AI tools for your work
Limited betaChoose an AI tool by starting with the task you want to complete. usedby connects work areas and tasks to tool categories, with public examples to examine.
Your role is not listed? Describe the task you want to do.
Train and evaluate models
These results show public use in this category. They do not establish use by your profession or suitability for this exact task. Your requirements have not been evaluated.
Category, industry and company size
Company size describes the employer. It does not establish access for a solo practitioner.
ML platforms & training data
297 companies, 12 tools
About these numbers
Counts cover companies recorded on usedby. They are not market shares. All four proof levels count. Missing size data is excluded only from size-based views. Your requirements have not been evaluated.
Companies with known size: 63%. Vendor companies excluded from this category: 1.
Weights & Biases
58 companies
36 confirmed22 observed
Meta's AI research team provides baseline learning curves in Weights & Biases for the experiments that accompany its MiniHack open-source reinforcement learning framework.
Original source text
We also provide baseline learning curves in Weights & Biases for our experiments.
Meta · Read the source 
H2O.ai
53 companies
37 confirmed16 observed
Tech Mahindra uses H2O Driverless AI to predict whether a truck roll is needed at a customer's premises.
Original source text
Tech Mahindra uses H2O Driverless AI to predict whether a truck roll is needed at customer premises, delivering quick ROI through a three-step POC process.
Tech Mahindra · Read the source 
Hugging Face
42 companies
4 confirmed35 observed3 signals
Labelbox
29 companies
19 confirmed10 observed
Intuitive Surgical's data science team uses Labelbox to label surgical videos frame by frame for detecting and tracking instruments, with model-assisted workflows and a shared ontology across clinical and data science teams to train its computer vision models.
Original source text
The team scaled signal throughput, lowered the overhead of gathering performance and quality metrics, and doubled the speed at which they deliver training signal for their multiple ML models.
Intuitive · Read the source
