adverbly
To me, science is not a database of facts and data, and the scientific process is not just the process of adding to this database.
It is more than that.
Science is building the database of facts and data, but it is also sharing/disseminating that database so that others can write to it too.
We both agree that "openness" is critical for this, but to me, the scientific process includes things like the actual words that a scientist uses to communicate their ideas/data, the paper they wrote, the collaborations they had, the work that they built upon. Science is not like a database only - its more like a distributed system, and the scientific community is like a living, breathing thing. It is the health of that system which has been damaged in my opinion.
So I have no problem that OpenAI updated the database.
They didn't just make the information available though.
They updated the knowledge database, then released low quality slop papers.
They made it clear that they don't give a damn about sharing/disseminating information.
They are trying to fundamentally say "we can do science without prioritizing sharing.
We don't think its important. We'll release the proof because it makes our stock go up, but we're gonna keep going and building and not spend any time on communication or comprehension because we think that it doesn't matter, and your contributions don't matter, and AI is gonna do all of this independently anyway. We spent $20m on the proof because it made our stock go up $20b, but we'll spend 20 min on the paper. Priorities clear.
Does any of that make sense?
They didn't just "start" it though - they released slop papers.
That's finishing it - not starting it as far as scientific publishing is concerned.
> Or are you saying the community has no incentive to do that because there is no reward/recognition for doing that?
Not exactly - but that is part of it.
I think what would have went over better is:
1. Immediately announce a solution has been found.
2. Do not publish the solution.
3. Put out an open request for anyone with experience in the area who wants to get involved to help collaborate on a construction and human-comprehensible paper. Accept anyone who can demonstrate potentially useful work/experience in the field/problem. Share the solution with them after they sign some kind of NDA that they won't independently publish or share the solution/work.
4. Work with people until a paper is ready (I mean actually ready - not the kind of slop that they released).
5. Publish. Include names of everyone who made meaningful contributions to the paper (not just the proof).
EDIT: Notice the incentive with my proposed second path is that it gives OpenAI an incentive to improve the interpretability of its proofs. This is a good thing! The maths community would be thrilled to actually gain understanding from such releases, and OpenAI would be happy because they could more quickly and independently publish their results. At the moment the "value" of their mathematics research "product" is low because of the lack of this interpretability, and this current approach is simultaneously destroying the opportunity value of the community as well as the incentive for OpenAI to ever improve on what's missing.
No.
But its worth a lot less than one that can be understood.
They really should be trying to partner with the mathematics community to add maximum value.
Their current approach is reckless and risks doing more harm than good.
It looks like the spent $20 on writing the actual papers.
If they actually wanted to do good for the world, they wouldn't have released these as the slop grenades they are.
In their current state, they are actively damaging the mathematics community.
It shows a lack of respect and care for the impact that their technology has.
It shows that they cannot be trusted for things like private data, AI safety, and company partnerships.
In math/science, repeatability and review are critical to the process.
The right way to handle this would have been to work with the mathematics community to co-develop and create meaningful proofs rather than slop grenades.
If they proceed in the current state, we'll just get a bunch of spaghetti math that won't do anything for helping people build an understanding.
Maybe some day, we won't need people to understand things, but that's certainly not the case at the moment, and likely won't be for several more years.
Perhaps this is projection, and the staff at OpenAI doesn't understand their work anymore? Not a great sign regardless.
It would be like trying to look at a completed video game's assembly code, being told that it was call of duty, and then being asked questions about the high level code architecture.
AI models are perhaps unsurprisingly good at low level translation (see the progress being made for decomp games)
These models have surpassed human capabilities at math/machine code, but they can't "simplify" yet - in part because they don't have the same need to due to their comparative lack of cognitive constraints. AI Slop code is getting better, but it takes time. At the moment, its embarrassing frankly. It will come eventually, but right now OpenAI is not handling this with the care, respect, or concern that it deserves.
Excellent point.
I don't blame the AI for this - I blame OpenAI.
Literal slop grenade (see https://fortune.com/2026/09/17/shopify-tobias-lutke-ai-slop-...)
Responsive iframes been a long time coming.
Good to see.
Or the fact that historically speaking, immigrants have always been scapegoated.
Are you willing to at least consider the fact that wages and cost of living might both be headed in the wrong direction due to some other factors beyond immigration such as economic policy or geopolitical conflicts driving up energy costs or changes in market power between labor and capital or general debt levels?
Emotions can be funny.
This is where the analogy to the stages of grief breaks down.
If you're talking about the stages of grief as being stages of dealing with death, there is no uncertainty or going back.
In the case of AI disruption, there is still uncertainty. Denialists might be right in the end still. Bargaining or getting angry might work.
You can only really progress through the stages if you're emotionally bought in to the reality of a future event that has not yet happened. It's quite a roller coaster emotionally speaking.
Part of the acceptance stage recognizing and internalizing:
1. life will be different
2. life will go on
3. there are still many good things in life
To me, the #1 priority here is ensuring that life DOES go on.
I don't think we can ignore x-risk or the other problems like social disruption or government/propaganda control which get worse as AI improves.
Acceptance is pointless if we're all dead.
If you think being dead is fine, you're still in the depression phase.
The reality is that life can be awesome, and it is within the realm of possibility for us to make it so, but it requires us to get up, take action, push for changes, mobilize, organize. Don't just go to the potato office. We only really get one shot at "landing" AI safely. Now is the time for action, and to make sure that we get it right or as right as we can get it on behalf of all future generations.
The hype rollercoaster is unique for sure.
If people did resurrect, I can just imagine the hype people coming back and saying "We're so back baby!", at which point I'd probably just try and bury them again...
Hate to nitpick, but that's classic bargaining - not acceptance.
Gotta be patient before making claims like that.
Its a hard thing, but time is ultimately what helps the most here, so making a claim like that without having given it a few years is premature.
• Denial
• Anger
• Bargaining
• Depression
• Acceptance
Here is what I see(and common thought patterns)
• Denial (models will never be able to replace the majority of important work)
• Anger (angry at data centers, energy use, IP theft)
• Bargaining (people thinking that their personalized agentic dev setup or self-hosting is gonna somehow leave them with meaningful work long-term)
• Depression (people who are being honest about what it will mean to day-to-day lives of many workers in the industry over the next decade)
• Acceptance (people who are focused on the problems that get worse as AI gets better - social disruption, x-risk, government/corporate control)
Can you be more specific about what isn't just a growing pain/maturity problem that will eventually be baked into the default products once the unit costs come down?
I can one-shot full video production that takes almost an hour on claude right now and it'll run ffmpeg for a good chunk of that. I don't see how the delegation + infra isn't a solved problem a couple years from now.
I agree with this part.
Everything else I disagree with. You need to do some more reading about history sir or madame or bot.
Interesting that its only an excerpt. I wonder what else they include but didn't share.
1. I don't want to love it. I hate it. You can learn to live with things you hate though, and not have it impact your day to day life or mental health though.
2. Its still a bomb. Until we find out how we can de-value the data, it will have an incentive to be stolen.
One thought here that I don't personally agree with, but might be important regardless:
Imagine a society without secrets or privacy at all for example.
I don't personally like the sounds of it, but it is sort of where we're headed at the moment, and if the fundamental reality is that obtaining data is much more easy than defending it, then perhaps we need to come to terms with a world without privacy, and how to create the best version of that unconstrained world.
Again, I don't like the sounds of this, but I'm curious to read more about it. Can someone give a philosophical pitch of why GDPR style regs on personal and company data are so important?
At least reasoning is not guaranteed.
Would sure be nice though...
2. Even if it didn't work, Georgism is fundamentally a more just and fair system.
3. The world really needs it right now. Housing, wealth inequality, climate change, the inability for most populations to understand how to properly balance aspects of capitalism and socialism.
Friends let their friends know about Georgism! Do the right thing!
When georgists refer to land, they are referring to locations - not dirt.
Locations refer to the sections of physical 2D space that makes up a country. Why 2D when the world is 3D? Because parcels are allocated and segmented based on a 2D model.
Locations are best thought of as being similar to "spectrum" (what typically gets auctioned off every few years to the highest bidder) - there is a total fixed amount. Nobody made the physical space, and nobody will make more of it in the future. It all existed before life even began on this planet, and it will exist long after all of us are dead.
What happens when AI is better at that part too? Are you confident it's not already better?
For who though?
Is it important that each person understand it on their own?
Why does it impact me if another human understands something or not?
It impacts me right now because that human can use that knowledge to explain things to me or to build new things using that knowledge.
But if an AI can explain and build better, then what good does it do having the other human know the thing?
Understanding might have intrinsic value to me, but intrinsic value to me doesn't pay the bills.
What am I missing here? I kinda expected better from Terrance given such an audacious title.
Got my vote!
Au contraire! Please continue!