dataset – AI.RadicalShift

datasetsSNLI: A Benchmark Dataset Fueling Advances in Natural Language Inference (NLI)

AI Inference, Americas, Artificial Intelligence, Datasets, Deep learning, Language model training, Machine learning

September 18, 2024

RadicalShift.AI

annotators, attention mechanisms, BiLSTMs, contradiction, dataset, deep learning, entailment, Flickr30k dataset, LSTMs, natural language inference, Neutral, NLI, recognizing textual entailment, RTE, SNLI, Stanford Natural Language Inference, training

The Stanford Natural Language Inference (SNLI) Dataset is a large-scale dataset developed to support research on natural language inference (NLI), also known as recognizing textual entailment (RTE). The dataset contains 570,000 pairs of sentences manually annotated as entailment, contradiction, or neutral, which are the three possible relationships between a premise and a hypothesis. Key Features:…
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newsMeta Launches SAM 2: Revolutionizing Object Segmentation in Images and Videos with Advanced AI Capabilities

Algorithms, Americas, Analytics, Artificial Intelligence, Datasets, Internet & Online, Machine learning, Media, Open Source LLMs

July 29, 2024

Oleg Lazarov

AI, AI community, Amazon SageMaker, annotation, Apache 2.0 license, computer vision, dataset, generative video model, images, Llama, machine learning, Mark Zuckerberg, Meta, metadata, multimodal understanding, object segmentation, open science, open-source, real-time processing, real-world applications, SA-V dataset, SAM 2, video segmentation, videos, zero-shot generalization

MENLO PARK — In a significant leap forward for computer vision technology, Meta has introduced SAM 2, the next iteration of its acclaimed Segment Anything Model (SAM). This cutting-edge model now empowers real-time, promptable object segmentation in both images and videos, achieving state-of-the-art performance that sets a new standard for the industry. Continuing Meta’s commitment…
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newsGeorgia Tech and Meta Collaborate on Groundbreaking Dataset to Drive Innovation in Direct Air Capture Technology

AI assistants, Algorithms, Americas, Analytics, Artificial Intelligence, Datasets, Environment, Machine learning, Open Source LLMs

May 2, 2024

Sheryl Rivera

ACS Central Science, AI, Andrew J. Medford, Anuroop Sriram, Carbon Capture, carbon dioxide removal, carbon emissions, climate change, collaboration, dataset, David Sholl, direct air capture, energy, environmental impact, FAIR, Fundamental AI Research, Georgia Tech, innovation, machine learning, materials chemistry, Matt Uyttendaele, Meta, MOFs, negative-emission technologies, open-source, OpenDAC, quantum mechanics, scientific research, sorbent discovery, sustainability

This post was originally published on the Georgia Tech Blog. MENLO PARK — In an ambitious effort to combat climate change, Georgia Tech and Meta have joined forces to develop a massive open-source dataset designed to advance AI-driven solutions for carbon capture. This initiative, dubbed OpenDAC, aims to accelerate the development of direct air capture (DAC)…
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newsMeta Unveils Emu Video and Emu Edit: Pioneering New Frontiers in Generative AI

AI assistants, Americas, Artificial Intelligence, Generative AI, Internet & Online, Media, Text-to-image, Text-to-video

November 16, 2023

Sheryl Rivera

10 million samples, AI-driven assistance, AI-powered editing, animated images, background removal, computer vision tasks, creative expression, creativity, custom GIFs, dataset, diffusion models, Emu Edit, Emu Video, factorized approach, generative AI, geometry transformations, global edits, high-quality video, image generation, Imagine feature, Instagram, local edits, Make-A-Video, Meta, photorealistic images, precision editing, professional artists, social media, state-of-the-art performance, stickers, text prompts, text-based instructions, text-to-video generation, video generation

MENLO PARK — Meta has reached new milestones in its generative AI research, unveiling two significant advancements: Emu Video and Emu Edit. Authored by Meta, this announcement builds on the company’s earlier successes in generative AI, following their introduction of the Emu model for image generation. At Meta Connect, Emu-powered features were showcased, including AI-driven…
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newsFacebook AI Launches Hateful Memes Dataset and Challenge to Combat Harmful Multimodal Content

AI assistants, Algorithms, Americas, Analytics, Artificial Intelligence, Internet & Online, Machine learning, Society

May 12, 2020

Sheryl Rivera

AI research, AI systems, baseline-trained models, competition, content moderation, dataset, Deepfake Detection Challenge, DrivenData, Facebook AI, Getty Images, harmful content, hate speech, Hateful Memes, multimodal classifiers, multimodal content, multimodal machine learning, NeurIPS 2020, Reproducibility Challenge, text and images

MENLO PARK — On May 12, 2020, Facebook AI introduced a new dataset and competition aimed at advancing the detection of multimodal hate speech, which includes both text and images. The Hateful Memes dataset, containing over 10,000 examples, was created to help AI researchers develop systems capable of understanding and identifying harmful content that blends…
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newsFacebook AI Launches Deepfake Detection Challenge to Combat Manipulated Media

AI assistants, Algorithms, Americas, Analytics, Artificial Intelligence, Internet & Online, Machine learning, Media, Responsible AI

December 11, 2019

Oleg Lazarov

AI, AI Models, AI-driven manipulations, AWS, Cristian Canton Ferrer, Data Science, dataset, deepfake detection, Deepfake Detection Challenge, deepfakes, DFDC, Facebook AI, Kaggle, machine learning, manipulated media, Microsoft, NeurIPS, NeurIPS conference, open-source, prevention of deepfakes, real-world deepfakes, responsible AI, video manipulation

MENLO PARK — Facebook AI, in partnership with leaders from academia and industry, has launched the Deepfake Detection Challenge (DFDC), an open initiative to accelerate the development of technologies aimed at detecting deepfakes and manipulated media. The challenge was introduced at the NeurIPS conference, offering participants access to a new dataset containing over 100,000 videos…
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newsTech and Academic Leaders Join Forces to Tackle Deepfake Threats with New Detection Challenge

AI assistants, Algorithms, Americas, Analytics, Artificial Intelligence, Internet & Online, Machine learning, Media

September 5, 2019

Oleg Lazarov

academia, AI, artificial intelligence, challenge, collaboration, Cornell Tech, dataset, Deepfake Detection Challenge, deepfakes, DFDC, digital age, ethical data use, Facebook, ICCV, information integrity, International Conference on Computer Vision, manipulated media, media integrity, Microsoft, misinformation, MIT, neural networks, NeurIPS, Partnership on AI, Steering Committee, University of Oxford

MENLO PARK — A coalition of leading tech companies and academic institutions, including Facebook, Microsoft, and universities such as MIT, Cornell Tech, and the University of Oxford, have launched the Deepfake Detection Challenge (DFDC) to address the growing threat posed by AI-generated “deepfake” videos. The challenge aims to spur innovation in detecting manipulated media by…
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newsAI and Medical Imaging Community Invited to Participate in First-Ever fastMRI Challenge

AI assistants, Algorithms, Americas, Analytics, Artificial Intelligence, Healthcare, Internet & Online, Machine learning

September 4, 2019

Oleg Lazarov

Accessibility, AI, artificial intelligence, challenge, clinical practice, collaboration, dataset, diagnostic imaging, Efficiency, Facebook AI, fastMRI, Healthcare, image quality, image reconstruction, innovation, knee MRI, magnetic resonance imaging, medical imaging, Medical Imaging Meets NeurIPS Workshop, medical technology, MRI, neural network, NeurIPS 2019, NYU School of Medicine, Radiologists, scan time, Speed, SSIM, Structural Similarity measure, technology

MENLO PARK — The fastMRI project, a collaboration between Facebook AI and NYU School of Medicine, has launched its inaugural fastMRI image reconstruction challenge, inviting the global AI and medical imaging communities to develop innovative solutions to significantly speed up MRI scans. The challenge opens on September 5, 2019, with participants tasked to create AI-driven…
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What is RadicalShift AI?

RadicalShift.ai represents the paradigm shift the artificial intelligence (AI) brings upon all of us, from the way we live and work to the way we do business. To help cope with these fundamental changes across life, industries and the world in general, we are obsessively observing (30+ markets across multiple continents) and covering the AI industry while building a scalable open platform aimed at people, businesses and industry stakeholders to contribute across (benefit from) the entire spectrum of the AI industry from news, views, insights to knowledge, deployments, entities, people, products, tools, jobs, investors, pitch decks, and beyond, helping build what would potentially be a resourceful, insightful, knowledgeable and analytical source for AI related news, information and resources, ultimately becoming the AI industry graph/repository.