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Thanks for the review. I just submitted my application today (before I saw your post). I was a bit wary, due to fluttershy's post you mentioned, but more because of the lack of results (ie actual job placements) on their website compared to more established programs. The main benefit I see to this program is being in a space with other people who you can easily bounce ideas off (ie, the social experience). I tend to work bettered in a structured environment, also. Its also good to hear that it is useful for networking as well. I wasn't sure about that, because whereas other data science programs have working relationships with major companies, I didn't get that impression when reading about Signal.
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A Review of Signal Data Science
Signal do have contacts in a few high profile companies.
I suspect that the track record issue is somewhat a timing thing, but also somewhat because other bootcamps are quite good at creative statistics to cook up their 90% figures.
For example, I started a springboard data science course with a monthly fee, but pulled out when I realised it was useless. However they will not count me as a "fail", because I didn't complete.
The mentor they assigned to me at springboard just told me to go Google everything, and their curriculum was not as good, you were left to fend for yourself with no help.
Contrast Signal where you're actually there and get help when you're stuck.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
There's also "Persistence of Long-Term Memory in Vitrified and Revived C. elegans", Vita-More & Barranco 2015 - so we know that in at least one species (which did not evolve for being frozen) that long-term memory is preserved by the best cryonics techniques.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
Given that c. elegans survived vitrification, it's not surprising that its memory persisted, though it does underline the point that memory is not some kind of magic - it's physically recorded. Of course large mammals like humans are very different from c. elegans.
Given that
- humans survive immersion in freezing water and 60 minutes of brain death with their memories intact
- c elegans survives full vitrification with memories intact
- connectome information and intercellular structure survives aldehyde stabilised cryopreservation
we can conclude that the skeptical case is trying to thread through an ever narrower gap. If you claim that the physical correlates of memory are too delicate, you contradict existing results. If you claim they are too robust, you are forced to conclude that they are preserved by the best cryo.
A Review of Signal Data Science
I took part in the second signal data science cohort earlier this year, and since I found out about Signal through a slatestarcodex post a few months back (it was also covered here on less wrong), I thought it would be good to return the favor and write a review of the program.
The tl;dr version:
Going to Signal was a really good decision. I had been doing teaching work and some web development consulting previous to the program to make ends meet, and now I have a job offer as a senior machine learning researcher1. The time I spent at signal was definitely necessary for me to get this job offer, and another very attractive data science job offer that is my "second choice" job. I haven't paid anything to signal, but I will have to pay them a fraction of my salary for the next year, capped at 10% and a maximum payment of $25k.
The longer version:
Obviously a ~12 week curriculum is not going to be a magic pill that turns a nontechnical, averagely intelligent person into a super-genius with job offers from Google and Facebook. In order to benefit from Signal, you should already be somewhat above average in terms of intelligence and intellectual curiosity. If you have never programmed and/or never studied mathematics beyond high school2 , you will probably not benefit from Signal in my opinion. Also, if you don't already understand statistics and probability to a good degree, they will not have time to teach you. What they will do is teach you how to be really good with R, make you do some practical machine learning and learn some SQL, all of which are hugely important for passing data science job interviews. As a bonus, you may be lucky enough (as I was) to explore more advanced machine learning techniques with other program participants or alumni and build some experience for yourself as a machine learning hacker.
As stated above, you don't pay anything up front, and cheap accommodation is available. If you are in a situation similar to mine, not paying up front is a huge bonus. The salary fraction is comparatively small, too, and it only lasts for one year. I almost feel like I am underpaying them.
This critical comment by fluttershy almost put me off, and I'm glad it didn't. The program is not exactly "self-directed" - there is a daily schedule and a clear path to work through, though they are flexible about it. Admittedly there isn't a constant feed of staff time for your every whim - ideally there would be 10-20 Jonahs, one per student; there's no way to offer that kind of service at a reasonable price. Communication between staff and students seemed to be very good, and key aspects of the program were well organised. So don't let perfect be the enemy of good: what you're getting is an excellent focused training program to learn R and some basic machine learning, and that's what you need to progress to the next stage of your career.
Our TA for the cohort, Andrew Ho, worked tirelessly to make sure our needs were met, both academically and in terms of running the house. Jonah was extremely helpful when you needed to debug something or clarify a misunderstanding. His lectures on selected topics were excellent. Robert's Saturday sessions on interview technique were good, though I felt that over time they became less valuable as some people got more out of interview practice than others.
I am still in touch with some people I met on my cohort, even though I had to leave the country, I consider them pals and we keep in touch about how our job searches are going. People have offered to recommend me to companies as a result of Signal. As a networking push, going to Signal is certainly a good move.
Highly recommended for smart people who need a helping hand to launch a technical career in data science.
1: I haven't signed the contract yet as my new boss is on holiday, but I fully intend to follow up when that process completes (or not). Watch this space.
2: or equivalent - if you can do mathematics such as matrix algebra, know what the normal distribution is, understand basic probability theory such as how to calculate the expected value of a dice roll, etc, you are probably fine.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
I'm afraid the preservation techniques are still so bad that you can't be revived correctly even with improved future techniques.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
Anyway, the bottom line here is that you can't reasonably bet against cryonic preservation success at the kind of extreme odds you were proposing upthread. You wouldn't bet on any medical claim at odds anywhere near 100,000:1, even in the case that there was a lot of evidence against it (and there is none at all against cryonics - the skeptical argument is entirely based on hypothetical information carrying entities that may or may not actually exist).
If you still think 100,000:1 against is reasonable, imagine making 100,000 statements about medical controversies, and being wrong only once.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
I'm afraid the preservation techniques are still so bad that you can't be revived correctly even with improved future techniques.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
It is not known for certain whether modern cryopreservation preserves "enough", partly because we are not entirely sure how long-term memories and personality are actually stored. We do know that the connectome is preserved, and modern techniqued such as aldehyde-stabilized cryopreservation seem to preserve cell membranes, synapses, and intracellular structures. See Wikipedia and the relevant paper.
It is possible that some key piece of information is destroyed by these protocols, with no way of recovery. Everything that we know is required to be preserved, is preserved.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
I think the reason a person would object is that the default hypothesis would be that when revival technology is invented, it will be invented in conjunction with a matching cryopreservation protocol, and previous cases will not have used that protocol. So previous cases will not be revivable.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
default hypothesis would be that when revival technology is invented, it will be invented in conjunction with a matching cryopreservation protocol, and previous cases will not have used that protocol. So previous cases will not be revivable.
Right.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
More like 1/100000, and then when they thaw you you'll be brain damaged and have to live in an institution forever. They don't really know how to do this yet. How far along are they now? Have they frozen and thawed a mouse yet, and did it behave the same as before? I won't let them freeze me earlier than that, because there's essentially no chance I'll be even able to walk and talk, let alone be someone present me would recognize as 'me'.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
Well, the position you're advocating here is certainly not one I - or other smart cryo advocates - agree with, but there is room for debate to be had. Let me keep it short for this comment though.
First of all, cryonics aims to vitrify people, not freeze them. This means they - ideally - turn into glass, not ice.
As such, they could not be thawed.
Going up a step in complexity, most cryo advocates don't believe that they will be revived in the same body, rather that the information that makes them who they are will be extracted and used to construct a real or virtual or robotic body.
Also, this:
They don't really know how to do this yet. How far along are they now? Have they frozen and thawed a mouse yet,
Putting aside that cryonics is not about freezing and thawing, there is the issue of wanting to wait until the revival side of cryonics is perfected. Well, sure, by the time science has advanced to that point, you would no longer have to make a probabilistic decision. But by that point, medical conditions - including aging - will probably have been eliminated. If you survive that far, good on you. But suppose we reach that point in 200 years' time. If you refuse cryonics because it's not yet proven, you will be dead by the time the proof comes.
So you have to make the decision right now: do you want to lose $1/day if cryonics doesn't work, or do you want to gain your life back if it does?
And this:
I won't let them freeze me earlier than that, because there's essentially no chance I'll be even able to walk and talk
I'm confused here. If you are cryopreserved (please, not frozen) at date X, and then at a later date X+100 they invent better revival technology, you can have that better revival technology used on you, even if it hadn't been invented when you were deanimated and cryopreserved! This seems so obvious to me that I'm confused about why you're objecting to it. Help me out?!
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
But won't it be difficult convincing others to sign up (and sign up as soon as possible) if you are not signed up yourself? Even if it is financial, many people live paycheck-to-paycheck, but I believe could still afford cryonic preservation.
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
many people live paycheck-to-paycheck, but I believe could still afford cryonic preservation.
I would not personally advise this course of action, so we'll have to agree to disagree. Especially if you are young, I think it makes more sense to first sort out your finances.
Are you signed for cryonics?
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Inverse cryonics: one weird trick to persuade anyone to sign up for cryonics today!
Nope, but my finances are pretty dire right now, though when I do I will certainly post about it. Thanks for asking.
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Avoid this program.
Jonah and Robert have good intentions, and I was actually happy with the weekly interview sessions taught by Robert. However, I had a poor experience with this program overall. I'll list some observations from my experience as a member of the first cohort below.
First, this program is effectively self-directed; most of the time, neither the TA nor the instructor were available. When they were, asking them questions was incredibly difficult due to their lack of familiarity with the material they were supposed to be teaching. To be sure, both the instructor and the TA were intelligent people--the problem was just that they knew lots of math, but not very much data science.
Second, there were lots of communication issues between the instructors and the students. I really do not want to give specific examples, since I don't want to say something that would reflect so poorly on the LessWrong community. However, I assure you that this was an incredibly large issue.
Lastly, everything about this program was disorganized. Several of us paid for housing through the program, which ended up not being available as soon as we'd been told that it would be. The furniture in the office space we used was set up by participants because Signal was too disorganized to have it set up before we were supposed to start using it. The fact that only two out of twelve students pair programmed together on an average day was also due to a lack of organization of the part of the instructors.
Jonah and Robert clearly worked very hard to make this program what it was, but attending was still a bad experience for me. If you already have a background in software engineering and want to pay $8,000 to teach yourself data science alongside other students who are doing the same, this program is a good fit for you. Otherwise, consider attending a longer, more established program, like Zipfian Academy that actually uses pair programming and has instructors available to answer questions.
Just commenting as I have a new review up that disagrees with this comment.