Fonoa
Automating taxes for the internet economy
- Headquarters
- San Francisco, California
- Company size
- 50+
- Industry
- Computer Software
- Since
- 2018
About Us
Data curation, AI-assisted labeling, model training & diagnostics, labeling services, and intuitive APIs, all in one platform, to build better AI products, remarkably fast.
Our mission is to build the best products for humans to advance artificial intelligence.
We believe that AI has the power to transform every aspect of our lives — from healthcare to agriculture. The exponential impact of artificial intelligence will mean mammograms can happen quickly and cheaply, irrespective of the limited number of radiologists there are in the world, and growers will know the instant that disease hits their farm without even being there.
Current Jobs
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Senior Backend Engineer
In machine learning, data curation is only part of the battle to create a successful model. Once a model is trained, it…
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Senior Software Engineer
As a team, we are making our customers win if we minimize the time from where unstructured data has been introduced to…
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Remote Work Digest
Employee reviews
Twitter feed
Understanding how different models compare to each other is crucial aspect to #AI development. Learn how you can use Labelbox Model to configure, track, and compare essential model training #hyperparameters alongside #trainingdata and #datasplits. https://labelbox.com/guides/how-to-curate-and-version-your-training-datasets-and-hyperparameters/
"Model performance increased 5% when we dropped a third of the data points which Labelbox helped us identify as low quality."
Thank you @dylanbarrell and @dequesystems for sharing your #AI #dataengine story. We're proud to enable the vital #accessibility work you do.
Producing high-quality #trainingdata takes up so much time and resources that reducing the amount of data you need to train a model can help your #AI development go twice as fast. With Labelbox, you can build performant AI in half the time and with half the labeling cost.
Seamless collaboration is key to creating high-quality #trainingdata and building successful #AI solutions — but it can be a challenge for teams with many stakeholders.
Labelbox enables easy collaboration between all your team members right within our intuitive UI.
Many #AI teams lack the infrastructure to manage #datacentric workflows as they train their models. With Labelbox Model, you can easily create and version data splits and hyperparameters.
https://labelbox.com/product/model/?utm_source=twitter&utm_medium=organic_social
Knowing exactly where your model is failing is key to improving its performance in the next iteration. With Labelbox Model, #AI teams can pinpoint model errors and add similar data to the next labeling project in just minutes.
http://ow.ly/ELjT50KFQQn
Heading to #BigDataLDN later this month? Don't miss this session on improving #AI model performance with less data with a #dataengine at 12:40 pm on 22nd September. Learn more and register: https://bigdataldn.com/register
Filtering out low quality data before labeling can not only save you hours in labeling time — it will also significantly boost model performance after training. Do it in just minutes with Labelbox Catalog.
https://labelbox.com/product/catalog/?utm_source=twitter&utm_medium=organic_social
Many #AI teams integrate #activelearning techniques into their #dataengine to accelerate their model's journey into production. With Labelbox Model, teams can use their model to curate high-value data for labeling at every iteration — within minutes.
https://labelbox.com/product/model/?utm_source=twitter&utm_medium=organic_social
In August we improved Labelbox to help #ML teams accelerate #AI development across annotation, data curation, and #modeltraining workflows. Learn more about these new features in this blog post.
http://ow.ly/g6Rp50KypX2
Duplicate data delays both labeling time and #AI model progress, but finding them in large datasets is often even more time consuming. Labelbox Catalog enables teams to find duplicate data and remove them in just minutes.
Try it yourself for free.
http://ow.ly/INVF50KvS5O
Labeling errors in your training data can result in long delays and low model performance. Learn how Labelbox Model enables teams to catch errors in minutes by comparing labels to model predictions.
#AI #ML #dataengine #trainingdata #datacentricAI
http://ow.ly/pABQ50Ktznt
Does it take you hours to track down specific images in your raw #dataset? Labelbox Catalog makes the task easy by using model embeddings to search and filter their unstructured data.
#AI #ML #trainingdata #dataengine #activelearning
http://ow.ly/ZQjZ50KtrZX
This month, we made several improvements to help #ML teams accelerate #AI development across annotation, data curation, and #modeltraining workflows. Learn how to classify messages in a conversation, compare model runs, and more in this blog post.
http://ow.ly/pCrn50KsiKS
Finding the data you need among millions of assets is a challenge. That's why we built Labelbox Catalog to make it easier than ever to filter your data and narrow your search, saving you hours of manual searching and scrolling. Try it for free.
#NLP #AI
http://ow.ly/yiBF50KrAET
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FAQ
Where is Labelbox headquarters?
Labelbox headquarters is located at San Francisco, California.
When was Labelbox founded?
Labelbox was founded in 2018.
How many employees does Labelbox have?
Labelbox has 50+ employees.
What is Labelbox's core business?
Labelbox is Computer Software company.
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