hedgehog
Giphy has a documented API that you could use. There have been bulk downloaders, but I didn’t see any that had recent activity. However you still might be able to use one to model your own script after, like https://github.com/jcpsimmons/giphy-stacks
There were downloaders for Gfycat - gallery-dl supported it at one point - but it’s down now. However you might be able to find collections that other people downloaded and are now hosting. You could also use the Internet Archive - they have tools and APIs documented
There’s a Tenor mass downloader that uses the Tenor API and an API key that you provide.
Imgur has GIFs is supported by gallery-dl, so that’s an option.
Also, read over https://github.com/simon987/awesome-datahoarding - there may be something useful for you there.
In terms of hosting, it would depend on my user base and if I want users to be able to upload GIFs, too. If it was just my close friends, then Immich would probably be fine, but if we had people I didn’t know directly using it, I’d want a more refined solution.
There’s Gifable, which is pretty focused, but looks like it has a pretty small following. I haven’t used it myself to see how suitable it is. If you self-host it (or something else that uses S3), note that you can use MinIO or LocalStack for the S3 container rather than using AWS directly. I’m using MinIO as part of my stack now, though for a completely different app.
MediaCMS is another option. Less focused on GIFs but more actively developed, and intended to be used for this sort of purpose.
I’d love an invite!
No. Trickle down economics refers to things that benefit the wealthy (mostly government policies, particularly related to taxes and subsidies) that will allegedly benefit everyone by “trickling down.” Supply-side economics are an example of trickle-down economics. Trickle-down economic policies have been shown to effectively increase income inequality and studies suggest a link between them and reduced overall growth.
Giving the wealthy tax breaks in the hopes that they’ll spend the extra money they have available on security details, on the other hand, would be an example of trickle down economics.
Wouldn’t be a huge change at this point. Israel has been using AI to determine targets for drone-delivered airstrikes for over a year now.
https://en.m.wikipedia.org/wiki/AI-assisted_targeting_in_the_Gaza_Strip gives a high level overview of Gospel and Lavender, and there are news articles in the references if you want to learn more.
This is at least being positioned better than the ways Lavender and Gospel were used, but I have no doubt that it will be used to commit atrocities as well.
For now, OpenAI’s models may help operators make sense of large amounts of incoming data to support faster human decision-making in high-pressure situations.
Yep, that was how they justified Gospel and Lavender, too - “a human presses the button” (even though they’re not doing anywhere near enough due diligence).
But it’s worth pointing out that the type of AI OpenAI is best known for comes from large language models (LLMs)—sometimes called large multimodal models—that are trained on massive datasets of text, images, and audio pulled from many different sources.
Yes, OpenAI is well known for this, but they’ve also created other types of AI models (e.g., Whisper). I suspect an LLM might be part of a solution they would build but that it would not be the full solution.
Both devices have integrated memory, so that 16 GB will look more like a 11/5, 12/4, or maybe even 14/2 split. The Steam Deck is also $400 for an LCD model or $550 for the OLED, not $800. It’s reasonable to expect more performance when you pay more.
Because the Steam Deck has a lower native resolution, that means that less of the RAM will be used for the integrated GPU. Downscaling from 1080p to 720p doesn’t look good, either - and you could downscale to 540p if supported, but if you need to do that (vs choosing to for an emulated game) it probably won’t be pretty, either.
This device is also running Windows, rather than a streamlined Linux-based launcher, meaning that more of that RAM will be taken up by OS processes by default.
The article talks about how the 8840U benefits from more, fast RAM. You won’t get near the 8840U’s full potential gaming with 16 GB. 24 GB, on the other hand, would have been enough that games expecting 16 GB of system RAM would have been able to get it, even while devoting 6-7 GB to the GPU and 1-2 GB to the OS.
Unless something has changed, it did. The page linked reads:
And, obviously, this POC is open source, the code is publish here on our forge.
The link takes you to their repos. The server repo has instructions on self-hosting directly on your server or with Docker. The app repo has code for both the iOS and Android apps. That’s good, because the iOS app at least doesn’t have a built-in way to select a different backend server.
Whisper is by OpenAI and as far as I know they have not shared the training code, much less the data sets, so the best you can do is fine-tune the models they’ve provided.
If use of Whisper is a problem, but the project is otherwise interesting to you, you could ask them to consider using a different STT solution (or allowing the user to choose between different options). I’m not aware of any fully open STT applications that are considered to be as capable as Whisper, but if you do, that would be great info to share with them.
Realistically, no LLM that’s large enough to be competitive will be able to remain open-source, even if it was initially (and most that claim to be weren’t actually, as you point out), because so much training data is needed.
Often the training data can’t be re-distributed in the first place, but even if it can be, its availability makes it much more likely that someone will request the takedown of some data in the set (even if the data was licensed, someone who holds copyright might claim that the person who submitted it to the set wasn’t permitted to do so). At that point, unless the takedown request is refused or the model itself is re-trained (which would be quite expensive) the data is no longer sufficient to generate the model.
Depends on your perspective. Would it be fine for Meta Threads to replace it? Threads supports ActivityPub, so in some ways it likely interacts better with the fediverse.
If we agree that Threads isn’t a suitable replacement, then clearly there’s some criteria a replacement should meet. A lot of the things that make Threads unpalatable are also true of Bluesky, particularly if your concern relates to the platform being under the control of a corporation.
On the other hand, from the perspective of “Twitter 2.0 is now a toxic, alt-right cesspool where productive conversations can’t be had,” then both Threads and Bluesky are huge improvements.
