Company Updates & Technology Articles
The Scale AI team hosted its first ever Hackathon last month. The hackathon was designed to: Encourage innovative thinking to solve some of Scale’s biggest challenges. Prototype and potentially launch impactful projects that make Scale better in practice. Facilitate long-term cross-functional relationships. 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 we continue to develop our ambitious roadmap to accelerate the development of AI, I’m delighted to welcome Brad Porter—formerly Amazon’s VP and Distinguished Engineer of Robotics—as our first CTO.
Aug 31st, 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 3rd, 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 has officially expanded into Europe with a new office in Munich! I’d like to take this opportunity to have the Scale EMEA team introduce themselves, talk a little about why each of us joined, and provide a way to get in touch.
Jul 26th, 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 4th, 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 —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
When I first joined Scale, we just offered 2D annotation products. A few of our self-driving customers mentioned off-hand that they would also potentially use a 3D annotation product. After roughly sizing the market and contemplating the trade-offs, we decided to build a minimum viable product to see if this additional business was a good direction for the company.
Feb 12th, 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
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
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
We recently worked with the team at Cloudinary to help build and evaluate a better image compression and quality measurements. The results of Cloudinary’s work on Scale were very insightful and we wanted to share it broadly to demonstrate how more companies can leverage human judgments to build high quality features.
Aug 25th, 2017
We are excited to announce that we have raised a $4.5 million Series A round of funding led by Accel. Along with this funding, Accel’s Daniel Levine has joined Scale’s board. The funding will be used to invest in our rapid growth, expand our offerings, and grow our team.
Jul 16th, 2017
One of the largest automobile companies in the world uses Scale to help build self-driving cars. Self-driving cars (SDCs) are one of the most exciting technologies being developed today. If they become a reality, the benefits that come will significantly impact our lives in several ways.
Jan 16th, 2017
