Ulrik Stig Hansen

Ulrik Stig Hansen

Ulrik is the President & Co-Founder of Encord. Ulrik started his career in the Emerging Markets team at J.P. Morgan. Ulrik holds an M.S. in Computer Science from Imperial College London.

In his spare time, Ulrik enjoys writing ultra-low latency software applications in C++ and enjoys experimental sushi making.

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All blogs by Ulrik Stig Hansen

sampleImage_generative-ai-and-gpt4-is-overrated-long-live-old-school-ai
Machine Learning
Generative AI is overrated, long live old-school AI!

5 min

sampleImage_sam-2.1-explained
Computer Vision
SAM 2.1 Explained: Smarter Segmentation and Developer Tools For the Future

sampleImage_spirit-lm-meta-ai
Machine Learning
Spirit LM: Meta AI’s Multimodal Model for Seamless Text and Speech Generation

sampleImage_outsourcing-data-labeling-guide
Data Operations
The Full Guide to Outsourcing Data Labeling for Machine Learning

12 min

sampleImage_object-detection
Machine Learning
Object Detection: Models, Use Cases, Examples

4 min

sampleImage_how-to-start-computer-vision-startup
Machine LearningComputer Vision
How to Start a Computer Vision Startup

10 min

sampleImage_computer-vision-use-cases-insurance
Machine LearningComputer Vision
6 Use Cases for Computer Vision in Insurance

10 min

sampleImage_key-insights-from-the-inaugural-ai-after-hours
Machine Learning
Key Insights from the Inaugural AI After Hours

sampleImage_an-introduction-to-data-labelling-and-training-data
Data Operations
The Full Guide to Training Datasets for Machine Learning

10 min

sampleImage_floy-customer-interview
sampleImage_floy-customer-interview
Customers
Customer Interview: Annotating and Reviewing Medical Imaging Data with Encord

8 min

sampleImage_teton-ai-customer-story
sampleImage_teton-ai-customer-story
Customers
Automating Data Labeling for Teton.ai

3 min

sampleImage_finance-for-data-annotation-automation
Company
Startup Taps Finance Micro-models for Data Annotation Automation

3 min

sampleImage_how-we-raised-a-seed-round
Company
How We Raised a $4.5M Seed Round

7 min

sampleImage_what-the-european-ai-act-means-for-you
Learn
What the European AI Act Means for You, AI Developer [Updated December 2023]

11 min

sampleImage_visual-foundation-models-vfms-webinar
VideoMachine Learning
Webinar: Are Visual Foundation Models (VFMs) on par with SOTA?

3 min

sampleImage_why-ai-is-the-mother-of-all-unicorns
Company
Why AI Is the Mother of All Unicorns

4 min

sampleImage_ai-regulatory-compliance
Data Operations
3 Key Considerations for Regulatory Compliance in AI systems

4 min

sampleImage_ai-regulation-explained
Learn
Proposed AI Regulation: EU AI Act, UK's Pro-Innovation, US AI Bill of Rights

4 min

sampleImage_european-ai-act-learning-pack
Video
Learning Pack: The European AI Act's Impact on AI Developers

30 min

sampleImage_video-what-the-european-ai-act-means-for-ai-developers
Video
What the European AI Act Means for AI Developers

30 min

sampleImage_improve-quality-of-labeled-data-guide
Data Operations
5 Ways to Improve The Quality of Labeled Data

8 min

sampleImage_action-classification-guide
Data Operations
How to use Action Classifications In Video Annotation

8 min

sampleImage_cb-insights-ai-100-2022
Company
Encord Named to the 2022 CB Insights AI 100 List 2022

2 min

sampleImage_what-is-computer-vision
Machine Learning
What Is Computer Vision In Machine Learning

5 min

sampleImage_soc-2-compliant
Company
Encord: The SOC 2 Compliant Platform for Computer Vision

4 min

sampleImage_review-encord-g2
Company
How to Review Encord on G2

5 min

sampleImage_project-stormcloud-infrastructure
Company
Providing Computer Vision Infrastructure for Project Stormcloud

2 min

sampleImage_data-operations-guide
Data Operations
Best Practice Guide for Computer Vision Data Operations Teams

10 min

sampleImage_build-vs-build-data-annotation-guide
Data Operations
Data Annotation Tooling: Build vs. Buy: Lessons from Practitioners

4 min

sampleImage_in-house-training-data-tools-guide
Data Operations
Why You Should Ditch Your In-House Training Data Tools

5 min

sampleImage_harvard-medical-school-mgh-customer-story
sampleImage_harvard-medical-school-mgh-customer-story
Customers
How Harvard Medical School and MGH Cut Down Annotation Time and Model Errors with Encord

sampleImage_automotus-customer-story
sampleImage_automotus-customer-story
Customers
Boosting Last-mile Model Performance: Increase mAP by 20% while reducing your dataset size by 35% with intelligent visual data curation

sampleImage_four-growers-customer-story
sampleImage_four-growers-customer-story
Customers
Transforming Fruit and Vegetable Harvesting & Analytics with Computer Vision

sampleImage_viz-customer-story
sampleImage_viz-customer-story
Customers
Accelerating Diagnosis to Treatment with Encord

sampleImage_kings-college-london-customer-story
sampleImage_kings-college-london-customer-story
Customers
How King's College London used Encord to annotate videos 6.4x faster

3 min

sampleImage_sdsc-customer-story
sampleImage_sdsc-customer-story
Customers
How Surgical Data Science Collective (SDSC) Conducted Video Annotation 10x Faster

sampleImage_conxai-case-study
sampleImage_conxai-case-study
Customers
Improving Efficiency in the Construction Industry with Encord

sampleImage_vida-id-customer-story
sampleImage_vida-id-customer-story
Customers
Reducing Model False Positive Rate from 6% to 1% with Vida ID

8 min

sampleImage_treeconomy-customer-story
sampleImage_treeconomy-customer-story
Customers
Accurately Measuring Carbon Content in Forests

sampleImage_floy-customer-story
sampleImage_floy-customer-story
Customers
Floy Reduced CT & MRI Annotation Time with AI-Assisted Labeling

7 min

sampleImage_computer-vision-in-agriculture-ai
sampleImage_computer-vision-in-agriculture-ai
Customers
Saving the Honey Bees with Computer Vision

3 min

sampleImage_voxel-case-study
sampleImage_voxel-case-study
Customers
Finding a reliable ecosystem to scale model development

sampleImage_kings-college-london-customer-interview
sampleImage_kings-college-london-customer-interview
Customers
Customer Interview: Overcoming The Mental Torture of Manual Data Labelling

7 min

sampleImage_human-pose-estimation-with-tetonai
sampleImage_human-pose-estimation-with-tetonai
Customers
Using Computer Vision to Prevent Falls in Care Homes and Hospitals

7 min

sampleImage_stanford-medicine-customer-story
sampleImage_stanford-medicine-customer-story
Customers
Reducing Experiment Duration for Stanford Medicine

3 min

sampleImage_neurons-case-study
sampleImage_neurons-case-study
Customers
Accelerating the Prediction of Consumer Behaviour with Encord

sampleImage_rapid-ai-customer-story
sampleImage_rapid-ai-customer-story
Customers
Reducing MRI and CT Annotation Time by 70% for Rapid AI

5 min

sampleImage_restaurant-automation-customer-story
sampleImage_restaurant-automation-customer-story
Customers
From 37 Annotation Hours to 1 with AI-assisted Labeling

3 min

sampleImage_computer-vision-for-insurance-tractable
sampleImage_computer-vision-for-insurance-tractable
Customers
Building Computer Vision Models for Insurance with Tractable

3 min

sampleImage_sports-analytics-customer-story
sampleImage_sports-analytics-customer-story
Customers
Rapid Annotation & Flexible Ontology for a Sports Tech Startup

10 min

sampleImage_memorial-sloan-kettering-customer-story
sampleImage_memorial-sloan-kettering-customer-story
Customers
Creating Advanced Ontologies for Memorial Sloan Kettering Cancer Center

3 min

sampleImage_captur-customer-story
sampleImage_captur-customer-story
Customers
Training Computer Vision Models to Track Rented Assets

6 min