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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.
The Bay Area is the densest area in the world for high-tech job opportunities. Why else would so many people brave the sky-high real estate prices and regular wildfires to live here? I was extremely fortunate to be faced with the Bay Area’s abundance of technology jobs when I thought about possibly changing careers.
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.
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.
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.
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.
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to run on a schedule, so that we can always go to a report and see data that’s no more than fifteen minutes to an hour out of date
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.
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.
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.
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:
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.
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.
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.
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.
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.
We’re excited to be launching a bunch of new annotation types for images. Since the launch of our bounding box API, we’ve annotated millions of images with boxes to identify a host of different objects, from cars and hats to roof damage and parking lots. Scale is becoming an industry-standard tool for solving computer vision problems. We’re committed to offering developers all the tools they need.
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.