Scale Highlighted in Gartner Inc.’s 2021 AI Hype Cycles

Machine Learning Papers at NeurIPS 2021

Scale Rapid

Content & Language

Determining the Sentiment of Movie Reviews with Scale Rapid

Government

Highlights from TransformX 2021: U.S. Government Sessions

Scale Text

Scale AI And Oxford University's Reddit Dataset Provides Comprehensive Online Discourse Data 

Autonomous Drones

Autonomous Checkout

Manufacturing

Transportation

Real Estate

Scale 3D Sensor Fusion

Scale Image

Scale Video

Retail & eCommerce

Autonomous Vehicles

Robotics

AR/VR

How Does Scale AI Partner with Customers to Produce High-Quality Training Data?

Scale Team Spotlight: Veterans at Scale

Faster Semantic Segmentation with Machine Learning-Assisted Workflows

7 Elements of a Well-Thought-Out AI Strategy: Salesforce COO Bret Taylor

Scale Document AI

Document Processing

Financial Services

Blend and Scale AI: Leveraging ML to Make Smart, Instant Lending Decisions

On Teaching Robots To Perform Complex Tasks with Dr. Fei-Fei Li 

Scale Nucleus

SiaSearch Acquisition: Delivering the Full Data Engine to Our Customers

Dmitri Dolgov of Waymo Discusses Data-centric AI

Eric Schmidt Discusses the Geopolitics of AI

Netflix Explains Recommendations and Personalization

HuggingFace CEO, Clement Delangue: Are Transformers Becoming the Most Impactful Tech of the Decade?

Managing 3D Sensor Fusion Data with Scenes in Scale Nucleus

Microsoft CTO Kevin Scott's Seven Insights on the Future of AI

Lambda and Scale Nucleus: Empowering Your Model Training with Better Data

Highlights From TransformX 2021 Conference

Our Commitment to Securing Customer Data: Scale + ISO 27001

Scale Rapid: Now Generally Available

Scale Synthetic

Human Annotations Remain Indispensable for Developing Deep Learning Models

Scale Audio

ML & Human Consensus: The Best of Both Worlds

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

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

Processing mission-critical logistics documents with Scale Document AI.

Flexport

“Scale’s machine learning-based Document AI is very different from traditional OCR models, or template-based learning. No templates, high quality, and low latency every time.

We rely on Scale for document processing, because with higher extraction accuracy, almost zero human labor is required afterward to correct it. With lower latency, we can enable products like air freight where document data has to arrive much faster since air shipments take less than two days.”

Enhancing Log Scaling and Inventory Management with Scale Rapid

TimberEye

“I cannot fathom a faster or easier way to achieve production-quality annotations. Rapid was like magic. We kept kicking the segmentation work to the back burner, and honestly almost abandoned it, but three days after kicking off our project with Rapid, we had all the data we needed in perfect shape."

Powering automated bill pay with Scale Document AI.

Brex

The reasons we chose Scale was one, the fine-tuned machine learning models that gave us the output in seconds. Two, the optional human-in-the-loop workflow that further increases accuracy in as little as two minutes. And three, the data compounding advantage. The more data we send, it gets better. I actually see this day-to-day. It does get better every single day, as we use it more.

Delivering a Seamless Cellar Management Solution.

CellarEye

There was one particular class where our model’s average precision was 76%. We improved average precision on that class to 87%+ after just one round of data cleaning with Nucleus.

Machine intelligence for faster and safer real estate transactions.

States Title

Scale has provided the fuel to put our machine learning systems on overdrive. They make sure the highest quality training data is there in time to meet our aggressive roadmap. Lenders and borrowers will experience faster and more efficient closings sooner as a result.

OpenAI

OpenAI threw a bunch of tasks at Scale AI with difficult characteristics, including tight latency requirements and significant ambiguity in correct answers. In response, Scale worked closely with us to adjust their QA systems to our needs.

Lyft

Scale is basically providing the ground truth for our perception systems. It’s a very, very critical piece for us to develop.

Developing safe and reliable systems with high-quality 3D training data.

Optimus Ride—3D

We really liked all the SLAs that were provided to us and the whole Scale AI team stepped up and worked with us to meet our needs.

Research and development of next-generation autonomous systems that can safely operate in a range of work environments.

Otto Motors

“We had to start from scratch on getting datasets and we needed a partner who could supply us with a steady supply of data in a domain that was quite different from what everyone else was working on."

Annotating large volumes of videos to develop advanced control technology for workboats and other commercial vessels.

Sea Machines Robotics

Since starting our partnership with Scale, our data annotation needs have evolved and changed multiple times. The team at Scale has done an excellent job responding to increases in volume and refinement to our annotation rules. 

Scaling ground-truth data with Scale AI. Classifying large volumes of images to develop an autonomous checkout system.

Standard Cognition

“It was easy to get started with Scale AI because they had the platform and the people with the skillset to perform the annotation tasks we needed.”

Scaling ground-truth perception data with Scale. Voyage works with Scale to create large volumes of sensor fusion data for their self driving cars.

Voyage

When I think about what Scale brings to the table, it comes down to machine learning expertise. Scale has a team of very talented engineers who really understand the problems in training machine learning models, of data annotation, and of data quality.

Embark works with Scale to create large volumes of sensor fusion data for their self driving trucks.

Embark

Scale makes it easy to focus on developing leading self-driving technology rather than the operations of labeling data. The Scale platform provides the technology and operations to power our machine learning development and is our trusted training data solution.

Creating large volumes of training data without sacrificing quality

Toyota

Imagine a future where mobility is truly for all. Regardless of physical faculties, age, or income, you can participate in this world because technology has progressed to enable you to move as you want.

Making drones useful

Skydio

We appreciate how the Scale AI team proactively seeks feedback and holds themselves accountable. Their QA team is careful and quick to seek clarification, and their attention to detail has produced some truly impressive results.

Scaling ground-truth data with Scale. We work to create large volumes of training data for their classification models.

Skip Scooters

Scale AI proved to be a valuable data annotation partner for our City Operations Team, providing us high quality of training and validation data that helped us significantly improve the accuracy of our image classification models.

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