Luddite - is the Singularity near?

Negative Feedback Loop major topic of this blog was AI vs. ELE, takeoff of the Technological Singularity vs. Extinction Level Event. There is already a negative feedback loop of the ELE present:

'Taiwan is facing a drought, and it has prioritized its computer chip business over farmers.'

'U.S. Data Centers Rely on Water from Stressed Basins'

'Musk Wades Into Tesla Water Wars With Berlin’s “Eco Elite”'

With an incoming ELE, is there still enough momentum in pipe for the TS to take off?

Three Strands of AI Impact...

Prof. Raul Rojas called already for an AI moratorium in 2014, he sees AI as disruptive technology, humans tend to think in linear progress and under estimate exponential, so there are sociology-cultural impacts of AI present - what do we use AI for?

Prof. Nick Bostrom covered different topics of AI impact with his paper on information hazard and book Superintelligence, so there is an impact in context of trans/post-human intelligence present - how do we control the AI?

Prof. Thomas Metzinger covered the ethical strand of creating an sentient artificial intelligence, so there is an ethical impact in context of AI/human present - will the AI suffer?

TS Feedback Loop

DeepMind has created an AI system named AlphaCode that it says "writes computer programs at a competitive level." From a report:
The Alphabet subsidiary tested its system against coding challenges used in human competitions and found that its program achieved an "estimated rank" placing it within the top 54 percent of human coders. The result is a significant step forward for autonomous coding, says DeepMind, though AlphaCode's skills are not necessarily representative of the sort of programming tasks faced by the average coder. Oriol Vinyals, principal research scientist at DeepMind, told The Verge over email that the research was still in the early stages but that the results brought the company closer to creating a flexible problem-solving AI -- a program that can autonomously tackle coding challenges that are currently the domain of humans only. "In the longer-term, we're excited by [AlphaCode's] potential for helping programmers and non-programmers write code, improving productivity or creating new ways of making software," said Vinyals.

encode, decode, transmit, edit...train, infer

If we look back to the history of our home computers, what were these actually used for? Encode, decode, transmit and edit. First text, then images, then audio, then video, then 3D graphics.

Now we have additional some new stuff going on, neural networks. With enough processing power and memory available in our CPUs and GPUs, we can infer and train neural networks at home with our machines, and we have enough mass storage available for big data, to train bigger neural networks.

Further, neural networks evolved from pattern recognition to pattern creation, we use them now to create new kind of content, text, images, audio, video...that is the point where it starts to get interesting, cos you get some added value out of it, you invest resources into creating an AI based on neural networks and it returns added value.

Home - Top