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US condemns French inquiry into Elon Musk's social media platform X/Twitter.

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  • OpenAI Announces Massive US Government Partnership

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    M
    If its a repeating pattern is there ever a winner or a loser? Except for us, of course, who always lose.
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    E
    No, I don't mean prompting users. Typical ways to increase conversion rate are locking popular features behind the subscription (like you need premium account to comment), making some content available only to premium users or limiting the amount of content you can access as a free user (like only 2h per day). So far I'm still watching videos on youtube without even creating an account and without ads (ad-block).
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  • Apple sued by shareholders for allegedly overstating AI progress

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    finishingdutch@lemmy.worldF
    For this comment, I want to be absolutely clear that I do not give a shit about AI, and that it in no way factored into my decision to buy this iPhone 16 Pro Max. With that disclaimer out of the way: I very much look forward to a class action lawsuit. Apple advertised specific features as coming ‘very soon’ and gave short timeframes when asked directly. And they basically did not deliver on those advertising promises. Basically, I think there’s a good case to be made here that Apple knowingly engaged in false advertising in order to sell a phone that otherwise would not have sold as well. Those promised AI features WERE a deciding factor for a lot of people to upgrade to an iPhone 16. So, I’ll be looking forward to some form of compensation. It’s the principle of it.
  • YouTube Will Add an AI Slop Button Thanks to Google’s Veo 3

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    anunusualrelic@lemmy.worldA
    "One slop please"
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    This is interesting to me as I like to say the llms are basically another abstraction of search. Initially it was links with no real weight that had to be gone through and then various algorithms weighted the return, then the results started giving a small blurb so one did not have to follow every link, and now your basically getting a report which should have references to the sources. I would like to see this looking at how folks engage with an llm. Basically my guess is if one treats the llm as a helper and collaborates to create the product that they will remember more than if they treat it as a servant and just instructs them to do it and takes the output as is.
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    I think the principle could be applied to scan outside of the machine. It is making requests to 127.0.0.1:{port} - effectively using your computer as a "server" in a sort of reverse-SSRF attack. There's no reason it can't make requests to 10.10.10.1:{port} as well. Of course you'd need to guess the netmask of the network address range first, but this isn't that hard. In fact, if you consider that at least as far as the desktop site goes, most people will be browsing the web behind a standard consumer router left on defaults where it will be the first device in the DHCP range (e.g. 192.168.0.1 or 10.10.10.1), which tends to have a web UI on the LAN interface (port 8080, 80 or 443), then you'd only realistically need to scan a few addresses to determine the network address range. If you want to keep noise even lower, using just 192.168.0.1:80 and 192.168.1.1:80 I'd wager would cover 99% of consumer routers. From there you could assume that it's a /24 netmask and scan IPs to your heart's content. You could do top 10 most common ports type scans and go in-depth on anything you get a result on. I haven't tested this, but I don't see why it wouldn't work, when I was testing 13ft.io - a self-hosted 12ft.io paywall remover, an SSRF flaw like this absolutely let you perform any network request to any LAN address in range.
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