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Large text-to-video models trained on internet-scale data have shown extraordinary capabilities to generate high-fidelity films from arbitrarily written descriptions. However, fine-tuning a pretrained huge model might be prohibitively expensive, making it difficult to adapt these models...
Researchers have proposed a novel approach to enforcing distributional constraints in machine learning models using multi-marginal optimal transport. This approach is designed to be computationally efficient and allows for efficient computation of gradients during backpropagation. Existing methods...

Document Processing and Innovations in Intelligent Character Recognition (ICR) Over the Past Decade

With automation coming to the forefront of technology trends in 2023, document scanning technologies are rising in popularity. ICR and OCR technology removes the...

Leveraging TensorLeap for Effective Transfer Learning: Overcoming Domain Gaps

Nowadays, constructing a large-scale dataset is the prerequisite to achieving the task in our hands. Sometimes the task is a niche, and it would...

Unlocking the Secrets of Deep Learning with Tensorleap’s Explainability Platform

Deep Learning (DL) advances have cleared the way for intriguing new applications and are influencing the future of Artificial Intelligence (AI) technology. However, a...

How To Monitor Your Machine Learning ML Models

What is a Machine Learning Model? Machine Learning (ML) models are data sets that have been taught to identify specific occurrences. The trained model may...

Data-Centric Computer Vision with Superb AI’s DataOps Platform

Data-Centric Computer Vision is a term inspired by Data-Centric AI - the process of building and testing AI systems by focusing on data-centric operations...

Meet Hailo-8™: An AI Processor That Uses Computer Vision For Multi-Camera Multi-Person Re-Identification

Multi-person re-identification is an important aspect of today's video surveillance systems. This process allows the user to identify individuals across multiple video streams, which...

An Introduction to Automated Data Labeling

Artificial intelligence has made waves throughout the past decade, where advancements are showing up in everyday applications. But getting there requires a ton of...

A Primer on Data Labeling Approaches To Building Real-World Machine Learning Applications

Introduction‍ In computer vision and machine learning operations, data labeling is an essential part of the overall workflow. For reference, data labeling is the process...

3 Machine Learning Business Challenges Rooted in Data Sensitivity 

Machine Learning (ML) and, in particular, Deep Learning is drastically changing the way we conduct business as now data can be utilized to guide...

Google Highlights How Statistical Uncertainty Of Outcomes Must Be Considered To Evaluate Deep RL Reliably and Propose A Python Library Called ‘RLiable’

Reinforcement Learning (RL) is a machine learning technique that allows an agent to learn by trial and error in an interactive environment from its...

IBM Research Achieves Quantum Speed-Up in Supervised Machine Learning

Quantum Machine Learning techniques have become quite popular in recent years among many computer scientists and physicists investigating their potential.  Machine learning algorithms have achieved...

MIT Researchers Employ Machine Learning To Discover New Sequences To Boost Drug Delivery In Cells Using Neural Networks

Machine learning has been widely used in finding efficient solutions in the healthcare sector to help in diagnosing and treating various illnesses.  Sarepta Therapeutics, located...

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