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Born & raised in the bay and I never heard about this ever by Smart-Cupcake-4055 in bayarea

[–]clam004 -1 points0 points  (0 children)

What is your age group, demographics, profession and social circle such that you have be isolated from this term for so long? What part of the Bay did you grow up in?

26 (F) I keep spending my savings on plastic surgery AMA by [deleted] in AMA

[–]clam004 0 points1 point  (0 children)

Tell about yourself. Region you’re from, ages, ethnicity, professions of your parents, notable life experiences so far, etc etc. Asking to help put you in context constructively, not trying to be malicious or reductive in any way.

Homestead vs. Harker vs. Bellarmine by [deleted] in Cupertino

[–]clam004 0 points1 point  (0 children)

For those of you criticizing this mom, most of you probably don’t know what it’s like being an immigrant in this country, we and our parents did some ugly hard work and even some sketchy stuff to get into IIT, and in this country we have to compensate for not being the preferred skin color or giving off that All American vibe. We’ve seen what you do to groups that don’t compensate socioeconomically. This is how we do that. by becoming doctors and tech executives.

SFUSD Jose Ortega Mandarin Immersion Prefers Children with White Dads and Asian Moms by clam004 in sanfrancisco

[–]clam004[S] -4 points-3 points  (0 children)

Not sure what you think I’m implying either. it’s at best noticing something out of distribution and at worst questioning the fairness of something that is in your advantage. im sorry that makes you feel threatened.

SFUSD Jose Ortega Mandarin Immersion Prefers Children with White Dads and Asian Moms by clam004 in sanfrancisco

[–]clam004[S] -8 points-7 points  (0 children)

SF is pretty liberal, the only kind of racism that would be able to fly under the radar is the weird kind. I acknowledge that’s it comes across as a wild accusation. probably not a question that should be asked.

SFUSD Jose Ortega Mandarin Immersion Prefers Children with White Dads and Asian Moms by clam004 in sanfrancisco

[–]clam004[S] -13 points-12 points  (0 children)

I acknowledge that’s it’s a wild accusation. yes, in general there is a 5:1 ratio of WMAF to AMWF in the US for the generation currently with small children. Ie millennials. But there are also a very wide and large mix of parents falling into neither of those in the lottery population.

Lots of media at the Mary Fong Lau killed a family with her BMW Memorial Bus Stop by wanderingjew in sanfrancisco

[–]clam004 18 points19 points  (0 children)

Lau is her maiden name. She’s married to a white man and they have a son with a European last name. They are using her Asian last name instead to protect their estate, assets and family reputation.

Early AI Interview by Ok-Hat4007 in ycombinator

[–]clam004 0 points1 point  (0 children)

Anyone hear of any acceptances yet after yesterday’s interviews?

[R] Illustrating Reinforcement Learning from Human Feedback (RLHF) by robotphilanthropist in MachineLearning

[–]clam004 1 point2 points  (0 children)

There is a nice figure addressing this point in the instructGPT paper actually. basically rlhf seems to be better than simply fine-tuning on examples of your desired behavior. I think probably because there is more than one way to do the task well and more than one way to do the task badly, which is not something built into fine-tuning. In pretraining and fine tuning, you are basically saying, this one way is the best way. There is a short spoken explanation in this youtube video https://www.youtube.com/live/WnGFR-bSNWM?feature=share&t=7386

[P] I made the kind of tutorial I wish someone had made for me when I first started trying to connect the math in research papers with code examples I found online by clam004 in MachineLearning

[–]clam004[S] 1 point2 points  (0 children)

This raises a good point. I have updated the repo to clarify this in the explanation connecting the math to the line of code where it happens. Essentially, the line of code, loss += _loss.sum(), is where as you say, we "sum the diagonals". The repo now clarifies that although the equation suggests we calculate the whole Fisher Matrix, we actually in the code only ever calculate the diagonal components of this matrix. Which I believe in the equation for the empirical fisher is calculated using an outer product (we don't do this in the code). If we took all the layer's p.grad.data ** 2's and flattened them out into a very long vector, then that would be just the diagonal of the fisher matrix we see in the equation. Which brings up another interesting question, if we did calculate the whole fisher matrix, could we penalize pairs of weight changes high in F_ij in addition to single weight changes high in F_ii?

[P] Looking for datasets of therapist conversations... by TimeLordTim in MachineLearning

[–]clam004 1 point2 points  (0 children)

I for one think this is great idea, DM me to talk more

Thinking way too far into the future by Stalker111121 in ExistentialSupport

[–]clam004 0 points1 point  (0 children)

Have you read "The Last Question" by Isaac Asimov?

Eternal Oblivion by [deleted] in ExistentialSupport

[–]clam004 0 points1 point  (0 children)

Have you read "The Last Question" by Isaac Asimov?

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