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Today, we're launching the largest open-source dataset of gaming data for computer-use. 500+ hours of gameplay screen recordings + keystrokes/mouse movements, across Valorant, Minecraft, GTA and more. Link in the comments :) @markov__ai

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109,477 görüntüleme • 3 ay önce •via X (Twitter)

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Today, we're launching the world's largest open-source dataset of computer-use recordings. 10,000+ hours across Salesforce, Blender, Photoshop and more, to automate the next level of white-collar work. Link in the comments :) @markov__ai
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Today, we're launching the world's largest open-source dataset of computer-use recordings. 10,000+ hours across Salesforce, Blender, Photoshop and more, to automate the next level of white-collar work. Link in the comments :) @markov__ai

Dev

475,305 görüntüleme • 7 ay önce

Today, we're launching the world's largest open-source CAD dataset for computer-use. 1,000+ hours across SolidWorks, Siemens-NX, AutoCAD & more. Screen recordings, mouse/keyboard actions, input diagrams, output files, rubrics and narrations. Link in the comments :)
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Today, we're launching the world's largest open-source CAD dataset for computer-use. 1,000+ hours across SolidWorks, Siemens-NX, AutoCAD & more. Screen recordings, mouse/keyboard actions, input diagrams, output files, rubrics and narrations. Link in the comments :)

Dev

158,270 görüntüleme • 1 ay önce

Today we're launching the most advanced computer-use dataset in the world. 1,000+ hours of screen recordings along with mouse/keyboard inputs + annotations. Sourced from experts across coding, design, browser-use, research and more. Link in the comments :) Markov
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Today we're launching the most advanced computer-use dataset in the world. 1,000+ hours of screen recordings along with mouse/keyboard inputs + annotations. Sourced from experts across coding, design, browser-use, research and more. Link in the comments :) Markov

Dev

47,966 görüntüleme • 6 ay önce

today we're launching a dataset of computer-use recordings to build the next generation of computer-use agents. 300+ tasks across all kinds of software. open-source. link in the comments. Markov
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today we're launching a dataset of computer-use recordings to build the next generation of computer-use agents. 300+ tasks across all kinds of software. open-source. link in the comments. Markov

Dev

81,060 görüntüleme • 7 ay önce

Today, we’re launching computer-use CAD environments to train AI models for engineering. Task prompts, reference files, gold outputs, rubrics & human walkthrough screen-recordings. We're open-sourcing 50 tasks across AutoCAD, Solidworks & Siemens-NX. Link below @markov__ai
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Today, we’re launching computer-use CAD environments to train AI models for engineering. Task prompts, reference files, gold outputs, rubrics & human walkthrough screen-recordings. We're open-sourcing 50 tasks across AutoCAD, Solidworks & Siemens-NX. Link below @markov__ai

Dev

13,316 görüntüleme • 2 ay önce

Today, our computer-use datasets crossed 50,000+ hours. Screen recordings + synced mouse/keyboard actions + narrations across CAD, design, browser-use & more. Sourced from humans and available off the shelf today :) Samples below.
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Today, our computer-use datasets crossed 50,000+ hours. Screen recordings + synced mouse/keyboard actions + narrations across CAD, design, browser-use & more. Sourced from humans and available off the shelf today :) Samples below.

Dev

83,300 görüntüleme • 1 ay önce

Today, we're open sourcing the first computer-use dataset for design. We captured 200+ hours and 3400+ trajectories of real design work in Figma, recording step by step how designers execute complex, long-horizon tasks. FigmaTrace dataset, paper, and blog below :) PatronusAI
0:19

Today, we're open sourcing the first computer-use dataset for design. We captured 200+ hours and 3400+ trajectories of real design work in Figma, recording step by step how designers execute complex, long-horizon tasks. FigmaTrace dataset, paper, and blog below :) PatronusAI

Anand Kannappan

137,566 görüntüleme • 1 ay önce

Spatial AI ( is building large real-world datasets to teach robots how to navigate the world and complete tasks. Their first open source dataset, SEA (Spatial Everyday Activities), is the largest curated egocentric dataset of people carrying out real tasks, with 10,000 hours of data.
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Spatial AI ( is building large real-world datasets to teach robots how to navigate the world and complete tasks. Their first open source dataset, SEA (Spatial Everyday Activities), is the largest curated egocentric dataset of people carrying out real tasks, with 10,000 hours of data.

Y Combinator

20,944 görüntüleme • 10 ay önce

Most of the data needed to scale Physical AI models is private. At Lightwheel, we think that's worth changing. So this week we released the first 10,000 hours of EgoSuite-Open100K — an open egocentric human dataset for Physical AI. 100,000 hours coming in total. Learn more here:
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Most of the data needed to scale Physical AI models is private. At Lightwheel, we think that's worth changing. So this week we released the first 10,000 hours of EgoSuite-Open100K — an open egocentric human dataset for Physical AI. 100,000 hours coming in total. Learn more here:

Jonathan Stephens

10,613 görüntüleme • 1 ay önce

A Rerun Viewer for the DROID Dataset! DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset is a robot manipulation dataset by Alexander Khazatsky et al. with 76k demonstration trajectories or 350h of interaction data, collected across 564 scenes and 86 tasks.
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A Rerun Viewer for the DROID Dataset! DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset is a robot manipulation dataset by Alexander Khazatsky et al. with 76k demonstration trajectories or 350h of interaction data, collected across 564 scenes and 86 tasks.

Rerun

21,794 görüntüleme • 2 yıl önce

1/ Today we're announcing the stable Cua Driver release for Omarchy - a new foundation for computer use, built into the OS from the ground up. Over the last month, we worked directly with DHH, Spencer Bull and vaxry to bring a native synthetic cursor to Omarchy's Hyprland compositor, enabling true multi-cursor computer use at the OS level. Cua Driver is open source and available at
0:15

1/ Today we're announcing the stable Cua Driver release for Omarchy - a new foundation for computer use, built into the OS from the ground up. Over the last month, we worked directly with DHH, Spencer Bull and vaxry to bring a native synthetic cursor to Omarchy's Hyprland compositor, enabling true multi-cursor computer use at the OS level. Cua Driver is open source and available at

Cua

337,766 görüntüleme • 15 gün önce

📅 We're thrilled to unveil today the top Priority 1 from our Q2 Roadmap: the Launch of the Data Lake Chain! This priority comes along with a new ground-breaking use case for $LAKE and the Data Lake App ready for deployment! Get ready for our most ambitious quarter yet as we embark on the largest implementation of blockchain in healthcare ever witnessed! 🔜🪐
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📅 We're thrilled to unveil today the top Priority 1 from our Q2 Roadmap: the Launch of the Data Lake Chain! This priority comes along with a new ground-breaking use case for $LAKE and the Data Lake App ready for deployment! Get ready for our most ambitious quarter yet as we embark on the largest implementation of blockchain in healthcare ever witnessed! 🔜🪐

Data Lake Token

60,416 görüntüleme • 2 yıl önce

Today we’re releasing SAIR, the Structurally Augmented IC50 Repository. SAIR is the Largest Open-Sourced Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📰Read the Press Release: 📥Learn More and Download the Dataset at #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQ
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Today we’re releasing SAIR, the Structurally Augmented IC50 Repository. SAIR is the Largest Open-Sourced Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📰Read the Press Release: 📥Learn More and Download the Dataset at #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQ

SandboxAQ

129,416 görüntüleme • 1 yıl önce

Registration for the 2026 NASA #SpaceApps Challenge is now open! 🚀 Be a part of the largest annual hackathon, where you can use open data from #NASA and space-based data from 17 Space Agency Partners to address the most pressing challenges in Earth and space exploration to spark innovation that’s grounded in experience and ready for tomorrow. 💫 Register now:
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Registration for the 2026 NASA #SpaceApps Challenge is now open! 🚀 Be a part of the largest annual hackathon, where you can use open data from #NASA and space-based data from 17 Space Agency Partners to address the most pressing challenges in Earth and space exploration to spark innovation that’s grounded in experience and ready for tomorrow. 💫 Register now:

NASA Space Apps Challenge

195,937 görüntüleme • 1 ay önce

The newest version of our Almanac preprint is out, and just in time for our demo at the Stanford AIMI Symposium 2023! Almanac is a retrieval-augmented LLM that provides up-to-date and verifiable answers to medical queries. Link: We benchmark our approach on a novel dataset of clinical scenarios (n = 130) evaluated by a panel of 5 board-certified & resident physicians, and demonstrate significant increases in factuality (mean of 18% at p-value < 0.05) across all specialties. More interestingly, because the retrieved data acts as a single source of truth, we find retrieval-based LLMs to be more robust to prompt injection and manipulation! Future work will involve expanding the scope of our dataset to more specialties and multimodal settings. #Medtwitter #MedEd
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The newest version of our Almanac preprint is out, and just in time for our demo at the Stanford AIMI Symposium 2023! Almanac is a retrieval-augmented LLM that provides up-to-date and verifiable answers to medical queries. Link: We benchmark our approach on a novel dataset of clinical scenarios (n = 130) evaluated by a panel of 5 board-certified & resident physicians, and demonstrate significant increases in factuality (mean of 18% at p-value < 0.05) across all specialties. More interestingly, because the retrieved data acts as a single source of truth, we find retrieval-based LLMs to be more robust to prompt injection and manipulation! Future work will involve expanding the scope of our dataset to more specialties and multimodal settings. #Medtwitter #MedEd

Cyril Zakka, MD

18,168 görüntüleme • 3 yıl önce

Most companies that shut down give up their impact. This startup did something much better: they open-sourced 1,274 hours of egocentric robotics data. 13,451 recordings of humans doing everyday tasks, as a gift to the robotics community. Thank you EIDON AI! Open source has a superpower: work can outlive the organization that created it. More startups should do this!
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Most companies that shut down give up their impact. This startup did something much better: they open-sourced 1,274 hours of egocentric robotics data. 13,451 recordings of humans doing everyday tasks, as a gift to the robotics community. Thank you EIDON AI! Open source has a superpower: work can outlive the organization that created it. More startups should do this!

clem 🤗

146,362 görüntüleme • 19 gün önce

It's #TeaseYaGame time! We're gonna use the opportunity to tease some new places from Alabaster Dawn Lots of new enemies, areas, puzzles and music in the works! Steam Link in the comments!
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It's #TeaseYaGame time! We're gonna use the opportunity to tease some new places from Alabaster Dawn Lots of new enemies, areas, puzzles and music in the works! Steam Link in the comments!

Alabaster Dawn EA Out Now

11,446 görüntüleme • 7 ay önce

The Last of Us Part II released six years ago today and is still one of the most decorated titles in gaming history. Incredible stealth gameplay, crazy story, and still one of the most visually stunning games ever. Really can't wait to see more of Intergalactic.
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The Last of Us Part II released six years ago today and is still one of the most decorated titles in gaming history. Incredible stealth gameplay, crazy story, and still one of the most visually stunning games ever. Really can't wait to see more of Intergalactic.

KAMI

30,810 görüntüleme • 3 ay önce

Landing accurately under parachute has historically been more art than science. We're changing that with physical AI. The flexibility of the fabric has traditionally made modeling performance and controllability extremely difficult. By using the latest computer vision and AI models, we have been able to accurately track the movements and shape of the canopy across more than a hundred flights, variable control inputs, and changing flight conditions. The tracking remains effective through visual disruptions, canopy deflections, and changes in vehicle orientation. We feed this data back into our 8-DOF models to better tune Arc's GNC algorithms for the highest accuracy landing in a wide range of flight conditions. This, along with other updates, has reduced landing error by 90%. We're aiming for the controllability of a metal wing with a piece of fabric.
0:12

Landing accurately under parachute has historically been more art than science. We're changing that with physical AI. The flexibility of the fabric has traditionally made modeling performance and controllability extremely difficult. By using the latest computer vision and AI models, we have been able to accurately track the movements and shape of the canopy across more than a hundred flights, variable control inputs, and changing flight conditions. The tracking remains effective through visual disruptions, canopy deflections, and changes in vehicle orientation. We feed this data back into our 8-DOF models to better tune Arc's GNC algorithms for the highest accuracy landing in a wide range of flight conditions. This, along with other updates, has reduced landing error by 90%. We're aiming for the controllability of a metal wing with a piece of fabric.

Inversion

32,627 görüntüleme • 3 ay önce

Qubic #OpenScience #Neuraxon Life 2.5 (Research) version code released & and a new Hugging Face massive dataset, almost 500Gb of raw TimeSeries Game data, 10 Sessions with 270+ rounds each, in total 100K+ Nxers in 2791 games with 3.76 Million Neurons & 17M Synapses to explore in a huge 1 Billion + events. By Jose Sánchez David Vivancos - e/acc for Qubic Science: Open Data Source Code: Dataset: Paper : Stay Tunned for more releases this week!
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Qubic #OpenScience #Neuraxon Life 2.5 (Research) version code released & and a new Hugging Face massive dataset, almost 500Gb of raw TimeSeries Game data, 10 Sessions with 270+ rounds each, in total 100K+ Nxers in 2791 games with 3.76 Million Neurons & 17M Synapses to explore in a huge 1 Billion + events. By Jose Sánchez David Vivancos - e/acc for Qubic Science: Open Data Source Code: Dataset: Paper : Stay Tunned for more releases this week!

David Vivancos - e/acc

12,657 görüntüleme • 8 ay önce