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AI, ML, Data Engineering News Round up: Claude 2, Stable Doodle, CM3leon, Llama 2, Azure and xAI
The most recent update, covering developments from July 17th, 2023, showcases significant progress and announcements in the fields of data science, machine learning, and artificial intelligence. This week's focus centers on Anthropic, Stability AI, Microsoft, Meta and xAI.
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Berkeley Open-Sources AI Image-Editing Model InstructPix2Pix
Researchers from the Berkeley Artificial Intelligence Research (BAIR) Lab have open-sourced InstructPix2Pix, a deep-learning model that follows human instructions to edit images. InstructPix2Pix was trained on synthetic data and outperforms a baseline AI image-editing model.
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EU AI Act: the Regulatory Framework on the Usage of Machine Learning in the European Union
After the first publication of the proposal on the operation of machine learning applications in 2021, on June 14th negotiations have started for the realization of the legislation in the EU Council. The EU countries are expected to reach an agreement by the end of 2023. The EU Act takes a risk-based approach and plans to avoid disproportionate prescriptions when executing the regulations.
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OpenAI Introduces Superalignment to Address Rogue Superintelligent AI
OpenAI announced the formation of a specialized Superalignment team with the objective of preventing the emergence of rogue Superintelligent AI. OpenAI highlighted the need to align AI systems with human values and emphasized the importance of proactive measures to prevent potential harm.
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Meta's Open-Source Massively Multilingual Speech AI Handles over 1,100 Languages
Meta AI open-sourced the Massively Multilingual Speech (MMS) model, which supports automatic speech recognition (ASR) and text-to-speech synthesis (TTS) in over 1,100 languages and language identification (LID) in over 4,000 languages. MMS can outperform existing models and covers nearly 10x the number of languages.
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Meta Open-Sources Computer Vision Foundation Model DINOv2
Meta AI Research open-sourced DINOv2, a foundation model for computer vision (CV) tasks. DINOv2 is pretrained on a curated dataset of 142M images and can be used as a backbone for several tasks, including image classification, video action recognition, semantic segmentation, and depth estimation.
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Google's Universal Speech Model Performs Speech Recognition on Hundreds of Languages
Google Research announced Universal Speech Model (USM), a 2B parameter automated speech recognition (ASR) model trained on over 12M hours of speech audio. USM can recognize speech in over 100 languages, including low-resource languages, and achieves new state-of-the-art performance on several benchmarks.
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Stability AI Open-Sources 7B Parameter Language Model StableLM
Stability AI released two sets of pre-trained model weights for StableLM, a suite of large language models (LLM). The models are trained on 1.5 trillion text tokens and are licensed for commercial use under CC BY-SA-4.0.
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Meta's Toolformer Uses APIs to Outperform GPT-3 on Zero-Shot NLP Tasks
Meta AI Research announced Toolformer, a language model that learns to call APIs to help solve natural language processing (NLP) tasks. Toolformer automatically annotates a training dataset which is used to fine-tune the model and can outperform the much larger GPT-3 model on several zero-shot NLP tasks.
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Meta Open-Sourced AI Tool to Animate Child and Amateur Drawings of Human Figure
Based on a joint research by Meta AI Research, Tencent America, MIT CSAIL, and Carnegie Mellon, Meta released Animated Drawings, an AI-based tool to create animations from hand drawn human-like characters.
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Twitter Open-Sources Recommendation Algorithm
Twitter recently open-sourced several components of their system for recommending tweets for a user's Twitter timeline. The release includes the code for several of the services and jobs that run the algorithm, as well as code for training machine learning models for embedding and ranking tweets.
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PyTorch 2.0 Compiler Improves Model Training Speed
The PyTorch Foundation recently released PyTorch version 2.0, a 100% backward compatible update. The main API contribution of the release is a compile function for deep learning models, which speeds up training. Internal benchmarks on 163 open-source AI projects showed that the models ran on average 43% faster during training.
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Google Uses AutoML to Discover More Efficient AI Training Algorithm
Researchers at Google have open-sourced EvoLved sIgn mOmeNtum (Lion), an optimization algorithm for training neural networks, which was discovered using an automated machine learning (AutoML) evolutionary algorithm. Models trained with Lion can achieve better accuracy on several benchmarks than models trained with other optimizers, while requiring fewer compute cycles to converge.
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Meta AI’s Large Language Model with 10x Fewer Parameters
Meta AI recently released a new large language model called Language Large Models Meta AI (LLaMA) that outperforms foundational models such as GPT-3 and is competitive with PaLM, despite having 10 times fewer parameters. LLaMA has better performance in language tasks such as natural questions, common-sense reasoning and mathematical reasoning.
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Microsoft Open-Sources Weather Forecasting Deep Learning Model ClimaX
Researchers from Microsoft's Autonomous Systems and Robotics Research group have open-sourced ClimaX, a deep learning foundation model for weather and climate modeling. ClimaX can be fine-tuned for a variety of prediction tasks and performs as well as or better than state-of-the-art models on several benchmarks.