FlyingSaucer (u/FlyingSaucer)

FlyingSaucer commented on 'Great Flirtation': Should workers constantly job hunt? bbc.com/worklife/article/... · Posted by u/perfunctory

atlasunshrugged · 4 years ago

I don't know about 'constantly' but I think once you're 8-10 months into a gig it doesn't hurt. For one, it gives you some real data about your market value in case you want to negotiate at the end of the year for a raise/bonus and second, it's just good to keep these skills in practice just in case of a layoff or you want something better. A bit time consuming but I've found it useful.

FlyingSaucer · 4 years ago

Maybe its only my gig and my area of the world, but going through the rounds with companies can be quite a grueling process and many recruiters can't explain the exact technical details or give any concrete salary information.

It's hard to just do it to test the waters when you have a technical project and multiple interviewing rounds (which also include live coding, which for me is very stressful).

FlyingSaucer commented on Neuro Evolution of Augmented Topologies fev.al/posts/neat/... · Posted by u/charlieirish

MrQuincle · 4 years ago

There's also for example HyerNEAT. I'm out of the field now. Has recent progress been made recently with these technologies?

FlyingSaucer · 4 years ago

I'm by no means an expert in the field but I do find it exceptionally interesting so i try and keep tabs on some of the research done by people who originated from the same group as Kenneth Stanley.

Seems like many from this group now pursue open-endedness in AI and view evolution as a way towards this goal (or lack thereof).

A very interesting evolution (ha!) of these ideas was presented in POET[0] towards evolution of agents in evolving environments.

There is also an interesting paper about accelerating neural architecture search when generating fake training data in generative teacher networks[1].

Lastly, a paper that i find very very interesting but might not be as relevant but still is 'First return, then explore'[2]

[0] : https://eng.uber.com/poet-open-ended-deep-learning/

[1] : http://proceedings.mlr.press/v119/such20a.html

[2] : https://arxiv.org/pdf/2004.12919.pdf

FlyingSaucer commented on Klimaticket: All public transport in Austria with a single ticket for 1095 EUR/y klimaticket.at/en/... · Posted by u/the_mitsuhiko

scrollaway · 4 years ago

I really want this to exist for Belgium. Right now the public transport prices are absurd here... An all year pass for just the train in all of Belgium ranges in the 10k eur/year, and there is no national metro+bus+tram access (just Brussels is 700 EUR / year for that with no access to other cities).

It's absurd and caused by fragmentation of services between Flanders, wallonia and Brussels with no coordination between them.

FlyingSaucer · 4 years ago

I completely agree. I used to live in Liege and would travel to NL, Brussels and Hasselt regularly. The juggle between different public transport subscription was difficult on top of the constant outages.

FlyingSaucer commented on Australia has lost one-third of its koalas in the past three years reuters.com/world/asia-pa... · Posted by u/nreece

FlyingSaucer · 4 years ago

The extensive bushfires and droughts are definitely big factors. I worked briefly for a forestry in rural Victoria, where we would encounter koalas somewhat frequently where we would plant trees, These are lots that would be planted completely and years later cut and burned.

Wonder what would be also the effects of this on them and wildlife in general.When I have seen Koalas in the wild they seemed very apathetic- saw one stay at the very top of a blue-gum (which famously can shed huge pieces without much warning) even during a storm.

FlyingSaucer commented on Scikit-Learn Version 1.0 scikit-learn.org/dev/what... · Posted by u/m3at

zibzab · 4 years ago

Is anyone using scikit for NN?

Why/why not?

FlyingSaucer · 4 years ago

I have used the MLP classifier[1] before. It's very simple to use (like most of sklearn's models). Worked well for standard and reasonably small classification model, but lacks some features for it to be a flexible way of using NNs:

- No saving checkpoints (can be crucial for large models who need alot of compute and time)

- No way to assign different activation functions to different layers

- No complex nodes like LSTM, GRU - No way to implement complex architectures like transformers, encoders etc

I also do not know if its even possible to use CUDA or any GPU with it.

[1] : https://scikit-learn.org/stable/modules/generated/sklearn.ne...

FlyingSaucer commented on Sam Altman Q&A: about GPT-4 and AGI lesswrong.com/posts/aihzt... · Posted by u/yoquan

FlyingSaucer · 5 years ago

from the article: 'Warning sign (of a critical moment in AGI development) will be, when systems become capable of self-improvement.'

Is the meaning of self improvement here means that the model will actively optimize itself towards improving on its mistakes outside of training? Because under my understanding for this to happen we would need the model to be in a different form than current ML.

FlyingSaucer commented on The First Delta Force Trainee Class historyofyesterday.com/th... · Posted by u/stanrivers

craftinator · 5 years ago

I can offer a bit of insight on this, having seen a fair amount of training of a free different groups (helped run a heavily used MOUT town, basically a fake town where they could run around shooting without hurting anyone).

You'd actually be surprised about how good their accuracy is, and even more so their reaction time. Their weapons are almost always pointed in the right direction, and they just move faster than the normal Marines and Army infantry.

Their gear is better, but not all that much better than an average recon team. Their Intel is better, in that they are fully briefed on it, rather than the chopped down versions the regulars get.

The biggest difference is their training and lifestyle. They don't have to deal with the bullshit that regulars do, don't have to play stupid games. Their job is to be good at their job, so that is all they do. And because of all that training time, because they can focus without being pulled into a working party or parade duty.

FlyingSaucer · 5 years ago

While many units generally consist of smaller teams, the teams can often be changed and switched around as people get specialized or re-assigned at different points, this generally doesn't happen for the very elite units.

Small teams are kept together at all times since very early in the training. Doing the same exercises many many times with the same exact people leads to mastery that makes them just seem faster and more fluid.

The lifestyle point is also true, its easier to keep your edge when there aren't constant mindless tasks to be done (gate duty) for many hours a day.

- I'm saying this from experience with armed forces, but can't claim its true for all elite units everywhere.

FlyingSaucer commented on Apple call center workers fear AI-powered surveillance cameras in their homes 9to5mac.com/2021/08/09/ap... · Posted by u/heshiebee

zimpenfish · 5 years ago

Everyone seems to have missed that Apple specifically ban contractors like Teleperformance from doing this.

[include] Apple spokesperson Nick Leahy said that the company “prohibits the use of video or photographic monitoring by our suppliers and have confirmed Teleperformance does not use video monitoring for any of their teams working with Apple.” Leahy said that Apple had audited Teleperformance in Colombia this year and did not find any “core violations of our strict standards.”

FlyingSaucer · 5 years ago

This is from my own experience working at a TP call center, for a major tech client and not in Albania or Colombia.

External and internal audits are known for weeks in advance such that they could put a facade on in time. During audits you suddenly don't have a limit on bathroom break time (generally an alert would come at 15mins per day) and there would be pizza at the office every other day. Only 'loyal' employees would be chosen to any interviews/meetings about culture etc.

FlyingSaucer commented on DeepMind says reinforcement learning is ‘enough’ to reach general AI venturebeat.com/2021/06/0... · Posted by u/webmaven

d110af5ccf · 5 years ago

Deep Mind is cutting edge ML in general, right? Doesn't Google actively apply the lessons learned all over the place? YouTube content recommendation stands out to me in particular. Translation and automated closed captioning are also obviously ML based. I'd guess that most of the really interesting stuff would be behind the scenes and not immediately visible to end users though.

FlyingSaucer · 5 years ago

Yes, its hard to tell the exact algorithmic underpinnings of production models that Google uses but you have to assume that although they have some done some impressive strides in fields that isn't immediately profitable (AlphaGo, AlphaFold...) they also continuously push new research in things that are obviously of interest for Google and Alphabet- especially in text-to-speech, speech-to-text, information-retrieval etc.

For reference : https://deepmind.com/research

FlyingSaucer commented on Language learning with Netflix languagelearningwithnetfl... · Posted by u/skanderbm

arkitaip · 5 years ago

This is a tangent, but has any noticed just how terrible Netflix subtitles can be? Occasionally, when watching with family members, I will enable Swedish subtitles for English movies and sometimes it's as if they have worked on a different material than what the actors on screen are saying. It's bizarre to see this low quality effort in movie after movie, show after show.

FlyingSaucer · 5 years ago

Yes! The subtitles can be completely different than the dubbing in some cases which makes it difficult for me to watch with both.

Also, they sometime use a bit odd translations. I saw a Belgian show and they translated smoking a cigarette into smoking a fag. Which I guess is technically correct (based on the cambridge dictionary), just an odd choice for general EU viewership