explained

AI Generative AI

Parti – Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Parti is a new autoregressive text-to-image model that shows just how much scale can achieve. This model’s outputs are crips, accurate, realistic, and can combine arbitrary styles, concepts, and fulfil even challenging requests. Yannic explains the research paper. Time stamps: 0:00 – Introduction 2:40 – Example Outputs 6:00 – Model Architecture 17:15 – Datasets (incl. […]

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AI

Is This the Worst AI Ever?

GPT-4chan was trained on over 3 years of posts from 4chan’s “politically incorrect” (/pol/) board. (and no, this is not GPT-4) You can imagine what it learned. Maybe we need to be better people so that we can make sure our AI overlords will have better behavior to model.

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AI Generative AI

The Weird and Wonderful World of AI Art (w/ Author Jack Morris)

Since the release of CLIP, the world of AI art has seen an unprecedented level of acceleration in what’s possible to do. Whereas image generation had previously been mostly in the domain of scientists, now a community of professional artists, researchers, and amateurs are sending around colab notebooks and sharing their creations via social media. […]

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AI Computer Vision Open Source

Exploring the LAION-5B: a 5 billion image-text-pairs dataset

LAION-5B is an open, free dataset consisting of over 5 billion image-text-pairs. Today’s video is an interview with three of its creators. We dive into the mechanics and challenges of operating at such large scale, how to keep cost low, what new possibilities are enabled with open datasets like this, and how to best handle […]

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AI Natural Language Processing

AlphaCode Explained: AI Code Generation

AlphaCode is DeepMind’s new massive language model for generating code. It is similar to OpenAI Codex, except for in the paper they provide a bit more analysis. The field of NLP within AI and ML has exploded get a lot more papers all the time. Hopefully this video can help you understand how AlphaCode works […]

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Machine Learning

DeepMind tackles Math and More in ML News

Here’s the latest round up of ML News: 0:00 – Intro 0:15 – Sponsor: Weights & Biases 3:10 – DeepMind tackles fundamental math 6:45 – Microsoft focuses on scaling effectively and efficiently 10:15 – NeurIPS Anthology Visualization 13:30 – Timnit Gebru launches research institute independent from big tech 16:50 – SageMaker Canvas for no-code ML […]

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AI Research

Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions

Backpropagation is the workhorse of deep learning, but unfortunately, it only works for continuous functions that are amenable to the chain rule of differentiation. Since discrete algorithms have no continuous derivative, deep networks with such algorithms as part of them cannot be effectively trained using backpropagation. This paper presents a method to incorporate a large […]

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