The first reason is that serverless architectures are inherently scalable and elastic. They automatically scale up or down based on the incoming workload without requiring manual intervention through serverless compute services like AWS Lambda, Azure Functions, or Google Cloud Functions. - Source: dev.to / 15 days ago

The FaaS platform gained a lot of popularity which resulted in many competitors. There was OSS providers like OpenFaaS or Fission. There were of course the commercial versions to like Azure Functions and Google Cloud Functions. - Source: dev.to / 23 days ago

One of the issues developers can encounter when developing in Cloud Functions is the time taken to deploy changes. You can help reduce this time by dynamically loading some of your Python classes. This allows you to make iterative changes to just the area of your application that you’re working on. - Source: dev.to / 6 months ago

I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights. Source: 8 months ago

Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment. - Source: dev.to / 10 months ago

Try this: https://experiments.withgoogle.com/collection/ai. Source: over 1 year ago

But Google has a whole set of AI writing tools - https://experiments.withgoogle.com/collection/ai So by their own definition they are producing spam? - Source: Hacker News / about 2 years ago

Https://experiments.withgoogle.com/collection/ai might also help (I haven't used this IRL). Source: over 2 years ago

It's hard to imagine you've not seen Google's doodle guessing training (or their other experiments) but it's just another example of how little information you actually need to create a recognizable image, though Canvas also shows this off, but it has the benefit of material information. Source: over 2 years ago

To come back to your original question, as far as I'm aware anyone can publish on arxiv or researchgate. People will just tend to take you less serious. Maybe a better solution for you is something like this https://experiments.withgoogle.com/collection/ai . You already said you think your idea might be industry changing so if it truly is, I'm sure people will start noticing you. Source: about 3 years ago