And I am not even talking here about other ethical issues, training data, less junior job positions, job replacement of journalists with LLM-equipeed contractors, etc.

LLMs make my personal and work life so much better, but social life unbearable. Is it worth the trade-off? I guess it doesn't matter at this point.

My anecdotal experience from 20y of bodybuilding and doing ~3 cuts a year: for cutting, I tried IF, 6 meals a day, low fat, low carb, high fat true keto, balanced... everything works. And works equally well - this is backed by numerous studies. The only difference is the impact on health parameters (different will get worse on low fat vs high fat), satiety, and how easy it is for someone to sustain the diet and stay in a deficit. This will depend on the lifestyle and personal preferences. So my preferred way to cut is high protein, low carb, essential fats, a ton of fiber. When building muscle I go high everything but balanced.

Anything else and more is sectarianism and people bragging about their choices not having verified their true claimed efficacy or benefits.

Frictionless, pleasant, not thinking too much how to express things (and still managing to write them reasonably idiomatic), tends to support clean encapsulated code, quite rich environment/libraries, great tools (debuggers, profilers), safe, relatively fast, not many foot guns, zero build setup, on small project zero build times, trivial to create good functional simple UI, can get fancy dynamic with reflection when I need "magic".

Basically not many pain points that would make me rage quit and almost everything I'd want is simple to achieve.

Trilinear interpolates across three dimensions, such as 3D textures or mip chains. It is not a method for downsampling, but a method for filtering that interpolates two bilinear results, such as two bilinear filters of mip levels that were generated with "some" downsampling filter (which can be anything from box to Lanczos).

Anisotropic is a hybrid between trilinear across a smaller interpolation axis under perspective projection of a 3D asset and multiple taps along the longer axis. (More expensive)

One of many reasons why Google invented Transformers and many components of GPT pre-trainint, but ChatGPT caught them "by surprise" many years later.

And if you join as a PhD fresh grad (RS or SWE), L4 salary is ok, but not amazing compared to costs of living there. From L6 on it starts to be really really good.

Even being in elite research groups at the most prestigious companies you are evaluated on product and company Impact, which has nothing to do with how groundbreaking your research is, how many awards it gets, or how many cite it. I had colleagues at Google Research bitter that I was getting promoted (doing research addressing product needs - and later publishing it, "systems" papers that are frowned upon by "true" researchers), while with their highly cited theoretical papers they would get a "meet expectations" type of perf eval and never a promotion.

Don't get me wrong - those are miraculous drugs. First real non-stimulant low side effect appetite suppresion that will help millions. But let's wait for honest research on lean people before spreading marketing on how it improves overall health.

Also, how nobody mentions the need for increasing the dosage and tolerance build-up (just check reddits how much people end up having to take after months of continuous use). You cannot be on it "for life".

But I guess you know better than me. ¯\_(ツ)_/¯

If you can change the exposure or WB - it is what is the minimum practical/useful definition of a RAW.

In images, scrambling phase yields a completely different image. A single edge will have the same spectral content as pink/brown~ish noise, but they look completely unlike one another.

On GPUs, ML "just works" (inference and training) and are always order of magnitude faster than whatever CPU you have. TPUs work very well for some model architectures (old ones that they were optimized and designed for) and on some novel others can be actually slower than a CPU (because of gathers and similar) - this was my experience working on ML stuff as an ML Researcher at Google till 2022, maybe it got better but I doubt. Older TPUs were ok only for inference of those specific models and useless for training. And anything new I tried (fundamental part of research...) - the compiler would sonetimes just break with an internal error, most of the time just produce terrible and slow code, and bugs filed against it would stay open for years.

GPU is so much more than a matrix multiplier - it's a fully general, programmable processor. With excellent compilers, but most importantly - low level access that you don't need to rely on proprietary compiler engineers (like TPU ones) and anyone can develop something like Flash Attention. And as a side note: while a Transformer might be mostly matrix multiplication, many other models are not.

Chances of being caught are close to zero (I have contacted many times authors of papers who's work I was unable to replicate - most of the time zero reply, sometimes "yeah it was a honest mistake, oops"), super high competition (only a few tenured positions in all world's high visibility institutions per year), full control over student's future and being able to force them to do fraud (and later blame on them).

Obviously, not all, blah blah - but many academic scientists are the last people that should be doing science.

But my question remains - how do you scale up your approach to the already-full SF? How do you make it more affordable, as prices are insane due to demand >> supply? Or do you just envision a more sprawled, but similarly dense SF as the solution?

I grew up in Eastern Europe (Warsaw) in "commie" blocks and there was a lot of valid criticisms and problems (like poor quality of buildings, small apartments, or thin walls - but consider that they rebuilt whole Warsaw after it was completely grounded in WW2 in a decade or two!), but also a lot to love. Extremely walkable, safe, all amenities (cinemas, stores, cultural centers, playgrounds) in the walking distance, lots of trees and green, easy access to public transit. As a kid or teenager they were great. I preferred it 100x over suburbs where my parents moved later, and to typical American cityscapes. (And this is why I moved to NYC and love it)

Here is a fun and a bit provocative/exaggerated video https://youtu.be/1eIxUuuJX7Y

Everyone is different so I'm not forcing my perspective onto anyone, just worth considering - especially if you have not had such first hand experience (and the main objection to tenements comes from how depressing they look or American association of "projects = crime", which misses a lot of "why"). Feel free to disagree!

And apart from that, I don't think "more of small houses" solves anything. It has to create more car dependence and social isolation. And it does not really scale, where would you fit more of smaller homes in SF?

I agree with a lot, but like others - disagree with some.

My background: I've worked in tech for ~14 in all kinds of roles - from pure junior IC, through a "team lead" (something between an expert IC, a tech lead, and a manager), "tech lead," company's "technical architect" (highest level tech lead, peer to the technical director, but without any direct reports), and something akin to a tech director. Now I'm back to IC. Companies from small gamedev ones (80 people total, 15 engineers), medium gamedev (30 engineers and coding technical artists), huge gamedev (Ubisoft where you can have 100+ engineers and 1500 people total on a project), and for the last 7y "big tech".

The idea I would like to push back the most is that "your words have more weight". I have never had trouble getting my opinions heard, even if I didn't push them. Being the expert IC and "problem solver" sometimes I'd have even CEO asking me directly for advice and how to solve some issues (both technical and non-technical!). Not always following them, but I didn't expect that. Having an official title, in theory, you can use some "authority" to formally push those ideas. But... in practice, it does not work better. People will still go directly to the most technical experts. And if you abuse the position/authority/title (I hope I never did that, but that's not for me to judge...), it can cause resentment, pushback, and more disagreements. You will also hear less of gossip and honest feedback, to some engineers you becomes "not one of us anymore".

It can also destroy friendships. I had a great friend (meeting socially with our wives once a week, sharing interests) who was my peer and was then promoted to my lead. I still really liked them and wanted to stay friends. We always had technical disagreements (which were fine for peer ICs). Later, some of those technical disagreements and my bringing up issues publicly caused him to get bitter with me (as the upper management saw those and took my side on some occasions), and eventually stopped the friendship completely; after I left the company, they started ghosting me. :(

Similarly, on a few occasions, I agreed to lead/manage formally (in one case, it came from me - in other cases, I was asked to). I agreed because I thought, "Things are f-d up; I can solve them by being closer to the upper leadership and helping the team succeed." Man, I was so naive. :( I didn't have any more authority or power with the higher-ups, and there were more disagreements. They expected me to enforce policies I disagreed with. As you can imagine, this didn't last long, and I always ended up leaving the team/company and being super burnt out.

So now I'm happy to be a staff-level IC, an expert, and a "hacker," playing with problems hands-on and building my expertise further. The field grows so quickly that there is always something exciting and new to learn and do. I would happily be a tech lead of some project close to me (luckily, at Google and similar, it's flexible, per-project, and not formal), but I probably do not want to manage again. Maybe it will change, depends.