- SpaceX will land a human on Mars and create some super great marketing material. This will strongly galvanize interest in space. Many ambitious people will be interested in space projects or startups
- deep learning will continue to amaze people in being able to solve problems considered not well suited to it. Some of these applications will seem crazy in retrospect
- folks at OpenAI or Google will get something crazy to happen with a huge amount of compute. It won't feel like AGI but it'll make AGI seem way less insane
- theorem proving with deep learning will start to work
- material science using lots of compute and deep learning will start to work
- deep learning will be applied to fuzzing (finding vulnerabilities in software) and this will be a big thing by the end of the decade
- there will be some large scale multiagent AI projects aiming to learn intelligence through just big simulations of civilization but they will not have interesting results. Definitely happens at OpenAI and possibly elsewhere. They really expect this to work but it won't
- Apple releases an AR headset. Oculus turns into an AR effort instead of VR. The VR wars turn into the AR wars. Lots of money pumped into it. Unclear if it actually becomes the next mass platform, but there's a small chance
- crypto people will find success approaching incentive design problems in more traditional avenues like large organizations and charter cities. Most crypto projects will be dead in the water, including Ethereum, but there will be diehard enthusiasts who stick to it. The money will dry up, forcing others out. Cryptocurrency, like BTC, will still be a big thing on the internet
- teleop robots. Globalization of physical labor starts to happen. It will seem like an emerging trend by the end of the decade
- self driving cars will be seen to be largely a fad, with lots of wasted money
- there's a chance the olivine beach climate change project gets a huge amount of traction
- student loans and for profit colleges in the United States have some kind of reckoning. People stop believing in college: more people all over the world think like Lambda School and the software industry
- senior software engineer salaries in the Bay Area continue to climb
- Silicon Valley stops being so obsessed with China. It's more obvious that Chinese innovation is heavily lagging behind
- defense technology starts to capture the attention of more of Silicon Valley and the innovative class. Anti-defense stance stops being the default. Tech bro patriotism: more people think like Anduril. This leads to some really crazy defense capabilities of the US. E.g, auto targeting killer drones
- Social media usage per person goes down, for high income people
- YC is no longer cool at the end of the decade, but hacker news still is.
- lifestyle software businesses continue to be seen a lot more positively in the industry: more software engineers think like patio11/csallen/levelsio. Starting a small software business becomes more of a viable career path and seen as more responsible and mature than the VC unicorn path.
- meat alternatives grow faster than anyone expected them to
- Tesla is the most valuable car company but still hasn't figured out full self driving
- sci-fi reading and blog post style writing will be a major status symbol in the tech industry
- Bay Area will be less dominant in interesting tech startups than it is today, because of immigration and housing. The next place will be the internet or somewhere open to outsiders like Estonia, not China
- Donald Trump will do something too shocking and it will actually end his career. Society will learn an antibody to his populism, but it might be a long time after he's president. Will happen by the end of the decade though
- deep learning is a very centralizing technology. Even bigger tech companies will be started where the value they create is their machine learning network effect. They might not be as big as 1T by the end of the decade but they'll get there in another 10 years
- more power shifts from government to private enterprise
- tech companies remain underrated and continue to grow and have way bigger market caps
- VR porn ends up driving adoption of the current set of VR hardware. Funny but FB executives won't be happy about this and that'll make them look to AR.
- Facebook social VR with strangers doesn't work. But FB social VR with your real life friends might work and be really popular. This would be the main application of VR, if any : then it'll morph into AR
- religion continues its decline. New internet ideologies continue to proliferate. Some of them will be pretty weird yet have a lot of impact, like the alt-right did this decade
- the penny is abolished in the United States
- US inflation is a lot higher than it has been in the past; US treasury bonds not seen as super safe anymore
- if there's a recession, it won't affect the economy as uniformly as historical recessions (overall hit may still be really big, but higher percentage of people will end up well off). More variety in the economy and people's lives where it's not as correlated
- tech companies funding more and more media/content (like Netflix/Amazon, but also upstarts). Traditional media gets eaten by tech-enabled companies
- everyone worldwide has a lot less sex
- marijuana and psylicobin legalized federally in the US; stigma against drugs on the decline globally (related to decline in religion + rise of internet ideologies)
- more local manufacturing. Specialized manufacturing countries/cities stop making as much sense. Let going to China to make your hardware thing; you'll just do it wherever.
- the US will be more obsessed with Africa than China (may take 25y instead of 10y; caused by population dynamics)
- 10-30% more happens in 2020s than 2010s; accelerating progress but it's not very noticeable yet
- Stripe becomes a gigantic company Because of that, the SaaS economy goes global: microSaaS is the new doctor/lawyer/engineer, especially in India and Africa
Faces... Videos of all kinds of people and places.. Friend networks (via who you follow).. What videos you like showing what you think.. They have a lot of data
Posting Nat Friedman's tweets here so they're easier to read - they're doing more than most companies about the whole thing, not sure where the vitriol in these comments is coming from:
It is painful for me to hear how trade restrictions have hurt people. We have gone to great lengths to do no more than what is required by the law, but of course people are still affected. GitHub is subject to US trade law, just like any company that does business in the US.
To comply with US sanctions, we unfortunately had to implement new restrictions on private repos and paid accounts in Iran, Syria, and Crimea.
Public repos remain available to developers everywhere – open source repos are NOT affected.
The restrictions are based on place of residence and location, not on nationality or heritage. If someone was flagged in error, they can fill out a form to get the restrictions lifted on their account within hours.
Users with restricted private repos can also choose to make them public. Our understanding of the law does not give us the option to give anyone advance notice of restrictions.
We're not doing this because we want to; we're doing it because we have to. GitHub will continue to advocate vigorously with governments around the world for policies that protect software developers and the global open source community.
It's the nature of economic sanctions that there are real people's livelihoods which are directly affected. That happens with all economic sanctions... nothing unique about this one
I don’t think that it would have been different if someone else was the president. Pre-Trump I had a vacation in Cuba and since I knew that the internet is a luxury there I made Spanish available offline on Google Translate. Works great, then I made the mistake to launch the app when I hade one hour access to the internet in Havana and puff translate is gone. I’m not allowed to use it there. That surely destroyed the communists.
Hmm this blog post and the website doesn't mention that this dataset was mostly annotated by Scale (scale.ai), as part of a partnership with Lyft ... We're going to publish a blog post about this soon, but if anyone at Lyft is reading this, please figure out how to reasonably credit Scale since I doubt leaving out Scale completely from the announcement is in the spirit of the agreement. Scale should probably also be added to the bibliography and website in some form
Contrast this with the nuScenes website, which was also annotated by Scale, and whose data format set the standard for this dataset: they credit Scale pretty reasonably
This comment does not represent the company's viewpoint, and cardigan is not speaking on behalf of Scale.
We are very excited to have been able to work with Lyft in open-sourcing this dataset and advancing the research community. We are also very grateful to Lyft for choosing to leverage our point cloud viewer and have credited the annotations to us on their launch page.
Hopefully not. Cardigan obviously is has the company's interest in mind, even if perhaps the execution is a little flawed. Cardigan has just learnt a lot about PR and also gave a lot of free airtime to Scale.
Also hopefully Scale will use this opportunity to educate team members about situations like this.
That’s a strange take on this. Not all staff are authorized to speak on the company’s behalf. That’s true almost anywhere I’ve worked. Your efforts cannot always be recognized externally. NDAs and various other types of contracts commonly outline that.
I would be surprised if many people here really just assumed that a pseudonymous user chatting with us in the HN comments was speaking on behalf of the company in an official capacity. I mean, obviously there are legal niceties to be observed and he should have appended the usual disclaimers, blah blah blah, but we do have common sense here right?
No, people don't have common sense. People should not post publicly on behalf of their employer without running it by a manager. This is lesson one at every major corporate introduction and I now understand why, because people don't have common sense.
I didn't say anything about whether he should or should not have spoken out about the deal. And I specifically said that common sense doesn't cut the mustard legally. But I am asserting that the damage from people supposedly assuming that he was speaking officially is speculative and likely zero.
This isn’t really about employee recognition. The whole comment was about attribution for the company and marketing the partnership with Scale. Which is pretty standard in some business arrangements but which wasn’t the case here, which the employee wasn’t aware of and turned out to not that big of a deal for scale. Plenty of companies work in the background supporting other. Businesses and don’t always need attribution.
OP is trying to pigeonhole this into some sort of anti capitalist diatribe by trying to make it about individual employees wanting recognition and some big evil company is treating them like invisible cogs in the machine... which doesn’t make much sense since he asked for the company itself to be attributed, not individuals. It’s up to the company to reward and recognize employee contributions, not in some 3rd party partners announcements.
Plus he was always free to comment how he helped work on it or letting people know Scale had a role in helping make it (which are both common on HN). Only if the parent company tried to suppress that would this argument make any sense. But I don’t know why I’m bothering to counter such a position.
that's a strange response. i'm already clearly critiquing the dominant paradigm, capitalism. why would you just itemise a bunch of conventions from this paradigm, which i likely disagree with?
do you need hn to be an agreeable echo chamber for you?
capitalism depends on people not thinking thoroughly about the "deal" they are being drawn into. i'm here to harm this situation.
Quick tip: voice concerns about partners in private. Lyft will probably be happy to credit Scale more - it was likely an honest mistake. But now you dragged them through the mud publicly, which is going to make big companies less likely to work with Scale in the future.
Yeah, this comment to me really gives off a bad impression of Scale as a whole. My immediate reaction, assuming this is how Scale normally deals with PR, is that this company is still far too immature to be properly handling any sort of legitimate partnership.
FYI, you’re unlikely to solve any of your problems airing grievances on a public forum instead of just directly emailing the people involved.
If you are an officer of scale you should take this offline. If not then you’re probably not authorized to speak on behalf of scale. Check your NDAs and service agreements. This is in such poor taste, anyone who would consider scale’s service now has to consider this sort of public commentary.
Out of curiosity, isn't Lyft just a customer that pays Scale for annotation services? Or is there a reason for this to be more of a partnership and less of a customer-client relationship?
yeah, i'd say so. what if lyft's lidar manufacturers said that they should be included in this release because it's their lidars? I agree, it doesnt really need mentioning
OP here, just waking up (I'm remote) - I can't edit my original comments so let me modify them here:
I wasn't involved in our communications with Lyft, so I was talking about something I didn't know much about. My audience was just the anonymous commenteriat: turns out a lot of people whose opinion makes a material difference to Lyft/Scale read these comments too. Sorry for not realizing that; I probably wouldn't have posted an uninformed personal opinion had I realized that.
I was being way too aggressive - genuinely sorry to anyone at Lyft who felt maligned by these comments. I woke up to 20 messages from coworkers who told me I was being an ass - genuinely sorry :(
Also I really should've clarified I was not speaking on behalf of the company: this was just a personal, uninformed opinion.
I cannot go into the details I learned about Scale's agreement with Lyft since it's confidential
I seriously suggest you to add "Disclaimer" to every comment you leave on threads related to your company (see boulos' comments for example here on HN).
Also, and I really mean this in a friendliest way possible, take a pause commenting here. You're not doing yourself a favor. I suggest you talk to your PR/marketing department before exposing more internal details, or run comments by them before posting.
Word of advice. If someone is paying you for a service (Lyft in this case), you really should think twice, three times, four times, before you disparage them in public. Live and learn. Good luck.
Also, the viewer packaged with nuScenes was built by Steven Hao from Scale, and while it was packaged as part of nuScenes it should probably be called Scale's viewer instead of nuScenes' viewer. The original viewer in the nuscenes SDK has the Scale logo, but it looks like Lyft removed that in the fork. Maybe a bit of public shaming will fix that...
Dear Lyft marketing person who wrote this: we are a data labeling company, and you may think that means we have a bunch of useless bozos working here like most other data labeling companies, but that's not true - e.g, Steven is one of the smartest people in the world - https://stats.ioinformatics.org/people/3113 - he learns ridiculously quickly - e.g, gets to number one on random video games in a few weeks and learned to boulder L10 in a few months from scratch (normally takes years/decades and most climbers never get there)
At first I was on kind of on your side against the other comments telling you to delete your other comment. I think its important to set the record straight if you can as early as possible. A small retraction/correction isn't guaranteed to make the frontpage of HN again.
But then this comment took it into a weird turn with how fast steven can learn rock climbing (seriously, i am still kind of unsure if we're talking about rock climbing because its so random and unrelated).
There is no such thing. They have to have meant v10, and climbing v10 "in a few months" is an incredibly skeptical claim.
Without some kind of gymnast background I honestly don't think it's possible. Even 0 to v10 in a year is hard to believe. I've heard of phenoms doing it in 2 or 3 years, and don't doubt a year is possible... but a few months? Kind of like going from couch to sub 5-minute mile in a few months.
I've had it with you Scale.AI people always trying to take credit for Lyft's work. We've been working weekends and nights for years, even the hourly workers have had to take unpaid overtime. All that time, I've never seen Scale.AI do extra work to help us before a big deadline.
Check out my other comment on this thread. I interviewed these folks and wrote the blog post (got lots of feedback from friends and design help from our awesome designers) - I'm a software engineer, not a PR department, lol :P
I tried to pick the answers which were most well written, not the ones which were most positive/negative. Personally I do think this is representative of the labelers who've stuck with us, but at this point don't have the energy to argue this; hopefully my other comment is convincing (i.e, there isn't a high bar to making people happy when their next best alternative is a lot worse)
I'm a software engineer at Scale and the author of this blog post.
Let's talk about Venezuela for a second. ~75% of the population lost >19lb in body weight in a year according to this survey: https://www.upi.com/Top_News/World-News/2017/02/19/Venezuela... It's unbelievable that we haven't figured out how to prevent people from living like that in the 21st century. I think it's totally deplorable and honestly an affront to humanity.
You know what I think the most effective way to combat large scale poverty is? Not by working for an aid agency (we've all heard the horror stories) - instead, how about making those people economically valuable? The internet is an amazing way to reach those people - and guess what - Scale is actually doing that (evidence: these stories). If we continue to grow, we'll be doing that even more.
To be clear, this isn't the main mission of the company - but I don't see how anyone could think it isn't a great side effect. Hence the title of the blog post - positive externalities.
I believe the OP assumed, as a company, Scale means well and that the team is potentially bringing better wages to people who don't traditionally have it.
The outright dismissal of OP's criticisms/comments doesn't allow for a discussion in that data entry is a very tedious job along with maybe there are people who are unhappy with the work but very happy with the pay (which I think is perfectly okay).
The comment reads as "I'm going to tell you off" with the `- and guess what -`.
Sorry I should've explicitly said this, but I was responding to just this part, not the part about the job being tedious:
But I do see a lot of data around company engagement.
There’s basically no chance this level of positivity is ubiquitous for them
When a company hires many regular people in a place like Venezuela, why wouldn't there be ubiquitous positivity? I'm not from the US; I've lived in a few places with extreme poverty; maybe this is based too much off of personal experience. i.e, I don't think the data the OP is referring to applies here. Getting money for basic needs (if you wouldn't have it otherwise) likely dominates most other concerns, including the work being tedious. From another comment, it looks like the OP's other experience with labelers is in the US - where the next best alternatives they can imagine are a lot better - so it makes sense that those labelers aren't as happy.
I guess what you're asking is - how many of these people find their job tedious? I will say it's a lot less tedious than you might imagine as a first impression - e.g, if you see something weird in some data, you talk to other people about it; if you get good, you train people; when doing a new project, you're learning from your coworkers; if you get really good, you might be asked to help develop training materials, etc. So there's a lot of interacting with other people, and a sense of community. For me personally, I honestly find it meditative to label a lot of data - it feels kind of like tending to a large garden, maybe even fulfilling some deep OCD/obsessiveness desire. Some of our labelers find it meaningful that they're contributing to robotics / self driving cars - e.g, the last interviewee in the blog post.
Back to your question though - how many of these people find their job tedious? I'm not sure how to ask the question to them in a way which gives a satisfactory answer. e.g, I'd expect if we just asked "do you feel like your work is tedious?" the answer would be dominated by people's realistic alternatives, and wouldn't have much to do with the job itself. (so we'd get similarly positive responses) If you can think of a better way to frame that question, I'm happy to ask it and post the responses here :-)
I heard a talk by Edward James Olmos in which he made the point that if US companies think of themselves as socially responsible then they should pay non-US workers the same wage as they pay their US workers.
Given that all of Scale's open positions, and current FT employees presumably, are in San Francisco (and not remote), a pessimistic view would be that the data labelers are subsidizing Scale's lifestyle choices.
This is so interesting. Because it can't be this hard to do this kind of physics simulation at the correct level of fidelity if you want to apply RL to physical problems
What does RL have to do with this? The laws governing gravity are already well understood and specialized code will always be more computationally efficient while having less unexplainable behavior. Why would you use a slower, more opaque method to accomplish the same thing?
I think you're referring to the SupportAssist Client being an HTTP server - while it is weird that they exposed all those other routes, the driver install route allows for drivers to be installed from a website (which a named pipe would not).
I wouldn't characterize it as "pure laziness" - more a questionable feature
The whole process starts with the installation of aoftware to identify the computer. The vulnerable service is part of that. Thw list of drivers could just as well be shown by a local GUI ghat is started by thenbrowser through an URL handler registered in the system. There would be no need for any of this frankly stupid Rube Goldberg website/webservers interaction. It would be one less TCP server socket in the system.
Scale | Backend/Full Stack and Frontend and ML | SF or Remote
We label data for your favorite computer vision teams. Our mission is to accelerate the development of AI applications - we believe building a high quality labelled dataset is the biggest bottleneck to deploying supervised deep learning systems, so that's what we're tackling first.
We've had phenomenal breakout revenue, raised an $18 MM series B, and are looking to grow our team of 55.
We're looking for engineers to work on projects ranging from making labelling more efficient via front-end work/ML work to launching new product lines demanded by our existing customer base.
- deep learning will continue to amaze people in being able to solve problems considered not well suited to it. Some of these applications will seem crazy in retrospect
- folks at OpenAI or Google will get something crazy to happen with a huge amount of compute. It won't feel like AGI but it'll make AGI seem way less insane
- theorem proving with deep learning will start to work
- material science using lots of compute and deep learning will start to work
- deep learning will be applied to fuzzing (finding vulnerabilities in software) and this will be a big thing by the end of the decade
- there will be some large scale multiagent AI projects aiming to learn intelligence through just big simulations of civilization but they will not have interesting results. Definitely happens at OpenAI and possibly elsewhere. They really expect this to work but it won't
- Apple releases an AR headset. Oculus turns into an AR effort instead of VR. The VR wars turn into the AR wars. Lots of money pumped into it. Unclear if it actually becomes the next mass platform, but there's a small chance
- crypto people will find success approaching incentive design problems in more traditional avenues like large organizations and charter cities. Most crypto projects will be dead in the water, including Ethereum, but there will be diehard enthusiasts who stick to it. The money will dry up, forcing others out. Cryptocurrency, like BTC, will still be a big thing on the internet
- teleop robots. Globalization of physical labor starts to happen. It will seem like an emerging trend by the end of the decade
- self driving cars will be seen to be largely a fad, with lots of wasted money
- there's a chance the olivine beach climate change project gets a huge amount of traction
- student loans and for profit colleges in the United States have some kind of reckoning. People stop believing in college: more people all over the world think like Lambda School and the software industry
- senior software engineer salaries in the Bay Area continue to climb
- Silicon Valley stops being so obsessed with China. It's more obvious that Chinese innovation is heavily lagging behind
- defense technology starts to capture the attention of more of Silicon Valley and the innovative class. Anti-defense stance stops being the default. Tech bro patriotism: more people think like Anduril. This leads to some really crazy defense capabilities of the US. E.g, auto targeting killer drones
- Social media usage per person goes down, for high income people
- YC is no longer cool at the end of the decade, but hacker news still is.
- lifestyle software businesses continue to be seen a lot more positively in the industry: more software engineers think like patio11/csallen/levelsio. Starting a small software business becomes more of a viable career path and seen as more responsible and mature than the VC unicorn path.
- meat alternatives grow faster than anyone expected them to
- Tesla is the most valuable car company but still hasn't figured out full self driving
- sci-fi reading and blog post style writing will be a major status symbol in the tech industry
- Bay Area will be less dominant in interesting tech startups than it is today, because of immigration and housing. The next place will be the internet or somewhere open to outsiders like Estonia, not China
- Donald Trump will do something too shocking and it will actually end his career. Society will learn an antibody to his populism, but it might be a long time after he's president. Will happen by the end of the decade though
- deep learning is a very centralizing technology. Even bigger tech companies will be started where the value they create is their machine learning network effect. They might not be as big as 1T by the end of the decade but they'll get there in another 10 years
- more power shifts from government to private enterprise
- tech companies remain underrated and continue to grow and have way bigger market caps
- VR porn ends up driving adoption of the current set of VR hardware. Funny but FB executives won't be happy about this and that'll make them look to AR.
- Facebook social VR with strangers doesn't work. But FB social VR with your real life friends might work and be really popular. This would be the main application of VR, if any : then it'll morph into AR
- religion continues its decline. New internet ideologies continue to proliferate. Some of them will be pretty weird yet have a lot of impact, like the alt-right did this decade
- the penny is abolished in the United States
- US inflation is a lot higher than it has been in the past; US treasury bonds not seen as super safe anymore
- if there's a recession, it won't affect the economy as uniformly as historical recessions (overall hit may still be really big, but higher percentage of people will end up well off). More variety in the economy and people's lives where it's not as correlated
- tech companies funding more and more media/content (like Netflix/Amazon, but also upstarts). Traditional media gets eaten by tech-enabled companies
- everyone worldwide has a lot less sex
- marijuana and psylicobin legalized federally in the US; stigma against drugs on the decline globally (related to decline in religion + rise of internet ideologies)
- more local manufacturing. Specialized manufacturing countries/cities stop making as much sense. Let going to China to make your hardware thing; you'll just do it wherever.
- the US will be more obsessed with Africa than China (may take 25y instead of 10y; caused by population dynamics)
- 10-30% more happens in 2020s than 2010s; accelerating progress but it's not very noticeable yet
- Stripe becomes a gigantic company Because of that, the SaaS economy goes global: microSaaS is the new doctor/lawyer/engineer, especially in India and Africa