Seems the same is playing out out in Postgres with this extension, maybe will take it another 20 years
I don’t use numpy often enough - but this explains the many WTF moments why it’s so annoying to get numpy pieces to work together.
For instance, Ffmpeg can do that with the filter `select=gt(scene,0.3)`. It selects the frames whose scene detection score is greater then 0.3 (the scene change detection score are values between 0 and 1).
Otherwise you’d select frames with 0.3, 0.7, 1.0, 0.7, 0.3 - selecting 5 frames instead of 1?
Two pass with sobel filter comes to mind.
All I've seen are vague definitions of new terms (ex. signatures) and "trust me this very powerful and will optimize it all for you".
Also, what would a good way to reason between DSPy and TextGrad?
So lambda pricing scales down to cheaper than a VPC, but it also scales up a lot faster ;)
I've published LambdaFlex as an Infrastructure as Code (IaC) template. It automatically scales and manages traffic between AWS Lambda and AWS Fargate [1].
This setup leverages the strengths of both services: rapid scaling, scaling down to zero, and cost-effectiveness.
[1] GitHub: https://github.com/okigan/lambdaflex
Not only does it say what users the app is for, but also who it is NOT for. I think this kind of information is invaluable in deciding whether or not to use or suggest an app.
I can understand if app developers want EVERYBODY to user their app (whether or not its the best for the job) or if the app developer just doesn't want to take the time to write out who the app is NOT for. But I will praise those who do include that information.
But after reading it on the product page - I fully agree: seeing clearly the targeted personas and out of scope usage significantly elevates my trust in the product and the team behind it.
Have not used the software, but now I want to try
Dead Comment
It's too many layers of over-engineered complexity, and it's for underlying components that are changing very rapidly, so you are getting bogged down with out-dated architecture very quickly.