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STYLEDIFFUSION: PROMPT-EMBEDDING INVERSION FOR TEXT-BASED EDITING

Researchers address limitations in pretrained diffusion models for image editing by optimizing the input of the value linear network in cross-attention layers and introducing attention regularization to maintain object-like attention maps. These improvements result in superior editing capabilities, demonstrated through extensive experimental prompt-editing on various images.

2023.03.30
arxiv.org15 min readTLDR AI

INTRODUCING GPT4ALL

GPT4All is a 7B parameter language model, trained on high-quality assistant data and accompanied by 800K data samples, training code, and model weights for open research and reproducibility. A 4-bit quantized version that can run on a CPU is also provided.

2023.03.30
github.comGitHub repositoryTLDR AI

ADDING CONSISTENCY TO TEXT-TO-3D MODELS

Since the advent of powerful text-to-image models last year, people have been trying to move from 2d to 3d generation. One issue is the “multi-view consistency” problem, where if you only see part of an object, how do you infer what the other parts look like. Many naive methods will copy and paste the 2d image around the object which results in very odd images. By using a consistency injection technique, you can leverage the semantic understanding from 2d models to create fairly robust 3d models. The text to 3d printing pipeline is coming!

2023.03.30
github.comGitHub repositoryTLDR AI

The authors present VIVE3D, a new technique that extends the capabilities of image-based 3D GANs to video editing. It uses a novel GAN inversion technique optimized for camera parameters and introduces new edits that show novel views of the head using optical flow-guided compositing to combine the head with the background video, resulting in high-fidelity, consistent quality face edits from various camera viewpoints.

2023.03.30
afruehstueck.github.ioGitHub repositoryTLDR AI

INSTRUCT 3D-TO-3D: TEXT INSTRUCTION GUIDED 3D-TO-3D CONVERSION

Instruct 3D-to-3D, a high-quality 3D-to-3D conversion method, leverages pretrained Image-to-Image diffusion models to transform 3D scenes based on text instructions while maintaining consistency and controllability. Quantitative and qualitative evaluations demonstrate superior conversion quality compared to baseline methods, with the addition of dynamic scaling for adjustable geometry transformation intensity.

2023.03.30
sony.github.ioGitHub repositoryTLDR AI

GPT4ALL

GPT4All provides demos, data, and code to train an assistant-style LLM.

2023.03.30
github.comGitHub repositoryTLDR AI

LIT-LLAMA

Lit-LLaMA is a fully open source model of LLaMA.

2023.03.30
github.comGitHub repositoryTLDR AI

THE NFT MEV LANDSCAPE

The NFT market's structure differs significantly from that of fungible tokens, featuring more frequent capital formation events, lower secondary volumes, bid liquidity challenges, and numerous offchain orderbooks. This results in a unique NFT MEV landscape with fewer arbitrage opportunities and more MEV extraction during mints. Unique MEV forms in the NFT market include sweeping and re-listing floors, trait sniping, and extraction from inactive listings. Opportunities to address these challenges include MEV-aware minting solutions, open pricing data, dynamic on-chain orderbooks, new auction styles, and additional communication channels for traders.

2023.03.30
frontier.tech10 min readTLDR Crypto

GOOGLE PARTNERS WITH AI STARTUP REPLIT TO TAKE ON MICROSOFT’S GITHUB

Google is partnering with Replit, a startup with software that helps computer programmers write code. The partnership will see Google combine its artificial intelligence language models with Replit's Ghostwriter, which has 20 million users. Ghostwriter will rely on Google’s AI to suggest blocks of code and answer developers' questions. Replit will expand its use of Google's cloud services and aims to attract more corporate customers. Google will distribute Replit's software as part of the partnership.

2023.03.29
archive.ph4 min readTLDR

VISION-LANGUAGE MODELS WITH IN-CONTEXT LEARNING

OpenFlamingo is an open-source reproduction of DeepMind's Flamingo model. It enables the training and evaluation of large multimodal models. OpenFlamingo features a Python framework for training Flamingo-style LMMs, a large-scale multimodal dataset, an in-context learning evaluation benchmark for vision-language tasks, and the OpenFlamingo-9B model based on LLaMA.

2023.03.29
laion.ai5 min readTLDR

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2023.03.29
nsoftware.comSponsorTLDR

GOOGLE PARTNERS WITH AI STARTUP REPLIT TO TAKE ON MICROSOFT’S GITHUB

Google is teaming up with Replit to combine its AI language models with Replit's Ghostwriter software, which helps programmers write code. This collaboration aims to compete with Microsoft's GitHub Copilot, which uses OpenAI's language-generating AI. Ghostwriter will use Google's AI to improve code suggestions, program completion, and answering developer questions. Replit plans to enhance its software by offering end-to-end support for code writing, testing, deployment, app review, and collaboration. The partnership will also see Replit expand its use of Google's cloud services and distribution of its software.

2023.03.29
archive.ph2 min readTLDR AI

OPENFLAMINGO

Last year Deepmind published research on their Flamingo model which is a powerful multi-modal text and vision model. This model could answer questions about images while still being a powerful text model. Laion has now released a framework for training Flamingo models and a 9B parameter checkpoint trained on 5M samples of the Multimodal C4 dataset and 10M samples from LAION-2B image dataset. The model is not usable for commercial applications as it uses the 7B Llama checkpoint from Meta. It also doesn’t yet match Deepmind’s Flamingo on benchmark performance.

2023.03.29
laion.ai4 min readTLDR AI

PERPLEXITY AI SERIES A

One of the startup leaders in AI enabled search has launched an iPhone app and raised additional funding. They’re aiming to be the leader in knowledge discovery. We’ll see which of these services find differentiation, but the 2 million users in just a few months is impressive growth.

2023.03.29
perplexity.ai1 min readTLDR AI

CHATGPT IS THE NEW MTURK

NLP needs data, this data is usually labeled by crowdsourced workers on various platforms. It turns out, maybe unsurprisingly, that gpt-3.5-turbo is extremely good at following instructions for labeling and often outperforms human annotators on relevance, stance, topic, and other important measures. Even more importantly, it also costs much less (about 20x) than hiring human annotators.

2023.03.29
arxiv.org18 min readTLDR AI

EVA-CLIP: IMPROVED TRAINING TECHNIQUES FOR CLIP AT SCALE

The paper introduces EVA-CLIP, a set of models that significantly improve the efficiency and effectiveness of CLIP training. EVA-CLIP achieves superior performance compared to previous models with the same number of parameters but smaller training costs, and the complete suite is released for open research.

2023.03.29
arxiv.org7 min readTLDR AI

UNRAVELING IMAGEN: ZERO-SHOT CLASSIFICATION SHOWDOWN

Imagen, a text-to-image diffusion model, rivals CLIP in zero-shot classification, outperforming in shape/texture bias tests and suggesting generative pre-training as a valuable approach in vision-language tasks.

2023.03.29
arxiv.org12 min readTLDR AI

SYNTHESIS

This paper discusses how text-to-image diffusion models, like DreamBooth, can generate realistic images from simple text inputs, but can also be misused to produce fake news or disturbing content targeting individuals. The paper proposes a defense system called Anti-DreamBooth that adds subtle noise perturbations to user images to disrupt the generation quality of any DreamBooth model trained on them, and evaluates its effectiveness against a wide range of algorithms on various text-to-image model versions.

2023.03.29
github.comGitHub repositoryTLDR AI

AIX

AIx is a CLI tool to interact with LLM APIs.

2023.03.29
github.comGitHub repositoryTLDR AI