We shipped many cool features like one-click cuboids, default dimensions, ML proposals, etc. We also perfected interpolations and other new features for video and sensor fusion annotations. Our human annotators label faster by correcting near-perfect annotations created by our tools.
Playment: View Company Profile
The CabinetM marketing technology management platform enables full lifecycle support around technology discovery, qualification, implementation, and management. Marketing teams using CabinetM gain critical visibility and leverage to save time, money, drive revenue, and manage digital transformation. We are more than grateful to our customers who believed in us and continue to partner with us. Most importantly, we would not have made it this far without a few key employees who have completed four years or more with us and helped us build this high-yielding data labeling platform we have today. The pandemic took over in March, and India announced a 2-month lockdown. We devised quick and efficient contingency plans to ensure frictionless services for our customers.
In 2020, we saw an increased rate of AI adoption by different governments worldwide and enterprises keen gt studio playment on automation. While we started out with a deep focus on autonomous driving use cases, this year we expanded with other industries like agriculture, real estate, mining, and defense among others. Currently, Playment services a host of international clients including Samsung, German automotive tools giant ZF, US-based self driving solution company Nuro and Daimler AG among others. “With TELUS in the driving seat we hope to reach a larger client base globally. We are also aggressively hiring for these opportunities,” says Malasane.
- Lidar(Light Detection and Ranging) which measures distances using sensors between objects by illuminating them using a pulsed laser.
- We are excited to see the increased pace of CV adoption in several sectors.
- But in retrospect, we cannot deny that this tumultuous year has helped us grow immensely.
After signing up, the users are taken to the management dashboard which is light in color. To maintain visual uniformity in the journey, we chose to go ahead with the light colored illustration. Unlock special offers and join 10,000+ founders, investors & operators staying ahead in India’s startup economy.
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We can all collectively agree that 2020 was an unexpected year for the world at large. And it is almost too easy to dwell on the negatives during such a large-scale crisis. But in retrospect, we cannot deny that this tumultuous year has helped us grow immensely. We took charge of the situation, consistently exceeded customer expectations, and used opportunities to stay true to our mission of expediting the AI age.
Project ID
In 2015, the team started with providing cataloging and content moderation services to large marketplaces such as Flipkart, Lazada, Paytm, Ola and others. “At Flipkart, we used to address a lot of repetitive cataloguing requirements. Especially because a lot of sellers did not know how to categorise their products properly. This led us to build the Playment solution,” said Malasane speaking to Inc42. The platform is powered by a workforce of 300,000+ users which is managed by the human intelligence experts who build the tasks and deliver results with assured quality. Playment has been proactively working on creating infrastructures that offer maximum flexibility and scalability.
The Generational Edge: Mastering Hybrid Skills Across a Multigenerational Workforce
It will need software that recognises objects and visual cues that the vehicle driver normally sees. However, before the machine learns that it has to avoid some visual elements- like people and animals- and respond to elements like traffic signals, the software has to know what these elements are. Throughout the year, we have had many pilot successes, and we managed to bag long-term partnerships with global ML teams from companies like Samsung, Intel, Siemens, Sony, Dell, BMW, Bosch, LG, ZF, and Solera. Earlier in the year, we had an incredible opportunity to partner with Microsoft and showcase our data labeling capabilities along with the Azure ML team in CES 2020, Las Vegas. To make this feasible, Playment technology divided the big chunk of work into small micro-tasks like lego blocks and qualified users on its platform solve the entire puzzle.
It was in the process of looking out for partners and investors in the business that Playment founders engaged with TELUS leading to the eventual acquisition. All 85 of the startup’s employees, including founders, will join TELUS post acquisition. This dashboard allows us to set up and monitor customized workflows and build an end to end project management with playment workforce. ML engineers can use Python code to integrate their pipelines.
Video Annotation
- As in case of technology outsourcing opportunities, India has emerged as a leading data labelling destination globally.
- We shipped many cool features like one-click cuboids, default dimensions, ML proposals, etc.
- We also gave early access to a few of our customers and teams interested in exploring a data labeling platform that’s perfect for remote setups.
- However, before the machine learns that it has to avoid some visual elements- like people and animals- and respond to elements like traffic signals, the software has to know what these elements are.
Thriving in the new normal came with its own challenges, yet, we were well-prepared to go remote because of our web-based labeling platform and pre-established collaboration and communication protocols. We executed more than 776,475 hours of labeling and shipped ~64M high-quality annotations remotely for our customers worldwide. As a 2D/3D annotation tool and a platform to manage labelling teams of any size with team management software, all in one place, we wanted to communicate our distinguishing features through it. Globally, most companies outsource data labelling jobs to dedicated data annotators. Data labelling takes up the bulk of data scientists’ time, which could otherwise have been devoted to building algorithms. As in case of technology outsourcing opportunities, India has emerged as a leading data labelling destination globally.
We leveraged ML to make data labeling easier, faster & scalable.
Annotators go through the platform and complete pending tasks and get points. The points can be exchanged in the form of vouchers on online e-commerce sites. A batch is a way to organize multiple jobs under one batch_id. You can create new batches from the dashboard or by using the batch creation API.If batch_id is left empty or the key is not present, the job is created in the Default batch in your project. Read all about our automation features, workflow builder, and sensor fusion tools.
As labeling needs became more sporadic, timelines also started becoming shorter. And we are all aware that human labeling is a time-consuming process. That’s why we introduced ML automation features that reduce the time taken for labeling.