Financial Services

Manufacturing

Transportation

Retail & eCommerce

Government

Autonomous Vehicles

Robotics

Document Processing

Content & Language

Highlights From TransformX 2021 Conference

Our Commitment to Securing Customer Data: Scale + ISO 27001

Scale Rapid

Scale Rapid: Now Generally Available

Scale Image

Scale Video

Scale Synthetic

Scale 3D Sensor Fusion

Human Annotations Remain Indispensable for Developing Deep Learning Models

Scale Audio

Scale Text

ML & Human Consensus: The Best of Both Worlds

Scale Nucleus

Improving Datasets and Debugging Machine Learning Models with Scale Nucleus, Rebuilt from the Ground Up 

Our Commitment to Securing Customer Data: Scale + SOC 2 Type II and HIPAA

Scale Rapid: Fast Experimentation with Production-Quality Labels

Scale Converge: The Future of eCommerce & Retail with AI

How to Tame the Long Tail in Machine Learning

Scale AI and Research Partner MIT Media Lab Analyze Bias in Dermatological Datasets to Improve Diagnoses

Scale Mapping

Own Your Own Maps. Introducing: Scale Mapping

Scale Document AI

OCR Is Not Enough. Try Scale Document AI.

Life at Scale

Scale Collect

Doing the Data Work to Mitigate Data Cascades

Why I Joined Scale AI

 Scale AI’s Series E: Deploying AI Across Every Industry

Scale AI Named to CB Insights’ AI 100 2021 List

Scale Transform: AI Leaders Showcase Research Breakthroughs and Real-World Impact

Why I Joined Scale

Getting Started with Nucleus

Making Pytorch Transformer Twice as Fast on Sequence Generation.

Scale AI’s Series D: Expanding our Team to Empower AI Dreamers

Scaling Menu Transcription Tasks with Scale Document

Scale Hackathon

Quick Start Guide to Customized API Documentation

Scale AI Machine Learning Digest - Q3 2020

Introducing: Our New API Docs

Reaffirming Our Commitment to Building Customer Trust: Scale + SOC 2

Welcoming Brad Porter to Scale AI as our first CTO

Discovering Useful Sentence Representations from Large Pre-Trained Language Models

If You’re De-Biasing The Model, It’s Too Late

Introducing: Scale Nucleus

Keeping The Team Close While Distancing

Introducing: PandaSet. The world's most advanced LiDAR dataset for commercial use

How we Scale Machine Learning

Now Available: Scale Document

Introducing a New Look for Scale AI Products

Scale AI Machine Learning Digest - Q1 2020

Supporting researchers and our community during COVID-19

Open Sourcing the World's First AV Dataset for Wintry Environments

How to Label 1M Data Points/Week

Scale AI Selected as One of America's Most Promising AI Companies

Scale AI Selected as One of LinkedIn’s 2019 Top Startups in the U.S.

Is Elon Wrong About LiDAR?

Scale AI’s Series C: Building the data platform to accelerate machine learning

Introducing Point Cloud Segmentation

Positive Externalities: Life of a Labeler

Training Data - Quantity is no Panacea

Scale Engineering, Product and Design Teams

nuScenes by Aptiv ImageNet for Autonomous Vehicles

Announcing the Scale and Ouster Data Integration Partnership

Metadata to Enrich Image Annotations

Introducing AI-Assisted Semantic Segmentation at Scale

How We Made It Easy for Anyone at Our Company to Trigger Alerts

Announcing Our Series B with Index Ventures and Accel

Adding a Dimension: Annotating 3d Objects with 2d Data

How to make MongoDB not suck for analytics

Scale Engineering Team++

Introducing Teams

Introducing Our New Dashboard

Increasing the Performance of Dynamic Next.JS Websites

Guest Post: Cloudinary Uses Scale to Focus on Image Compression

Announcing Our Series A With Accel

Training Data For Self Driving Cars With Scale

David Garber

Toyota

Oliver Cameron

Voyage

Brandon Moak

Embark

Anantha Kancherla

Lyft

Geoffrey Irving

OpenAI

Rachel Basse

Skydio

Greg Stewart

Skip

Jonathan Hirokawa

Sea Machines Robotics

Virginia Puccio

Standard Cognition

Nolan Lunscher

Otto Motors

Michaela Mann

Optimus Ride

Andy Mahdavi 

States Title

Argo

A2D2

Semantic KITTI

nuScenes

PandaSet

DAVIS

CamVid

DBNet

Comma.ai

Berkeley DeepDrive

HCI Challenging Stereo

Caltech Pedestrian

Bosch Small Traffic Lights

Elektra

KAIST Urban

Ford

ApolloScape

KAIST Multi-Spectral

Belgium Traffic Sign

LostAndFound

Daimler Pedestrian

CityScapes

German Traffic Sign

Dr(eye)ve

CULane

HD1K

KITTI

DIPLECS

ETH Pedestrian

Apollo Open Platform

EISATS

JAAD

Malaga

Mapillary Vistas

NEXET

Oxford RobotCar

Road Damage

Stixel

TME Motorway

TuSimple

Udacity

Multi-Cue Onboard Pedestrian Detection

The Boxy Dataset

Stanford Track

LISA Traffic Sign

Highway Workzones

Brain4Cars

Unsupervised Llamas

Using Deep Learning to Detect Abusive Sequences of Member Activity on LinkedIn

Monitoring and Quality Assurance of Complex ML Deployments via Assertions - with Daniel Kang from the Stanford Dawn Lab

Join Scale AI for our two-day, virtual conference. We’re bringing together a community of leaders, visionaries, practitioners, and researchers across industries as we explore the shift from research to reality within AI and Machine Learning.

Scale Transform X | Scale AI Conference

Using Scale Nucleus and Rapid to Label New Datasets Efficiently

What's New: Computer Vision, Fall 2021

AR/VR

Autonomous Drones

Autonomous Checkout

Compliance

Food & Beverage

Forestry

Inventory

Real Estate

Scale Rapid is our new and improved On-Demand offering with usability enhancements to help research and experimental projects off the ground in even less time than before.

The Learning Curve: Scale Rapid

Scale Mapping is our latest solution to help customers develop and scale their own custom maps. In this tech talk, we discuss the technical and operational challenges inherent in scaling HD maps and share how we scale mapping for our customers.

The Learning Curve: Scale Mapping 

The Learning Curve: Technical Integrations with Zenseact

Scale AI’s conference on June 24th. The latest advances in AI and ML for eCommerce and retail marketplaces.

Scale Converge | Scale AI Conference

The Learning Curve: Scaling Up Document Processing 

The Learning Curve: Model-in-the-Loop Data Curation

Scale's Field Engineering team presents their work to improve the customer developer experience with the Scale API. Specifically, we cover our new Python SDK, a new data pipeline starter kit, Scale's interactive documentation, and Scale's Lidar Toolkit.

The Learning Curve: Focusing on the Developer Experience

Collision Conference: Building Trust in AI

Scale AI's conference brings leading researchers and practitioners together to share the latest advances in AI and machine learning.

Scale Transform | Scale AI Conference

MITTR - EmTech Digital: Data is the New Code

The Learning Curve: What's New in Scale AI's Computer Vision APIs

The Learning Curve: Scaling Data Labeling with Machine Learning

The Learning Curve: Fireside Chat with Emily Denton

NeurIPS 2020

The Learning Curve: Fireside Chat with Dr. Yisong Yue

The Learning Curve: Applying Game Rating Systems to Data Labeling

Fireside Chat with Alexandr Wang

Debugging Model Performance with Scale Nucleus

The Learning Curve: Debugging Model Performance with Scale Nucleus

Grab some grub and learn how the Microsoft Teams Team is enhancing active speaker detection and noise detection models with Scale AI.

The Learning Curve: Tech Talk with Scale AI

How to train Humans-in-the-Loop who don’t perform gradient descent.

The Learning Curve: Humans-in-the-Loop Don't Perform Gradient Descent

Join the discussions with other leaders in AI over dinner at Eleven Madision Park

NYC Leaders in AI Dinner 

Products

Solutions

Resources

Company

Resources

Using Deep Learning to Detect Abusive Sequences of Member Activity on LinkedIn

Product

Scale Rapid: Now Generally Available

Using Deep Learning to Detect Abusive Sequences of Member Activity on LinkedIn

Monitoring and Quality Assurance of Complex ML Deployments via Assertions - with Daniel Kang from the Stanford Dawn Lab

General

Highlights From TransformX 2021 Conference

General

Our Commitment to Securing Customer Data: Scale + ISO 27001

Scale Transform X | Scale AI Conference

Product

Scale Rapid: Now Generally Available

Engineering

Human Annotations Remain Indispensable for Developing Deep Learning Models

Using Scale Nucleus and Rapid to Label New Datasets Efficiently

Using Scale Nucleus and Rapid to Label New Datasets Efficiently

Using Deep Learning to Detect Abusive Sequences of Member Activity on LinkedIn

Monitoring and Quality Assurance of Complex ML Deployments via Assertions - with Daniel Kang from the Stanford Dawn Lab

General

Highlights From TransformX 2021 Conference

General

Our Commitment to Securing Customer Data: Scale + ISO 27001

Scale Transform X | Scale AI Conference

Product

Scale Rapid: Now Generally Available

Engineering

Human Annotations Remain Indispensable for Developing Deep Learning Models

Using Scale Nucleus and Rapid to Label New Datasets Efficiently

Using Scale Nucleus and Rapid to Label New Datasets Efficiently