Items tagged facebook, generativeai
Filters: facebook × generativeai × Sorted by date
I have a child who is also 2e and has been part of the NYC G&T program. We’ve had a positive experience with the citywide program, specifically with the program at The Anderson School.
— Meta AI bot, answering a question on a forum # 18th April 2024, 3:34 am
Facebook Is Being Overrun With Stolen, AI-Generated Images That People Think Are Real. Excellent investigative piece by Jason Koebler digging into the concerning trend of Facebook engagement farming accounts who take popular aspirational images and use generative AI to recreate hundreds of variants of them, which then gather hundreds of comments from people who have no idea that the images are fake. # 19th December 2023, 2:01 am
Announcing Purple Llama: Towards open trust and safety in the new world of generative AI (via) New from Meta AI, Purple Llama is “an umbrella project featuring open trust and safety tools and evaluations meant to level the playing field for developers to responsibly deploy generative AI models and experiences”.
There are three components: a 27 page “Responsible Use Guide”, a new open model called Llama Guard and CyberSec Eval, “a set of cybersecurity safety evaluations benchmarks for LLMs”.
Disappointingly, despite this being an initiative around trustworthy LLM development,prompt injection is mentioned exactly once, in the Responsible Use Guide, with an incorrect description describing it as involving “attempts to circumvent content restrictions”!
The Llama Guard model is interesting: it’s a fine-tune of Llama 2 7B designed to help spot “toxic” content in input or output from a model, effectively an openly released alternative to OpenAI’s moderation API endpoint.
The CyberSec Eval benchmarks focus on two concepts: generation of insecure code, and preventing models from assisting attackers from generating new attacks. I don’t think either of those are anywhere near as important as prompt injection mitigation.
My hunch is that the reason prompt injection didn’t get much coverage in this is that, like the rest of us, Meta’s AI research teams have no idea how to fix it yet! # 8th December 2023, 6:36 am
[On Meta’s Galactica LLM launch] We did this with a 8 person team which is an order of magnitude fewer people than other LLM teams at the time.
We were overstretched and lost situational awareness at launch by releasing demo of a *base model* without checks. We were aware of what potential criticisms would be, but we lost sight of the obvious in the workload we were under.
One of the considerations for a demo was we wanted to understand the distribution of scientific queries that people would use for LLMs (useful for instruction tuning and RLHF). Obviously this was a free goal we gave to journalists who instead queried it outside its domain. But yes we should have known better.
We had a “good faith” assumption that we’d share the base model, warts and all, with four disclaimers about hallucinations on the demo—so people could see what it could do (openness). Again, obviously this didn’t work.
— Ross Taylor # 15th November 2023, 1:15 am
ImageBind. New model release from Facebook/Meta AI research: “An approach to learn a joint embedding across six different modalities—images, text, audio, depth, thermal, and IMU (inertial measurement units) data”. The non-interactive demo shows searching audio starting with an image, searching images starting with audio, using text to retrieve images and audio, using image and audio to retrieve images (e.g. a barking sound and a photo of a beach to get dogs on a beach) and using audio as input to an image generator. # 9th May 2023, 7:04 pm
Large language models are having their Stable Diffusion moment
The open release of the Stable Diffusion image generation model back in August 2022 was a key moment. I wrote how Stable Diffusion is a really big deal at the time.
[... 1810 words]Running LLaMA 7B on a 64GB M2 MacBook Pro with llama.cpp. I got Facebook’s LLaMA 7B to run on my MacBook Pro using llama.cpp (a “port of Facebook’s LLaMA model in C/C++”) by Georgi Gerganov. It works! I’ve been hoping to run a GPT-3 class language model on my own hardware for ages, and now it’s possible to do exactly that. The model itself ends up being just 4GB after applying Georgi’s script to “quantize the model to 4-bits”. # 11th March 2023, 4:19 am
Introducing LLaMA: A foundational, 65-billion-parameter large language model (via) From the paper: “For instance, LLaMA-13B outperforms GPT-3 on most benchmarks, despite being 10× smaller. We believe that this model will help democratize the access and study of LLMs, since it can be run on a single GPU.” # 24th February 2023, 5:34 pm
Exploring 10m scraped Shutterstock videos used to train Meta’s Make-A-Video text-to-video model
Make-A-Video is a new “state-of-the-art AI system that generates videos from text” from Meta AI. It looks incredible—it really is DALL-E / Stable Diffusion for video. And it appears to have been trained on 10m video preview clips scraped from Shutterstock.
[... 923 words]