Company
Scale partners with Deloitte to accelerate AI adoption across the U.S. government
With this partnership, Scale will provide services focused on data management, AI modeling and innovative development to all federal agencies
Jun 28th, 2022
Scale RapidThe fastest way to production-quality labels.
Scale StudioLabeling infrastructure for your workforce.
Scale 3D Sensor FusionAdvanced annotations for LiDAR + RADAR data.
Scale ImageComprehensive annotations for images.
Scale VideoScalable annotations for video data.
Scale TextSophisticated annotations for text-based data.
Scale AudioAudio Annotation and Speech Annotation for NLP.
Scale MappingThe flexible solution to develop your own maps.
Scale NucleusThe mission control for your data
Scale ValidateCompare and understand your models
Scale LaunchShip and track your models in production
Scale Document AITemplate-free ML document processing
Scale Content UnderstandingManage content for better user experiences
Scale SyntheticGenerate synthetic data
Company Updates & Technology Articles
With this partnership, Scale will provide services focused on data management, AI modeling and innovative development to all federal agencies
Jun 28th, 2022
Dennis will be leading Finance, Accounting, Corporate Development, and Strategic Partnerships
Jun 14th, 2022
Every year since 1995, a pink triangle has been constructed at the top of Twin Peaks in San Francisco during the month of June for Pride.
Jun 6th, 2022
As Memorial Day nears, Scale U.S. Army veteran Jacob Sheehan shares his experiences with the costs of war
May 27th, 2022
Scale engineer Sasha Harrison details her experience building ML products at Scale, and what she has learned.
May 19th, 2022
We show that using Adaptive ML models to catch common errors meaningfully improves metrics for our customers.
May 9th, 2022
Scale Operations leader Willow Primack shares her personal experience for International Transgender Day of Visibility.
Mar 31st, 2022
Scale recently sponsored Treehacks, Stanford University’s annual hackathon. In this blog, we discuss how to use Scale Rapid for a successful machine learning (ML) hackathon.
Mar 30th, 2022
At Scale AI, we are always looking to find ways to leverage ML to deliver the best results for our customers. In this blog post, we discuss the importance of understanding operational and business context to ship ML systems that work.
Mar 28th, 2022
In our latest blog, we explore how to implement transfer learning for object detection using Scale Rapid.
Mar 22nd, 2022
Bon Strout shares what he learned in his experience at Scale as a Shift Venture Fellow.
Mar 14th, 2022
Scale board member William Hockey details why he believes AI/ML has the fundamental ability to restructure the way that systems and businesses are built.
Mar 9th, 2022
Starting today, Scale will be providing a series of AI-Ready datasets that algorithm developers can use to rapidly train and deploy AI in support of Ukrainian and NATO operations. By providing these datasets at no cost to national security practitioners, we hope to support a diplomatic solution and swift end to this conflict.
Mar 7th, 2022
In this blog, we explore using CycleGAN to anime-fy images with Scale Rapid.
Feb 15th, 2022
Don’t trust your dataset just because everybody else does. Learn how to use Scale Nucleus with Rapid to improve your dataset strategically, only sending problematic and business-relevant images to be labeled.
Feb 14th, 2022
Even "intelligent" OCR falls short of new ML-based approaches to whole-document extraction, where artificial intelligence models perform context-aware, accurate extraction from messy documents.
Feb 10th, 2022
Scale Synthetic is the most efficient way to enhance ML performance with synthetic data that complements real-world datasets. Talk to us to participate in our Early Access program.
Feb 2nd, 2022
Scale’s Field Engineering is a global team of creative engineers who collaborate with clients to understand their challenges and architect solutions. Learn more about what a day in the life of a Field Engineer at Scale looks like.
Jan 24th, 2022
In an exciting announcement to close out the year, Scale has been featured in two of Gartner, Inc.’s 2021 Hype Cycles. We are honored to have been featured in Hype Cycles for both Artificial Intelligence and Data Science and Machine Learning.
Dec 21st, 2021
The ML team at Scale is proud to contribute to the field of machine learning (ML) through its own research and partnerships with leading Universities such as Oxford University. Read on for an overview of the three papers accepted to NeurIPS 2021.
Dec 8th, 2021
In early October, we hosted our second virtual conference: TransformX. Catch up on some key insights and takeaways that the foremost government leaders have on the future of AI.
Nov 30th, 2021
Scale AI And Oxford University's Reddit dataset provides comprehensive, realistic online discourse data to pave the way to train socially aware language models.
Nov 22nd, 2021
To move fast, we align with our customers early. We strive to understand what our customers ask for and why, so that we can use the best combination of product and operational expertise to label their data with high quality - with their ML goals in mind.
Nov 16th, 2021
As we prepare to celebrate Veterans Day, we wanted to share some of our Scale veterans’ stories to honor them and their commitment to our country, and to also offer advice for those navigating the transition from service to civilian life.
Nov 10th, 2021
This blog post introduces Autosegment, an ML-powered tool that can segment instances within a human-provided box. We have found that we can delegate high-level reasoning to Taskers (the labelers on our platform) and leave basic semantic segmentation to an ML model. This division of labor allowed us to build a 30% faster generalizable and accurate ML labeling tool through a conceptually simple implementation.
Nov 9th, 2021
In his talk at the Scale TransformX 2021 conference, Taylor discussed the key considerations that businesses of all sizes should keep in mind to ensure that they delight their customers and achieve sustainable business outcomes.
Nov 8th, 2021
Today we’re thrilled to announce a new partnership with Blend, a leading fintech company that is re-architecting banking software around the consumer. Through this partnership, we’re bringing the most advanced machine learning capabilities to Blend’s mortgage loan process, enabling easier and faster lending decisions for home buyers.
Nov 5th, 2021
In this TransformX session, Dr. Li shares how vision is critical for first perceiving the physical world and then interacting with it. She explores how recent advances in AI research help machines perceive the environment around them and then engage with it, to perform both short-horizon and long-horizon tasks.
Nov 4th, 2021
Today we're annoucing the acquisistion of SiaSearch to further enhance data management for Scale Nucleus.
Nov 3rd, 2021
‘We like to say that we are not building a vehicle, we are building a driver’, says Dmitri Dolgov co-CEO of Waymo. He sat down with Scale CEO Alexandr Wang to discuss Waymo’s approach to a complex machine learning problem.
Nov 3rd, 2021
Eric Schmidt, a co-founder of Schmidt Futures and a former CEO of Google, discusses how AI will shape our global future. Eric joined Scale AI CEO Alexandr Wang in this fireside chat at TransformX.
Oct 28th, 2021
In this TransformX session, Justin Basilico, Director of Machine Learning and Recommender Systems at Netflix describes how ‘everything at Netflix is a recommendation’. He explores recent trends in recommendations and how they are applied for each of Netflix's 200 million users.
Oct 22nd, 2021
In this TransformX session, Clement describes the pervasiveness and capabilities of Transformers. He explores how we might ensure they are used in an ethical and transparent manner.
Oct 21st, 2021
Following on the announcement of Scale Nucleus, rebuilt from the ground up, Nucleus now supports 3D LiDAR point cloud data using the Scenes paradigm to keep data from multiple sensors organized and manageable.
Oct 20th, 2021
In this TransformX session, Kevin Scott, CTO of Microsoft joined Scale AI CEO Alexandr Wang to discuss the most impactful recent advances in AI and how we can enable a new wave of innovation by democratizing AI for the benefit of everyone in society.
Oct 19th, 2021
That's a wrap for TransformX 2021 Conference! Over 23,000 registrants attended 60 sessions from 100 of the world's top leaders, researchers, and practitioners of AI and Machine Learning. Here are the top highlights from some of our favorite sessions.
Oct 15th, 2021
We take the trust of our customers and the security of their data seriously, and today, we are proud to announce the availability of our ISO 27001 certificate.
Oct 12th, 2021
Scale Rapid is the fastest way to production-level quality labels, with no data minimums. Scale Rapid is now Generally Available.
Oct 6th, 2021
Research conducted by Scale AI's ML team has found that human annotations remain indispensable for deep learning models. Learn about our team's latest research paper.
Oct 4th, 2021
Achieving high-quality training data in taxonomy categorization is a major challenge. In this blog, we discuss how we leverage a Human + ML consensus pipelines to enhance taxonomy categorization.
Sep 27th, 2021
Nucleus, rebuilt from the ground up, makes it even easier to assess data quality, identify edge cases, and automatically categorize and tag objects in your training dataset for labeling.
Sep 13th, 2021
We take the trust of our customers and the security of their data seriously, and today, we are proud to announce the availability of our System and Organizational Controls (SOC) 2 Type II report, and the achievement of HIPAA compliance.
Sep 1st, 2021
Scale Rapid is the fastest way to production-quality labels with no data minimums, all with full control.
Jul 19th, 2021
Last week we hosted Scale Converge, to showcase the latest advances in AI and ML for eCommerce and online marketplaces. We brought together technical leaders to hear from the people and companies leading the eCommerce and retail industry forward. It was an event full of thoughtful conversations that examined the advancements made, the challenges that still lie ahead, and what we can expect in the years to come.
Jun 30th, 2021
It is often difficult and costly to achieve strong performance on the rare edge cases that make up the long tail of data distribution. In this blog post, we’ll take a deeper look at how sophisticated data curation tools can help machine learning teams target their experiments toward taming the long tail.
Jun 29th, 2021
Recent studies demonstrate computer vision models can serve as a useful decision support tool in healthcare but darker skin is underrepresented in datasets. The lack of consideration has been shown to lead neural networks to produce large accuracy disparities. This research sought to determine if adding Fitzpatrick labels would allow researchers to assess algorithmic fairness to ensure better performance.
Jun 23rd, 2021
Scale Mapping provides customers with the most flexible, scalable, and transparent mapping solution. With Scale Mapping, customers can generate high precision maps for simulations and real-world testing, enhance prediction and motion planning by effectively predicting another agent’s intent, train perception models to live detect map features, and improve navigation and route planning to maximize efficiency.
Jun 21st, 2021
Scale Document AI is the next-generation approach for intelligent document processing. Its latest capability, Adaptive AI, deploys refined machine learning models for customers who demand high quality and low latency at scale when it comes to document processing.
Jun 17th, 2021
I strongly believe in our mission to democratize and accelerate the development of AI. What excites me is that we're solving problems that are new, that other companies haven't solved before. We're tackling issues that are going to be more and more important as AI becomes more and more prevalent.
Jun 9th, 2021
Scale AI was founded on the belief that better data → better AI. In this blog, we aim to outline the downstream impacts of "bad" data and how Scale aims to mitigate these impacts.
Jun 7th, 2021
I cannot express how excited I am to join the team at Scale AI. To understand why, one needs to look no farther than my background. Over the past 33 years, I’ve dedicated my career to serving our country, keeping our citizens safe, and improving the technology our warfighters and analysts use to protect us. I’ve seen first-hand how artificial intelligence (AI) already has and will continue to change our world.
May 24th, 2021
We’re happy to share that Scale has raised $325 million in Series E funding, co-led by Dragoneer, Greenoaks Capital, and Tiger Global. Additional new investors in the round include Wellington Management and Durable Capital followed by existing investors Coatue, Index, Founders Fund, and YC.
Apr 13th, 2021
Scale AI has been named to [CB Insights’ AI 100](https://www.cbinsights.com/research/report/artificial-intelligence-top-startups/) 2021 ranking of the most innovative private AI startups – highlighting our leading data annotation services.
Apr 7th, 2021
Today we hosted our inaugural conference, Scale Transform, to showcase the state of AI today, from the latest research breakthroughs to the real-world impact across industries. It was a day full of thoughtful conversations and presentations that examined the strides made in advancing these core resources, the challenges that still lie ahead, and what we can expect in the years to come.
Mar 26th, 2021
The most impactful technology trends often start with infrastructure buildout. As an early employee of Twilio, I had the opportunity to shape their history. I am thrilled to join Scale as the Chief Revenue Officer to to shape, mold and build the future of Scale.
Mar 2nd, 2021
An introduction to Scale Nucleus, a dataset management tool that helps machine learning teams improve their models by improving their data. In this article, we show how Nucleus can help debug model failures, trace them back to dataset issues, and make it easy to prioritize which data to label next.
Feb 10th, 2021
At Scale AI, we use Machine Learning models in a wide range of applications to improve the quality of our annotations. In this blog, we discuss some tricks to drastically improve PyTorch Transformer implementation in just a few lines of code.
Dec 17th, 2020
Today we are excited to share several key updates that build on Scale AI’s mission to accelerate the development of AI. Scale has raised $155M in Series D funding at a valuation north of $3.5B led by Tiger Global.
Dec 1st, 2020
How Scale AI combined partial automation with human quality control in our Scale Document labeling pipeline to make menu processing and restaurant onboarding faster and smoother.
Nov 16th, 2020
The Scale AI team hosted its first ever Hackathon last month. The hackathon was designed to: 1. Encourage innovative thinking to solve some of Scale’s biggest challenges. 2. Prototype and potentially launch impactful projects that make Scale better in practice. 3. Facilitate long-term cross-functional relationships. 4. Give all Scaliens a creative break from their daily work.
Oct 28th, 2020
Following up on the launch of our new API docs, this post provides further details on how we implemented our docs with Next.JS, Tailwind CSS, and ReadMe.
Oct 20th, 2020
Machine learning is a field of study with tremendous strides being made through active academic research. The machine learning team at Scale AI regularly hosts reading groups to discuss papers they find interesting. In this blog post, we go over the papers the team has read throughout the quarter and provide insights on how a paper influenced our own work here at Scale AI when relevant.
Oct 7th, 2020
The latest update to our API documentation provides a better user experience and more consistent experience between our API documentation and the rest of our platform.
Sep 16th, 2020
At Scale AI, we take the trust of our customers and the security of their data seriously. We are pleased to reaffirm our commitment to building customer trust with the availability of our SOC 2 report.
Sep 14th, 2020
As our AI/ML team continues to grow, we aim to contribute to the broader research community by conducting and publishing cutting edge research. In this blog post, we spotlight a research paper we submitted on learning useful sentence representations from large transformer-based language models.
Aug 20th, 2020
Unless machine models are trained on representative data, they can develop serious biases, significantly harming underrepresented groups and leading to ineffective products. In this blog post, we investigated the CoNLL-2003 dataset—a standard for building algorithms that recognize named entities in text—and found that the data is highly skewed toward male names. Read on to find out how we mitigated this bias.
Aug 18th, 2020
Our latest product offering provides advanced tooling for understanding, visualizing, curating, and collaborating on your data – allowing teams to build better ML models via a powerful interface and APIs.
Aug 5th, 2020
Fostering connection when everyone is remote is tricky. Shelter-in-place restrictions pose new challenges that inspired our people team to think of creative ways to keep the team connected. In this blog, we highlight and share our social connection initiatives.
Jul 1st, 2020
We are proud to introduce PandaSet: a new open-source dataset for training machine learning (ML) models for autonomous driving released in partnership with the LiDAR manufacturer Hesai.
May 20th, 2020
In this blog, we discuss how Scale AI uses machine learning (ML) to supercharge its data annotation pipeline, enumerate some of the technical challenges, and describe our approach to create scalable ML solutions.
May 18th, 2020
Our latest product offering is capable of supporting a range of inputs from PDFs, Microsoft Word Documents, JPEGs and more. Scale Document builds on the previously released Scale Text product to better support customers with document processing and understanding use cases.
Apr 22nd, 2020
We have expanded our data annotation products over the years to support an increasing range of data inputs and annotation types. As our data annotation products grew, it became clear that we needed a better way to group and name our products. We invite you to explore our updated product line up.
Apr 20th, 2020
Machine learning is a field of study with tremendous strides being made through active academic research. The machine learning team at Scale AI regularly hosts reading groups to discuss papers they find interesting. In this blog post, we go over the papers the team has read throughout the quarter and provide insights on how a paper influenced our own work here at Scale AI when relevant.
Apr 6th, 2020
As the COVID-19 pandemic continues to spread, it affects all of our communities in different ways. The health and safety of Scale’s employees, as well as our global community of labelers, is a critical matter and a responsibility we do not take lightly. We also want Scale to make a contribution to combating this disease if we can.
Mar 17th, 2020
In partnership with researchers from the University of Toronto and University of Waterloo, Scale AI is pleased to announce the release of the Canadian Adverse Driving Conditions (CADC) dataset. The CADC dataset is the first of its kind to advance perception under winter driving conditions.
Feb 3rd, 2020
How do you scalably maintain the quality of labels, without having labelers check each other’s work? Take a deep dive into how we solved this problem while working with OpenAI on fine tuning their GPT-2 model.
Nov 12th, 2019
Scale AI is pleased to be selected as one of America's Most Promising Artificial Intelligence Companies by Forbes.
Sep 17th, 2019
Scale AI is pleased to be selected as one of LinkedIn’s 2019 Top Startups in the U.S. Read on to find out the top three reasons you should join Scale AI.
Sep 4th, 2019
Elon Musk recently took a high-profile swipe at LiDAR technology, predicting that "anyone relying on LiDAR is doomed" and that the only hardware Tesla needs is the existing suite of cameras and sensors installed on their vehicles. As leaders in data annotation or data labeling for autonomous driving companies, we compared training data from both camera and LiDAR to figure out how well each system will work.
Aug 12th, 2019
Our mission at Scale is to accelerate the development of AI applications. We’re proud of what we’ve built over the last three years, and today we’re announcing our Series C funding round to support our continued work against that mission.
Aug 5th, 2019
Scale AI is pleased to announce the launch of Sensor Fusion Segmentation - Scale’s endpoint for point cloud segmentation.
Jun 24th, 2019
At Scale, we contract a lot of people from all over the world as labelers. We've believed for a while that creating jobs like this can be very impactful — so we asked some of our labelers for times when working for Scale made a positive difference in their lives.
Jun 5th, 2019
Deep Learning models have the capacity to get better with more data seemingly without limit. To get a well-functioning model, however, it is not enough to just have large amounts of data, you also need high quality data annotation.
May 1st, 2019
We’ve had an incredible group of people join Scale—and we’re still hiring! We wanted to take a moment to call out some of the recent team members who have joined Scale.
Apr 29th, 2019
Scale AI is pleased to announce the full release of [nuScenes by Aptiv](https://www.nuscenes.org) —a large-scale open source dataset for autonomous driving. Scale AI was involved as Aptiv's data labeling partner on this initiative.
Mar 29th, 2019
Scale is committed to accelerating the development of AI applications and serving customers with high-speed, accurate, and affordable data annotation. As part of this mission, Scale and Ouster are pleased to announce a data integration partnership that makes it significantly easier and faster for Ouster customers to send their LiDAR data to the Scale platform for annotation.
Dec 4th, 2018
At Scale, we pride ourselves in developing superior tooling and implementing forward-looking solutions for problems our customers on the cutting edge of computer vision, including self-driving cars, AR/VR, and drones encounter. For example, our 2D image annotation endpoints now support both __per-annotation attributes__ and __label hierarchies__, allowing you to get richer labeled data out of Scale.
Oct 15th, 2018
In the grand scheme of things, most decisions that we make in life are fairly inconsequential. What to eat for lunch, where to get a haircut, which route to take to work… while there’s a small chance each choice has a dramatic impact - maybe you meet your soulmate on the bus - it most likely won’t.
Sep 18th, 2018
At Scale, we are excited to help you solve your most challenging computer vision problems. One important and well-studied problem within computer vision is that of semantic segmentation, which aims to understand images at the pixel level.
Aug 22nd, 2018
Scale relies on Mode Analytics for internal SQL and Python based reporting and analytics, helping power our operations, insights and business decisions. Many of these reports we set to run on a schedule, so that we can always go to a report and see data that’s no more than fifteen minutes to an hour out of date
Aug 20th, 2018
We have exciting news to share today! Scale raised $18M in Series B funding led by Index Ventures with Accel, Y Combinator, Drew Houston, and Justin Kan joining. Mike Volpi of Index Ventures will be joining our board. Scale has come a long way from the dorms at MIT, and we still have a long way to go.
Aug 8th, 2018
Here at Scale, one of the image annotation services we offer is Cuboid Annotation, which annotates your two-dimensional images with projections of cuboids enclosing objects such as cars, trucks, pedestrians, traffic cones, you name it.
Jul 31st, 2018
Scale partners with Lambda to ensure that our customers have access to industry-leading model training infrastructure. Lambda's engineering team explains how to upload a public dataset to Nucleus, curate and augment the dataset, and then train a pedestrian detection model on a Lambda workstation.
Oct 19th, 2021
TLDR: Row stores are fast to write but slow to read. Column stores are fast to read but slow to write. Load data from Mongo into Parquet files for fast querying using AWS Athena.
Jun 26th, 2018
We’ve had an incredible group of people join Scale—and we’re still hiring! We wanted to take a moment to call out the amazing engineering team at Scale:
Jun 9th, 2018
In this blog, we put Scale Rapid to the test by annotating the public IMDB movie review dataset and creating a model that can accurately determine the sentiment of new movie reviews.
Dec 7th, 2021
Scale AI welcomes our new Synthetic team leadership, Joel Kronander and Vivek Muppalla.
Feb 7th, 2022
You can now be a part of a team on Scale! Until recently, only the original creator of a task could access its history, visually inspect responses, and provide direct feedback on quality. It was a hurdle to our users getting the fullest possible value out of our platform.
Apr 3rd, 2018
Today we are happy to announce a new version of our customer dashboard! We’ve cleaned up the dashboard so it’s faster and more efficient for you to use.
Nov 11th, 2017
One of the most obvious signs that a site is made with Next.JS is that you load the page, you click a link to another section and it loads instantly. That’s because when a page is loaded, Next.JS will download in the background all the other pages linked with tags.
Nov 6th, 2017