Noone cared.
You don’t know what questions they did not ask you, and the assumptions of shared cultural background that they made because they saw that. They would not tell you. (unless you have comparisons to job searching before getting the degree).
Fundamentally, this is the expected phenomenology, since people do not tend to notice sources of your own status.
Credentialism is good because the limiting factor on employment is trust, not talent for most credential requiring positions (white collar, buisness and engineering work).
Universities are bad at teaching skills, but generate trust and social capital.
Trust that allows the system to underwrite new white collar workers to do things that might lose buisnesses lots of money is important and expensive.
Consequently you get credential requirements, because there is no test other than years of being in social systems that can tell you that a person has the ability to go 4 years without crashing out (which is the key skill).
Additionally, going to university has become a class signifier, and all classes wish they were bigger and more prominent.
The alternative to credentialism is selection, or real meritocracy.
The alternative to credentialism is not selection, it is hiring your buddies, hiring by visible factors, and hiring randomly. Most business are not that guy that they can run a competitive selective process (THOSE ARE REALLY EXPENSIVE).
“universities provide to employers is the ability to confirm you are clever, driven, and have relevant skills” is false. They provide that you are a member of the professional class that is not going to do stupid things that lose money/generate risk.
Fundamentally, this misunderstands the purpose of the degree to the hiring bureaucracy, and the political economy behind it.
In short, it seems like the current system unfairly kills drugs that take a long time to develop and do not have a patentable change in the last few years of that cycle.
If the story about drug prices and price controls is correct (that price controls are bad because the limiting factor for drug development is returns on capital, which this reduces), then we must rethink the political economy of drug development.
Basically, we would expect if that to be the case that the sectoral return rates of biotech to match the risk adjusted rate , but drug development is both risky and skewed, effecting costs of capital.
Most of drug prices are capital costs, and so interventions that lower the capital costs of pharmaceutical companies might produce more drugs.
Most of those capital costs from the total raise required, which is effected basically by the costs of pharmaceutical research (which is probably mostly the labor of expensive professionals).
The expected rate of return is dominated by the risks of pharmaceutical companies.
Drug prices are what the market will bear/monopoly for a time, then drop to a very low level once a compound is generic.
There is a big problem here with out of patent molecules, since if a drug is covered by a patent and stalls 20 years, there is not the return to push it through the process, which means that there might be zombie drugs around from companies that fell apart and did a bad job of selling that asset (so it did not finish the process and did not fail the process).
There seems to be space for the various approvals to become more IP like (so that all drugs have the same exclusivity, regardless of how long they took to prove out).
I don’t think that people from the natsec version have made that update, since they have been talking this line for a while.
But the dead organization framing matters here.
In short, people think that democratic institutions are not dead (especially electoralism). If AGI is “Democratic”, that live institution, in which they are a stakeholder, will have the power to choose to do fine stuff. (and might generalize to everybody is a stakeholder) Which is + ev, especially for them.
They also expect that China as a live actor will try to kill all other actors if given the chance.
I am neither an American citizen nor a Chinese citizen.
does not describe most people who make that argument.
Most of these people are US citizens, or could be. under liberalism/democracy those sorts of people get a say in the future, so think AGI will be better if it gives those sorts of people a say.
Most people talking about the USG AGI have structural investments in the US, which are better and give them more chances to bid on not destroying the world. (many are citizens or are in the US block). Since the US government is expected to treat other stakeholders in its previous block better than China treats members of it’s block, it is better for people who are only US aligned if the US gets more powerful, since it will probably support its traditional allies even when it is vastly more powerful, as it did during the early cold war. (This was obvious last year and no longer obvious).
In short, the USG was commited to international liberalism, which is a great thing for AGI to have for various reasons which are hard to say, but basically of the form that liberals are commited to not doing crazy stuff.
People who can’t reason well about the CCP’s internal ideologies /political conflicts(like me), and predict ideological alignemnt for AGI, think that USG AGI will use the frames of international liberalism (which don’t let you get away with terrible things even if you are powerful), and worry about frames of international realism (which they assign to China, since they cannot tell, and argue that if you have the power you must/should/can use it to do anything, including ruining everybody else).
As a summary, if you are not an american citizen, do not trust the US natsec framing. A lot of this is carryover from times when the US liberal international block (global international order), was stronger, and so as a block framing it is better iff the US block is somehow bigger, which at the time it was.
You would need to make sure that this change in asset values does not wipe out highly leveraged players. But that is also a thing that has been done in the past. (see 2023 banking failures for what happens).
Problem is that the relation of asset values to realized returns (that they will equalize between assets with fixed returns), means that any tax on asset returns immediately reflects in the valuations. But that is not the end of the world, since if you hold assets, paine would argue, you can afford a haircut.
I noticed another thing.
All these analysis put a lot of stock on the democrats being Anti-market, because well, it is in the democratic discourse. But I think that is misreading that discourse. A lot of it is that the democrats are rightly very scared and suspiscious (almost paranoid), over monopolies, monopsonies, and cartelization. And they don’t just endorse the obvious solution of agressively breaking up companies. (since it is bad for buisnesses even though it is good for competition)
But i just don’t think that it is the only way to frame that. Especially Biden’s SEC and FTC are very skeptical of M and A because they are very scared of monopolies, and most of the democratic policies make sense in a we think that there might be an x monopoly, and we dont just want to point antitrust at it, so what should we do.
And generally the solution that they come up with is that government should engage in effectively price negotiations with the monopoly provider, where they use to law to get people to coordinate in bargining for a better price, so you end up with 2 agent no alt bargianing as the pricing mechanism), hopefully to agree to something closer to the free market pricing (the price capping). That is a bad pricing mechanism (often ending up below market). It is really hard to figure out the coordination method used so as to break them up. This is a bad solution. If you think there is a cartel, you don’t put in a price cap, you break the cartel.
Another broad problem is not noticing (or caring) about the degree to which being a good administrator of the federal bureaucracy, is a critical skill for a president. The things where it seems like Trump has no clue what is going on was baked in in P2025, when it talked about doing things that disrupted the normal function of agencies, because 90% of what the president knows he is getting from his secretaries and advisors, which get stuff from their departments. The fact that Trump watches Fox but sometimes ignores briefings is in fact a big deal.
Harris winning probably would not stop the democratic civil war, (unless she got some deals done), because the democrats have a civil war every election cycle and did not get a chance to do so in the primaries. We don’t know how she would govern through that.
Note that knowing != doing, so in principle there is a gap between a world model which includes lots of information about what the user is feeling (what you call cognitive empathy), and acting on that information in prosocial/beneficial ways.
Similarly, one can considers anothers emotions both to mislead or to comfort someone.
There is a bit of tricky framing/ training work in making a model that “knows” what a user is feeling, having that at a low enough layer that the activation is useful, and actually acting on that in a beneficial way.
Steering might help taxonimize here.
. It is within our power to prevent lab-originated pandemics but not natural pandemics
Might be false.
If you could clear vaccines for deployment with good transmission prevention before zoonosis, and the hypothesis that viruses in the wild that are prone to zoonosis are observable (so you can prepare), then you could basically prevent zoonosis events from becoming pandemics (because you could immediately begin ring vaccination).
So there are no “natural pandemics”, there are new diseases which interact with social conditions to become pandemic (just as existing diseases can mutate past current limitations). If those social conditions do not exist, disease does not reach pandemic status.
Generally the releases of the “open source” models release the inference code and the weights, but not the exact training data, and often not information about training setup. (for instance, Deepseek has done a pile of hacking on how to get the most out of their H800s, which is private)
Thank you.
The effect will at first be most clear in fields where entry-level cognitive tasks are especially prone to near-term AI automation, like software engineering and law as seen above. Other industries where complex human interaction or physical dexterity are crucial, for example healthcare and construction, will hold out for longer before being automated too through a combination of AI and robotics.
Repeat Paragraph
Historically, the social contract describes the set of agreements concerning the legitimacy of government and its role in governing citizens. This concept, developed by philosophers like Hobbes, Locke, and Rousseau, posits that individuals surrender certain natural freedoms and contribute a portion of their wealth to governments in exchange for protection, order, and social stability.
Over time, this foundational concept evolved beyond the basic relationship between citizen and state. The industrial age expanded the social contract to encompass economic relationships between workers, employers, and broader society. Citizens came to expect not just security, but also economic opportunity. Governments increasingly took on responsibilities for education, infrastructure, and basic welfare as part of their obligation under this implicit agreement.
This evolution produced the modern social contract we recognize today: citizens contribute their labor and a portion of their earnings through taxation; in return, they receive not just protection but also economic security and the promise that hard work would be rewarded with prosperity.
I am not sure how this social change is discontinuous with previous developments which introduced new social conditions, new capabilities, and new externalities. In short, it is clear that if there is big economic change, there will be political changes too, but if this is rethinking the social contract, then we have been doing this continuosly. We do not need to begin to rethink the social contract. We need to recognize that we have always been continually rethinking it.
There is another analogy where this works. It is like bank failures, where things fall apart slowly, then all at once. That is to say that being past the critical threshold does not guarntee failure timing. Specifically, you can’t tell if an organization can do something without actually trying to do it. So noticing disempowerment is not helpful if you notice it only after the critical threshold, where you try something and it does not work.
Mainly things that we would never think of, as fruitful for AI and not for us.
Things that are useful for us but not for AI is things like investigating gaps in tokenization, hiding things from AI, and things that are hard to explain/judge, because we probably ought to trust the AI researchers less than we do human researchers with regards to good faith.
o3 has a different base model (presumably).
All of the figures are base model equivalated between RL and not
I would expect “this paper doesn’t have the actual optimal methods” is true, this is specifically a test for PPO for in distribution actions. Concretely, there is a potential story here about PPO reinforces traces that hit in self-play, consequently, there is a sense which we would expect it to only select previously on policy actions.
But if one has enough money, you can finetune GPT models, and test that.
Also note that 10k submissions is about 2 OOM out of distribution for the charts in the paper.
Pass at inf k includes every path with nonzero probability (if there is a policy of discarding exact repeat paths).
We know that RL decreases model entropy, so the first k passes will be more different for a high variance model.
Pass at k is take best, so for normal distribution take best has EV mean+variance*log(samples).
At very large K, we would expect variance to matter more than mean.