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MACHINE LEARNING AND DATA LANDSCAPE - MATT TURCK

This 9th edition of the state of AI companies and growth gives great insight into the blistering pace of innovation. It is organized into four parts: Landscape (interactive), Financing, Data Infrastructure trends, ML/AI trends. The interactive landscape is a treat to go through to see various companies in different verticals.

2023.02.23
mattturck.com8 min readTLDR AI

3D OBJECT RECONSTRUCTION FROM A SINGLE IMAGE

This work uses off the shelf diffusion models to generate a prompt and “dream up” other 2D views for an object given a single image. They then fit a neural radiance field to generate a 3D representation of the object. This hierarchical chaining of models results in extremely compelling results. They also introduce some novel regularization for the final reconstruction step.

2023.02.23
arxiv.org38 min readTLDR AI

ANIMATED AI

A cool collection of novel animations to help understand deep learning concepts like padding, stride, and normalization strategies! They are also permissively licensed if you want to use them for your teaching and presentations.

2023.02.23
animatedai.github.io2 min readTLDR AI

LANGUAGE MODELS WITH LIMITED GPU MEMORY

The high computational and memory requirements of large language model (LLM) inference traditionally make it feasible only with multiple high-end accelerators. FlexGen aims to lower the resource requirements of LLM inference down to a single commodity GPU (e.g., T4, 3090) and allow flexible deployment for various hardware setups. The key technique behind FlexGen is to trade off between latency and throughput by developing techniques to increase the effective batch size.

2023.02.23
github.com8 min readTLDR AI

THE FUTURE OF CHATBOTS IN SEARCH BY ANDREW NG

Microsoft and Google's attempts to integrate large language models (LLMs) into chatbots for search have faced criticism due to their tendency to make up facts and produce toxic output. However, this article remains optimistic about the future of chat-based search, emphasizing the potential of retrieval augmented generation to improve factual accuracy and the development of techniques to reduce toxic behaviors. The author believes that with continued research and innovation, chatbots will evolve to better meet user needs and expectations.

2023.02.23
deeplearning.ai7 min readTLDR AI

HEAT UP

Amazon's cloud unit is partnering with AI startup HuggingFace to offer customers access to their products, including a language generation tool called Bloom that competes with OpenAI's ChatGPT. The companies already have a close relationship and over 1,000 customers in common. The cloud deal is not exclusive, so Huggingface is free to work with other providers.

2023.02.22
archive.ph4 min readTLDR

2023.02.22
interestingengineering.com3 min readTLDR

JELLY

Jelly is a static analyzer for JavaScript and TypeScript programs that use the Node.js platform. It can perform call graph construction, library usage pattern matching, and vulnerability exposure analysis. Jelly has a flow-insensitive control-flow and points-to analysis for tracking library usage. It models parts of the ECMAScript language and standard library, but not the Node.js standard library.

2023.02.22
github.comGitHub repositoryTLDR

MOON

moon is a task runner and repository management tool designed for web ecosystems. It is optimized for JavaScript and TypeScript. moon provides users with repository management, organization, orchestration, and notification features. It can increase productivity, improve the developer experience, reduce script confusion, and ensure that the same version of each tool is the same across every developer's environment.

2023.02.22
github.comGitHub repositoryTLDR

2023.02.22
gizmodo.com3 min readTLDR

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2023.02.22
7t04.short.gySponsorTLDR

NP-COMPLETE ISN'T (ALWAYS) HARD

The saying, 'NP-complete is hard', refers to the worst-case complexity - the average-case complexity is often much more tractable.

2023.02.22
hillelwayne.com5 min readTLDR

DOUBT THE WORTH OF YOUR WORK

This article discusses how the prevalence of impressive AI projects on social media platforms like Instagram can make other developers feel inadequate about their own work. The author encourages AI developers to judge their projects based on their own standards and not to be swayed by what's currently trendy. The field of AI is constantly evolving, with new technologies emerging all the time, and it's important to keep learning and stay up to date. The article reminds developers that the emergence of a new hot technology doesn't mean their current project is any less valuable.

2023.02.22
deeplearning.ai5 min readTLDR AI

TALKING ABOUT LARGE LANGUAGE MODELS

Technology and Philosophy have found a fun intersection with Large Language Models (LLMs). We often use anthropomorphising words such as “knows”, “understands”, or “believes” when referring to these systems. This paper advocates the community to take care when talking about these extremely capable systems and use more fitting language (e.g., encodes, stores, contains).

2023.02.22
arxiv.org22 min readTLDR AI

ENCODING IMAGES IN TEXT, UNSUPERVISED TEXT-IMAGE ALIGNMENT

This paper introduces LQAE which uses a pre-trained language model and encodes images as a sequence of text tokens, then they train a decoder with the BERT masking objective which learns to represent similar images with similar clusters of text tokens. They train the decoder to reconstruct the original image from the predicted text token embeddings. This serves to align the two modalities in an unsupervised manner. A fun side effect is the ability to compress images as text (just a few kb) and reconstruct a lossy version via a single forward pass.

2023.02.22
arxiv.org32 min readTLDR AI

PIX2PIX3D: 3D-AWARE CONDITIONAL IMAGE SYNTHESIS

This work proposes pix2pix3D, a 3D-aware conditional generative model for controllable photorealistic image synthesis. Given a 2D label map, such as a segmentation or edge map, the model learns to synthesize a corresponding image from different viewpoints. To enable explicit 3D user control, the authors extend conditional generative models with neural radiance fields. Given widely-available monocular images and label map pairs, the model learns to assign a label to every 3D point in addition to color and density, which enables it to render the image and pixel-aligned label map simultaneously.

2023.02.22
github.com5 min readTLDR AI

TURN YOUR DATAFRAME INTO A UI FOR VISUAL ANALYSIS

PyGWalker (pronounced Pig Walker) is a graphical tool for exploratory analysis of your data. It allows you to quickly inspect relationships, correlations, and distributions. Examples and screenshots are available in the repository readme.

2023.02.22
github.comGitHub repositoryTLDR AI

UNIVERSAL AUDIO SYNTHESIS MODEL

Universal vocoder for generating high fidelity audio with the ability to condition on specific features. This is the first large scale GAN model of its kind. Models, code, and samples are available.

2023.02.22
github.comGitHub repositoryTLDR AI

ADDING EXTRA CONDITIONS

Researchers have introduced a neural network structure called ControlNet, which can control pretrained large diffusion models to support additional input conditions. This new method allows for task-specific learning in an end-to-end fashion and is capable of learning with a small training dataset. The training is as fast as fine-tuning a diffusion model and can be done on a personal device, or it can scale to large amounts of data using powerful computation clusters. The researchers demonstrate that ControlNets can enable conditional inputs such as edge maps, segmentation maps, and key points for large diffusion models, which can benefit various related applications.

2023.02.22
github.comGitHub repositoryTLDR AI

BIOGPT

This GitHub repository contains the implementation of BioGPT, a generative pre-trained transformer for biomedical text generation and mining. It outperforms GPT-3 with just a fraction of the parameters.

2023.02.22
github.comGitHub repositoryTLDR AI

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2023.02.22
ratherlabs.comSponsorTLDR Crypto