The vm_write function writes an array of data to a task's virtual memory.
We discuss two fault scenarios: one based on the corruption of all data of a target task, and the other involving the corruption of a single data point.
Our multitask learning method is based on the task regularization framework, which formulates the multitask learning problem as an objective function with two terms: an empirical loss term on the training data of all tasks, and a regularization term that encodes the relationships between tasks.
To work well, many of today's algorithms must be trained on huge amounts of data, a task that takes a lot of computer power.
"Big Data" projects will also gather steam as companies in many industries look for insights by sifting through huge volumes of data, a task that requires both whizzy software and bright minds.
In order to reason about the types of data a task can produce or consume, each task is characterized by a contract.
Engineering intelligence into systems, and finding insights in a ubiquitous sea of data, is a task that cries out for a diverse workforce.
I believe narrow AI — computers performing a narrow task, such as facial recognition or sifting through huge volumes of data — is a task that machines are better equipped to do than humans are.
In turn, data quality depends on processes of data collection, a task undertaken by frontline research staff in many research programmes in Africa and elsewhere.
Finally, a data-flow element interacts with the control-flow perspective, e.g., a pre- or postcondition of data existence for a task, data-value based condition evaluation, etc.
