Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 2327

In a new interview, Elon Musk identifies genetics, AI, and brain bandwidth as three areas in which today’s youth can have the biggest impact on the future. However, he doesn’t think an idea needs to be revolutionary to be worthwhile.

While many 2o-something-year-olds are just finding their way in the world, young Elon Musk was already looking for ways to change it way back in 1995 (when he was that age).

In a well-known 2015 discussion with Neil deGrasse Tyson for the physicist’s StarTalk Radio podcast, Musk lists the five things he thought would most affect the future of humanity (the internet, sustainable energy, space exploration, artificial intelligence, and rewriting human genetics).

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The research lab that developed Siri, SRI International, is creating virtual assistants that can detet your emotional state, and react accordingly. It envisions assistants that can detect emotions and tailor their reactions to those emotions.

Artificial intelligence (AI) is all about getting a machine to mimic a human in every way: thought, speech, movement. That’s why one of the tests for AI is the Turing test: whether a robot can fool a human into thinking it is conversing with another of its own species.

An integral part of accomplishing this is making the AI recognize human emotions. So one research lab is working on the next iteration of virtual assistants, those that can recognize and react to emotional cues. SRI International, the birthplace of Siri, is working on better chatbots and phone assistants that can detect agitation, confusion, and other emotional states, and respond accordingly.

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Advances in machine learning have been driven by innovations and ideas from many fields. Inspired by the way that humans learn, Reinforcement Learning (RL) is concerned with algorithms which improve with trial-and-error feedback to optimize future performance.

Board games and video games often have well-defined reward functions which allow for straightforward optimization with RL algorithms. Algorithmic advances have allowed for RL to be in real-world problems, such as high degree-of-freedom robotic manipulation and large-scale recommendation tasks, with more complex goals.

Twitter Cortex invests in novel state-of-the-art machine learning methods to improve the quality of our products. We are exploring RL as a learning paradigm, and to that end, Twitter Cortex built a framework for RL development. Today, Twitter is open sourcing torch-twrl to the world.

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This is not that far fetch especially when we have seen DARPA’s efforts around BMI, the nanobot technology being experimented on to enable BMI, stent technology as well that is being looked at for BMI, etc. which all leads us into the concept of superhumans.

“Humans are so slow” says Elon Musk, so let’s become AI-human symbiotes instead.

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