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tguedes

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It's not the compute hardware itself. PCC used to be data centers owned and operated by Apple, running on chips designed by Apple.

With this announcement, Apple is expanding the definition of PCC to Google Cloud data centers. Theoretically, this is Google Cloud, not Google servers, so there should be a separation of access there.

From the Apple security blog:

Originally built exclusively on Apple silicon with our world-class software security technologies, PCC set a new bar for AI privacy in the cloud, and continues to power the most demanding Apple Intelligence features. Since then, the wider industry has been working to provide a set of confidential inference primitives that could theoretically be combined to reach the security level of PCC. However, until today, those primitives have never been integrated into a comprehensive, end-to-end confidential inference pipeline capable of operating at global scale. That’s what we’ve done with PCC on Google Cloud, which incorporates PCC’s exceptional security and privacy properties at every stage, including the industry’s most comprehensive transparency guarantees that allow external security researchers to verify our privacy commitments.

There is a comment in this thread from an alleged Apple employee that said that, but it doesn't seem like it's possible to send a link for a specific comment. Over the years I've seen comments and blogs posted here in Hacker News reaffirming the same thing.

But to answer your question directly, I don't have any links for those blogs or comments

From my understanding of the architecture, Apple and Google have basically developed a fork of Gemini that is built to run on Apple's PCC. There is no data being sent to any Google servers.

From this MacRumors article:

"The new architecture centers on Apple Foundation Models co-developed with Google, which Apple says are adapted to run both on-device and on servers through its existing Private Cloud Compute infrastructure."

And

"The company reiterated that Apple Intelligence relies on on-device processing and Private Cloud Compute, with a promise that user data is only used to execute the immediate request and is not accessible to Apple or third parties. Apple added that outside experts can verify those privacy guarantees "at any time.""

They don't have the cash laying around. Their "actual" profit, meaning money added to their bank account after stock buy backs, dividends, employee stock allocations, and capex was $7B.

In this statement, their 2025 capex was $91.45B. They expect their 2026 capex to be $180B-190B. And they expect their "2027 capital expenditures to significantly increase compared to 2026."

So they simply don't have the money. Up until now, I thought the bubble talks about AI were silly because all these companies were using cash flow to fund their capex. These numbers are so astronomical now that a company that had $132B in net income has to take debt or issue stock to pay for it.

You cherry-picked examples. Counter examples would be:

Crowdstrike up 1067% Cloudflare up 1408% Robinhood up 148%

For an index fund, I would take a break even or even a slight loss on AirBnb to get those Crowdstrike and Cloudflare returns. I do agree with the overall sentiment that the foundation AI companies are overvalued but the whole point of an index fund is not have to analyze each individual company.

I'm not sure how they are related. USB-C was not really a technical challenge or had trade-offs. I'm not a hardware engineer but from what I've read, having an easily replaceable battery would degrade the water resistance of the phone.

I despise the Cook hate from some Apple fans. No he’s not the visionary that Jobs was. But I think he was the best person to scale Apple up to what it is today while still keeping the soul of the company alive.

To me it seems like an LLM-based implementation of automation software like Zapier. The problem with Zapier is you need services to provide APIs and Zapier needs to support those APIs to implement it in the automation workflow.

But because OpenClaw can just use a web browser like a normal user, you don't need all these APIs and there's no theoretical limitations on the services that can be integrated and automated.

Right now there's a lot of issues/bugs. People have more trust in a deterministic solution like Zapier. But maybe the LLMs and OpenClaw will get there eventually, and if it does, I can see how that's a better solution than a deterministic system.

You're absolutely right and the order of operations matters. But I'm not arguing about what's right in this case. If as Dario says, that advanced AI is at the level of nuclear weapons, then governments around the world will see it as a threat to their power and sovereignty.

Potentially. Or the US government can force over control of the technology. It's impossible to predict right now the implications of this technology in 5 years, let alone 10 years.

You're right in those cases. But if what Dario says is true, that advanced AI is on the scale of nuclear weapons, then that is a threat to the power and sovereignty of the government.

I don't think he ever said in the article that he is not making the argument about the importance of democratic oversight, if anything, in the conclusion, he says:

"The way to address this new reality, however, is with new laws and through strengthening accountable oversight; cheering or even demanding that an unelected executive decide how and where such powerful capabilities can be used is the road an even more despotic future."

But I think you drastically misunderstood the point of this article. Ben is pointing out the implications of Amodei's analogy of advanced AI being like nuclear weapons. The government has a monopoly on nuclear weapons and has extreme regulations and oversight on the companies that help build nuclear weapons for it. And those companies do not tell the government how or when they can use the nukes.

So if advanced AI is like nuclear weapons, why can an unelected executive tell a democratically elected government how to use it?

But that's the problem with this. The vast majority of the spend is going to be on the Nvidia chips which have a shelf life of 3-5 years. They are not making any significant long term investments.

During the dot com bubble, telecom companies spent 10s of billions of dollars laying down cables and building out the modern public internet infrastructure that we are still using today. Even if a lot of companies failed, we still greatly benefited from some of the the investments they made.

For this bubble, the only long term investment benefits seems to be the electricity build out and a renewed interest and investment in nuclear.

Most (if not all) of Oracle's investments are mostly in chips and data centers.

The only downside of this in the US is that homeless people will tend to hang around Aldi's asking people if they can return their cart to get the coin. Most of them are friendly and thankful but every once in awhile an aggressive person would make me very uncomfortable.

I also expect Aldi management isn't thrilled about homeless people camping outside their stores.

Still, I think there needs to be a specific term for a company that has recently had a funding round and will likely IPO in the future, like Stripe. That's a different category than a start-up or privately owned company that will never IPO like Koch Inc.

I think what you're trying to reference is APIs or libraries, most of which I wouldn't consider abstractions. I would hope most senior front-end developers are capable of developing a date library for their use case, but in almost all cases it's better to use the built in Date class, moment, etc. But that's not an abstraction.

Because if LLM inference is going to be a bigger priority for the majority of companies, they're going to go where they can get the best performance to cost ratio. AWS is falling behind on this. So companies (especially new ones) are going to start using GCP or Azure, and if they're already there for their LLM workloads, why not run the rest of the infrastructure there?

It's similar to how AWS became the de-facto cloud provider for newer companies. They struggled to convince existing Microsoft shops to migrate to AWS, instead most of the companies just migrated to Azure. If LLMs/AI become a major factor in new companies deciding which will be their default cloud provider, they're going to pick GCP or Azure.

Study mode 12 months ago

It really depends on the query. I'm not a Google query expert, but I'm above average. I've noticed that phrasing a query in a certain way to get better results just no longer works. Especially in the last year, I have found it returns results that aren't even relevant at all.

The problem is people have learned to fill their articles/blogs with as many word combinations as possible so that it will show up in as many Google searches as possible, even if it's not relevant to the main question. The article has just 1 subheading that is somewhat relevant to the search query, even though the information under that subheading is completely irrelevant.

LLMs have ironically made this even worse because now it's so easy to generate slop and have it be recommended by Google's SEO. I used to be very good at phrasing a search query in the right way, or quoting the right words/phrases, or having it filter by sites. Those techniques no longer work.

So I have turned to ChatGPT for most of the queries I would have typically used Google for. Especially with the introduction of annotations. Now I can verify the source from where it determined the answer. It's a far better experience in most circumstances compared to Google.

I have also found ChatGPT to be much better than other LLMs at understanding nuance. There have been numerous occasions where I have pushed back against ChatGPT's answer and it has responded with something like "You would be correct if your input/criteria is X. But in this case, since your input/criteria is Y, this is the better solution for Z reasons".

It looks like this will support physical buttons. From the article: "Drivers can also use onscreen controls, physical buttons, or Siri to manage both standard vehicle functions like the car’s radio and climate, as well as advanced, vehicle-specific features and controls like audio system configurations or performance settings, right from CarPlay, giving them a more fluid and seamless experience."

And if you look at the picture from the article, all the physical buttons are there.