InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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3D Point Cloud Object from Text Prompts Using Diffusion Models
OpenAI recently released an alternative method called Point-E for 3D object generation from text prompts that takes less than two minutes on a single GPU, versus the other methods that could take a few GPU hours. This new model is based on diffusion models, which are generative models like GLIDE and StableDiffusion.
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Google AI Unveils Muse, a New Text-to-Image Transformer Model
Google AI released a research paper about Muse, a new Text-To-Image Generation via Masked Generative Transformers that can produce photos of a high quality comparable to those produced by rival models like the DALL-E 2 and Imagen at a rate that is far faster.
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Deep Learning Pioneer Geoffrey Hinton Publishes New Deep Learning Algorithm
Geoffrey Hinton, professor at the University of Toronto and engineering fellow at Google Brain, recently published a paper on the Forward-Forward algorithm (FF), a technique for training neural networks that uses two forward passes of data through the network, instead of backpropagation, to update the model weights.
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Waymo Developed Collision Avoid Test to Evaluate Its Autonomous Driver
Waymo developed a testing framework called Collision Avoidance Test (CAT) to evaluate the ability to avoid crush or potential hazard situations of its Waymo Driver, compared to a human driver.
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Amazon Releases Fortuna, an Open-Source Library for ML Model Uncertainty Quantification
AWS announced that Fortuna, an open-source toolkit for ML model uncertainty quantification, has been made generally available. Any trained neural network can be used with the calibration methods offered by Fortuna, such as conformal prediction, to produce calibrated uncertainty estimates.
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Generating Text Inputs for Mobile App Testing Using GPT-3
A group of researchers from the Chinese Academy of Sciences and Monash University have presented a new approach to text input generation for mobile app testing based on a pre-trained large language model (LLM). Dubbed QTypist, the approach was evaluated on 106 Android apps and automated test tools, showing a significant improvement of testing performance.
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Google Publishes Technique for AI Language Model Self-Improvement
Researchers at Google and University of Illinois at Urbana-Champaign (UIUC) have published a technique called Language Model Self-Improved (LMSI), which fine-tunes a large language model (LLM) on a dataset generated by that same model. Using LMSI, the researchers improved the performance of the LLM on six benchmarks and set new state-of-the-art accuracy records on four of them.
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Microsoft’s New Memory Optimized Ebsv5 VM Sizes in Preview Offer More Performance
Microsoft recently announced two additional Memory Optimized Virtual Machines (VM) sizes, E96bsv5 and E112ibsv5, to the Ebsv5 VM family developed with the NVMe protocol providing performance up to 260,000 IOPS and 8,000 MBps remote disk storage throughput.
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Researchers Publish Survey of Algorithmically-Efficient Deep Learning
Researchers from Lawrence Livermore National Laboratory and MosaicML have published a survey of over 200 papers on algorithmically-efficient deep learning. The survey includes a taxonomy of methods to speed up training as well as a practitioner's guide for mitigating training bottlenecks.
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Meta Releases data2vec 2.0 a High Efficiency Self-Supervised Model
Meta has released version 2.0 of Data2Vec, a self-supervised algorithm that can learn in the same way from three different modalities: speech, vision, and text, and achieves the same accuracy of the other computer vision models but 16x faster. The code and pretrained models are also shared with the other researchers.
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ML.NET 2.0 Release Contains New NLP APIs and AutoML Updates
Microsoft announced the release of ML.NET 2.0, the open-source machine learning framework for .NET. The release contains several updated natural language processing (NLP) APIs, including Tokenizers, Text Classification, and Sentence Similarity, as well as improved automated ML (AutoML) features.
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OpenAI Unveils a Powerful, Cost-Effective, and User-Friendly Embedding Model
OpenAI is introducing text-embedding-ada-002, a cutting-edge embedding model that combines the capabilities of five previous models for text search, text similarity, and code search. This new model outperforms the previous most capable model, Davinci, on most tasks, while being significantly more cost-effective at 99.8% lower pricing.
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How Twitter Automated Data Quality Check Process
Twitter engineering has recently shared a blog post on how they architected and developed a quality automation platform. Twitter digests and creates thousands of data sets for different data products and applications. The next natural step is to make sure of the quality of the data by adding automation on top of it. In this news post, we explore this architecture in more detail.
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Meta's CICERO AI Wins Online Diplomacy Tournament
Meta AI Research recently open-sourced CICERO, an AI that can beat most humans at the strategy game Diplomacy, a game that requires coordinating plans with other players. CICERO combines chatbot-like dialogue capabilities with a strategic reasoning, and recently placed first in an online Diplomacy tournament against human players.
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AWS Makes it Simpler to Share ML Models and Notebooks with Amazon SageMaker JumpStart
AWS announced that it is now easier to share machine learning artifacts like models and notebooks with other users using SageMaker JumpStart. Amazon SageMaker JumpStart is a machine learning hub that helps users accelerate their journey into the world of machine learning.