This administration is both fundamentally anti-science and wants to enforce political control over all government institutions. Science was never a particularly stable work environment, but the sheer insanity you have now makes it a deeply unattractive place. You have no idea if your grant might be denied, or even canceled at any point later by some political commissar that doesn't understand science.
And it's not just particular topics they hate, they hate the entire system and institutions. And they try to either break them and force them to adopt their political views, or they attack their funding or use any other powers to dismantle them.
It is far worse than "this administration", the population in general are vastly undereducated, to the degree they do not even realize how serious this is.
There has been a massive, decades long educational failure in the United States, and probably the entire western hemisphere of culture: no where are people taught how to manage disagreement. due to that, we have this moronic destruction taking place where "idiots of authority" see no reason not to dismantle anything that irritates them, and nobody has the langage to explain nor the peer power to stop the desolation of our entire supporting infrastructure. All because idiots of power do not like being told and proved they are wrong. So, power removed the education that taught people how to debate without emotions, and here we are.
Science, or more specific to what we're talking about, public research which happens mostly in universities, has turned political long before this administration.
That's the simple reality. Administrations impose their politics, but also universities do the same, and they're not any more noble for doing so.
Research groups need to have more independence and that can only happens through a very meritocratic funding process, and also, at the risk of sounding like a STEM lord, by being very cynical and realizing that not all fields of research merit the same amount of funding. Countries like China have already realiezed this.
> realizing that not all fields of research merit the same amount of funding
Unless america does it _very_ different than the rest of the western world, this is already the case. STEM research receive way more public funding and have way more PhDs than other fields, in my country it's almost two order of magnitude (this has to do with the cost of instrumentation mostly, but not only).
On the "science have turned political", yes, but that has always been the case. You can be political and non-partisan. UNSCEAR has been political from its creation, but is still non-partisan, anybody can use its research to make partisan proposition on nuclear. Same for WHO, it was _obvisouly_ political, advanced the interest of the first world in poorer countries, but it stayed non-partisan. This is probably the same for any medical research: obviously what is researched is political. Non-partisan though. Just because heart attack research was done by, with and for men, women also benefit from the research (although to a way lower degree until like 2010).
The only counter-example i can think of is the GIEC group3. I don't think it is partisan, but i can hear arguments that say that it is, and debate. But it has the lowest amount of funding of the 3 groups, and Group 1 and 2 are not partisan at all.
What happens right now is vastly different than before. Of course there are different priorities in funding for each administration, but those are usually more gradual shifts and especially don't cancel running grants arbitrarily.
And if you think this administration is prioritizing science with actual applications, I have a bridge to sell to you. The cuts they made are not sensible policy, they are inherently destructive and wasteful. They aborted studies that were still running, so a lot of money was spent and we'll never get any results from that because they were not finished.
Just lies upon lies. Always the same weak rhetoric of "it's both sides!". The truth is that science didn't get more political, the right is just going in a direction orthogonal to material reality.
Science will appear political to you if you claim that climate change isn't real, that vaccines and Tylenol give autism, that oil prices will soon go down when the wells are destroyed, that the economy is hotter than ever when everything's going to shit, that the weather channel is just anti-American and woke when they predict rain for the UFC Freedom 250 held for the emperor's birthday...
> 30-50% of engineers on core teams have been forcefully reassigned to data labeling and RLHF, upsetting folks even more.
This really doesn't sound believable to me, but who knows with all the craziness going on. Software developers in the US are seriously expensive, using them for data labeling would be a waste of resources. And the percentage sounds very high, unless "core teams" is only a small subset of the total developer count.
> Software developers in the US are seriously expensive, using them for data labeling would be a waste of resources.
The frontier work is on labeling and training expert content, by experts. It's unglamorous work and almost certainly doesn't warrant FAANG pay, but neither did most of the work that most FAANG engineers were already doing. But it does require competent talent from the expert domain.
Like their peer companies, Meta is still sitting on a huge pool of vetted-as-competant workers from the hiring boom and expert AI training is the most ripe business opportunity in a fragile economy where pretty much every comparable opportunity has evaporated.
Yes, this is not labeling what is an apple and what is a pear. "Annotation" does not do this work justice.
For a coding agent, for example, there is *very detailed* analysis of the turns and ranking of different portions of the conversation.
Adherence or deviation from specific rules matters. Writing quality matters. Expertise in the topic under discussion matters. Having intuition for the tone and beat of a good conversation matters.
Scoring a 15-20 turn conversation can easily take two and a half hours.
Clicking submit does not mean the author is done. Many annotations will be turned back to them by a reviewer to touch up in some way.
This work can be far more mentally taxing than programming, is measured much more by completions more of a timed exercise than SWE.
FWIW, Meta employees would probably make great coding agent conversation annotators. But it is absolutely not SWE and they won't enjoy it (for long).
I doubt it'll pay off. Let's face it, the average FB engineer is no better than the average Polish engineer, and the Polish guy is 20x cheaper. If you wanted cost-effective labeling you'd send it to Poland. Or better, Chile.
They’ve largely filtered their employees for people who have a mental breakdown if they don’t get 110% on a 100% scale or get the top of the top rating because they’ve done that their whole life until they got their first job at the tender age of 25-28 after getting their masters or PhD.
I’ve met too many meta members who have stories about their direct reports or peers who had a crashout because they got Exceeds Expectations and a mid 5 figure raise instead of Greatly Exceeds Expectations with a higher 5 figure raise not because of the money but because of not getting the top score.
I’m pretty sure zuck is being a rational sociopath and realizing he can use the PSC system to get these people to widely work against their best interests due to their ego.
idk... In their own way these types of people who have blinders on to such a degree that they crashout over such things are also sociopaths...
Seems like a side effect of the k shaped economy... our society increasingly doesn't have rewards for normal hardworking people. Given tech has been disrupting blue collar jobs for decades I have a hard time feeling sorry for them. Working at Meta already meant you were chasing a bag knowing the product was more or less social poison anyway. It doesn't seem to me that Zuck is uniquely culpable... maybe he's just the best one at the game they're all playing...
The fact he still cares so much about Meta when he is a billionaire is just like those crashouts. Again, it's the same type of person. He's just better at it than they are.
I have no empathy for the types of people who got layd off from meta who can’t see the similarities between them and the industry they disrupted.
I advocated for people who lost their jobs due to tech disruption to learn how to become software engineer not from a place of superiority but from a place of “this is one of the last places you can be self taught and earn a middle class income”
I am saying this has now hit the tech world and I will hold zuck culpable, although not uniquely since that requires a set of 1, but because he’s in charge of one of the top 10 companies in terms of big tech.
You don’t get to be that rich and that in charge of decisions, without holding responsibility. If you want to claim otherwise, then cool, you shouldn’t complain when we take all the assets you are apparently not responsible for.
Zuck literally said that he wants folks with higher intelligence on the Applied Intelligence team. And the best way to do that was to move folks internally, since they were "intelligent" enough to pass the Meta interviews.
Soooo, yes it is a waste of resources ($$$). But this was the initial intention.
The belief that engineers are not doing anything for x amount of time that could be better spent on other immediately measurable things is as old as the profession itself.
Ironically this vanishes when the tables are turned and we ask for things like better hardware or software. There are plenty of us here with stories of how much effort it took to convince employers that SSDs were worth it when they were new, small, and very expensive.
One of the funniest things is how hard it was to get approval for a $100 software license but now people are being encouraged to burn thousands on tokens.
see also: we're all developing on min spec Macbook Pros while being encouraged to burn > max spec Macbook Pros cost in tokens/month while still waiting for builds to compile.
I can't give you exact numbers, but this is line with what I'm hearing through the grapevine. Lots of senior managers being converted back to ICs as well.
A lot of people are going to leave as soon as they hit their next vest.
My partner works there as an engineer. The org they work in had loads of people transferred to the "AAI" org doing data labelling. I find it almost unbelievable as well, but it is true.
I don't know what Cold Harbor means in a Meta context, but its interesting that its named after the battle that exemplified Grant's strategy of attrition during the American Civil War. I suspect it means waves of engineers ground down against the defenses of OpenAI/Anthropic in the hopes of eventually finding a crack. Might be best to get out while you can.
> I don't know what Cold Harbor means in a Meta context
Cold Harbor is a reference to the TV show Severance.
Without going into any real spoilers it was the code name of a data classification project so mysterious that the people working on it weren't allowed to know what they were working on (and yes, the project in the show was probably named after the battle in the Civil War).
The Meta connection is that there are some humorous parallels between that project and a project involving people tagging data to train technology to replace themselves, and just the overall creepy dystopian vibe of both the fictional and real-world companies (and founders) involved.
I totally agree, it sounds unbelievable… Problem is, I’m on one of these core infrastructure teams, and for my team at least we lost between 50-75% of our engineers to the AI org. Most of the other infra teams I collaborate with have a similar story
>using them for data labeling would be a waste of resources
Would it? It seems like they can spend a few months extracting intelligence and "taste" from their engineers then get years worth of it back from the AI.
I wouldn't trust any engineers I know of with their "taste". At best it's a highly skewed view of the world. At worst, it's outright opposite to genpop.
Are there any examples of this actually working? I keep seeing this fantasy repeated but have not seen a plausible explanation for how they wouldn't be contibuting to the pile of negative examples which are just as valuable if not more.
what about just... becoming mediocre? engineers are already infamously lazy at reviewing PRs. how is Meta incentivizing these Data Labelers to give a shit and actually scrutinize the AI-generated code they're supposed to be reviewing? what's the reward structure? what prevents engineers from flagging minor nitpicks all day while they look at LinkedIn?
Probably forcing them to review each other's work to panopticon "quality," and keeping track of the average throughput per engineer so if people fall behind the taskmasters can pay them a visit.
Poison pilling skills is a thing, though finding evidence for it is difficult given the crux is an absence of information. The baseline instruction and training is given to the model by the expert, but edge cases are willfully neglected. The degree of neglect generally determines how detectable it is, but if all the SMEs are in on it a lot of them will probably persist. Effectiveness and impact are obviously relative to the system and the edge case. Not particularly different from the fallout previously seen during the offshoring era.
Have you heard about the various startups that specialize in expert data labeling, like Mercor? They can pay $100-$200/hr for highly specialized work, who knows how much they charge their clients. Translated to an annual wage, that's definitely in the SF/SV engineer range
As others have commented, some of the training is very specialized.
I believe it, because it makes a kind of sense. Post-training has a huge impact on how well LLMs perform, and labeled data is what determines the effectiveness of post-training. This is why companies like Anthropic are so worried about distillation.
So if you have access to a large number of highly skilled people, and you really don't absolutely need them to do other things, why wouldn't you force data labeling tasks on them?
Facebook is also planning a 10% layoff, so this also works as encouragement for people to leave voluntarily.
(Before you downvote me, note that I'm not endorsing this or saying it's a good idea. I'm just saying that I believe it's true, because I can see how Facebook's leadership would think it's a good idea.)
> I doubt that you get high quality from forced reassignments
Their bonuses depend on it. They'll have to play ball unless they have other jobs lined up, are ready to retire early, or prepared to be on the shitlist for the next round of layoffs due to "underperformance"
Do the skills these people have overlap with the skills needed for a good data labeler? I'm guessing being a domain expert is most valuable as a data labeler.
Those percentages seem in line with what I have heard. Not company-wide, MSL was exempted, of course, and probably a few other golden geese here and there.
But people want to drink coffee/espresso hot, not room-temperature. So you have to heat the water afterward anyway. I'm not seeing that much potential for energy savings here, unless you're comparing setups with large boilers inefficiently used for small amounts of coffee.
According to the article they see the main use for industrial scale production of coffee/espresso based drinks, in that regard it does make sense. For home use not so much even if there could be some niche market for cold espresso drinks at home, using less ice would allow for less dilution and faster than prepping and then refrigerate the coffee. I sometimes put concentrated ice coffee into my whey/oat shakes, but this is indeed very niche use even for me.
They explicitly mention large scale producers for mixed drinks as a massive target audience. E.g. iced coffee manufacturing will be heavily impacted, they would normally need to heat the liquid, extract the coffee and then cool it back down.
If I read it correctly, they did espresso and filter taste tests at room temperature (thought they don't state the exact temperature, and how they managed to brew filter coffee with the described setup). Overall the press release is somewhat misleading in what the goal is until the part you mention. If the focus is industrial production of cold, mixed coffee drinks I'd have expected more quantitative measurements instead of taste tests. Testing how well your coffee is extracted is pretty trivial with the right equipment.
An awful lot of people drink iced espresso drinks these days. Room temperature (or below) brewing would make a big difference to the dilution in those drinks.
Some kind of versioning is extremely important for certain use cases. And having it a core DB feature makes it easier to show that you implement that checkbox.
One thing I'm wondering about is the performance of temporal tables for the common case, when you only query current rows. When you manually version tables, one strategy is to have a second table that contains archived versions. So your main table only has the current rows, avoiding a performance hit for having many versions per entry. Is there a way to do this with temporal tables? For example partitioning between active and old rows?
For application time, everything lives in one table (although you could partition it). The biggest performance hit, I suspect, will come from GiST indexes instead of B-Trees. Some general GiST improvements are on my TODO list, and I learned at PGConf.dev that several other people already have patches for cool perf-related GiST enhancements.
Appears a bit too superficial to me to be useful. It groups topics very weirdly (bool and timestamp, uuid and JSONB) and there is almost no detail in each topic.
Explaining text column types without mentioning limiting length with constraints instead of using varchar also seems a bit questionable to me.
The only case I've used them was to mark classes that I need to find via reflection and do something with them. For example a migration system where you want to load all migrations that are defined and check if you need to run them. Of course you don't really need an attribute for that, but I find it helpful to leaven a marker on the class that there's something else going on there.
To solve this problem I have seen the following pattern:
1. Create an abstract base class named MigrationBaseClass
2. Have all migrations classes inherit from MigrationBaseClass
3. Use .Net Reflection to get all types that inherit from MigrationBaseClass
4. Do something with these types.
Doesn't even need to be an abstract base class. It's just as easy to use reflection to find all implementations in an assembly of an IMigration interface.
(ETA: Though my favorite pattern here became using DI for this instead of reflection. For every IMigration have a `services.AddTransient<IMigration, SomeMigrationImplementationClass>()` somewhere and then your service to run all migrations can just request from DI `IEnumerable<IMigration>`. I can then put the Reflection into a unit test to make sure everything that implements IMigration is registered in the DI container. But using DI in the main assembly to register all the migrations rather than Reflection leaves more room to try to AOT compile the assembly in production builds.)
Assuming you have all the code in your solution, you could do this with a source generator instead and have no need of reflection and are AOT compatible
yeah, there's plenty of ways to do that. I like having the attribute there so that there is a strong hint that some magic is happening somewhere with that class.
They didn't mention anything about SLAs. This is about all the time, effort, paperwork and risk it takes to add yet another vendor. Having fewer vendors does actually reduce risk, as long as your chosen vendors are reasonably good. Though the bigger reason is certainly avoiding the additional bureaucracy, which is partly self-inflicted in larger companies but also not without merit.
Yeah, I understood the original point. And I'm tired of it.
I'm just tired of the 'everyone follows their immediate incentives while the system stays incoherent' as the de facto reality. I think shedding some light over the actual mechanics would maybe make someone consider 'perhaps we shouldn't allow our acquisition team just turn off their brain and choose the default to cover their bottoms; maybe vendors are worth more decision investment via actual thinking instead of performatively ending up on the default choice after a little ritualistic game of "eeny, meeny, miny, AWS"'.
I think it's worth pointing out that Jeff Bezos would fight this tooth and nail from happening in his companies. He popularised 'process as proxy'. Yet AWS as sold to external enterprises is the exact proxy Bezos warned against internally. Do what Bezos does, and even what Bezos preaches, just don't do by default what Bezos sells.
Which vendor would you rather use in this context, with your sensitive customer data?
-vendor A's list of sub-processors is a mile long and includes providers of questionable repute;
-vendor B's list is short and includes AWS and GCP
I think he's arguing about OpenAI vendoring specifically, where OpenAI has a lot of subprocessors, but AWS doesn't and there's not really a 3rd camp to choose from, yet. But even there you can't just choose AWS as I tried to illustrate in uncle comment.
The politics of multimillion dollar contracts for public clouds go far, far, far beyond the preferences of an acquisition team, or what the engineers may think.
> This is about all the time, effort, paperwork and risk it takes to add yet another vendor.
This is stupid. This protects you from having a risk to have to do small things (very small things), and updates, by increasing the risk you have to redo everything all at once. It's eliminating a tiny effort by massively increasing systemic risk.
It would, by the way, be a very good business and SRE exercise to actually trip those small risks from time to time and fix it.
Otherwise: ask Iranians what happened to their AWS accounts when Trump decided to sanction them. Ask ICC judges what happened to their email and visa cards. Everything just stopped and died. Is that what you want for your company?
And it's not just particular topics they hate, they hate the entire system and institutions. And they try to either break them and force them to adopt their political views, or they attack their funding or use any other powers to dismantle them.
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