A Meat-Flavour Entrepreneur, Creative Technologist & UI+UX+Software Engineer 🦄🤤🥩🏳️🌈 Compulsive Autodidact: ML + FinTech // AI + Generative Art + NFT + 3D
Vancouver, British Columbia
Joined April 2016
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meatflavourdev retweeted
In LLM pre training, curating and preparing data is perhaps the most impactful step. NeMo data curator is now open source with lots of features you will need. We used it to curate trillions of tokens for our own models training. github.com/NVIDIA/NeMo-Curat…
meatflavourdev retweeted
Introducing SIMA: the first generalist AI agent to follow natural-language instructions in a broad range of 3D virtual environments and video games. 🕹️
It can complete tasks similar to a human, and outperforms an agent trained in just one setting. 🧵 dpmd.ai/3TiYV7d
meatflavourdev retweeted
Do you want to keep your humanity in the onslaught of AI's exponential progress? Immerse yourself in paradox because every time we break the symmetry of a paradox, we transcend to a new meaning. Recognize the awe that is everywhere.
meatflavourdev retweeted
Announcing Score Entropy Discrete Diffusion (SEDD) w/ @chenlin_meng @StefanoErmon.
SEDD challenges the autoregressive language paradigm, beating GPT-2 on perplexity and quality!
Arxiv: arxiv.org/abs/2310.16834
Code: github.com/louaaron/Score-En…
Blog: aaronlou.com/blog/discrete-d…
🧵1/n
meatflavourdev retweeted
Meta presents SpiRit-LM
Interleaved Spoken and Written Language Model
paper page: huggingface.co/papers/2402.0…
introduce SPIRIT-LM, a foundation multimodal language model that freely mixes text and speech. Our model is based on a pretrained text language model that we extend to the speech modality by continuously training it on text and speech units. Speech and text sequences are concatenated as a single set of tokens, and trained with a word-level interleaving method using a small automatically-curated speech-text parallel corpus. SPIRIT-LM comes in two versions: a BASE version that uses speech semantic units and an EXPRESSIVE version that models expressivity using pitch and style units in addition to the semantic units. For both versions, the text is encoded with subword BPE tokens. The resulting model displays both the semantic abilities of text models and the expressive abilities of speech models. Additionally, we demonstrate that SPIRIT-LM is able to learn new tasks in a few-shot fashion across modalities (i.e. ASR, TTS, Speech Classification).
meatflavourdev retweeted
🧑🔬👷 The LLM Course is now complete!
I added the LLM Engineer Roadmap, a list of high-quality resources to build LLM-powered applications and deploy them.
💻 LLM Course: github.com/mlabonne/llm-cour…
meatflavourdev retweeted
PrivateGPT is a production-ready service offering Contextual Generative AI primitives like document ingestion and contextual completions through a new API that extends OpenAI’s standard.
Talk to your documents privately using the default UI and RAG pipeline or integrate your own.
meatflavourdev retweeted
Motorica has officially initiated the open beta phase for MoGen, the team's powerful tool for AI-generated character animation, powered by diffusion models.
Details: 80.lv/articles/a-new-tool-fo…
#mogen #ai #artificialintelligence #3danimation #animation #tech #technology
meatflavourdev retweeted
Meet StreamingLLM! Use LLMs for infinite input streams without losing efficiency and performance.
Now, you can build a ChatBot that persistently works on your recent chats!
📄 Paper: arxiv.org/pdf/2309.17453.pdf
🔧 Code: github.com/mit-han-lab/strea…
meatflavourdev retweeted
Tomorrow I'll be presenting Instruct-NeRF2NeRF at #ICCV2023! Come watch the talk tomorrow at 4:30 in Paris Sud or come by the poster (#164) to chat at 2:30 in Foyer Sud!
instruct-nerf2nerf.github.io…
We enable instruction-based editing of NeRFs via 2d diffusion models!
InstructNeRF2NeRF, w/@ayaanzhaque, Matt Tancik, Alyosha Efros, @holynski_
Edit your 3D capture with instructions🎨✨
instruct-nerf2nerf.github.io
Friday Afternoon *Oral* & Poster! Ayaan is just a sophomore :) excited for the talk!!
meatflavourdev retweeted
🚀 LLaVA-1.5 is out! Achieving SoTA on 11 benchmarks, with simple mods to original LLaVA! Utilizes merely 1.2M public data, trains in ~1 day on a single 8-A100 node, and surpasses methods that use billion-scale data.
🔗arxiv.org/abs/2310.03744
🧵1/5
meatflavourdev retweeted
Releasing Yarn-Llama-2-13b-128k, a Llama-2 model, trained for 128k context length using YaRN scaling. The model was trained in collaboration with u/bloc97 and @theemozilla of @NousResearch and @Void13950782 of @AiEleuther.
meatflavourdev retweeted
This is the fastest llama I've ever seen.
I can tell from the tokens and from chatting with quite a few llamas in my time.
llama2.lepton.run (h/t lepton.ai) – at San Francisco, CA
meatflavourdev retweeted
I wrote about a 23x improvement (!) in LLM live-inference throughput, measured on OPT-13B on A100. There are 2 new innovations which make this possible: Continuous batching & PagedAttention. Short thread below; see writeup, experiments, and results at anyscale.com/blog/continuous…
meatflavourdev retweeted
Truly excellent people root for others to succeed.
- Make money
- Build a family
- Travel the world
- Get physically fit
- Meet their heroes
- Achieve their goals
- Experience cultures
That's why they win.
meatflavourdev retweeted
Some of my early experiments with @runwayml GEN-1
It’s still early days of AI video - this tech will only get better. A whole new generation of filmmakers is gonna be able to make whatever they want on zero budget
See below for my process
meatflavourdev retweeted
The smallest checkpoint (OPT-2.7b) requires 15GB of GPU RAM, and the biggest one (Flan-T5-xxl) 50 GB, but we'll share quantization tricks on Monday which allow to roughly half the amount of memory required for all models
meatflavourdev retweeted
21st century technological advances have made our lives easier. But convenience has come with a price: Canadians are now more vulnerable to foreign state interference in cyberspace.
ALT A photo of the Canadian Security Intelligence Service’s Foreign Interference and You publication cover page with board game pions scattered on a large circuit board.