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jaskyle

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Sometimes it comes down to having a third party service handle support or provide the framework, so adding it as a subdomain makes it easier to integrate into your site. And Google often treats subdomains as their own site so you can have a well structured support driven layout, rather than a site trying to showcase featured content while battling with support content.

Since the introduction of AI, doctors using AI to help in detection (not as a replacement to their own work) has been the driving force in improving healthcare outcomes. There may come a time where AI can be the sole source in locations that have a deficit of doctors (cause something is better than nothing), but I don't see it changing any time soon.

It's tough to top their arc with Infinity Way/Endgame. They definitely need to regain focus on where they want to go since they are introducing so many new characters.

TorchArrow looks pretty cool:

TorchArrow is a machine learning preprocessing library over batch data, providing performant and Pandas-style easy-to-use API for model development. Currently it provides a Python DataFrame that allows extensible UDFs with Velox, with the following features:

- Seamless handoff with PyTorch or other model authoring, such as Tensor collation and easily plugging into PyTorch DataLoader and DataPipes - Zero copy for external readers via Arrow in-memory columnar format - Multiple execution runtimes support: - High-performance C++ UDF support with vectorization

100% look for a new job if the current employer is not willing to enable your success. It's completely reasonable as a developer to expect a work computer that allows you to do your job effectively. If they gave you an older model that doesn't perform well, make sure you document on the performance and detail how its limitations are holding up your work. You don't need to request some supercomputer but a reasonable alternative to what you have now. If they refuse without giving any reasonable explanation, then move on.

Interesting to see a couple use case scenarios that give the win to each, so there doesn't seem to be a clear cut overall winner. Just depends on what you are looking to do.

A 4th point missing in this blog post is the simple fact that producers and gas stations can easily start adjusting the price up again, wiping out the 18-20 cents per gallon consumers would be saving in an effort to gain that as new profit. Then when the tax holiday ends, gas prices would jump back up to an even higher price with no guarantees that prices would decrease to pre-tax holiday levels.

"Meta’s move is the first time that a fully trained large language model will be made available to any researcher who wants to study it." - Is that true? Isn't GPT-2 open source? I mean, I am totally onboard with releasing models like this as open source but Meta isn't the first one to do it...