random computing

Problem-solving

For many years, researchers have turned to the public logs of search engine terms to help them track the spread of disease. They can analyze the keywords and phrases that people use and when they become interested in a disease or have symptoms. Much value has been recognized in this kind of disease tracking and it has been used to research influenza outbreaks, the spread of MERS and the Zika virus, and other health problems. At the time of writing, it is approximately three months since we first recognized the emergence of a new coronavirus in China that would ultimately become known as the pathogen to cause the novel pandemic disease, Covid-19.

A blog about robots and physical computing.

This is really part two of a set of post in response to a question from Carl Simmons (@Activ8Thinking) concerning building a micro:bit simple neuron. In the previous post a single neuron was produced. This post looks at producing a network of neurons, ie. neural network; looking to solve the problem that a single neuron can't solve, making an Exclusive OR gate (XOR)

using Mozzila's brilliant AFrame, a web-based Virtual Reality model of a planet with rings and include a moon with the school's logo on it. This post replicates the steps to build something similar.

I am fascinated by connections and seeing connections between things, One area that particularly intrigues me is people connecting via social media and Twitter in particular.

Blog about the work by computing by professionals, academics and students in Northamptonshire.

A recent study led by Princeton University researchers, in collaboration with University of Maryland and IBM, explored the architectural design of quantum computers (QC). In a paper presented at the 2019 ACM/IEEE International Symposium on Computer Architecture, the researchers performed the largest real-system evaluation of quantum computers to date, using seven quantum computers from IBM, Rigetti and the University of Maryland.

Monte Carlo computational methods are behind many of the realistic images in games and movies. They automate the complexities in simulating the physics of lights and cameras to generate high-quality renderings from samples of diverse image features and scenes. But the process of Monte Carlo rendering is slow and can take hours—or even days—to produce a single image, and oftentimes the results are still pixelated, or "noisy."

Problem-solving

In order to better solve complex challenges at the dawn of the third decade of the 21st century, Alphabet Inc. has tapped into relics dating to the 1980s: video games.

he cat (Scratch) moved across the screen and a button burst when the object moved in the camera onto it using Scratch 3.

A blog about robots and physical computing.

A blog about robots and physical computing.

Blog about the work by computing by professionals, academics and students in Northamptonshire.

Blog about the work by computing by professionals, academics and students in Northamptonshire.

SimBlock, a new blockchain simulator, lets users play around with the parameters of Bitcoin, Litecoin, and Dogecoin

Learn how to use the Speech Recognition API to convert speech to text for easy input into forms.

In recent years, researchers have proposed a wide variety of hardware implementations for feed-forward artificial neural networks. These implementations include three key components: a dot-product engine that can compute convolution and fully-connected layer operations, memory elements to store intermediate inter and intra-layer results, and other components that can compute non-linear activation functions.