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Featured E-Book


Mighty AI Platform Overview

You need high-quality data to train and validate your computer vision models. You’ve tried labeling your data in-house but can’t scale, and the annotation vendors you’ve evaluated don’t provide the flexibility or high quality that your models require. Unlike other annotation vendors that advertise convenience at low cost, Mighty AI promises exceptional quality at great value by building an annotation program tailored to your exact model requirements. This brochure provides an overview of our image annotation platform that combines the best of machine and human intelligence to deliver unbeatable quality at enterprise scale.



Featured Podcast


Mighty AI: Data for 2020 vision

From autonomous vehicles to new retail applications, computer vision is opening new vistas of opportunity. But to realize them requires rigorous training.

Listen as Matthew Quinlan, Global Geospatial Platforms Lead at Accenture and Daryn Nakhuda, CEO of Mighty AI, explore the challenges involved in making sure that computer vision algorithms are trained using the data and machine learning techniques they need to operate in complex visual environments.



Featured Webinar


Data Driving Automated Vehicles

Before millions of automated vehicles are deployed in the coming decade, the deep neural networks powering them will require large quantities of carefully annotated and labeled data for training and validation. With the vast and often unpredictable nature of driving, billions of virtual driving miles in simulation using both real world and synthetic datasets will be essential to ensuring that these systems are safe for use. In this webinar, join Sam Abuelsamid from Navigant Research, Danny Shapiro from Nvidia, Ryan Eustice from Toyota Research Institute, and Daryn Nakhuda from Mighty AI as they discuss how the data is captured, curated, prepared, and used to enable autonomous vehicles.



Featured White Paper


The Data Driving Automated Vehicles: 
Where It Comes From and Why Quality Matters


The diversity of environments in which autonomous vehicles must learn to operate is virtually endless: from unknown weather conditions, to pedestrians and cyclists, damaged roads, and other vehicles, machine learning models require vast amounts of data to account for as many scenarios as possible. But data quantity is not the only challenge. Accurately labeling that data is an even more challenging piece of the puzzle that data scientists and engineering teams are trying to solve.


Featured Podcast


TWiML Talk #57 with Daryn Nakhuda, founder and CEO of Mighty AI

Training Data for Autonomous Vehicles

TWiML Talk #57 with Daryn Nakhuda, founder and CEO of Mighty AI

Daryn and show host Sam Charrington chat about the demand for highly specialized and accurate data within the autonomous vehicles market.

In this episode, Daryn shares how our expertise in predictive machine learning across industries helped us evolve to a Top 10 Auto Startup in 2017. Other topics you can look forward to: scale concerns in the race to autonomy, the need for diverse data from around the world, the secretive marketplace, and so much more.


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