TLDR AI

TLDR AI 2023-09-15

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01HEADLINES & LAUNCHES

MICROSOFT OPEN SOURCES EVODIFF

Microsoft has open-sourced EvoDiff, a novel AI model that the company claims can generate high-fidelity, diverse proteins given a protein sequence.

techcrunch.com2 min read

STORAGE

MLPerf has released results from two benchmark suites: MLPerf Inference v3.1, which showcases record participation and performance gains, and MLPerf Storage v0.5, which assesses storage system performance for ML training workloads. The Inference benchmark suite introduced a large language model and updated recommender tests, reflecting emerging AI trends.

mlcommons.org5 min read

02RESEARCH & INNOVATION

ALIGN A LANGUAGE MODEL WITHOUT TRAINING

Alignment helps make language models more helpful and harmless. It can sometimes hurt performance, but in general is a positive. Alignment is expensive and requires substantial alignment data. However, if you allow the model to rewind during generation after evaluating its own output, it can improve alignment performance on the frozen model by up to 81%.

arxiv.org25 min read

PUSHING MIXTURE OF EXPERTS TO THE LIMIT WITH PARAMETER EFFICIENCY

Mixture of experts (MoEs) is a cool way to increase the capacity of a model without increasing per token runtime. However, they're still tricky to run quickly and fine-tune. Researchers find that if you modify dense model parameters efficiently fine tuning to work with MoEs you can dramatically reduce tuning costs without hurting performance too much.

arxiv.org28 min read

MAKING BETTER RECOMMENDATIONS

Researchers have developed a new model called HAMUR to improve how models make suggestions or "recommendations" across multiple subjects or domains, like music, books, or movies. Unlike older methods that mix up information between these domains, HAMUR uses a special technique to keep data separate and more flexible.

arxiv.org18 min read

03ENGINEERING & RESOURCES

LLM APPLICATIONS

A comprehensive guide to building RAG-based LLM applications for production.

github.comGitHub repository

MAKING JPEG PLAY NICE WITH DEEP LEARNING

JPEG images are everywhere, but they don't work well with deep learning because you can't easily tweak them during training. This project reviews existing solutions and introduces a new method that fixes these problems, making JPEG images fully adjustable and compatible with deep learning systems.

christophreich1996.github.ioGitHub repository

A NEW DATASET TO SPOT FAKE CELEBRITY IMAGES

DeepFakeFace (DFF) is a collection of fake celebrity photos made with advanced technology designed to help us get better at telling real pictures from fake ones.

arxiv.org9 min read

04MISCELLANEOUS

THE BUMPY ROAD TOWARD GLOBAL AI GOVERNANCE

Researchers suggested a global AI ethics agreement a few years ago, emphasizing its feasibility despite philosophical differences. As the U.S.-China AI competition grows, challenges like misperceptions and language barriers persist in achieving global AI regulation.

noemamag.com10 min read