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The FTC article links to the federal complaint[0] which names the third-party data recipient as Clarifai, Inc.

"In September 2014, the CEO of Clarifai, Inc. e-mailed one of OkCupid’s founders requesting that Humor Rainbow give Clarifai, Inc. (i.e., the Data Recipient) access to large datasets of OkCupid photos."

[0] https://www.ftc.gov/system/files/ftc_gov/pdf/OkCupid-MatchCo...


So, your dating photos were going to a government contractor involved with AI killer drone technology.

https://en.wikipedia.org/wiki/Clarifai#Military_work


> Their technology was used by Unilever, Ubisoft, BuzzFeed

And apparently also your deodorant, Assassin's Creed, and tabloid rags as well. That's what I call variety.


Killing singles near you!

Killing significant others to broaden the dating pool! Delivering value to existing users!

This is clearly the follow up to the dril tweet - you do not, in fact, have to hand it to them for figuring out how to monetize the enemy combatant guidelines

That’s must the reason why some people can’t get a partner /s

> The platform includes the ability to moderate content, perform visual search, visual similarity, and organize media collections. It has pre-built recognition models that can identify a specific set of concepts like food or travel, NSFW, and its general model which can identify a range of concepts including objects, ideas, and emotion.[18] It also has the ability to create custom models which can identify other arbitrary objects such as cars or breeds of dogs.[19] The 2018 Model 1.5 with machine-labeled datasets claims to recognize up to 11,000 concepts from object detection, as well as things like mood or theme.

sooo, why are they after some dating profile pics if the model was about “identifying and labeling pictures”? You can safely assume their new model will be (already) trained on your pictures to crosscheck you on other platforms or surveillance system, coupled with accurate positioning, you can guess the rest.


Former Apple employee here. This is a deeper quirk of Apple culture than one would guess.

Each and every Radar (Apple's internal issue tracker is called Radar, and each issue is called a Radar) follows a state machine, going from the untriaged state to the done state. One hard-coded state in this is Verify. Each and every bug, once Fixed, cannot move to Closed without passing through the Verify state. It seems like a cool idea on the surface. It means that Apple assumes and demands that everything must be verified as fixed (or feature complete) by someone. Quite the corporate value to hold the line on, and it goes back decades.

I seriously hated the Verify state. It caused many pathologies. Imagine trying to run a burndown of your sprint when zero of the Radars are closed, because they have to be verified in production before being closed, meaning you cannot verify until after the release. Another pathology is that lots (thousands and thousands) of Radars end up stranded in Verify. Many, many engineers finish their fix, check it in, it gets released and then they move on. This led to a pathology that the writer of this post got caught up in: There is lots of "org health" reporting that goes out showing how many Radars are unverified and how long your Radars stay in the unverified state on average. A lot of teams simply close Radars that remain unverified for some amount of time because they are being "graded" on this.


Interesting insight to what should be a good internal process if users followed up.

In this case the bug wasn't fixed.

> A lot of teams simply close Radars that remain unverified for some amount of time because they are being "graded" on this.

The simple solution here: you should also be graded on closing bugs that get re-opened.


> Imagine trying to run a burndown of your sprint when zero of the Radars are closed, because they have to be verified in production before being closed, meaning you cannot verify until after the release.

I think most teams use verify as a "closed" state to hide all that messiness. But sure, zero bugs is a project management fiction and produces perverse outcomes.


I think you're incorrectly assuming two things:

1. Apple engineers actually attempted to fix the bug.

2. Feedback Assistant "Please verify with the latest beta" matches the Radar "Verify" state.

I don't believe either of those are true.


> Am I missing something?

You are indeed missing a TON. A lot of Open Claw users don't give it everything. We give it specific access to a group of things it needs to do the things we want. If I want an agent to sit there 24/7 maximizing uptime of my service, I give it access to certain data, the GitHub repo with PR privileges, and maybe even permissions to restart the service. All of this has to be very thoughtful and intentional. The idea that the only "useful" way to use Open Claw is to give it everything is a straw man.


The problem is boundary enforcement fatigue. People become lazy, creating tight permission scopes is tedious work. People will use an LLM to manage the scopes given to another LLM, and so on.


> creating tight permission scopes is tedious work

I have a feeling this kind of boundary configuration is the bread and butter of the current AI software landscape.

Once we figure out how to make this tedious work easier a lot of new use cases will get unlocked.


I definitely think we'll write tools to analyse the permissions and explain the worst case outcomes.

I can accept burning tokens and redo on the scale of hours. If I'm losing days of effort I'd be very dissatisfied. Practically speaking people accept data loss because of poor backups, because backups are hard (not technically so much as administratively), but I'd say backups are about to become more important. Blast limiting controls will become essential -- being able to delete every cloud hosted photo is just a click away. Spinning up thousands of EC2 nodes is incredibly easy, and credit cards have extremely weak scoping.


100% this. Human psychology is always overlooked in these discussions, and people focus on "perfect technical solution" without considering how humans will actually end up using them. Linux permissions schema are a classic example, with many guides advising users to keep everything as locked down as possible, and expanding permissions as and when required. After the 100th time of fucking around with chmod, users often give up and just make everything 777. If there were a user-friendly (but imperfect) method (like Windows' UAC), people would actually use it, and be far safer in the long run.


You could do that with say Claude Code too with rather much simpler set up.

OPs question was more around sandboxes though. To which, I would say that it's to limit unintended actions on host machine.


I want to be proven wrong, but every use case someone presents for OpenClaw is just a worse version of Claude Code, at least, so far.


Can you talk us through that a bit more? I suspect it would need more access than the permissions you mentioned to be more useful than a simple rules based automation.


Why would I want non-deterministic behavior here though?

If I want to max uptime, I write a tool to track/monitor. Then write a small agent (non-ai) that monitors those outputs and performs your remediation actions (reset something, clear something, etc, depends on service).

Do I want Claude re-writing and breaking subscription flow because it detected an issue? No.


So, what does having inference done by NVIDIA directly add?


I have given the “never trust the judgment of someone who says it should be a one-line fix” so many times I am basically doxxing myself with this comment.


PV is fairly unique in that land is not required. It can be installed over existing land uses such as rooftops, canals, parking.


> You cannot build a good AI phone without first building a good phone. You cannot build a self-driving car without starting with a good car, etc.

More like you cannot build a self-driving car without starting with a good phone. See Huawei.


Comedy requires deep thinking, powers of observation, and self-reflection.


So among Harris voters, the assassination was about as popular as a Trump policy. And yet here we have people trying to say it's popular among lefties. We do not deserve nice things.


Put simply: It is in the national interest to have the world's most talented technologists here. It is yet more in the national interest that they work here, for us, and not for our enemies. One of the best ways we can compete with China is to attract their best and brightest with our free society and high wages.


The average L5 SWE salary at Google in the SF Bay Area is $215,000 [1].

1. https://www.levels.fyi/companies/google/salaries/software-en...


That's base pay. Equity is typically another $100k at least.


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