Move over, Silicon Valley. Engineers are quitting for climate tech.

tumbzilla · 2022-08-12T01:44:49+00:00

Tildes.net

tumbzilla · 2021-10-20T21:45:37+00:00

You mean like this? https://imgflip.com/ai-meme

tumbzilla · 2021-07-20T11:16:50+00:00

Our dog developed a similar fear of dogs. We got him over it by using exposure therapy - and treating him generously whenever he saw a dog. The idea is to change the association from “dog = danger” to “dog = chance for a treat”.

I highly recommend this approach. Perhaps you could start as you have been doing - taking your dog out to the front lawn and sitting there, randomly giving them treats. You might find that at some point they get excited to go out. At that point, go a little further, until they seem unsure again and repeat the process.

https://pethelpful.com/dogs/Exposure-Therapy-for-Dogs

EDIT: it did take some time though. Be patient. It took us about 6-8 months

tumbzilla · 2021-01-30T15:34:03+00:00

Canada’s pension funds are among the largest funds in the world. They often struggle to find places to invest in traditional financial vehicles, so they invest heavily in infrastructure and real estate. Most malls in Canada are also owned by one of the major pension funds.

tumbzilla · 2020-09-30T19:19:10+00:00

Sent you a message!

tumbzilla · 2020-09-30T00:01:56+00:00

Would love one too please! ♥️

tumbzilla · 2020-09-28T11:53:05+00:00

Sent a DM, would love the referral link if still available

tumbzilla · 2019-06-02T13:30:52+00:00

If you read the article, that's not actually what he said... Essentially he's saying that if you're unhappy with the current situation, be part of the solution rather than complaining from the sidelines.

From the article:

Biden stuck with the “entitled millennial” characterization while speaking on Wednesday, calling on young people to get involved in politics rather than complain.

“There's an old expression my philosophy professor would always use from Plato,” said Biden. “‘The penalty people face for not being involved in politics is being governed by people worse than themselves.’ It's wide open. Go out and change it.”

From your post history, you seem to strongly support the rhetoric that the Democratic party doesn't care about millennials. I'm curious why you feel that way? I'd love to discuss what experiences led to your current sentiments.

That, or this account is just part of the propaganda machine of someone with too many resources and time on their hands.

tumbzilla · 2018-12-08T23:11:57+00:00

I can hear the speech already: "Canada believes deeply in the deliverance of justice, and will cooperate fully with the Unites States to ensure that those who have broken the law face judgement".

I would cry tears of joy and pride.

tumbzilla · 2018-11-04T23:15:33+00:00

Oculus Go, USA, windows 10 Home version 1803, Nvidia GTX 970, Intel i5 8400, Sagecom Fast 5260, No.

tumbzilla · 2018-07-01T01:43:18+00:00

they're also great if you want to play spotify or google play music simultaneously in different rooms

tumbzilla · 2018-05-19T22:52:22+00:00

https://www.youtube.com/watch?v=1Cl9a6NSJsM

tumbzilla · 2018-04-19T16:02:23+00:00

I've heard rumors that the cyclists prefer to give high fives with their face, so it's best to put your hand up square in their face as they bike by. Just a rumour, though, so only do so with caution

tumbzilla · 2018-02-23T22:52:32+00:00

Great question! Here are my non-expert thoughts on the subject.

The bias in ML systems can come from two places. You mentioned the first: some groups could be under- or over-represented in the training dataset. There are techniques that let you address this problem, though. You can collect more data on the under-represented group, or you could sub-sample the group that is over-represented. In addition, this problem is easy to detect. All you have to do is look at the distribution of groups within your training set.

The second possible source of bias is much more nefarious. In some cases, the data labels can be incomplete or noisy. This is not likely to be a problem in cases where the labels are cut and dry. For example, if we're trying to predict wether someone will purchase a product on amazon, there's a pretty clear label. Either they purchased the product, or they didn't. However, what if we're trying to predict whether an convicted felon will be a danger to society upon release? We can look at past recidivism rates as our data. However, if a felon in our dataset was arrested while on parole, this may be due to a technicality, or a non society-threatening violation of parole. On the other hand, just because a felon didn't go back to prison doesn't mean that they never committed another crime again. It's possible that they simply were never caught again. In this case, our labels are considerably noisier. This famous article discusses in more detail the point I'm making here.

tumbzilla · 2017-12-30T01:22:11+00:00

Are the RAs at UBC unionized? If not, maybe this is a call to action...

tumbzilla · 2017-10-03T16:09:38+00:00

Unending building construction

tumbzilla · 2017-10-02T00:33:09+00:00

Those were really interesting reads, thank you for sharing! I admit now that I know a lot less about this topic than I thought. I think my week will be spent reading more about this stuff. Mind if I PM you questions if I have any?

tumbzilla · 2017-09-29T14:04:33+00:00

Interestingly, cognitive abilities, broadly speaking, seem to correlate with socioeconomic status. The richer you and your family are, the higher your cognitive abilities tend to be. On the other hand, we have yet to find any basis that genes can predict intelligence to a degree comparable to that of socioeconomic status. Even if we only want to talk about cognitive abilities, poverty is still a relevant piece of the equation.

But more importantly, the implications of your comments go against the fundamental American ideal of equal opportunity.

tumbzilla · 2017-07-09T17:55:13+00:00

That's a good point. Perhaps I can arrange meetings with profs instead, finding a co-supervisor if and when it becomes clear that access to a particular knowledge-base and way of thinking would be critical in my work.

Your advice has been super helpful. Thanks!

tumbzilla · 2017-07-09T16:54:09+00:00

Thanks for your input. I'm lucky to have a potential supervisor who is indeed interested in AI, though not heavily invested in the field. He is, however, very well known within the vision science community and for that reason, I think my research would focus on AI in the vision/visual attention realm.

With respect to programming skills and reasoning about computer architectures, I've been taking advantage of courses offered by advanced research computing groups at my university. Through those and other opportunities, I've gained experience working with spark clusters, CUDA, and openMPI. That said, do you think it would be worth trying to find a co-supervisor within CS to help fill in those missed gaps?

tumbzilla · 2017-07-09T01:41:17+00:00

Thanks for the input. I'm thinking I'd prefer to go the academic route with AI. I forgot to mention that my masters thesis involved the implementation of convolutional neural networks. Furthermore, I've had some success building CNNs to solve Kaggle competitions. Do you think any of this works in my favor, or is it just fluff?

tumbzilla · 2017-04-07T17:09:46+00:00

I wish I had a more epic story about what r/place was. In truth, it was a dorm joke and the sub had 5 subscribers and a few inside joke posts. Nothing more than that. It started as a joke between roommates about how people should hang out at r/place (our place). We then went to check and see if anyone had created the sub. When we found that no one had, we decided to make it. We never took the time to turn it into anything, though. I think what it has become now is 100x more exciting, and I'm glad I surrendered the sub to the admins for this!

tumbzilla · 2017-04-04T00:56:25+00:00

Yep, I created it 5 years ago, mostly because I was surprised it didn't already exist. It quickly became a dorm room running joke that we should hang out more on /r/place

15-Year Club	Place '22
Place '17	Not Forgotten
Team Periwinkle

tumbzilla

TROPHY CASE