks.
The argument is to increase disclosure requirements for organizations through which so much money is passing so that we have a better idea as to how nether those tax breaks we’re giving are actually giving us any value in return.
The problem is there is no guarantee the warehouse worker at a food bank is doing anything of value. So we can’t assume such things are productive without direct evidence.
I think the material point of HN User Yuliyp's comment is that the organization claiming to be providing us with "Charity Sense", for some reason is not providing us all of the data we need to make sense of charities. Even worse, it seems to be deliberately disingenuous in presenting the data it does give us.
At least provide explanations of why certain things are included or excluded from the numbers they're presenting. Why are hospitals and universities lumped in with the food bank in the first place for instance? When you remove them, the numbers and percentages radically change. Not only that, it doesn't feel like the average person sees a food bank and a university, or a hospital, (and certainly not a university hospital), as the same sort of "charity". When you start digging deeper into the numbers, it just looks like they were lumped in to make the less resourced charities like food banks look bad.
Maybe there was some other reason they had for using this amalgamation? But they should be forthcoming with what that reason was.
If you’re making sense of something you need to include everything in that category.
It’s perfectly reasonable to create different subdivisions / buckets based your own definitions or NTEE code etc, but all those sub categories combined must add up to the same thing as how charities are defined.
The question was not why did the IRS amalgamate those organizations.
The question was why did Charity Sense amalgamate those organizations.
What value is it adding if it does nothing other than report data we could get from the IRS in any case? Saying, "Hey man, we just re-post the data we get from the IRS." Is the same thing as saying, "We didn't really do any analysis."
Yes, non-profits is a superset of "charitable non-profits". The IRS puts all 501(c)(3) organizations under the same filing framework. Hospitals and universities are in there alongside food banks and shelters. Breaking them out by NTEE code gives a more granular picture is a great idea.
501(c)(3) is just one of 29 types of non profits defined by the IRS. Many non-profits aren’t charities and some of them can even distribute profits.
501(c)(7) IE non profit social club for example could be just about anything from knitting circle to a S&M sex club. Have that club buy property and then at some point in the future sell that property at a profit which is then distributed to those members.
None of what they're pledging is much of a change from how they've already been operating:
- They already invest in new power plants and connection infrastructure when they bring in new datacenters
- Electricity for datacenters is based on capacity rather than actual usage
- They already have backup generators at most datacenters that they can run during outages. It wouldn't be much work to allow those to feed power back into the grid in extraordinary circumstances
- They generally use local contractors to build them for practicality purposes anyway.
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