If Mozilla did that, we'd have monthly news stories about them adding ads into the client, removing features people depend on, cramming in AI where it doesn't belong, abruptly making all sorts of controversial ToS changes, going back on old promises, and all kinds of other things we know and love Mozilla for. All before they'd get bored and discontinue the product after a couple of years.
Or maybe they'd just buy some existing closed source Slack competitor, promise to open source it, and then just never get around to it. You know, like how they bought Pocket in 2017, promised to make it open source, but somehow never got around to it before discontinuing it in 2025.
FF is plenty competitive on the technical and feature front. It's market share is not a reflection of technical merit.
What's more, next to Linux itself it is maybe the only case I can see where a major piece of user facing software is kept competitive with the Apple/Google/MS tools.
LibreOffice or Nextcloud are technically far further behind Office and Google's online offerings.
Which therefore begs the question: Who else is in a position to do this?
At first glance, Moz with Firefox + a suite of self-hosted team and productivity stuff that works well in Firefox would make a ton of sense...
Worse, it's ridden with spyware, and is merely a honeypot for security-aware people that are not sufficiently paranoid to check any of the claims. Like, those VPNs from YT ads that use your IP to give AI companies residential proxies, the same kind of scam.
Spin up Wireshark and take a look at activity of Firefox. Try to shut the browser up. It won't work.
Even if they weren't a Google's proxy company, they would lose to standards commitees being infested by Google, and would have to play the "best luck catching up" game by constantly supporting new versions of JS, APIs and CSS features that nobody needs (except Google's YouTube will use them to stop you from using an adblocker).
FF is governed by ex-Oracle managers at the moment, singing the Google's song. Don't anthropomorphize your lawnmower.
So, not a home user then. If you make your living with computers in that manner you are by definition a professional, and just happen to have your work hardware at home.
Every time I'm tempted to get one of these beefy mac studios, I just calculate how much inference I can buy for that amount and it's never a good deal.
Every time someone brings up that, it brings me back memories of trying to frantically finish stuff as quickly as possible as either my quota slowly go down with each API request, or the pay-as-you-go bill is increasing 0.1% for each request.
Nowadays I fire off async jobs that involve 1000s of requests, billion of tokens, yet it costs basically the same as if I didn't.
Maybe it takes a different type of person, than the one I am, but all these "pay-as-you-go"/tokens/credits platforms make me nervous to use, and I end up not using it or spending time trying to "optimize", while investing in hardware and infrastructure I can run at home and use that seems to be no problem for my head to just roll with.
But the downside is that you are stuck with inferior LLMs. None of the best models have open weights: Gemini 3.5, Claude Sonnet/Opus 4.5, ChatGPT 5.2. The best model with open weights performs an order of magniture worse than those.
The best weights are the weights you can train yourself for specific use cases. As long as you have the data and the infrastructure to train/fine-tune your own small models, you'll get drastically better results.
And just because you're mostly using local models doesn't mean you can't use API hosted models in specific contexts. Of course, then the same dread sets in, but if you can do 90% of the tokens with local models and 10% with pay-per-usage API hosted models, you get the best of both worlds.
anyone buying these is usually more concerned with just being able to run stuff on their own terms without handing their data off. otherwise it's probably always cheaper to rent compute for intense stuff like this
Isn't it then even better to enjoy cheap inference thanks to techbro philanthropy while it lasts? You can always buy the hardware once the free money runs out.
Probably depends on what you are interested in. IMO, setting up local programs is more fun anyway. Plus, any project I’d do with LLMs would just be for fun and learning at this point, so I figure it is better to learn skills that will be useful in the long run.
Typometer is a tool to measure and analyze the visual latency of text editors.
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Check the article typing with pleasure to learn more about editor latency and its effects on typing performance.
entity resolution is the killer feature. context engineering is the problem with this benchmark attempt. The agent plan seemed to one shot, and the fact that the LLMs could write their own tools without validation or specific multi shot examples is worrisome. To me way to much left to the whims of the llms - with out proper context.
Yes, none of the top LLMs can do entity resolution well yet. I constantly see them conflate entities with similar names - they'll confidently cite 3 sources about what appears to be one company, but the sources are actually about 3 different businesses with similar names.
The fundamental issue is that LLMs don't have a concept of canonical entity identity. They pattern match on text similarity rather than understanding that "Apple Inc" and "Apple Records" are completely different entities. It gets even worse when you realize companies can legally have identical names in the same country - text matching becomes completely unreliable.
Without proper entity grounding, any business logic built on top becomes unreliable.
Because using htmx is asking to get defaced via XSS, or worse. Security is an afterthought for the project, which is evident from the placement of the related documentation.
It’d be nice if Mozilla (or a similar foundation) could create a baseline OS platform for a business communications suite.