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Apple Will 'Watch Everything Burn' When the AI Bubble Bursts | Ed Zitron (www.macrumors.com)
submitted 1 month ago* by to c/apple@lemmy.zip
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(…) Apple Intelligence was both the worst and best thing to happen to Apple as far as the AI bubble goes.

It was a mass-radicalization of its users against AI – an attempt to cram a barely-functional series of add-ons that nobody asked for in the most-obtrusive way possible, with summaries that were almost immediately turned into memes and a new Siri that was, somehow, even worse than the old Siri.

And I think that told Apple to pump the brakes. It's barely spent anything on capex. It's barely done anything with AI. Despite headline after headline claiming it's "falling behind," nobody can really explain what it is it's falling behind on or why it matters. People hate Apple Intelligence, and I think Apple knows that, and so they're going to jingle the keys for the markets by putting "AI" on stuff without ever really putting their back into it.

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[–] 1 point 1 month ago* (2 children)

What accusation? Apple themselves said they are partnering with Google Gemini. Not all AI queries will be on-device, as some tasks will need more power. Itll then be sent to their "Private Cloud Compute".

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  • [–] 2 points 1 month ago (1 child)

    The accusation that Apple will give your data to Google et al is one you made. You state that queries will be sent off-device but don’t recognize that this is with consent and exactly how it worked with ChatGPT integration.

    It’s a valid fear but not a valid fact.

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  • [–] 2 points 1 month ago*

    I havent yet made any claim that Apple is sending your data to Google.

    Apple acknowledges these issues per their Private Cloud Compute newsroom release:

    Cloud AI security and privacy guarantees are difficult to verify and enforce. If a cloud AI service states that it does not log certain user data, there is generally no way for security researchers to verify this promise — and often no way for the service provider to durably enforce it. For example, a new version of the AI service may introduce additional routine logging that inadvertently logs sensitive user data without any way for a researcher to detect this. Similarly, a perimeter load balancer that terminates TLS may end up logging thousands of user requests wholesale during a troubleshooting session.

    It’s difficult to provide runtime transparency for AI in the cloud. Cloud AI services are opaque: providers do not typically specify details of the software stack they are using to run their services, and those details are often considered proprietary. Even if a cloud AI service relied only on open source software, which is inspectable by security researchers, there is no widely deployed way for a user device (or browser) to confirm that the service it’s connecting to is running an unmodified version of the software that it purports to run, or to detect that the software running on the service has changed.

    It’s challenging for cloud AI environments to enforce strong limits to privileged access. Cloud AI services are complex and expensive to run at scale, and their runtime performance and other operational metrics are constantly monitored and investigated by site reliability engineers and other administrative staff at the cloud service provider. During outages and other severe incidents, these administrators can generally make use of highly privileged access to the service, such as via SSH and equivalent remote shell interfaces. Though access controls for these privileged, break-glass interfaces may be well-designed, it’s exceptionally difficult to place enforceable limits on them while they’re in active use. For example, a service administrator who is trying to back up data from a live server during an outage could inadvertently copy sensitive user data in the process. More perniciously, criminals such as ransomware operators routinely strive to compromise service administrator credentials precisely to take advantage of privileged access interfaces and make away with user data.

    We are still waiting for a full write-up on how Private Cloud Compute can protect against this, but I'm sure Apple will release more information as we get closer to September.

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