Jonas Cleveland

AI Entrepreneur

Hello! My name is Jonas, I am an entrepreneur focused on the areas of AI and robotics. My passion is in building a better world using technology! I have had the privilege of being recognized by some of the largest forums in the field - I am a recipient of the MIT Technology Review's 35 Under 35 Award for pioneering Technologists and LinkedIn's NextWave Award for rising entrepreneurs. I have been invited to keynote at international events including Emtech, TDWI, and Emerge Americas. I currently serve as Founder and CEO of – the world’s first automated content generation platform for video – and also, Commercial Advisor to– focused on machine perception. Previously I co-founded COSY, Inc a spinout of my research with Professor Kostas Daniilidis. I have had advisory or contribution roles at Northrop Grumman, Emergent Views, Brightday.IO, and Azavea. My primary interests are in computer perception, machine learning, and mobile robotics. Previously I worked as a Research Scientist at UPenn's GRASP Laboratory with Professor Vijay Kumar, and before that, I worked on autonomous vehicles at Carnegie Mellon’s General Motors Lab.

All Post

Backpropagation and Gradient Descent are two of the most important processes in machine learning. In this video, we excplore how gradient descent and back propagation work together to train neural nets.For more on AI and robotics –
There will be many careers created in AI. Prompt Engineering is one way we can make money using AI. In this video we will explore what an AI Prompt Engineer does. The best way to prepare for these roles is to gain relevant experience in the field. This can often be accomplished using a bootcamp.
In this video, we examine Generative Adversarial Networks (GANs) in Artificial Intelligence. GANs are often used for deepfakes and voice cloning approaches within artificial intelligence. In this video we aim to provide a very simple, but thorough explanation of how GANs work.For more on AI and robotics –
Neural Networks are an approach in Deep Learning. Deep Learning is a subset of Machine Learning. Neural Networks are often considered an approach that is foundational to Artificial Intelligence. Neural Networks are used to solve a multitude of problems from text classification to synthetic image generation. This video aims to explain neural nets using a series of simple examples. We start with ...
We explore how Generative AI works. Several components deep learning components are used across Generative AI systems. We will examine some of the building blocks of this field so we can better understand it. Generative Adversarial Networks, Embeddings, Transformers, Encoders/Decoders, Feed-Forward Neural Nets, Multi-head Attention, SoftmaxFor more on AI and robotics –
There are several incredible companies being built that leverage the breakthrough technology of Generative AI. In this series, we will be learning how to use Generative AI Apps to make us more productive. We will also be exploring the underlying technology that powers Generative AI. We will then be taking a look at how we can invest in Generative AI startups – most of which are currently ...
Join our mailing list to learn more
Social Media Feed