Message from Why Tea in MacGuyver - Skills & Academics #stem


2017-12-17 19:13:31 UTC  

I am not a fan of Tyson so much...a lot of his opinions rub me the wrong way, but that is just personal preference. He is definitely a smart guy

2017-12-17 19:14:06 UTC  

He teaches a pretty good lecture series on The Great Courses about explaining mysteries of the universe.

2017-12-17 19:15:39 UTC  

One cool thing he points out about relativity is that time stands still for photons since they travel at light speed which (if you believe it) means that a photon traveling across say 30 million light years of space does so in an instant.

2017-12-17 19:16:04 UTC  

He also understands that we don't really know anything about the universe.

2017-12-17 19:19:33 UTC  

If you ever want to blow your mind, look up some of the experiments in Retrocausality. Scientists claim they have proven that a future event triggered the present event (past from the future event's perspective) on the quantum level

2017-12-17 19:21:12 UTC  

And replicated the event in the lab and published complete with peer review

2017-12-17 19:27:24 UTC  

Not only does that photon not experience any passage of time -- space (space-time, ya know.) contraction occurs as well. So from the perspective of that photon it hasn't moved through space at all. It's merely emitted and absorbed instantaneously within a tiny portion of spacetime. Pretty cool stuff.

2017-12-17 19:33:58 UTC  

@Darth I think I heard about that! They had set up a transmitter and a receiver and thought they were close to the receiver receiving the transmission before it was sent.

2017-12-19 15:49:46 UTC  

Oh, I forgot about this since I have the whole server muted. So yes, relativity just says that objects moving through space can't go faster than light, space itself expanding isn't really covered by that, since it's not moving through anything. I haven't really studied GR so I don't know all about that though.

2017-12-19 15:57:11 UTC  

"Well, as I understand it, the modern view of light isn't so much that its a particle/wave as it is something that exists in spacetime itself."
Modern physics doesn't need to make a hard distinction between 'objects' and light, the same set of equations governs them. They both exist in spacetime, it's where everything exists, and they both have wave particle duality. Electrons have wave properties too, if you send them though a narrow opening, they behave in a way that a pure particle never could.

2017-12-19 15:57:31 UTC  

is there any way to get notifications from just one channel but not the others in a server?

2017-12-19 16:14:06 UTC  

I think you can mute channels.

2017-12-20 07:00:37 UTC  
2017-12-24 01:00:01 UTC  

https://discord.gg/ThkG7e New discord dedicated to sci + tech (and culture) with an emphasis on futurology and emerging tech (note: this server is not identitarian exclusive)

2017-12-24 09:30:20 UTC  

^ To be clear, this is not a replacement of this channel or server

2017-12-24 20:09:56 UTC  

Anyone into machine learning, deep learning, etc? @here

2017-12-24 20:14:10 UTC  

What’s that?

2017-12-24 20:56:26 UTC  

AI, I think.

2017-12-25 00:10:01 UTC  

@Why Tea I do some at work and did some for my degree

2017-12-25 00:10:29 UTC  

Do you ? @Why Tea

2017-12-25 00:11:52 UTC  

Cool. I've been reading some on coding it. My employer (big big company) is a huge player in it, but I'm not involved in it at all at work.

2017-12-25 00:12:44 UTC  

Is this a good place to start (sure looks like it) and what other resources do you think are worth looking at?

2017-12-25 00:14:01 UTC  

@Deleted User Yes, one way / model of dealing with AI.

2017-12-25 00:28:44 UTC  

@Why Tea what resource to use and what to focus on depends a lot on what you're actually working on.

Are you doing some sort of image or signal processing? If so then yes Neural Networks sounds good and that site is a good start.

But Neural Networks aren't useful for every problem (though some academics are trying to push the idea that they are) so step one I would ask are you absolutely sure they are necessary for your work.

You can tell what machine learning things to focus on by laying out what type of inputs and outputs you are doing. The dimensions your data can fit are usually sequential vs non-sequential (i.e. a sentence is a sequence of words, an image is just a single vector of numbers) and categorical/symbolic vs cardinal vs ordinal.

2017-12-25 00:31:22 UTC  

Right, right. Thanks. But I'm not working on anything *specific* yet, as I'm trying to learn.

2017-12-25 00:31:47 UTC  

Of course one of the best ways to learn is to pick a thing you'd like to do, and try to solve the problem, but I'm not there yet.

2017-12-25 00:41:53 UTC  
2017-12-25 00:42:02 UTC  

Excellent, thanks!

2017-12-25 00:42:13 UTC  

I love the MIT courses that are available.

2017-12-25 00:42:24 UTC  

MIT open courseware on Artificial Intelligence

2017-12-25 00:44:10 UTC  

You're welcome, yeah they are great

2017-12-25 01:12:34 UTC  

I’ve also heard good things about the Coursera online courses for this.

2017-12-25 01:13:29 UTC  

I took a Coursera course in Data Analytics learning R and they did a better job than Texas A&M’s graduate class on the same topic (I took both).

2017-12-25 01:17:31 UTC  

Yeah Coursera's first course was a pretty good Machine Learning Course by Andrew Ng, but last year they changed the format of the Coursera website SO MUCH that I now find it virtually unusable. That's partly by design, they give very little away for free anymore and they tightly restrict when materials are available.

2017-12-26 03:03:23 UTC  

So just pay for it.

2017-12-26 03:45:00 UTC  

That probably works for some people, but ever since after I finished school I usually study a subject in spurts in a way that doesn't fit well with Coursera's pricing model. I say this as someone who has paid for their courses and generally didn't get my money's worth before they expired.

2017-12-26 03:46:10 UTC  

The best experience I had with a paid Coursera course was when I was doing a programming course with other people. I feel like that model works best for Coursera because that's closest to the classroom model they are going for

2017-12-26 03:48:20 UTC  

When I study on my own though, I like to dive deep into something in a few goes when all of a sudden a few spare hours open up. Coursera is not conducive to this though. Courses start periodically so if it doesn't happen to be the first week of their course then you are SOL. And then the longer courses they have roll out the course material one week at a time, preventing a dive in.

2017-12-26 03:49:10 UTC  

That's why I like to just have all the course materials available at once, all the time. I don't think Coursera has that model for any of the courses I was interested in though.

2017-12-29 00:02:02 UTC  

I do some machine learning light for work and have a masters in data science from Berkeley