Auto Scaling for EC2 Spot Fleets
‘we are enhancing the Spot Fleet model with the addition of Auto Scaling. You can now arrange to scale your fleet up and down based on a Amazon CloudWatch metric. The metric can originate from an AWS service such as EC2, Amazon EC2 Container Service, or Amazon Simple Queue Service (SQS). Alternatively, your application can publish a custom metric and you can use it to drive the automated scaling.’
(tags: asg auto-scaling ec2 spot-fleets ops scaling)
How a Japanese cucumber farmer is using deep learning and TensorFlow
Unfortunately the usual ML problem arises at the end:
One of the current challenges with deep learning is that you need to have a large number of training datasets. To train the model, Makoto spent about three months taking 7,000 pictures of cucumbers sorted by his mother, but it’s probably not enough. “When I did a validation with the test images, the recognition accuracy exceeded 95%. But if you apply the system with real use cases, the accuracy drops down to about 70%. I suspect the neural network model has the issue of “overfitting” (the phenomenon in neural network where the model is trained to fit only to the small training dataset) because of the insufficient number of training images.”
In other words, as with ML since we were using it in SpamAssassin, maintaining the training corpus becomes a really big problem. :((tags: google machine-learning tensorflow cucumbers deep-learning ml)
Northland man denies burning down house but insurer refuses to pay out
This is a mad story. The insurance company is accusing a guy in NZ of using remote-login software from 400km away to trigger a “print” command to a complicated Heath Robinson setup in order to light a fire to burn down his house
(tags: fraud insurance weird nz crime printers remote-login)