Big Nothing and Inference?

[dsyme]

The age of the data scientist is upon us. In the era of big data we need frameworks that can handle the uncertainty and scale inherent in the never-ending rivers of data observations coming from IoT, DevOps, web analytics and microservices.

Now, ask yourself: what is at the heart of this? What is the core problem that no one has addressed? What does that data contain most of the time? Yes!! Nothing!!!!

What could possibly be more central to the challenges faced by the data industry than a scalable, streaming and inherently probabilistic treatment of Nothingness?

The timeliness of this framework is matched only by the urgency of the problem it addresses. We need a probabilistic, inference-ready, learning-powered nothingess. If you can take this wonderful Nothing framework in that direction, you will address the vacuous heart of information science today, right at its core.

[Aaronontheweb]

I love how @dsyme can get me this excited for the concept of implementing nothingness inside my applications.

[gregoryyoung]

Don,

I can only explain my current feeling with a story.

Many years ago there was the first alt.net in Seattle, it was the first time many of us who began the movement met each other. It was a nice hotel. In the lobby there were these huge plants setup covered in stones.

Someone (I will let the guilty remain nameless but he might have lived in Vancouver at the time) managed to acquire some organic substance that while some people make ropes out of it others like to smoke. Much of this occurred.

One evening someone made up a new game called "meta-stones". Basically the idea was you would select a stone from the hotel lobby plants and say something about it. An example might be "this stone is free". The other person would then take a stone out and relate it to your stone. The winner was solely determined by the other person saying "I agree you have won.".

Based on this issue. "I agree you have won".

:)

[DavidBrower]

“Nothingness lies coiled in the heart of being - like a worm.” - Jean Paul Sartre/Tony Hoar