ipunchghosts

The agents can check this and mitigate.

I ship overnight all the time now. I have a huge test set that runs before we ship. Users find updates each morning which we think feels nice.

Yes, or open Wrt

I have a different take....

I don't really care that they all look alike as long as the sites usable to me for its intended purposes. Honestly, having each site have its own brand is annoying to me.

For years of dealing with badly designed sites, I wished then that they _copy_ a better design even if it looked generic. Even copying a simple but usable design would have made many sites easier to use.

I don't want the site to win an art contest, I want the information to make a decision. At a min just be easy in the eyes and intuitive to use and get the info.

An adjacent question: is there an input dataset you can use for training that be computed in closed form so that when you train on your target dataset, learning is effecient.

Methods like formula driven supervised learning exist to arrive a good pretrained weight state, but could this procedure be generalized for specific datasets or flavors of input data.

I met Pete when I worked at kitware. Would u have time for a fifteen min call? I'm interested in the position but have questions about viabikity given that capabilitiea of ai. Send an email.

sorry, for some reason i was never notified that anyone replied.

I have work in synthetic aperture sonar for detection of these mines for almost two decades and can answer questions about this area for HN.

Eero simmoncellis group showed that specific network modifications allow the networks to extrapolate beyond noise they were trained in.

NNs can certainly learn beyond what they were trained for as new architectures have demonstrated. See benchmarks for any if the dan hendryks imagenet corruption dataset benchmarks (imagenet c r and a). Data + architecture work together to enable.

I have work using neural networks trained on synthetic aperture sonar SAS imagery using language only. The SAS datsets are extremely hard to come by. The dataset I used was from parts if world I can assure you we're never in the training set. My approach exceeds what clip models can do zero shot wise. Therefore, the network classified imagery if a modality and environment 100 percent not guaranteed to be in the training data.

This is a good way to think.