A complete solution for your training data problem with fast labeling tools, human workforce, data management, a powerful API and automation features.
No Motion Firefox videos yet. You could help us improve this page by suggesting one.
Service goes down often. Very slow team. Slow support.
Based on our record, Motion Firefox should be more popular than Labelbox. It has been mentiond 15 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Motion is what your are looking for. https://usemotion.com Disclaimer: I worked there for a bit. - Source: Hacker News / 12 months ago
I use this AI productivity app called "Motion" (usemotion.com). It requires google maps or outlook. I really can't stand that but it's been so helpful for me, I still use google calendar as my main calendar. Source: about 1 year ago
I’m curious to hear more about your experience. I don’t work closely with other people, but I use Motion, which has features specifically for teams to automatically rearrange their 1:1s and tasks based on each other’s availability. Source: over 1 year ago
RE specific products: I'm curious about usemotion.com and https://www.getinflow.io/. Source: over 1 year ago
Motion (usemotion.com) keeps advertising to me and as far as I can tell, it offers one really nice feature which is the ability to have events with concrete durations but times that aren't set in stone so the calendar can automatically move them for you. This seems really interesting to me and I'd be interested in trying it, but much like with Superhuman for email, I just can't justify the price. $34/mo or $240/yr... Source: over 1 year ago
Labelbox | Remote | Frontend / WebGL, Backend, Engineering Managers | https://labelbox.com Labelbox is building the training data platform to power breakthroughs in machine learning. We provide an end to end solutions for the full AI lifecycle from creating catalogs of unstructured data all the way to building the tools for humans to label the data to teach machines. Why choose us? - Source: Hacker News / over 1 year ago
Hey, I have currently developed a U-Net model for segmentation and I am trying to use the model assisted labeling feature on LabelBox to annotate some masks, so I can save time on relabeling. I am just wondering if anyone is familiar with this feature or can give me a step by step guideline on how to go about doing this. I went through the examples on their GitHub but I’m honestly still very confused. Any help... Source: almost 2 years ago
By now, I hope you see where I'm going with this. What is MDR doing? They're creating the labelled data used to train severance chips. They get a raw download of human brains in encoded format, and go about manually labelling the different pieces based on their most basic elements. Then, based on this manually labelled data, an algorithm can be trained to create a severance chip. MDR is basically Labelbox for... Source: about 2 years ago
LabelBox - they provide free versions for research. Source: about 2 years ago
Doing some progress, labelbox.com allows me to do the Video annotation, and access all data through python SDK/API... Working on converting myself to CSV GCP format :-). Source: over 2 years ago
Taskable - Using multiple work apps leads to tons of context switching, breaking flow and killing productivity.
V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.
TideTask - Control your procrastination and never miss a task again
Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...
Task Muncher - Task Muncher is a cross-platform and web-based application that is designed to organize and keep the track of everything and focus on munching the weekly tasks.
Playment - Playment is a fully-managed solution offering training data for AI, transcription, data collection and enrichment services at scale.