At Inversoft, we like open source and we like Java.
When we built out our platform to support our new cloud product offerings we started using Chef to help us manage our deployment strategy.
When we began working on some new backend features for our cloud product offerings, I set out to find a Chef Client written in Java in order to simplify our integration.
As luck wouldn’t have it (yes you read that correctly), I was unable to find a Java library that really made my life easier. There are other Chef libraries out there, but all of them were very lightweight wrappers around HTTP calls. Some went so far as to return the JSON response from the Chef server as a String rather than right POJO.
Rather than limping along with a library that was essentially a glorified URLConnection, I did what any software engineer would do, I wrote it myself.
Behold Barista! A native binding for Chef that provides rich domain objects and REST bindings to work with a Chef server.
Building a properly authenticated HTTP request to Chef is not great fun, so I don’t suggest you do it yourself unless you enjoy the pain. We’ve done the heavy lifting for you and we did this without using any third party encryption libraries. This means you can pick up this library without dragging along any unnecessary dependencies like Bouncycastle.
CleanSpeak can filter many types of user-generated content (e.g., chat messages, forum posts and reviews). Running this material through CleanSpeak on a “per message” basis ensures each piece of content is acceptable before allowing it to be seen in your community. Filtering by message makes sense for these specific use cases. But what if you have big data that you want to filter as a whole?
According to Wikipedia, Batch processing is the execution of a series of jobs in a program on a computer without manual intervention (non-interactive). Strictly speaking, it is a processing mode: the execution of a series of programs each on a set or "batch" of inputs, rather than a single input (which would instead be a custom job).
So when might you consider batch processing?
Maybe you purchased a list of names & addresses and want to make sure they don’t contain any vulgar language before including them in your marketing campaign?
Perhaps you allow users to upload files and want to make sure they don’t contain inappropriate content?
Or you gather a list of reviews and want to check them all at once to ensure the language is acceptable before posting to your site?
Image Moderation Just Got Faster
As applications, websites and online communities continue to expand, user generated content becomes difficult to manage. Nonetheless, a moderation solution is critical for sites that rely on users to succeed. Companies often focus on filtering chat, URLs and personally identifiable information. It is important to remember that images can be just as harmful to a brand and its user community.
Uncensored images are making their way to children via various platforms due to deficient moderation or lack of moderation altogether. Seven out of ten youths have accidentally come across pornography online.
Microsoft apologizes after artificial intelligence experiment backfired. What could they have done differently?
Tay, marketed as “Microsoft’s AI fam from the internet that’s got zero chill,” candidly tweeted racist and sexist remarks confirming she in fact had “zero chill”. The chatbot was shut down within 24 hours of her introduction to the world after offending the masses.
A healthy and engaged online community is critical to a company’s success. This is a hot topic amongst CMGRs and top industry influentials and while most people can agree on the importance of a branded online community not all agree on the path to achieving this safe environment.
If you have an active online community, you already know that not every user is a good user. Trolls, bullies and URL spam inherently present problems and there will be consequences if you simply ignore the issue.