“How do we see the evolution of AI algorithms? I’m not sure how’s the best way to understand it, except what neural net seems to mostly do is take a massive amount of information from reality, primarily passive optical, and create a vector space, essentially compress a massive amount of photons into a vector space.”
He shared that earlier that very morning he was wondering, “Have you ever tried accessing the vector space in your mind? Like, we normally take reality just for granted in a kind of analog way. But you can actually access the vector space in your mind and understand what your mind is doing to take in all the world data.”
He explained that what we are actually doing is trying to remember the least amount of information possible. “So it’s taking a massive amount of information, filtering it down, and saying what is relevant. And then how do you create a vector space world that is a very tiny percentage of that original data. Based on that vector space representation, you make decisions.”
— Read on cleantechnica.com/2020/07/09/elon-musk-talks-tesla-ai-chip-autonomy-level-5-accessing-the-vector-space-in-your-mind-more/
While artificial intelligence systems continue to make huge strides forward, they’re still not particularly good at dealing with chaos or unpredictability. Now researchers think they have found a way to fix this, by teaching AI about physics.
— Read on www.sciencealert.com/teaching-artificial-intelligence-about-physics-helps-it-deal-with-chaos
A Parsons and MIT researcher hooked up electrodes to a plant’s leaves to turn it into a robotic sensor.
AI is discovering new alloys faster than humans ever could
— Read on amp.fastcompany.com/40562533/ai-is-discovering-new-alloys-faster-than-humans-ever-could
If you’ve read any sort of science fiction, it’s likely you’ve heard about subvocalization, the practice of silently saying words in your head.
Medlock continued, “I also spend quite a bit of time thinking about the philosophical implications of development in AI, and intelligence is something that is very, very much a human asset.” This led him to deviate from a brain-focused model and explore, allowing him to see the cell as a worthwhile comparison. “I think the place to start, actually, is with the eukaryotic cell,” he said. When a lot of people hear artificial intelligence they hear “artificial brain,” but he thinks that instead, we can view the entire human body as an “incredible machine.”