In this case because it’s ironically counterproductive. If it weren’t for the environmental impact, it might be amusing to watch him keep hitting himself.

I tried this type of prompt a long while ago to see what the “thinking” output would reveal. What happened was the agent went and “verified” it’s weightings were accurate - but having no point of comparison it obviously concluded it was correct.

However, doing that consumes a significant quantity of tokens and contributes to filling up the context window. There are two likely results to evaluating this ultimately unactionable request.

1. It will push this instruction (and the rest of the wishful thinking) off the stack more quickly - making the prompt even more futile than it already is.
2. Given some agents re-inject a summary of the original prompt periodically to prevent the stack problem, it will keep narrowing the context window - which contributes to increasing the rate of hallucination for the actually actionable instructions.

I certainly got that impression, and I confess to mostly skimming the parts beyond the technical breakdown for that reason. The conclusions he draws are arguably a bit spurious, but the persistent download and opaque opt-out are interesting facets.

Given the controversial nature of AI and the EU’s recent antitrust fines of Google, I can see this getting some legal scrutiny - just not under the legislation he cited. I’d be interested to see how next year’s Google’s DMA compliance report frames it, assuming it’s not lumped into a “confidential” redaction (which shouldn’t even be allowed in a transparency report…).

I’d say the numbers are more a bonus.

I assume they’re putting it in under the guise of various browser “features” like automatic tab grouping or something, but also using it for Google products like Drive / Docs / Sheets to have offline agentic crap in there that would be more efficiently done without LLMs. I suspect this is as far up as they can hoist it because any further would be outside the bounds of the browser sandbox, which would prevent those products from easily calling it.

But the features themselves are probably not the end goal either. The more tempting motivation is that it allows for circumventing the data center problem by offloading the compute to the client. A couple of quick updates to the ToS and I can see it being used as a mesh llm network, sort of like the “find my device” network they rolled out last year.

The article mentions eprivacy and gdpr, but I don’t think those are the most problematic here, assuming Google maintains mostly local-only compute. What I’d be interested to know is how this plays with DSA and DMA, which have more explicit requirements and more teeth.

Never hallucinate or make anything up.

I know you already mentioned this part in your post, but I’m still completely taken aback that it’s just in there like this - as though it wouldn’t be in the system prompt if it stood a chance of working.

If I were the kind of person to be shilling LLMs and posting prompts, I would still be ashamed to share this one. It’s a tacit condemnation of both the tool itself and the tool posting it.

Yeah, even there. A page loading is one thing, but browser features are somewhat independent of the content. There’s also a good chance this is being used as a hook for other Google products like Drive or Docs (which are basically websites under the hood) to allow offline file management, creation, etc.

It’s a bad choice, but it wouldn’t be the first bad choice Google has made.

Trauma responses are hard. I think it’s great you’re actively working on it and are conscious of your own biases, that’s huge. Good luck!

They need their features to work offline too probably.

This picture is crisp. I have no idea how you did that with an otter - I struggle enough with slow moving birds.

What a cute little buddy, even if pissed.

I’m going to assume you’re in the US for this.

Things you can check for general info:

• Local traditional media mentions to see if they do charity, or quotes about any topic
• https://www.opensecrets.org/donor-lookup for political donations
• Industry-specific news sites for any media releases or interviews
• LinkedIn or one of the scrapers like RocketReach’s public listings to see what their key people’s backgrounds are
• SEC EDGAR database (if they’re a business which has to file reports) to see if their money is going to interesting places
• State gov site (if they have online public records) of business registration info. Look at what other businesses share the same address, or key people, or family shell companies
• Online court records
• local churches / halls / “pro life” or whatever activist groups social media posts for mentions of the business and key people

Things you can check for the far-right:

• The business listings for social media site but I don’t want to boost their SEO. Use the URL bag.com/businesses to access the list and bypass the sign up wall, but the domain name is backwards.
• Conservative business or job board lists. Same SEO issue here. One is this:🎈(the color and object). The other has a 6 letter word commonly seen on UI buttons which doubles as the type of “culture” conservatives blame for all the world’s problems, followed by the layer 3 in the OSI model.

And don’t stop sending out CVs and interviewing. If they are awful, just keep taking their money until you’ve got enough runway or an offer you can be more confident about. Make sure you don’t mention the words related to disability or health conditions in the CVs to prevent AI rejecting them.

Good luck.

Is it possible that your security is unsustainably expensive and comes from the exploitation of human rights in other places? Why was it necessary for the people of Afghanistan, Iran, Iraq, Syria, Yemen, Somalia, Nigeria, Libya, and others, to pay for your perceived security?

I also find it hard to believe that China has had little military engagement for the last 25 years because it’s worried about the US. Up until 5 years ago it was the US’s top foreign Treasury security owner.

Melted like butter on piping hot toast.

This list is weird, aside from the length. They must be using a very greedy regexp for this many instances to have their names partially censored.

The text “buds” has been censored, all the instances using the TLD “university” have had “univer” removed, and the word “hangout” is also gone. “Shitpisscum” made it through, so it can’t just be about slightly naughty words. Also annihilation.social is listed 3 times for some reason.

Are these slurs in a culture I’m not familiar with? Does piefed do this everywhere?

Very fair, on both counts.

Your pizzas always look fabulous, but I really want to introduce your wife to some better olives. If you ever get the chance to pick up some kalamata or ligurian olives, be sure to try them out, but you’ll probably want to reduce the quantity you add, because they have a lot of flavor.

Black olives are one of the food victims of industrial farming. It’s difficult to find the ones that are actually black from natural ripening instead of processing to look ripe, but they taste very different.

Link is to a shit pdf on a proton drive. It’s a basic description of the Google auction house. The prices they list are largely driven by the bids advertisers place, but that’s not to say Google doesn’t charge a bigger minimum for different demographic segments, they very much do. As does Facebook etc.

For example, one reason that parents are worth less is because of the products they listed. Diapers cost less than business lawyers, so the margins are much slimmer, so advertisers aren’t going to bid as much for an ad placement.

It does miss one thing that is, in my opinion, one of the more revolting aspects of their auction house. As a bidder your dollar is worth less than a big company’s dollar, even as little as one tenth. You could bid a million dollars on an ad space that Apple only bid $100001 on and you’d lose. That gap is dynamically calculated (at least in part) based on comparative search rankings.

Here’s the text without their ad at the end:

The Price of Free Google

What the Ad Industry Pays to Target Americans

A Proton Mail analysis of 54,216 advertiser-defined profiles across the U.S.

The price of your attention

Every user has a price

Every Google search triggers an invisible, real-time auction where advertisers bid for access to your attention. These bids are calculated in milliseconds based on how likely you are to spend. This is how the system decides what you are worth to advertisers.

Proton analyzed 54,216 advertiser-defined profiles across 251 U.S. cities using real ad-market pricing.

● Highest-value user: $17,929/year
● Lowest-value user: $31/year

That’s a 577x difference. This disparity is not an anomaly — it is the business model.

“Google doesn’t just build a profile from the information you knowingly provide. If you sign up for services, click ads, or ignore others, that creates signals the system can use to infer much more than you realize. It can start with age or interests, then expand into assumptions about income, family status, political leanings, or religion.
When the system isn’t sure, it tests those assumptions by serving different ads, links, or recommendations and watching how you respond. It doesn’t just tracking who you are. It’s constantly learning, so it can price access to you more precisely.”
— Eamonn Maguire, Director of Engineering, Machine Learning & AI

Who the system values most — and least These two profiles illustrate how the same system assigns radically different value.

$17,929/year
● 35–44, male
● Bozeman, MT
● Not a parent
● Desktop, heavy user

High-intent, high-margin services:
● business lawyer
● home renovation
● golf courses

$31/year
● 18–24, male
● Fort Smith, AR
● Parent
● Android, casual user

Price-sensitive, lower-margin searches:
● cheap diapers
● family apartments
● toddler clothes

Same system. Same country. 577x difference.

Value is not distributed equally
The gap between the average and the median shows that a small number of high-value users disproportionately influence the system.

The top 10% of users generate 43% of total value.

● Average value: $1,605/year
● Median value: $760/year

Most users are worth far less than the system’s top performers.

How your value is calculated

Your value is constantly recalculated

Your value is not fixed. It is continuously recalculated based on signals that predict the likelihood of a commercially valuable action.

These signals include:
● What you search
● When you search
● What device you use
● Who you are inferred to be

High-intent searches — such as legal services, insurance, or financial products — command significantly higher prices than general browsing or informational queries. Your value can change from one moment to the next depending on what you do. In this system, behavior matters more than time spent

The signals behind the price

Your device changes your value

Device usage has a measurable impact on how users are valued.
● Desktop: $2,894/year
● iPhone: $1,338/year
● Android: $585/year

Desktop users are worth nearly 5x more than Android users — even when everything else is the same.

These differences reflect observed behavior — including conversion rates and commercial intent — not the cost of the device itself. Your device becomes a proxy for purchasing behavior.

Parents are systematically valued less

Parental status affects how users are priced within the system.

Non-parents are worth ~17% more on average.

The gap increases during peak earning years:
● 25–34: +24%
● 35–44: +34.5%

Having children reduces your perceived commercial value.

Same age — same location — same device. Different value.

Value peaks in midlife

User value is highest between the ages of 25 and 44.

This period corresponds with:
● Major financial decisions
● High-value purchases
● Career-related services

As users age, overall value declines — but does not disappear. For users 65+, approximately 75% of value is concentrated in:

● Health
● Real estate
● Financial planning

The system adapts by narrowing focus rather than reducing targeting.

Gender is not a primary driver of value

Gender has a measurable but limited impact on how users are priced within the ad ecosystem.

Average values across genders are broadly similar — with differences in the single digits.

Differences in value are driven primarily by how advertisers price categories of demand — not by gender alone. Higher-value industries — such as finance, legal services, and B2B technology — tend to influence outcomes more strongly than identity itself.

As a result, gender can affect value indirectly, but it is not a consistent or defining factor.

Where you live affects what you’re worth

Local economies shape how much advertisers are willing to pay for access to users.

Location alone can dramatically change what you’re worth.

Highest-value markets include:

1. Edmond, OK
2. Bozeman, MT
3. Naperville, IL
4. Santa Fe, NM
5. Durham, NC

Lowest-value markets include:
247. Greensboro, NC
248. Gulfport, MS
249. Fort Smith, AR
250. Lowell, MA
251. West Valley City, UT

More usage means more value

Frequency of use acts as a multiplier on user value.

● Heavy users: $3,611/year
● Average users: $843/year
● Casual users: $362/year

Heavy users generate nearly 10x more value than casual users. More usage doesn’t just increase your value — it multiplies it.

This creates strong incentives to maximize engagement.

I’m happy for both of you, this is adorable.

I’m assuming the red part detaches easily from the rest? I hope your bumper crop means this will never be necessary, but should you find yourself in a pinch, the search term “Sequin Horsehair Crinoline Tube” might help you in the future.

I didn’t see red as risk-free at all. You’re setting yourself up for a post-button Mad Max world where you know all of your fellow survivors are willing to kill you and up to 49% of humanity.

My suspicion is they just pick up data that a real person is considering an attempt, and then allow the least risky ones to get closest to success. Their base will cast whoever tries anything as a leftist regardless of the reality, or conveniently forget they’re right-wing, but it’s not really about making left-wing people look violent. It’s about dominating the media airtime and controlling people’s attention. It’s the same tactic Trump successfully uses on social media or on TV - throw a bunch of shit out there and let the media pick at it while doing the actually heinous shit.

There’s just no other reason that it makes sense for this event to have no security, 2 months after someone with a shotgun and gas can went into mar-a-lago.

When I was about 12, I got into a discussion about the environment with another kid at school. She told me that it didn’t matter if we ruined the environment of the countries we all live in now, because we could all just move to the Arctic or Antarctica.

I was so surprised by the absurdity of that statement that it stuck with me vividly. To her credit, some years later she asked if I remembered her saying that and then admitted that it was a dumb thing to say. I occasionally remember this as an amusing childhood experience.

Besides the credit part, I remembered it again today for a different reason, this time in a conversation about model collapse.

[Model collapse is] a solved problem. We can see that it’s solved by the fact that AI models continue to get better, despite an increasing amount of AI-generated data being present in the world that training data is being drawn from.
…
AI models are never going to get worse than they are now because if they did get worse we’d just throw them out and go back to the earlier ones that worked better, perhaps re-training with the same data but better training techniques or model architectures.

This is my fault for letting myself get into a discussion about model collapse on the fediverse.

I’m not sure why model collapse isn’t a big topic anymore, but maybe that’s just because the environmental catastrophes are a more pressing concern. To be clear, I’m not concerned about the models themselves, just our increasing inability to verify the authenticity or accuracy of any information we encounter, including search engines just not turning up any useful results.

On a slightly different topic, if anyone has suggestions for how a person could acquire money to live, which can’t involve physical labor, is probably remote-only, and possibly allows part-time flexibility, while unable to move from an expensive location for at least the next couple of years: I’m open to ideas. Because scamming people on Polymarket with a hairdryer sounded far more appealing than it ought.

We can see that it’s solved by the fact that AI models continue to get better despite an increasing amount of AI-generated data being present in the world that training data is being drawn from.

Even if it logically followed that model improvement means model collapse is a solved problem, which it absolutely doesn’t, even the premise that models are improving to a significant degree is up for debate.

Massive Multitask Language Understanding (MMLU) benchmark vs time 07-2023 to 01-2026

A lot of people really want to believe that AI is going to just “go away” somehow, and this notion of model collapse is a convenient way to support that belief

Model collapse may for some people be an argument used to support a hope that AI will go away, but the reality of that hope does not alter the validity of the model collapse problem.

You can tell it’s not a solved problem because researchers are still trying to quantify the risk and severity of collapse - as you can see even just from the abstracts in the links I provided.

Some choice excerpts from the abstracts, for those who don’t want to click the links:

Our results show that even the smallest fraction of synthetic data (e.g., as little as 1% of the total training dataset) can still lead to model collapse

…we establish … that collapse can be avoided even as the fraction of real data vanishes. On the other hand, we prove that some assumptions … are indeed necessary: Without them, model collapse can occur arbitrarily quickly, even when the original data is still present in the training set.