A few quick thoughts---I stayed around for 3-4 mins so please read this from the perspective of a (techy) user didn't explore much:
The good:
The UI is simple and clean. Definitely feels like something that you can start with.
The bad:
Email went to spam folder.
Nobody within 100km of me (which is the max distance) and I live in a very busy city. Maybe for launch, allow a distance of infinity so people that just want to meet new people stick around and don't forget about the website.
Also, I am not really a fan of setting an intent and not being able to change it for 24 hours. It wasn't mentioned anywhere either.
I couldn't explore more as thats as far as I could explore without any people around me.
WHO's responsibility is not to a single person. Their policies are designed for the society as a whole. Minimizing the possibility of infection for critical jobs is much more valuable than minimizing the infection probability to a single person. Society is more than just me or you or our families.
They could have taken the path you are suggesting (possibly under inconclusive benefits of other types of masks) but that could have backfired and caused a lot more dmg than good.
You can't expect an entity like WHO to solely care about you as a person.
I re-read my comment and do see a lot of "my" and "I" in there. I should have thought about that more.
WHO failed in their societal obligation by diminishing their credibility. The misinformation may have increased mask supply to critical workers for a short period, but at the cost of strengthening the anti-maskers' message in the long run. And that cost was much larger IMO.
They created a long-term problem in order to fix a short-term one.
> You can't expect an entity like WHO to solely care about you as a person.
No, of course not. My whole point here is that WHO did the PR equivalent of that CEO who chases quarterly earnings at the expense of their company's future. Except instead of money, they did it with public confidence.
This. And one of the main reasons that the paper from Google are routinely of high caliber is due to the internal review processes and your peers.
Publishing a piece of work for the sake of publishing by ignoring the processes that are put in place is outright irresponsible and that's the end of it.
The statement that "Academic debate is, in fact, done through conferences and journals" is not strictly true. Specially given that a lot of reviews in more popular conference are very hit and miss. You can submit the same paper to the same conference multiple times and get wildly different opinions on the same paper.
The variation in reviewers' response is often due their lack of knowledge and unfamiliarity with the problem. Take a look at the recent reviews on some of the more popular conferences on OpenReview.net. Most of the reviews don't have any substance and are often vague/generic.
I'd take the reviews from peers that I trust and are aware of my work more seriously than reviewers of conferences.
How is this different than picking up the phone and having your convo go through ATT/Verizon networks? or using your ISP? Both parties can "legally" work with authorities to wiretap you?
Are you worried that the (training) algorithms that run on your voice somehow end up leaking your identity? Or are you worried that someone at Google knows your voice?
Also, not sure if Google has this fact in their ToS but if they do, what is the issue?
Phone networks are not primarily advertising agencies, and they're regulated as utilities, so the difference is nontrivial.
And the personalized risk isn't from random strangers knowing your voice -- it's your stalker ex, or other bad actors, who might get way more insight into your life than you want
> Or are you worried that someone at Google knows your voice?
Google already knows who you are, now they know a bit more about you, including what you talk about, and of course your voice which probably can be used to locate you with all those "smart" speakers around.
Please don't compare tech companies with telecommunications, banks or other sectors. There are hundreds of years of laws and jurisprudence regulating all other sectors an "basically none" regulating tech.
For the record, I don't what to need an ad tech support and feel like the no named someone on the other side knows that I had sex with my wife last night.
Am I asking too much? Is tech ignorance my only refuge?
Will I need to censor myself all the time because I can never know if/when some bad it ashaming situation may occur?
Can't people really see how 24/7 digital surveillance isn't healthy?
Haven't we learned already society can't blindly trust corporations?
I am genuinely curious to see what types of "compute-intensive" applications fit the bill here. Outside of storage workloads (syncing data, etc.), why would you need a 100x improvement in data transfer rates between the machines? (We have TPUs and their specialized network architecture for ML-like workloads ...)
Physical distance between the machines in a DC prevents RAM style "shared-memory" architectures, at least ones that aim to have 30~60ns access times (10-20 meters). Unless there are new paradigms for computation in a distributed setting, I don't see the benefit for this ...
Also, what are the fundamental limitations/research problems of todays hardware that prevent us from building a 400G NIC? I cannot think of anything outside of PCI-e bus getting saturated. We already have 400G ports on switches ...
>I am genuinely curious to see what types of "compute-intensive" applications fit the bill here.
Well, for example, physical simulations using finite element or boundary value approaches. Pretty much anything you'd use with MPI or do on a supercomputer is going to run better on a machine with a nice network stack like this.
Even large scale storage (think backtesting on petabytes of options data) that uses a map-reduce paradigm and is properly sharded for the data access paths and aggregates would benefit from something like this.
Do you have numbers or papers that support your argument? That these applications are bottlenecked by the network?
There is a 2015 paper [1] that argues that improving network performance isn't gonna help MapReduce/data analytics type of jobs much:
" .. none of the workloads we studied could improve
by a median of more than 2% as a result of optimizing
network performance. We did not use especially high
bandwidth machines in getting this result: the m2.4xlarge
instances we used have a 1Gbps network link."
Granted things might have changed by now, but I am curious to see how and by how much?
The 2015 paper is obviously wrong or selling something; it's virtually always IO bound. Yes, I know many people assert otherwise; they're wrong.
Some map reduce loads, especially the kind that people running spark clusters want to do, end up moving a lot of data around. Either because the end user isn't thinking about what they're doing (95% of the time they're some DS dweeb who doesn't know how computers work), or because they need to solve a problem they didn't think of when they laid their data down.
I guess I cite myself, having done this sort of thing any number of times, and helped write a shardable columnar database engine which deals with such problems. If you don't want to cite me; go ask Art Whitney, Stevan Apter or Dennis Shasha, whose ideas I shamelessly steal. FWIIW around that timeframe I beat a 84 thread spark cluster grinding on parquet files with 1 thread in J (by a factor of approximately 10,000 -the spark job ran for days and never completed), basically because I understand that, no matter how many papers get written, data science problems are still IO bound.
I'm not sure about the typical demands on the fabric of FE-type codes, but a typical HPC cluster (university or national) is likely to spend much of its time on materials science work using DFT, which requires low latency rather than high bandwidth for short messages. Somewhere under http://archer.ac.uk there are usage statistics as an indication of the workload, though it varies month-to-month.
> I could ask them to go look up papers in Oakland, CCS and NDSS over the last couple of years and see if anything catches their fancy.
Isn't this exactly the major thing that is wrong with research today? Limiting work/creativity to a few well known conferences done by elites for elites? I read blog posts, posted daily here on HN, that are way more informative, honest, and replicable than many papers published in the three conferences you named.
> "elite" status. Some of this is deserved, because these people have done good work. But some of this is also just a publication cartel where everybody cites their friends' work and make it impossible for others to break into a field.
Elite status happens exactly because there are conferences like the ones you mentioned. If you work with an advisor that publishes in Oakland, your chances of getting a paper in Oakland gets increased multiplicatively. And hint, that's not because your ideas (or papers) are better than anybody else's.
> The larger point is that in a scenario where there are so many papers that nobody could possibly look at all of them will lead to a few groups accumulating all the citations and all the awards.
This is already happening. Look at all the "prestigious" conferences.
> where researchers don't have the PR muscle power to highlight unpublished stuff.
Who cares? If the work is worth anything, people will cite it. If not, it will remain as is. Why does it matter? Why do you care if 10 people cited your work or 100 people if you are happy with the work?
Unfortunately, nobody in this forsaken field (computer science) cares about the scientific aspect of the field anymore; everybody wants their name to be known and that's all there is to it. The measure of success is how many papers you publish in elite conferences ...
I do actually think that by breaking down all the barriers people care less about having their name in conference X or Y and more about the scientific aspect or citation cartels. First one is good, second one can be fixed (at least more easily than giving a few elites lots of power with no checks and balances).
> Isn't this exactly the major thing that is wrong with research today? Limiting work/creativity to a few well known conferences done by elites for elites? I read blog posts, posted daily here on HN, that are way more informative, honest, and replicable than many papers published in the three conferences you named.
I totally disagree. The quality of papers at the "elite" conferences is way higher than most things I've read on HN. What is an example of an HN post that in your opinion is better than equivalent academic research in that area?
> Elite status happens exactly because there are conferences like the ones you mentioned. If you work with an advisor that publishes in Oakland, your chances of getting a paper in Oakland gets increased multiplicatively. And hint, that's not because your ideas (or papers) are better than anybody else's.
Sure, having an advisor on the Oakland PC helps a great deal. But it doesn't follow that your work is just the same as everyone else. Have you peer reviewed papers for these conferences? A majority of submissions, even at the "elite" conferences are just junk. That doesn't mean everything that gets published is not junk, but the stuff that does get published is significantly better than the average submission.
> Who cares? If the work is worth anything, people will cite it. If not, it will remain as is. Why does it matter? Why do you care if 10 people cited your work or 100 people if you are happy with the work?
Because the point of my research is not to sit in an ivory tower and produce academese that no one cares about. The goal is to have real impact on computer system design, and in my specific case, push practitioners towards methodologies that make systems more secure. That's not going to happen if no one reads our work.
Another way of looking at it is that a lot of our work is funded by taxpayer money. They aren't paying us to have fun proving lemmas that no one else cares about, the taxpayer would like us to produce research that results in tangible improvements in computer system design. In the system that we have today, the only way to have this tangible impact is to produce high quality papers that other people read, cite and build on top of.
Unpopular opinion, but they aren't that far off with regards to academia. Academia has little scientific agenda at its core—most things boil down to money.
If you want to make a case for your idea on any topic, put money on that topic and professors and researchers work towards making a case for it (this is less true about math and (maybe?) physics but the farther you get from those topics, the more impact money has on results and ideas).
Academia (mostly? in the US) is just yet another institution that is solely driven by money.
> Academia has little scientific agenda at its core—most things boil down to money.
It's like you're right, but completely wrong at the same time... At it's core, scientific research should not have an agenda. Researchers are normally happy to do important things and they have good ideas.
Yes, the funding is a really big issue and lack of needed followups to interesting results of the initial sponsor often happens when the sponsor is not involved anymore. Researchers essentially either have to work for someone or come up with topics and then beg potentially-interested people for money. (aka research grants)
Academia being driven by money has less to do with academia and more with lack of money it needs to work on independent research.
You are assuming that everybody in this system is honest: researchers, funders, and companies. None of these entities need to be honest to do research or to come up with topics. This is a big fallacy with academic research: nobody needs to be honest or truthful, and as much as you like to believe they are, they have no reason to be honest. I have experienced this first hand during my PhD life.
> Researchers are normally happy to do important things and they have good ideas.
That's not how research works, however---at least not what I experienced. Usually a goal is the prerequisite of the funding. If that goal doesn't align up with the interest of the company/or the funder, there won't be any funding to begin with. That's a lie that researchers tell themselves, that they have the freedom to work on w/e they find amusing.
> Academia being driven by money has less to do with academia and more with lack of money it needs to work on independent research.
Sure. If academia was a utopia that wasn't so dependent on money (and fame), science would take over. That utopia isn't anywhere in sight, however. Try going through academic job market: a popular question you get is how you are going to bring money into the university. If you don't have a good answer, you won't get a position. As a professor, you will be spending 80%+ of your time writing grants or, as you put it, begging different companies for money. The other 20% is spent on classes and bureaucratic headaches. A good professor that I knew had a long rant on how she never gets to do research anymore (from a very well known university).
People twist words and data to make their point, get a publication, make a name for themselves, get more money, and repeat the cycle, all in the name of research and science.
My point isn't that the academic people as a whole are bad, but many of them are trying to survive and are willing to do w/e it takes to bring in money. It is very easy to abuse the bunch when people are trying to survive.
All I am suggesting is that you need to be critical when reading academic papers. Regardless of the content, topic, etc. read and decide for yourself---if it is a field that you are proficient in---or read opinions on counter points.
> This is a big fallacy with academic research: nobody needs to be honest or truthful, and as much as you like to believe they are, they have no reason to be honest.
They don't have to be as long as others can verify their findings. At some point, mistakes and dishonesty should be treated the same way.
> Usually a goal is the prerequisite of the funding. If that goal doesn't align up with the interest of the company/or the funder, there won't be any funding to begin with.
I think we're very much in agreement. I just don't put that as academia's problem, but rather explicitly on how we fund it. A.k.a blame the game not the player.
I completely agree with your observation. It's not that the Ph.D. prepares you for it, but that most people that pursue Ph.D. have that attribute.
I don't think all Ph.D. students or any ordinary engineer can take a vaguely defined research problem and make it succeed. Ph.D. doesn't necessarily prepare you for the research part; it does, however, prepare you to advertise a very /bad solution/ as a novel contribution. It wasn't always like this, but it has come to it. It takes credibility, curiosity, character, and of course, research skills to solve a vaguely defined problem---none of which are given to you by a Ph.D. degree.
I have worked at two FAANGs, and more often than not my interactions with Ph.D. degree holders have left a bad taste in my mouth. Speaking of which, there was one person that was "selling" an event timeline as a root cause analysis system that does "temporal" correlation (with no filtering or association at all) :). And another person that was advertising a DFS compilation of a neural net during the training phase (as opposed to the typical BFS that people do) as a superior and novel contribution that changes how we think about neural nets or something along those lines.
A good engineer would have laughed at both after carefully considering all aspects of the problem.
I suspect that Ph.D. "engineers" are more desirable because of their broader skillset (they have worked with more tools and have taken more classes) and also the fact that companies can hire them at almost the same cost as a BS/MS degree holders. Plus universities have already done some filtering on Ph.Ds.
I find there are 2 kinds of PhD holders in engineering, those who are diligent and capable and were able to follow through on a difficult problem for years; and those whose problem solving abilities are so impractical that they stayed in school for as long as possible.
The first is worth their weight in gold, the second is fairly easy to detect after a few git check-ins.
Actually I lied, there's a third kind, brilliant people that get bored with their job and write super-complicated frameworks to satiate that boredom. That's not restricted to PhDs but I see it more often with them.
There's so many people in the second category for so many reasons, its pretty much made "PhD" a "don't hire unless good reason" filter for me.
Reasons might include: couldn't make it in real jobs and delayed joining the the job force for as long as possible
doesn't want to be held accountable for actual working solutions and likes working towards "novelty"
enjoys approaching every problem with the most complicated possible solution they are aware of
thinks generalization is the only way to approach specific special-case problems, if they can't find a generalized solution then they think its unsolvable even when the special-case solution is fine
has grand research ideas they weren't able to convince anybody in academia to fund and think they can chip away at those ideas by cowing coworkers into working on it for them
likes being the "smart guy in the room" and builds a career of talking a lot with complex technobabble and buzzwords but has no idea what they're saying (I've encountered many many of these myself) -- often has mile long CVs as well
creditialists who think racking up pretend education credits is the most important thing in life
failed academics who point to their large private sector salaries as why they've ended up on the superior path than their old peers
and so on....these are literally descriptions of people I've encountered just in my current job over the past 5 years...it keeps going on and on.
Same. The real problem in my mind is the paradoxical complete inability to learn new skills that are suitable for the workplace and instead a complete reliance on the training they received in their programs...sometimes decades old.
Considering a PhD is supposed to provide skills for learning and tackling problems, the incredibly high percentage of PhDs I've worked with that are completely unable to do so has really really put me off of the credential.
It’s a little of both, and like most debates with that answer, it’s not a particularly interesting question.
Some PhD-holders were self-motivated before. Others learned it at school. Still others were motivated, but unfocused, and had to become
disciplined.
Everyone who has a strong opinion on the topic is, by definition, extrapolating from limited data. Moreover, even if every single PhD learned nothing in school, it’s still a useful signal if it enriches the pool of candidates who are self-motivated and independent.
