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What’s Under the Hood of Neural Networks?

In this contributed article, Pippa Cole, Science Writer at the London Institute for Mathematical Sciences, discusses new research on artificial neural networks that has added to concerns that we don’t have a clue what machine learning algorithms are up to under the hood. She highlights a new study that focuses on two completely different deep-layered machines, and found that in fact they did exactly the same thing, which was a huge surprise. It’s a demonstration of how little we understand about the inner workings of deep-layered neural networks.

Research Highlights: Attention Condensers

A group of AI researchers from DarwinAI and out of the University of Waterloo, announced an important theoretical development in deep learning around “attention condensers.” The paper describing this important advancement is: “TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices,” by Alexander Wong, et al. Wong is DarwinAI’s CTO.

Machine Learning Beyond Predefined Recipes

The next evolution in human intelligence is automating the creation of machine learning models to not follow predefined formulas, but rather adapt and evolve according to the problem’s data. While machine learning has enabled massive advancements across industries, it requires significant development and maintenance efforts from data science teams. Enter Darwin, a machine learning tool that automates the building and deployment of models at scale.

An Introduction to Deep Learning and Neural Networks

In this contributed article, Agile SEO technical writer and editor Limor Wainstein outlines how deep learning, neural networks, and machine learning are not interchangeable terms. This article helps to clarify the definitions for you with an introduction to deep learning and neural networks.

AI for Pharma R&D – Creating Anti-cancer Drugs Faster, Reducing Process from Years to Days

The costs and process of developing anti-cancer drugs has been an extreme challenge for decades. Today one company, AccutarBio, is harnessing the power of AI to accelerate drug discovery and reform the current “hit-to-lead” drug discovery scheme. The company recently received $15 million in funding (including money from Chinese AI/facial recognition company YITU) and is now partnering with Amgen.

Surface Reconstruction Based on Neural Networks

Surface reconstruction is an important trend in 3D scanning. The problem is to recreate surfaces from a given point cloud within the shortest possible time and with a given quality criteria. There is a set of different approaches for solving this problem, which includes Self-Organized Maps, Bayesian reconstruction and Poisson reconstruction. The purpose of this article highlight a paper, “Surface Reconstruction Based on Neural Networks” that analyzes and compares results obtained with the usage of two self-organizing map types.

Surface Reconstruction Based on Neural Networks

Surface reconstruction is an important trend in 3D scanning. The problem is to recreate surfaces from a given point cloud within the shortest possible time and with a given quality criteria. There is a set of different approaches for solving this problem, which includes Self-Organized Maps, Bayesian reconstruction and Poisson reconstruction. The aim of the […]