TLDR Index
TLDR AI

TLDR AI 2023-09-01

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01HEADLINES & LAUNCHES

META RELEASES FACET DATASET

Meta has released a new AI benchmark, FACET, designed to evaluate the “fairness” of AI models that classify and detect things in photos and videos, including people.

techcrunch.com2 min read

BAIDU LAUNCHES ERNIE CHATBOT

Chinese tech giant Baidu officially launched its Ernie chatbot after the government approved its application.

theverge.com1 min read

GOOGLE LAUNCHES TPU V5 AND H100 ENABLED VMS

Google is one of the few large organizations with hardware that can take on Nvidia. It has been challenging to use in the past with somewhat poor PyTorch support. Now, with even faster chips, and better software support - it seems like a compelling offering from the search giant.

cloud.google.com6 min read

02RESEARCH & INNOVATION

EVALUATING THE FAIRNESS OF COMPUTER VISION MODELS

In its continued push to be an open source contributor for AI, Meta released their amazing DINO v2 model under a more permissive license that allows the community to build on top of it. In addition, they released a data set that helps determine and benchmark bias in various computer vision models.

ai.meta.com6 min read

PREDICT VIDEO CONTENT BY SEPARATING MOTION AND APPEARANCE

Predicting video content is tricky because the system must guess object movements and keep them looking consistent. This new system, MMVP, separately handles motion and appearance using special "motion matrices" that focus just on movement. This method is not only more accurate but also more efficient and compact than current top systems.

arxiv.org18 min read

ENHANCING IMAGE GENERATION WITH TEXTURAL MODULATION

Producing diverse images from just a few examples is challenging. TexMod uses unique techniques to blend in details from various images and makes sure the created images have a logical layout.

arxiv.org14 min read

03ENGINEERING & RESOURCES

IMPROVING IMAGE QUALITY WITH SMART DECODING TECHNIQUES

This project developed a method that adjusts how images are decoded, especially for unfamiliar datasets. This process updates certain settings in the decoder, ensuring high-quality images without using much data. The system also adapts on the fly, depending on the type of image, for optimal results.

github.comGitHub repository

HOW FEEDBACK AFFECTS LLMS?

When training large language models to understand and match human values, do we use scores (rating) or comparisons (ranking) as feedback? This study found that the choice matters a lot. For instance, models trained with rankings are preferred when evaluated by comparison but not always by scoring. This shows that how we choose to give feedback has big implications for how well the model works in real-life situations.

github.comGitHub repository

04MISCELLANEOUS

DO MOST PEOPLE REALLY WANT TO SLOW DOWN AI?

Despite what you may see in the media, there are a number of issues with the polls and surveys saying that a majority of people want to slow down AI development.

learningfromexamples.substack.com6 min read

OPENAI BASE MODELS ARE NOT SYCOPHANTIC

Inverse scaling problems are things that get worse as model size increases. Sycophancy is when a model tends to agree with a human regardless of the truth. Anthropic released great work recently that showed larger models are more sycophantic. However, recent experiments show that OpenAI models don’t suffer from this same problem.

lesswrong.com5 min read