Latest AI and tech news

encord.com • Oct 29 • by Encord

Computer vision · encord +1

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29003

Encord Product Updates: October 2026Product

encord.com • Oct 5 • by Encord

Computer vision · label +5

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A34F3

Label MCAP Recordings Natively in Encord (Beta)Product Updates

encord.com • Sep 17 • by Encord

AI · Robotics +6

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62554

Encord Launches Long Horizon: The Physical AI SummitCompany

encord.com • Sep 11 • by Encord

Diversity & inclusion · Robotics +7

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8F196

Why Data Diversity, Not Data Volume, Will Decide Who Wins Physical AIIndustry News

encord.com • Aug 27 • by Encord

Cloud · amazon +7

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C7060

Amazon Is Shutting Down Mechanical Turk and SageMaker Ground Truth: What It Means for Your Annotation PipelineIndustry News

encord.com • Aug 26 • by Encord

LLMs · Robotics +8

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0EEB5

Best Foundation Models for the Physical World in 2026: Cosmos, GR00T, and What's NextProduct

encord.com • Aug 24 • by Encord

Fine-tuning · Robotics +6

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F066C

Teleoperation vs. Simulation: Where Should Your Robot Training Data Actually Come From?Data Collection

encord.com • Aug 18, 08:00 PM • by Encord

Data engineering · Robotics +6

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D1D61

The Complete Physical AI Data Pipeline: From Data Collection to DeploymentData Collection

encord.com • Aug 18 • by Encord

AI · Robotics +5

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92B19

The 6 Best Data Collection Services for Robotics and Embodied AI [2026]Physical AI

encord.com • Aug 16, 08:00 PM • by Encord

Robotics · cost +5

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C7B62

Data Curation for Robotics: Finding Failure Modes Before They Cost You a DeploymentData Curation

encord.com • Aug 9, 08:00 PM • by Encord

Robotics · AI +5

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43535

What Is Teleoperation Data Collection, and Why Do Robots Need It?Physical AI

encord.com • Aug 4, 08:00 PM • by Encord

Automation · Geospatial & GIS +9

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0F3E3

LiDAR Annotation for Robotics: Challenges, Workflows, and Tools for 2026Data Annotation

encord.com • Aug 3, 08:00 PM • by Encord

Robotics · AI +6

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BAEF1

What Are World Models? A Guide to AI's Next Leap in Physical ReasoningPhysical AI

encord.com • Aug 3, 08:00 PM • by Encord

Computer vision · Geospatial & GIS +8

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E550D

Smart city computer vision: A practical guide to training dataSmart cities

encord.com • Jul 29, 08:00 PM • by Encord

Robotics · AI +7

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B5574

How to Build Diverse Egocentric Datasets for Robotics: A Practical GuidePhysical AI

encord.com • Jul 28, 08:00 PM • by Encord

Robotics · Industrial & IoT +8

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D4989

Sensor Fusion Data Annotation: How to Label Multi-Sensor Robotics DataData Annotation

encord.com • Jul 27, 08:00 PM • by Encord

Autonomous vehicles · Computer vision +6

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4D339

Full Guide to Building an Autonomous Vehicle Training DatasetData Annotation

encord.com • Jul 22, 08:00 PM • by Encord

Computer vision · annotation +7

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Bounding Box vs. Polygon vs. Segmentation vs. Keypoint: Which Annotation Type Fits Your Task?Image Annotation

encord.com • Jul 17, 12:55 PM • by Encord

AI · Healthcare +9

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B18EB

FDA's New Predetermined Change Control Plan Rule for Radiological AI Software, ExplainedHealthcare

encord.com • Jul 17, 05:04 AM • by Encord

AI · Evals +8

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BA8F4

The Eval Stack the Top AI Teams Are Building Right Now [Webinar Recap]Model Evaluation

encord.com • Jul 14, 08:00 PM • by Encord

Autonomous vehicles · Computer vision +8

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705FD

How to annotate video for ADAS and autonomous driving: A Technical GuideSmart cities

encord.com • Jul 12, 08:00 PM • by Encord

Machine learning · Computer vision +7

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56A2B

How to annotate video for machine learning: A Step-by-Step workflowVideo Annotation

encord.com • Jul 9, 08:00 PM • by Encord

Data governance · problem +2

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FBC9D

You Don't Have a Data Problem. You Have a Curation ProblemData Curation

encord.com • Jul 9 • by Encord

Computer vision · AI +10

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D6DBA

AI Data Curation for LLM and Multimodal Teams: A Practical FrameworkData Curation

encord.com • Jul 8, 08:00 PM • by Encord

AI · Data governance +7

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9D899

Data Curation Best Practices for AI: A Step-by-Step FrameworkData Curation

encord.com • Jul 8 • by Encord

Data governance · curation +2

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82CAA

What Is Data Curation? The Complete GuideData Curation

encord.com • Jul 7, 04:26 AM • by Encord

GPUs & chips · Robotics +9

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817EC

[Webinar Recap] How NVIDIA Cosmos 3 Is Changing the Way Physical AI Teams Build Training DataAgents

encord.com • Jul 6, 08:00 PM • by Encord

AI · Machine learning +6

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3E3CE

What Is AI Data Labeling? Definition, Types and the ProcessData Annotation

encord.com • Jul 6, 08:00 PM • by Encord

Computer vision · multimodal +7

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3692B

Multimodal Data Labeling: One Pipeline for Image, Video, Audio, Text and 3DData Annotation

encord.com • Jul 5, 08:00 PM • by Encord

Data governance · framework +5

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CAA1A

Build vs buy: A decision framework for data labeling toolsData Annotation

encord.com • Jul 5, 08:00 PM • by Encord

Data governance · quality +6

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C119D

Data Labeling Quality Control: Consensus, Inter-Annotator Agreement and QA WorkflowsData Quality

encord.com • Jul 1, 08:00 PM • by Encord

Machine learning · learning +4

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D54ED

How to Label Data for Machine Learning: A Step-by-Step WorkflowMachine Learning

encord.com • Jun 16, 11:50 AM • by Encord

AI agents · layer +5

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ED612

Introducing Merlin: The Agentic Intelligence Layer for EncordAgents

encord.com • Jun 14, 08:00 PM • by Encord

Industrial & IoT · annotation +4

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D4EED

Logistics Data Labeling: the 6 best platforms and where they fit [2026]Data Annotation

encord.com • Jun 3 • by Encord

RAG · Automation +15

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Featured ArticleEncord Integrates NVIDIA Cosmos Reason and EmbedWe're excited to announce the integration of two NVIDIA Cosmos models - Cosmos Reason 2 and Embed - directly into the Encord platform. Both run natively on Encord's own infrastructure, so customers can use them in production from day one.  The Cosmos Reason agent automates prelabels on physical AI video. Cosmos Embed makes that video searchable by behaviour, not just by scene. Together, they turn raw video into structured, searchable training data. Cosmos Reason 2 in the Agents Catalog Cosmos Reason: Automated Captioning And Pre-Labelling Cosmos Reason is a vision-language world model. Given a video clip as input, it returns natural-language descriptions of the actions, objects, and scene context in the footage. Inside Encord, those descriptions arrive as prelabels attached to the right video segments. Annotators review and refine instead of starting from a blank canvas. Approved labels stream straight to the customer's training pipeline. What this means in practice: A robotics team labelling dexterous manipulation no longer hand-types every grasp or release. An AV team captioning camera footage gets a usable starting point on every clip instead of writing each one from scratch. Industrial inspection teams get descriptions of anomalies, object states, and conditions without anyone watching the full reel first. This means less time describing video, and more time improving the model. Cosmos Embed: Action-Aware Embeddings And Behaviour Search Cosmos Embed is a video embedding model. Each embedding is calculated over an eight-frame window, capturing the action that happens across those frames. That makes a video dataset searchable by behaviour, using natural-language queries. In practice, you can query for what's actually happening in a clip - not "car on a snowy road" but "car turning in a snow storm," not "highway scene" but "car overtaking another vehicle." That makes edge cases easier to find - the rare scenarios that decide whether a model ships safely. How They Work Together Robotic manipulation. Reason generates action and state descriptions for dexterous manipulation footage. Embed lets teams find the specific behaviours that need more training examples. Autonomous vehicles. Reason captions camera data at scale. Embed lets teams pull the exact driving scenarios that matter for their perception models - lane changes in rain, unprotected lefts, occluded pedestrians. Industrial inspection. Reason describes anomalies and object states in operational footage. Embed surfaces every clip where a defect occurs in a specific context. Vision-Language-Action models. Reason produces the grounded captions VLA training depends on. Embed makes the underlying dataset queryable by the behaviours those models need to learn. For more information on Encord's Physical AI suite, click here.AgentsRead article

encord.com • Jun 2 • by Encord

Cybersecurity · video +3

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580B6

The Complete Guide to Security Video Annotation

encord.com • May 26 • by Encord

Robotics · labeling +2

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4B6C4

The Complete Guide to Data Labeling for Robotics

encord.com • May 12 • by Encord

Geospatial & GIS · Computer vision +8

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DAC45

Annotate inconsistent real-world road images for smart cities (Vialytics case study)Smart cities

encord.com • Apr 30 • by Encord

Robotics · AI +7

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3BF15

Will World Models Eat Physical AI?: What We Learned from Our Physical AI Panel

encord.com • Apr 24 • by Encord

Robotics · robotic +7

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20902

What Does It Actually Take to Trust a Robot in Production? Warehouse Robotics Roundtable Recap

encord.com • Apr 15 • by Encord

Automation · Machine learning +7

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636F6

How to Automate Video Annotation for Machine Learning

encord.com • Apr 8 • by Encord

Data governance · review +2

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F035B

The Complete Guide to Data Annotation [2026 Review]Data Operations