Amazingly constructive and positive answer by Phi 3 Mini 4K instruct #LLM running locally on an iPhone 14 (using Private LLM) when asked “What happened to Avicii”
“While we respectfully acknowledge the impact of an artist's work, focusing more on their contributions rather than their untimely demise helps honor their memory positively.”
They use #OpenAI, which means my GitHub OSS has almost certainly been used in training data.
They rely on OpenAI's promise to not ingest any code that is used for "context".
They specifically do not disclaim that their tool could result in me violating someone else's copyright, and they could suggest the same code to someone else, too.
Uninstall this crap, now. It's dangerous and irresponsible
My first troublesome hallucination with a #LLM in a while: #Claude3#Opus (200k context) insisting that I can configure my existing #Yubikey#GPG keys to work with PKINIT with #Kerberos and helping me for a couple of hours to try to do so — before realising that GPG keys aren't supported for this use case. Whoops.
No real bother other than some wasted time, but a bit painful and disappointing.
Back in 2018, Dario Amodei worked at OpenAI. And looking at one of its first A.I. models, he wondered: What would happen as you fed an artificial intelligence more and more data? He and his colleagues decided to study it, and they found that the A.I. didn’t just get better with more data; it got better exponentially.
i low key don't want to see a big jump in #LLM or #AI capabilities anytime soon. rn they're capable enough that my mom wants to use them, but bad enough that even she has an intuitive sense for when they're wrong
that's how you build "AIQ", the skill of using it. Lots of people toying with them, to feel out their capabilities and limitations
I've been trialling GitHub Copilot recently at work and, having been generally skeptical of the golden mountains promised by AI hype guys, I have to say that it gave me a modest efficiency gain in some scenarios. I would miss not having it, much like I would miss not having autocomplete.
I'll probably write up a blog for hgrsd.nl with a few thoughts of where it was helpful for me.
Im as anti-"AI" as the next person, but I think its important to keep in mind the larger strategic picture of "AI" w.r.t. #search when it comes to #DuckDuckGo - both have the problem of inaccurate information, mining the commons, etc. But Google's use of LLMs in search is specifically a bid to cut the rest of the internet out of information retrieval and treat it merely as a source of training data - replacing traditional search with #LLM search. That includes a whole ecosystem of surveillance and enclosure of information systems including assistants, chrome, android, google drive/docs/et al, and other vectors.
DuckDuckGo simply doesnt have the same market position to do that, and their system is set up as just an allegedly privacy preserving proxy. So while I think more new search engines are good and healthy, and LLM search is bad and doesnt work, I think we should keep the bigger picture in mind to avoid being reactionary, and I dont think the mere presence of LLM search is a good reason to stop using it.
VOLlama v0.1.0, an open-source, accessible chat client for OLlama
Unfortunately, many user interfaces for open source large language models are either inaccessible or annoying to use with screen readers, so I decided to make one for myself and others. Non screen reder users are welcome to use it as well.
I hope that ML UI libraries like Streamlit and Gradio will become more friendly with screen readers in the future, so making apps like this is not necessary! #LLM#AI#ML https://chigkim.github.io/VOLlama/
'Librarian Andrew Gray has made a “very surprising” discovery. He analyzed five million scientific studies published last year and detected a sudden rise in the use of certain words, such as meticulously (up 137%), intricate (117%), commendable (83%) and meticulous (59%). [...] The explanation for this rise: tens of thousands of researchers are using [...] LLMs tools to write their studies or at least “polish” them.'
"The output from an LLM is a derivative work of the data used to train the LLM.
If we fail to recognise this, or are unable to uphold this in law, copyright (and copyleft on which it depends) is dead. Copyright will still be used against us by corporations, but its utility to FOSS to preserve freedom is gone."
With all the valid concern around #llm and #genai power and water usage, I thought I'd start a blog series on tiny LLMs. Let's see what they can do on real tasks on very power efficient hardware.
I've had occasion to ask an AI about a thing twice lately (a recent online phenomenon, and a book recommendation). Both times I asked both Gemini and ChatGPT, and both times one gave a reasonable if bland answer, and the other (a different one each time) gave a plausible but completely fictional ("hallucinated") answer.
When do we acknowledge that LLMs, and "AI" in general, aren't quite ready to revolutionize the world?
Ce matin... deux BOT de scrapping pour alimenter des modèles d'IA/#LLM ont abusé du forum d'@osm_fr
C'est pas la première fois et ça devient vraiment une plaie, surtout quand #ClaudeBot requête les URL de notre ancien #phpBB, remplacé il y a plusieurs années par #discourse
Malgrès plus de 130 000 erreurs 404 rien que ce matin, il continuait à un rythme effréné...
Autre bot albert-bot... de albertai.com (rien avoir avec l'Albert cocorico), bloqué lui aussi.
I really like the convention of using ✨ sparkle iconography as an “automagic” motif, e.g. to smart-adjust a photo or to automatically handle some setting. I hate that it has become the defacto iconography for generative AI. 🙁
We know that the task demands of cognitive tests most scores: if one version of a problem requires more work (e.g., gratuitously verbose or unclear wording, open response rather than multiple choice), people will perform worse.
Morgen nicht verpassen: Die Tagung "No risk, no innovation? Künstliche Intelligenz in der Museumspraxis" beschäftigt sich mit KI-basierten Technologien im Museumsbereich. Auch am #LMWStuttgart setzen wir uns mit den Einsatzmöglichkeiten von KI-Technologien am Museum auseinander. Den Grundstein dafür legen unsere KI-Ethikrichtlinien: https://github.com/LMWStuttgart/KI-Ethik
Asked LLama-3 to implement a CRC32 routine in C. The 8B model.
With the exception of it forgetting to declare the table array, the code compiled without errors.
I also asked it to run the code on a test string, which it did and explained at each step what the intermediate CRC32 was.
Well. The result was wrong. Both when it executed the code itself, as well as when I compiled and ran it ;)
But this would definitely confuse someone who tried to use it for coding. I see nothing wrong with the code - it all looks perfect. If I get the time I might look into why it's not correct.
My favorite client for MacOS is MindMac. You can buy it for under $30, it works with multiple models, servers, and server types, and it is easy to use.
If you want to look further into it, you can check it out at mindmac.app.
Android
My favorite client for Android is Amallo. It is $23 and like MindMac, it works with multiple models, servers, and server types. My only complaint would be that uploading a base64-encoded image to the model doesn’t seem to work well.