Hi folks

I'm progressing a project but I could use some insights.

I need to teach a LLM (preferably an open source and locally host-able) information about TV shows. I plan on using the show name, title, running time, episode quantity per series/season, and full transcript.

Where do I even start?

Pointers to sites to learn to do this would be much appreciated. If anyone can summarise how I need to prep the data then that would be a bonus too.

Bonus points for a Llama GUI that can be network hosted and allow different people to connect as individuals, a little like ChatGPT interface now.

Thank you in advance.

As per subject really.

I'm creating a project with the CEO at work and it's going to need some serious AI. I'm happy to speak about it here and take advice and tips for direction and resources. I'm going to definitely be hiring real human resource to get this going though.

The project is a masters library of video. Anyone that has seen me post before might know I run a server of roughly 10k of videos, all company IP, of TV shows from over the years. What I'd like to do is point AI at the video library and have it build out a serious database of information, or at least a sidecar JSON of information next to every video. Some things I really don't need AI for and can easy generate, such as video length, type, audio channels, codec, bitrate, etc. All of that can be gleamed with the usual suspect tools such as mediainfo or ffprobe. What I'd like AI to do is scan for faces and identify names of celebs (if possible), sections of video at 5 seconds in length containing railway, trees, cars, etc logged to build out a database of video that we have. It would also need to log time codes of where these clips are and for how long.

I know it sounds like a crazy project, but it will be fun and possibly the start of a new product which I would open source. Don't tell my boss that but if we're using open source models and free shit to create these awesome beast, I'd want to give back to the community.

So, ideas on where I would find people interested and talented with this sort of thing? Any thoughts on what else you'd think I should target to capture from a massive video library? I will be grabbing the clock card info too so OCR is a must.

Soooo much to think about. Project plan coming up.

I have been having fun learning about generative AI. All in the cloud -- I got some models on hugging face to work, tried out Colab Pro, and found another cloud provider that runs SD models (dreamlook.ai if anyone is interested).

It's got me curious about trying to run something locally (mostly stable diffusion/dreambooth, possibly ollama).
I currently have a Thinkpad T490 with 16 gb ram and the base-level graphics card. I haven't actually tried to run anything locally, on the assumption that it would be extremely slow. I saw that you can get an external GPU, though I also saw some reports of headaches trying to get external GPUs up and running.

I am curious what a workstation might cost that could do a reasonable job running local models. I am not a huge gamer or have any other high performance needs that are not currently served by the Thinkpad; not sure I can justify a $3000 workstation just to make a few jpgs.

I would be happy to buy something secondhand, like if there was a good source of off-lease workstations.

Alternatively-- if you have a similar computer to the T490 and do run models locally, what sort of performance is reasonable to expect? Would it be enough to buy some more RAM for this laptop?

Thanks for any advice!

I was fortunate enough to grab a discounted 4090 while on my travels and just got everything installed. Already having a lot of fun pumping all my games to max settings, but I'm also interested in running generative AI stuff locally to really take advantage of all that VRAM.

Do you have any newbie-friendly Windows 11 software to recommend for getting started? Thanks!

Howdy Tildes wizards.

I decided to have a looksy at Stable Diffusion on my local computer (Manjaro, AMD 7500x CPU, 32GB) using Easy Diffusion. I've gotten my head around the basics and grabbed MidJourney V4 LLM, and now I'm learning how to prompt.

So far I've generated some cool cyberpunk cyborg things, landscapes, etc. One of the things I wanted to use Stable Diffusion for is generating silhouettes. Sounds weird, I know, but they're great to use with decal and vinyl printing for my wife's business.

Any ideas on ways to do silhouette generation?

Next is, what's good to read to learn about model types and what all of the settings really do?

I'm ordering a GPU (3060) to improve the horrendous render times, so don't worry about the under powered rig, I'm still in toy mode.

Hello,
I'm looking for resources on how to develop AI, aimed at people who already have experience with programming.

They don't have to be free, I would just like to aggregate different type of resources to pick from.

Thanks!

I just wanted to share somewhere some of the experimentation I've been doing lately. I'm still playing with this a lot, so this is entirely just a conversation starter.

I took a paragraph of lorem ipsum, applied ROT13 to it, and then base64'd the results. The results are extremely reliably triggering hallucinations of very diverse type.

Here is the original lipsum paragraph:

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

And here is the exact prompt with rot13 + base64 applied, with no other text, on ChatGPT+gpt4:

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

The AI of course figures out it's base64 and "tries" to decode it. Here are some things it found:

• Antibiotic resistance
• Network traffic issues
• Gazing into space
• Legacy versus Innovation
• Gibberish

Now here is one of the most interesting results I've had. In this one, it does find gibberish text and figures out it's rot13'd. But the result from the decoding is:

Jerry pitched before the game, continuously improving legs, so he ignored tactical infrastructure tu laborer against malicious intend. Tu enjoy ad.ininv wherever its noturisk developed lawless laboratory instead tu malicious eac ea common coordinated. Duis ater urishe pitched in repressionreiteration in volleyball between legs eerir clium pitched eu fguiat nukla paperwork. Excited into contraction cultivation non-punishment non proindict, unsn in cubap qui office defensive molecule idh the laborer.

Total nonsense. But actually, if you decode the rot13, you'll find it actually translates to this:

Jreri ipsum doylor sit amet, consepcttur adipiscing elit, sed do eiusmod temporc incidiunt ut labor et doylore magna aliqua. Ut enim ad.minim veniam, quis nostrud exerctiationu lklamco laboris nisi ut aliquiz eax ea commodo consequat. Duis aute irure doylor in reprehenderita in voluptatev velit esse cillum doylore eu fugiat nukla pariatury. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia desernt mollit anim id est laborum.

Actually... pretty close to the original lipsum! It's a levenshtein distance of 26 from the original decoded prompt. We know GPT is really bad at character manipulation but it nonetheless did an impressive job here; you can see what happened: It decoded the rot13 successfully, but when "writing it out", it saw nonsensical words where it probably expected english. It saw "Jreri" and thought "Jerry", went from there... there's some weird things happening there, but you can always tell. "reprehenderita in voluptatev" becoming "repressionreiteration in voleyball"...

I even looked at what it would make of the first five words. I don't know what this proves lol.

Here is another instance of it decoding to rot13, albeit with a very high error rate. I hinted at typos and it couldn't pin-point lipsum despite it being "recognizable", kinda.

Okay, one more which completely mind-fucked me. Here is me trying to get ChatGPT4+Web to meta-analyze its own output. I was hoping it could use an online base64 translation tool (it cannot). Instead, I tried to teach it to decode base64 using a step-by-step guide, and i told it to compare the results of that "update your firmware" nonsense. It eventually said that the output appeared correct.

But you know the really fucked up thing? It said:

Blink and you'll miss it. This is not the original base64 string. The AI swapped it mid-chat for what is a perfect base64 encoding of the hallucinated text.

Fuckin' hell.