MACHINE LEARNING

→ View original post on X — @demishassabis

AlphaDev discovers faster sorting algorithm for C++ library

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@demishassabis

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07 June 2023 22h39

Our latest work in @Nature today: #AlphaDev discovered a new faster sorting algorithm that we open sourced to the main C++ library for all developers to use. This is just the beginning of AI being used to find many more efficiencies in code in future http://
dpmd.ai/alphadev-tw

→ View original post on X — @erikbryn

AI Discovers New Sorting Algorithms Surpassing Human Benchmarks

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@erikbryn

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07 June 2023 22h36

Can AI help make important discoveries with practical value? Yes! "Algorithms such as sorting or hashing are used trillions of times each day…AlphaDev discovered sorting algorithms from scratch that outperformed previously known human benchmarks."

Data-IQ: Systematic Data Stratification Tool for AI Applications

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07 June 2023 22h05

AI poster competition finalist Nabeel Seedat, @Cambridge_Uni
, will discuss Data-IQ, a powerful tool enabling systematic stratification of data subgroups. Join the talk and vote for the best poster https://
future.snorkel.ai

JoinBoost: Python Library Converting Tree Algorithms to SQL

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07 June 2023 21h50

AI poster competition finalist Zachary Huang, @Columbia
, will discuss JoinBoost – a Python library transforming tree training algorithms into pure SQL queries. Join the talk and vote for the best poster https://
future.snorkel.ai

→ View original post on X — @jeande_d

Code-First Resources for Learning Deep Learning and Neural Networks

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@jeande_d

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07 June 2023 21h40

Thanks. Try code-first courses or pick up a book that emphasizes codes over math. There are many examples: Karpathy neural networks: zero to hero(new!!), one shared above by Sebastian Ras., practical deep learning for coders FAST dot AI, Chollet deep learning with python book.

Paprika: Procedure-Aware Pre-Training Model for Instructional Knowledge

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07 June 2023 21h35

AI poster competition finalist Honglu Zhou, @RutgersU
, will discuss Paprika, a procedure-aware pre-training model for instructional knowledge acquisition. Join the talk and vote for the best poster https://
future.snorkel.ai

→ View original post on X — @googleai

SQuId: AI Model for Speech Quality Assessment Across Languages

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@googleai

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07 June 2023 21h03

Learn how SQuId (Speech Quality Identification), a 600M parameter regression model that describes to what extent a piece of speech sounds natural, can be used to complement human ratings for the text-to-speech evaluation of many languages → https://
goo.gle/3J1kghg

→ View original post on X — @miketamir

GitHub Copilot: Inside the LLMs Technology Behind It

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@miketamir

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07 June 2023 21h01

Inside GitHub: Working with the LLMs behind GitHub Copilot | The GitHub Blog https://
bit.ly/3oi2PBO #AI #MachineLearning #DeepLearning #LLMs #DataScience

DataComp-1B CLIP Model Outperforms OpenAI with Lower Compute Cost

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07 June 2023 20h41

Delve into DataComp with @lschmidt3 next at https://
future.snorkel.ai about innovating #ML by experimenting with new training sets. A new CLIP model, DataComp-1B, outperforms OpenAI’s by 3.7pp on ImageNet, and a 9x improvement in compute cost vs. LAION-5B.