Indeed.

If you have a working market, product quality matters. The while disaster that is Microsoft is also a good example for a market failure. At fault is the US that never managed to do any meaningful anti-trust action against MS when it would still have accomplished something.

How repulsive.

"No backup" is amateur-level. Also that they did not use n-out-of-k with n k is a pretty basic mistake.

Yes, Google is profitable now. Tremendously so. But they're at risk of losing revenue and ceasing to be profitable as people cease using Google search and switch to asking questions of their AIs. So to retain their position as the place people go first for information, they have to stay ahead of the AI race. Well, they could also just sit back and wait to see if their competitors are overwhelmed by the query volume, but that risks losing traffic and then having to win it back. It's much better to keep it. And Google is better-positioned to win this race than its competitors both because of its existing infrastructure and expertise and because it already has the eyeballs.

In addition, you seem to be assuming that doubling serving capacity means doubling cost. Clearly Google is not planning to increase their annual operating expenses by 1000X. As the summary actually says in the third paragraph, Google is also going to have to improve efficiency to achieve the growth rate, with better models and better hardware. This is what the AI chief is challenging the employees to do; he's not challenging them to write bigger OPEX checks, that's his job.

Quite true. Unfortunately, MS crap is also a really good example for a market failure.

Indeed. Windows and MS Office are a disgrace to the whole human race. No product on that level should ever have long-term economic success.

Yep. As if denial would make their predicament any less bad.

The always have been. Unfortunately, most of their customers are too. It just has gotten more concrete with LLMs now.

I get the driver behind this. Also trade-secrets, etc.

But is this really a local model and is no data transferred? There is some fuzzy language in "use an on-device AI model to power some of its features". What bout other features? What about if it "powers" the features, bit the data is still sent home? The whole thing looks like a lie by misdirection to me.

Difficult to say. I have no idea how much power an "NPU" draws.

So the only thing that requires actual on-target rational thought? That does not sound good at all.

THAT is your criticism? Seems pretty invalid to me, because Windows did not really do any better back when.

Sad but true.

They will likely still listen to and record everything. The main difference is that you pay the power used. But now you have the illusion of the data staying on your device. Nice!

See also: https://thehackernews.com/2025...