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Better Machine Learning Demands Better Data Labeling: Key Takeaways

Better Machine Learning Demands Better Data Labeling: Key Takeaways

Machine learning (ML) techniques have had a huge societal impact in many cases and applications such as speech processing, natural language comprehension, neurosciences, health,...

The convergence of deep neural networks and immunotherapy – TechCrunch

The convergence of deep neural networks and immunotherapy – TechCrunch

What do deep neural networks and cancer immunotherapy have in common? While both are among the most transformational areas of modern science, 30 years ago, these fields were...

Predicting the past with Ithaca

Predicting the past with Ithaca

Predicting the past with Ithaca Predicting the past with Ithaca Authors * External authors Restoring, placing, and dating ancient texts through collaboration between AI and...

Apple Researchers Introduce 'NEO' to Generalize Confusion Matrix Visualization and Enable Machine Learning Practitioners to Find Hidden Confusions

Apple Researchers Introduce 'NEO' to Generalize Confusion Matrix Visualization and Enable Machine Learning Practitioners to Find Hidden Confusions

Machine learning is a complex, iterative design and development process aimed at creating a learned model that generalizes to new data inputs. Model assessment, which involves...

Restoring and attributing ancient texts using deep neural networks - Nature

Restoring and attributing ancient texts using deep neural networks - Nature

Restoring and attributing ancient texts using deep neural networks History Abstract Ancient history relies on disciplines such as epigraphy—the study of inscribed texts known as...

Vectors are over, hashes are the future of AI

Vectors are over, hashes are the future of AI

Artificial intelligence has been built on the back of vector arithmetic. Recent advances show for certain AI applications this can actually be drastically outperformed (memory,...

Multimodal Bottleneck Transformer (MBT): A New Model for Modality Fusion

Multimodal Bottleneck Transformer (MBT): A New Model for Modality Fusion

People interact with the world through multiple sensory streams (e.g., we see objects, hear sounds, read words, feel textures and taste flavors), combining information and...

Difference Between Algorithm and Model in Machine Learning

Difference Between Algorithm and Model in Machine Learning

Machine learning involves the use of machine learning algorithms and models. For beginners, this is very confusing as often “machine learning algorithm” is used interchangeably...

The history of machine learning algorithms

The history of machine learning algorithms

Machine learning algorithms can perform exponential tasks today—from mastering board games and identifying faces to automating daily tasks and making predictive decisions—this...

Alan Turing: Tech Ideas that revolutionized 20th Century

Alan Turing: Tech Ideas that revolutionized 20th Century

Turing over his lifetime produced various groundbreaking seminal papers and works. In this write-up, I am going to delve into four such major works: “On Computable Numbers, with...

The possibilities and limitations of machine learning

The possibilities and limitations of machine learning

Machine learning, the process whereby a computer learns future responses through data analysis via an algorithm, is already enmeshed in finance and accounting. It sits in the...

Causal Modeling in Machine Learning Workshop

Causal Modeling in Machine Learning Workshop

Causal Modeling in Machine Learning Workshop The most efficient path to engineering causal reasoning in machine learning applications. A online workshop in causal modeling and...

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