As a side note, the Apple Watch changes have completely made Camera Remote unusable for me, a feature I loved.
I don't know why, but I usually can only get Camera Remote to work when I close all of the recent apps on my Apple Watch, even when my watch and phone were the newest ones Apple released. Probably a bug with memory management they're never going to fix. Now, that's not possible, even when I reboot my watch :(
I'm with you. The new Watch update messed a lot of stuff up for me. I have Shazam linked to my Action Button; it's always been flakey but it feels flakier lately. Losing Walkie-Talkie is a big miss too, as my wife and I use that feature often.
Our experiences diverge surprisingly far. The new Siri was worse for everything I use it for before I turned it off.
The new Siri can not reliably return the weather (it seems it's prompting on the literal text of the town and asks for a clarification sometimes about whether I am in the United States or United Kingdom), and when I ask "what is the air quality index", the new Siri would sometimes return the definition of AQI. When it returns a value, new Siri would hallucinate an incorrect and fixed value. In the cases where it does work, it's very much slower than the classic "rainbow orb" Siri.
It does as long as you've typed something that doesn't match an app. "Safari" and enter will open Safari. "What is safari" and enter will ask Siri the question and show the answer.
Maybe you could set up an Alfred workflow for that using a special hotkey? And then you could use Karabiner-Elements to invoke that when you double-tap Cmd.
This sounds like speculation based on a few viral instances. Can you provide any sources? The moon problem you're describing was attributed to a 2023 Samsung, which was using neural upscaling. Can you provide a source describing this for this specific model (Huawei Pura 80 Ultra)?
Computational photography isn't just the smoke-and-mirrors of AI upscaling faking information. You really can get around the limitations of physics on a traditional lens with non-generative computational photography techniques, incorporating real information, like the time-series data over the length of an exposure, the data from other sensors like the accelerometer or lidar, or data from an array of lenses (as others have pointed out).
Even without those tricks, the Pura 80 Ultra specifically uses a much larger camera sensor than most phones.
This is a BBC article about the UK being at war. Not the USA.
That said, it argues that the various pre-war preparations fail to include "psychological preparedness". I think this is largely true for America as well, since war is something that the USA almost exclusively engages in offensively in distant countries, with only one small exception for one day on 9/11.
I know, I read the article I’m just saying, we Americans have no idea how big of a conflict we’re in right now, and we are not psychologically prepared for what it will mean to be bombed by hypersonic missiles or shaheds or what have you either.
I work with some Ukrainian refugees, we are not prepared.
Just anecdotally, increasing the blur seems to have an associated performance cost, especially in Springboard ("the home screen".) It's probably only ~100ms for each interaction, so it probably won't impact latency-insensitive users.
As others have said, it helps with the legibility but Liquid Glass is still distracting and illegible. I share the wish that Apple eventually returns to a more sensible, legible UI.
I want to stress this isn't something I measured. There are just these noticeable lags before the sigmoidal animation starts when, e.g. opening a folder.
It's on top of the latency inherent to the animations of sliding, wiggling, wobbling, jiggling, etc. that are throughout the interface. ~100ms on top of a ~600ms input-blocking sigmoid probably just looks like a 700ms sigmoid to people.
Yep; this has been the case since the very first iPhone, it can't be disabled, and there is no feedback it happens other than the typos. It is very crazy making and mind boggling.
I thought this was commonly accepted to be the case that companies which sell access to LLMs are also storing and training on the inputs?
I don't mean this as rhetoric, I did not think many people (except possibly those operating under government contracts, and 'normies' who don't know about these things) were under the belief that their IP was kept secret when they use these services.
Some offer zero data retention policies, but there can be weasel words. For example, on the individual pro plan, you can turn off the setting that lets them train models on your data, but they still have a section in their terms that allows them to evaluate your anonymized data for statistical and "research" purposes. You have to actually get a signed contract along with an enterprise plan that spells out exactly what they're going to use, and what settings enable what retention.
Seems naive to think that those providers - who have a financial interest in selling the data - would not also try to weasel out of the precise definition of ‘zero’ retention.
I have no inside information, but I always assume the tickboxes that "disable ____ data" from Google/Facebook/OpenAI just disconnects it from your own account, not hides it from the provider.
There's no independent verification of what that checkbox actually does. The company can say anything, and you are unable to verify that they actually do it.
The only verification you could do so far is GDPR-style data export, and also the adherence to GDPR regulations (and even those might get skirted if they aren't operating in europe).
Aren’t they usually phrased very specifically as “we collect this data and use it to show you relevant ads, you can opt out of us showing you relevant ads”?
What about inference providers like Baseten, Modal, Fireworks, Together, etc? I thought one of their value propositions was inference (using open weights models) that guarantees with crisp terms that they will not use your data.
I worked very briefly at Baseten, and I can say that it was a perpetual annoyance (from an engineering perspective) that customers would complain about issues with their models but we couldn't actually see the inputs/outputs. I don't know about the other providers, but at Baseten they literally weren't stored anywhere.
A provider can genuinely avoid storing inputs, as the Baseten engineer below describes. That is still different from proving what code received the prompt or protecting plaintext while it runs; I built TrustedRouter to separate ZDR, attestation, and confidential routes: https://trustedrouter.com/blog/attestation-is-all-you-need?u...
> to separate ZDR, attestation, and confidential routes
Could you please clarify what that means? Given what I've been searching for, I might in principle be part of your intended customer profile, but I can't figure out whether you are merely doing routing (alternative to OpenRouter) or also inference (alternative to the names I've mentioned above). If it's merely routing, then how do you protect me from any potential misbehavior on the part of the inference provider?
Just feedback for what you're building, so please take this in a positive spirit... I'm an AI researcher and not quite an infra guy, and I'm making recommendations on token APIs for several less knowledgeable around me (I've gotten a few people set up with Baseten recently), and I couldn't figure out whether/why I would be interested in TrustedRouter. You should communicate the story better :-)
EDIT: Here's what I now understand after some digging; please correct if wrong.
There are some M token providers (not the names I listed above?) who provide cryptographic guarantees about inference services. But somebody still needs to verify what they do on each request. For an individual running a single harness, that harness would be a logical place to perform this verification if possible. For an org with N users each running their own harness, TrustedRouter solves the N*M problem and becomes the single gateway for trusted inference -- provided one somehow trusts/verifies TrustedRouter.
AWS and Azure give you the same thing for Claude and ChatGPT, no need to be stuck with open weights. They might sometimes store some of it for other purposes (I don't know the specifics), but it is emphatically not being fed back to OpenAI or Anthropic.
I would wager that’s more acceptable if said learning is not in competition with the user. If they didn’t actually produce results but created the model only, then that could be advantageous for users too. But the moment they absorb your work to sell it, or for marketing, it’s a different moral ground.
You have some secret sauce. The model trains on it. Your competitor is solving a similar problem. The model "advantageously" helps them.
Your competitor is happy and continues to pay for the subscription. Sam and Dario just resold your code.
For what it's worth LLMs still suck at reproducing my little secret algorithm/implementation while being able to solve way harder problems. I have a good guess why that's the case.
> I thought this was commonly accepted to be the case that companies which sell access to LLMs are also storing and training on the inputs?
The services have toggles to allow prompts to be used in the training set. There is a conspiracy theory that the toggle is a false distraction and they’re actually keeping everything, and that none of the employees involved will ever whistleblow this fact.
Outside of Internet comment sections, I think most people assume these US-based companies are doing what they say.
For enterprise use there are services like AWS Bedrock which have strict isolation guarantees. There are some people who still believe those guarantees are a lie, but once someone has reached that point I don’t think they trust anything that isn’t running entirely within their house. People in that category are a very small minority, but a very vocal minority.
The impression I have (from interacting with people IRL using OpenAI and Anthropics offerings, and how they feel about the risks involved) is just the opposite. But we probably just have different life experiences.
I can name groups of people I interact with who lean both ways.
It’s still a commonly held belief that “Facebook sells your data” and it’s cool to be cynical about everything tech in many social scenes. Conceding that a tech company might be honest about something will get you classified as a bootlicker depending on who you talk to so the only winning move is to be super cynical.
Among actual professionals I work with in tech and legal, almost nobody holds a belief that these companies are blatantly lying to their customers (and zero of their employees are whistleblowing it, while said companies also have employees trying to whistleblow AI safety on Twitter daily)
Yes, I am talking about working professionals who use LLMs. Before this thread, I would have considered it surprisingly and singularly naïve if someone told me they trusted OpenAI. I still believe the common and correct take is that these companies are largely training on customer data against their consent.
I don't think they are "blatantly" lying either, just normal bog-standard lying that we've all come to accept. It's a profitable and competitive tech company.
We have already seen this lying. The toggles are opt-out, not opt-in. When you sign up, you agree to binding arbitration, which is effective for preventing lawsuits in the US. The toggles are regularly turned back on without our consent on ChatGPT and Claude. OpenAI's "don't train on my content" setting isn't even in the ChatGPT interface.
As far as I know, they haven't suffered even a tiny controversy in public opinion over any of this at all.
There's nothing to whistleblow about when it's public knowledge.
How many of the people who checked those boxes have cryptographic proof they did it? How many of those people have opted out of the arbitration clause? How many of those people would be able to claim damages? Would the amount of people who satisfy all three questions be large enough to make it worth _not_ training on user data?
I also don’t think these companies are lying at all, but I definitely think they’re training on all your data, toggle or not.
It’s truly trivial to “anonymize” and distill your prompts and model output. They could use just about any off-the-shelf cheap model for this. In fact, their TOS explicitly allows this, even with the toggle checked.
What that probably means is that the EXACT content of your prompt is secret. But the actual ideas are not. If you discover something truly novel, then yeah they get that. They can absorb trends in consumer behavior, too.
I’m sure if someone had access to all my paraphrased prompts, which retain 0% of my exact wording, they could find out literally everything about me. It’s a bit like how collecting metadata is as good (or better!) than collecting the real data.
And we all know “anonymizing” data doesn’t really exist like we think it does. Just removing names and identifiers doesn’t make anything anonymous for motivated actors. Or… say… an LLM that is trained to recognize patterns in text. Which is, like, all of them.
I don't know why, but I usually can only get Camera Remote to work when I close all of the recent apps on my Apple Watch, even when my watch and phone were the newest ones Apple released. Probably a bug with memory management they're never going to fix. Now, that's not possible, even when I reboot my watch :(
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