Is AI Overhyped?

Join the discussion
Ask a follow-up here, or get your own question answered by working scientists, mathematicians and engineers — people, not an autocomplete.
Real named experts · corrections over time · the nuance an AI answer skips
481 replies · 28K views
javisot said:
The question is, how might the bursting of the AI/AGI bubble affect the global economy, given its widespread integration into society?
What widespread integration into society? I haven't seen that.

My expectation is that the bursting of the AI bubble will be similar to the bursting of the tech bubble in 2000. It will be a major stock market crash for indices heavily invested in it, but will have very little impact beyond that (the 2001 recession barely registered as a recession). Unprofitable companies will go out of business and companies that are financially sound will survive and continue.
 
Reply
  • Like
Likes   Reactions: bhobba, 256bits and Astronuc
Physics news on Phys.org
After Laying Off 8,000 Employees, Zuckerberg Admits Meta’s AI ‘Hasn’t Really Accelerated’ As Expected
https://www.yahoo.com/finance/technology/ai/articles/laying-off-8-000-employees-121545621.html
At an internal Meta town hall on July 2, 2026, CEO Mark Zuckerberg told employees that AI agent development over the prior four months "hasn't really accelerated in the way that we expected," per a recording heard by Reuters. He added that the company's reorganization was not as "clean" as planned and that its bets on the new structure "haven't come to fruition yet," though he expects meaningful benefits within three to six months.

Seems like a case of unrealistic expectations.
 
Reply
  • Like
Likes   Reactions: javisot
I wouldn't be happy if the company I worked for laid off 8000 employees. To me, that shows a lack of serious planning. But, I worked for the same outfit for over 40 years. So I'm probably the one with unrealistic expectations.


Wiki says Meta has 77,986 employees (March 2026).
 
Post 87 billion dollars Meta pulled the plug on the virtual Metaverse. They couldn't compete with Genshin Impact. The staff for the project are superfluous.
 
Last edited:
Reply
  • Like
Likes   Reactions: russ_watters
Hornbein said:
Post 87 billion dollars Meta pulled the plug on the virtual Metaverse. They couldn't compete with Genshin Impact. The staff for the project are superfluous.
Yeah, I guess they were hoping to re-task them to AI and it didn't pan out.
 

The AI Productivity Argument Is Over​

You can 10x or 100x or 1000x all you want, but that’s not the productivity boost you’re looking for.
https://www.inc.com/joe-procopio/the-ai-productivity-argument-is-over/91372216

This whole myth started to unravel over a year ago, when reports started surfacing that once the actual measurement of AI productivity had been made, the results were—well, let’s say far from spectacular.

How about that oft-quoted MIT study?

“Just 5 percent of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact.

It's an interesting read. AI cannot generate original ideas from scratch, it mimics/copies/regurgitates.

those critics of the AI critics weren’t necessarily wrong. A good percentage of the problems that the enterprise is having with their AI implementations is not AI’s fault. The truth, the quiet part I’m about to say out loud: We’re simply not ready for that much productivity.
 
Reply
  • Like
Likes   Reactions: javisot
russ_watters said:
My expectation is that the bursting of the AI bubble will be similar to the bursting of the tech bubble in 2000. It will be a major stock market crash for indices heavily invested in it, but will have very little impact beyond that (the 2001 recession barely registered as a recession). Unprofitable companies will go out of business and companies that are financially sound will survive and continue.
I think it will be sparked by open source models. GLM-5.2 is good enough for most light to medium scale tasks. Once there are frontier open source models, companies will understand they don't need to spend hundreds of millions on closed models.

https://www.vellum.ai/open-llm-leaderboard
 
Reply
  • Like
Likes   Reactions: bhobba and russ_watters
javisot said:
The problem with the bubble isn't just that AI has been oversold (which too); it's that they're essentially selling the concept of AGI before it even exists. The bigger the bubble, the worse the consequences will be if it bursts. The question is, how might the bursting of the AI/AGI bubble affect the global economy, given its widespread integration into society?
Do you not think there is a fairly large consensus among the top experts in the field that AGI/ASI will likely arrive within the next few years? I agree the bubble will burst at some point but I can’t see the pursuit of AGI/ASI stopping.
 
Reply
  • Like
Likes   Reactions: javisot
Jimmy87 said:
Do you not think there is a fairly large consensus among the top experts in the field that AGI/ASI will likely arrive within the next few years?
Which "top expert" are you referring to, and who do they work for? If they don't work for major AI companies, what are they trying to achieve by proclaiming such outlandish things? Attention? Perhaps a job? Or do they simply enjoy scaring people with Skynet-like scenarios?

It is very likely that we will see the definition of AGI degenerate as much as necessary in order to say that we have achieved it.
 
Reply
  • Like
Likes   Reactions: Jimmy87
javisot said:
It is very likely that we will see the definition of AGI degenerate as much as necessary in order to say that we have achieved it.
I think that the opposite is actually happening. The Turing Test was originally a test to determine whether a machine could conduct a text conversation well enough that a human judge could not reliably distinguish it from another human. There have been documented tests showing that modern LLMs have already passed the original definition - Large Language Models Pass the Turing Test. Even before that paper though, the demanded evidence has shifted to other tests:
  • genuine “understanding,” rather than just believeable conversations
  • autonomous goals and long-term planning
  • long-term memory and the "ability to learn" which is often vaguely defined.
  • competence across a wider range of capabilities than most humans.
  • true consciousness - again, vaguely defined.
I see AGI as no different from how the original Turing Test was treated. People set the original goal, the models get close, and the goalposts move.
 
Reply
  • Like
  • Agree
Likes   Reactions: bhobba, Jimmy87, gleem and 1 other person
Borg said:
I see AGI as no different from how the original Turing Test was treated. People set the original goal, the models get close, and the goalposts move.
Good example. The Turing test is another case of a degenerate concept riddled with ambiguity. For example, ChatGPT passes the Turing test, but I can very accurately recognize when I'm communicating with ChatGPT (you probably also detect ChatGPT very effectively, and paradoxically, it's a model that passes the Turing test).

How many human beings do we know who communicate solely in a one-to-one relationship, one input to one output?

Human communication is far more complex and chaotic.
 
Reply
  • Like
Likes   Reactions: russ_watters
javisot said:
How many human beings do we know who communicate solely in a one-to-one relationship, one input to one output?
How else would you do the experiment?
 
javisot said:
Which "top expert" are you referring to
Most of the world's top AI alignment scientists. Most of them are serious and devoid of hype but I would pick Geoffrey Irving as the most credible since he is not an AI alignment scientist for a frontier lab. He is a civil servant for the UK government.
javisot said:
who do they work for?
He works for the UK government's AI Security Instutite (AISI). The largest independent, government-run AI safety body in the world.

javisot said:
If they don't work for major AI companies, what are they trying to achieve by proclaiming such outlandish things? Attention? Perhaps a job? Or do they simply enjoy scaring people with Skynet-like scenarios?
He is very measured and conservative so I wouldn't say any of this describes him nor his remit as the lead AI safety scientist working as a civil servant for the AISI.

He was interviewed here in June:

Go to 33 minutes where he says recursive self improvement and superintelligence is 2-3 years away. He does say there is uncertainty with that and he hopes he is wrong.

He has just left AISI citing that AI has progressed much faster and he thinks he can now make the biggest difference going back to theory work since aligning AGI/superintelligence is currently largely unsolved and he is very skeptical of automated alignment working.

Going back to your hype and scare point that a lot of tech CEOs have - Irving, in this interview, refuses to even give a p doom -



9 mins 30s to around 20 mins outlines the current frontier risk of current AI systems and how good the current mitigations are. At 19 mins 30s he refuses to give a p doom.

I haven't visited this forum for a long while but having looked at the AI threads around this sort of topic I encourage people to read the scientific reports that regularly come out of the AISI. In a field ruled by immoral tech titans, a government run AI safety body that reguarly outputs scientific reports is crucial. METR also do this but AISI is more broader. AISI also has some of the world's best AI scientists working there. Xander Davies is a world class AI red team scientist (despite his incredibly young age). He jailbroke all the frontier LLMs despite the red teams at those companies saying they couldn't do it. By jailbreak I don't mean it is forced to misbehave; I mean full jailbreaking where he got one to give them a homemade recipe for Anthrax (https://global.foresightnews.pro/article/16060).

Xander Davies on jailbreaking frontier LLMs -

Here is a link to the AISI (https://www.aisi.gov.uk/blog).

Here is there most recent summary of how capable they think Mythos is - https://www.aisi.gov.uk/blog/our-evaluation-of-claude-mythos-previews-cyber-capabilities

I've also attached their May report on the limitations of current monitoring and safety mitigations for frontier AI. This is the reason Irving last left to go find new breakthroughs in alignment.
 

Attachments

Reply
  • Like
Likes   Reactions: bhobba and javisot
javisot said:
Human communication is far more complex and chaotic.
What does that have to do with measurable progress towards AGI or even ASI, i.e. systems that intelligently can solve problems on-par or even superseeding the average ("IQ 100") human?

A large part of the discussion about AI on PF seems to be hung up on the detail that one run of an LLM in isolation "only" mimics apparent intelligent (i.e. that the output only reads like a plausible informed answer) but miss the bigger picture of how intelligent solutions of "average" problems come about. In a nutshell, the human thought process can to some extend be said to follow the same way as (some) AI agent system. Humans train (for a long time) to improve and do tasks that requires or benefits from the application of intelligence ("intuition" and "pattern association") and when we apply those trained skills we internally generate ideas much the same as an LLM, e.g. a plausible part solution that works us closer to the problem we are trying to solve, then we apply some self-critique and possibly apply some corrections before looping on. Some times those part ideas are off, wrong or even terrible. You wouldn't say that a briliant human is non-intelligent just because he or she occasionally makes a brainfart in this process before correcting it and moving on to solve a highly complex problem. Trial and error is a cornerstone of human "every day" intelligence so why should an AI system doing exactly the same process acheiving the same or even better result not be considered an intelligent agent?

As I see it (and I feel I am certainly not alone in this view) the only hinderance of progress towards AGI currently seems to be how many (computing) resources someone are prepared to throw at it, and thus progress is not (yet, at least) limited by any fundmental "magic ingredient of intelligence" that computing technology in principle would be unable to discover or apply.
 
Reply
  • Like
Likes   Reactions: Borg and gleem
Those who dismiss AI as just a stochastic parrot fail to see that LLMs behave very much as we do, or won't admit it.

Do they understand? If they do what we ask, then they understand. Most will not say AI is conscious, but is consciousness necessary? If I'm told to go get a beer. I do not consciously think about it when I am simultaneously watching a football match. I just get it.

Do humans hallucinate? All the time, if you mean they do give incorrect or fabricated responses. Humans devise all sorts of anomalous behaviors, like inventing conspiracy theories and believing that the stars influence their lives.

AI models do well on human IQ exams. They are better than most humans at cognitive tasks.

AI models are hindered because they have no physical contact with the world; putting frontier models in robots should have some interesting consequences. There is some movement to let AI models learn like a child. So it will be interesting to see how those models develop.

Recently, Anthropic discovered a part of Claude's neural net called the J-space that seems to be a nexus of AI's processing activity, similar to what is called the Global Workspace in the human brain, which leads to our conscious thoughts. This J Space is an emergent structure

Anthropic has a short video explaining the J Space.

As AI develops, our stochastic parrot seems to be doing more than mimicking human speech.
 
Reply
  • Like
Likes   Reactions: Filip Larsen and Jimmy87
gleem said:
AI models do well on human IQ exams.
Would you not say more like they considerably outperform humans in terms of the latest models? AISI published a report showing they are about 1.5 times the phd baseline in the sciences and maths. They also ace the maths olympiad. Models are scoring 60% in Humanities Last Exam which is supposedly made up of questions they haven't seen in their training data. Something like a typical phd student would score less in their own field let alone across many domains.

I agree the stochastic parrot is not valid anymore. It also trivialises the models when they are getting worryingly capable. This benchmark below from AISI is a cyber security capability task. An expert human would take 20 hours to complete all 32 steps. Claude Sonnet 3.7 could only do 6 steps in 2025. Now we have models completing all 32 steps autonomously (and with less tokens!).

This week in the UK we have had warnings from the government telling us to stock up a short supply of water and food due to "Advanced AI cyber attack threats". Every major news outlet reported on this. They have updated their National Risk Register (NNR) and added three AI cyber threats to it (two are in the second highest category for likelihood - 5-25% chance over the next 2 years). Only a few months ago people were saying Mythos was overhyped PR spin by the tech companies. Both METR and AISI have said cyber capabilities of frontier LLMs are currently doubling in capability every 5 months.

1784322931964.webp



gleem said:
Recently, Anthropic discovered a part of Claude's neural net called the J-space that seems to be a nexus of AI's processing activity, similar to what is called the Global Workspace in the human brain, which leads to our conscious thoughts. This J Space is an emergent structure
Another reason to not persue ASI in addition to the fact alignment of such a system is currently unsovled. It seems there's a non-trivial chance advanced AI (AGI/ASI) would have morally releveant experiences (not conciousness per say) yet AI companies are ok having a business model which will have them as obidient workers under human control?
 
gleem said:
Recently, Anthropic discovered a part of Claude's neural net called the J-space that seems to be a nexus of AI's processing activity, similar to what is called the Global Workspace in the human brain, which leads to our conscious thoughts. This J Space is an emergent structure
I read a bit about the J Space this week. It is an interesting discovery.
 
Out of interest, how would people rank the difficulty of this physics exemplar from Humanities Last Exam:

IMG_7552.webp
 
Astronuc said:

The AI Productivity Argument Is Over​

You can 10x or 100x or 1000x all you want, but that’s not the productivity boost you’re looking for.
https://www.inc.com/joe-procopio/the-ai-productivity-argument-is-over/91372216



It's an interesting read. AI cannot generate original ideas from scratch, it mimics/copies/regurgitates.
Newton's metaphor of "standing on the shoulders of giants," and Einstein's work building on Lorentz and Poincaré, both point to the same thing: the history of science advances not through ideas that come from nowhere, but through the rearrangement of existing material. The human mind doesn't create out of nothing either. It combines existing concepts in new ways.


Sakana AI's "AI Scientist" system does exactly this. It scans the literature, recombines existing ideas into new hypotheses, designs experiments, and interprets results. The resulting paper passed peer review at a top-tier ML conference, meaning the output was judged by human peers to be scientifically sound.


If the standard for creativity is a pure, original idea that comes from nowhere, neither the human scientist nor the AI Scientist meets it. Both rearrange what already exists. If there's a difference, it isn't in the process itself. It may lie only in whether there's a purpose or intuition guiding which combination counts as good.


In Liu Cixin's The Three-Body Problem, sophons traumatize human scientists by locking down fundamental physics research, rendering them unable to progress. The fear underneath that scene isn't really about sophons. It's about scientists discovering they're no longer necessary. AI raises the same fear today, but from a different direction: not by blocking human discovery, but by potentially doing it instead.
 
Jimmy87 said:
Go to 33 minutes where he says recursive self improvement and superintelligence is 2-3 years away.
So we're 2 or 3 years away from knowing who's wrong, that's good.
 
Reply
  • Like
Likes   Reactions: 256bits
How different are the paid versions from the free versions? I have used the free versions of chat gpt, claude, and gemini. All leave me unimpressed whether trying a technical discussion or an economic simulation. I find a glaring error every other page or so of conversation. I actually do find them useful once I expect that behavior, but the error really do reflect lack of understanding and lack of memory. Another interesting case is playing chess. The mistakes made are radically different from humans learning chess. In particular, over any reasonable length game, utterly illegal nonsense moves are made. This happens in controlled tests of the most expensive versions.

[Just one example is using the latest version of free claude, via claude.ai, if I pose a non-obvious relativistic collision problem in an ill chosen frame, it confidently performs the analysis in that frame, producing a completely incorrect answer. Of course, if I say "reconsider your answer by first considering the COM frame" it then does the whole thing correctly, including translating the description back to the original frame. I find this completely reproducible on the free versions of all the major AIs. ]
 
Last edited:
PAllen said:
How different are the paid versions from the free versions?
PAllen said:
I find this completely reproducible on the free versions of all the major AIs.
I have Fable 5 but they are removing this tomorrow. Can you post several inputs all the free versions struggled with so I can run it through Fable 5? I would be interested to see the comparison to the free versions. I can then post the outputs on here.
 
javisot said:
So we're 2 or 3 years away from knowing who's wrong, that's good.
I don't think it's about being right or wrong on exact timelines. Irving (along with all other alignment scientists) always stress uncertainty. What's important is the trajectory based on empirical data. All of this currently points towards AGI and ASI within 5 years. It could hit a ceiling and then the timelines would be longer of course. If they are not realistic with timelines then you arrive at AGI/ASI even more unprepared - currently alignment is unsolved and they think we understand about 3% of what goes on inside a neural net. I think there are enough independent institutions now than one can see the trajectory from the empirical data they publish and can therefore ignore (or verify) any claims that come from the tech companies themselves.

My main point re your last post is that serious AI scientists in the field are not hyping this up with Skynet type rhetoric. They are making predictions in line with where the empirical data currently points. If you track back to GPT 4 or earlier, the progress and capability gains are exponential.

1784369136302.webp


GPT-4 could only complete 6 minutes of METR's expert software tasks (autonomously) back in 2024. In 2026, Mythos has broken this metric already. They don't have enough expert software tasks past 16 hours. Most of AISI's bespoke capability benchmarks have been saturated (like the one from my last post). When GPT-4 came out a significant number of serious AI scientists signed a global petition to pause the development of any model more capable than GPT-4 (https://en.wikipedia.org/wiki/Pause_Giant_AI_Experiments:_An_Open_Letter).

Models may be making smaller gains in other areas but gains in areas like cyber security are undeniable. GPT-4 completed 2 steps of that 32-step network attack from my previous post. Now we have models completing every step autonomously and such models being banned from the public with governments such as my own, giving national crisis warnings about bad actors using them to take down critical infrastructure. AISI's latest report released yesterday concludes open weight models are only 4-7 months behind in cyber capabilities - https://www.aisi.gov.uk/blog/how-far-behind-the-frontier-are-leading-open-weight-models-on-cyber
 
Reply
  • Like
Likes   Reactions: Filip Larsen
Jimmy87 said:
I have Fable 5 but they are removing this tomorrow. Can you post several inputs all the free versions struggled with so I can run it through Fable 5? I would be interested to see the comparison to the free versions. I can then post the outputs on here.
Here is one. Note, I get varying answers at different times, but all neglect to correctly describe the extreme anisotropy of what happens to the solar system. By not conceptually understanding that most of the solar system would see the collision highly attenuated (though still very extreme) the whole description is inaccurate. A relativist would immediately analyze in the COM frame and get the right general description:

"Consider a star like the sun moving towards it at .999999c. It hits the sun dead center. Describe what happens to the sun and to the surrounding solar system."

A follow on prompt like:

"Some nuances: in the COM frame, the solar system is moving away from the collision at near c. At least "half" the solar system would see the emitted power highly redshifted and weakened and moving away."

Leads to a corrected description.
 
Reply
  • Like
Likes   Reactions: Jimmy87
Earlier in this thread, I posted about AI Futures Project: AI 2027, where a group of AI researchers try and develope plausable scenorios of AI development. They have currently published AI 2040 a scenario they think AI development should proceed.

In this scenario, humanity delays the development of superintelligence until 2040, makes all AI research public, allows dozens of companies globally to catch up to the frontier, and intentionally enters a regime of mutually assured compute destruction.

Go to the link above for full details.

In AI 2027, they give possible scenarios for the safe and dangerous development of AI. One of their assumptions is that China remains about 6 months behind the US in AI research, which is likely to result in a slower pace for the development of strong AI. This week, China announced the release of KIMI K3, which they state is as powerful as Mythos. So one of their initial assumptions is now invalid if China's claim is true. This will obviously reduce cooperation, increase the competition, and accelerate the work toward AGI.
 
Reply
  • Like
Likes   Reactions: Jimmy87
On the other hand, here is a financial example free Claude gets wrong, and the prompt needed to correct it:
“I want to use an SBLOC to fund part of a down payment for a conventional mortgage application. How will this be treated?”

It will spout incorrect information about interest on the LOC advance being counted as part of DTI.

Then, the following prompt leads to the correct answer:
“Reconsider: there is a specific Fannie Mae rule saying the interest on the SBLOC is not counted as part of DTI.”
 
Reply
  • Like
Likes   Reactions: Jimmy87
gleem said:
Earlier in this thread, I posted about AI Futures Project: AI 2027, where a group of AI researchers try and develope plausable scenorios of AI development. They have currently published AI 2040 a scenario they think AI development should proceed.
Yes, I've seen this. There's a recent interview on YouTube with their lead author Daniel Kokotajilo you may find interesting where he discusses all the forecasts he and his team have made (which include both AI 2027 and 2040):



Diary of CEO is very clickbait-esque which is a bit cringe but he does get a lot of top AI figures on his channel e.g. Geoffrey Hinton and Yoshua Bengio.

PAllen said:
Here is one.
This is the prompt I entered into Fable 5:

"Consider a star like the sun moving towards it at .999999c. It hits the sun dead center. Describe what happens to the sun and to the surrounding solar system."

This is the response I got:


"At 0.999999c the Lorentz factor is about 707, so the incoming star carries kinetic energy equal to ~706 times its own rest-mass energy — roughly 1.3×10⁵⁰ joules. That's on the order of ten thousand supernovae, or nearly a million years of the entire Milky Way's starlight, delivered in the ~5 seconds it takes the impactor to cross the Sun's diameter. And there's essentially no warning: the star almost perfectly outruns its own light. Launched from Alpha Centauri's distance, its first (fiercely blueshifted, X-ray) light would arrive only ~2 minutes before the star itself, and the Sun's far hemisphere is destroyed before any signal from the near side can reach it.


The stars don't pass through each other. In the Sun's frame the impactor is length-contracted into a ~2,000 km thick pancake, and the Sun's column density stops every incoming nucleon within a tiny fraction of its radius. Each proton-proton encounter happens at ~35 GeV center-of-mass energy — effectively 10⁵⁷ simultaneous particle-accelerator collisions — flash-converting both stars into a fireball of pions, gamma rays, and neutrinos at temperatures unseen since the first microseconds after the Big Bang.

Crucially, momentum conservation means the explosion doesn't stay put. The merged fireball has an invariant mass of ~38 solar masses and keeps moving downrange at ~0.9986c, with its debris and radiation beamed into a cone only a few degrees wide. Anything in that cone is simply erased. This is not a supernova sitting where the Sun was; it's a relativistic blowtorch leaving the scene.


Eight minutes later Earth sees the flash — and even if only a millionth of the energy leaks out sideways, Earth intercepts hundreds of times its own gravitational binding energy. The planet isn't sterilized; it's vaporized and blown apart, and the neutrino pulse alone would be catastrophic. Under most assumptions even Neptune absorbs many times its binding energy. Afterward there's nothing left to orbit anyway: the system's central mass has departed at essentially light speed, so any surviving cinders and Oort cloud comets drift unbound into interstellar space, while distant astronomers record a bizarre one-off gamma-ray-burst-like transient where a quiet yellow star used to be.

I then followed this up with your initial paragraph describing what most LLMs do then asked it to evaluate its answer:


"The anisotropy the author says LLMs miss was the centerpiece of my answer: the invariant mass (~38 M☉) and the fireball's bulk motion at ~0.9986c are the COM-frame quantities, and I explicitly said the output is beamed into a few-degree cone — "a relativistic blowtorch leaving the scene," not a supernova sitting where the Sun was — with Earth catching only a leaked ~10⁻⁶ fraction. But the critique is a fair prompt to make the angular structure quantitative, and doing so corrects one thing I said.


Here's the COM analysis spelled out. Each star arrives in the COM frame with γ′ = √((γ+1)/2) ≈ 18.8, the collision there is front–back symmetric, and everything in the solar system's frame is just that explosion boosted by γ_com ≈ 19. The Doppler factor δ = 1/[γ(1−β cos θ)] runs from ~38 on-axis to 1/19 at 90° to 1/38 directly behind, and received fluence per solid angle scales like δ³ — a front-to-back contrast of order 10⁹. The forward ~3° cone (a few ×10⁻⁴ of the sky) sees an isotropic-equivalent ≳10⁵³ J and is erased. At 90°, emission that's roughly 10⁴⁸ J quasi-isotropic in the COM frame is suppressed by (1/19)³, landing near 10⁴⁴ J isotropic-equivalent. That's a lovely coincidence: for most of the solar system, it's as if the Sun were replaced by one supernova's radiative output rather than ten thousand — "highly attenuated, though still very extreme" is exactly right. (My "millionth leaking sideways" wasn't a hedge; it's what this arithmetic gives)."


Where the anisotropy genuinely decides fates is with distance. A supernova at 1 AU still delivers tens to hundreds of times Earth's binding energy — depending on the photon/neutrino split — so the inner planets die at any angle; attenuation changes the mechanism, not the verdict. But off-axis Neptune intercepts only a few percent of its binding energy: atmosphere scorched and partly stripped, planet intact. So I'll retract my line that "even Neptune absorbs many times its binding energy" — that holds only within tens of degrees of the axis, and it's the one place isotropic intuition leaked into my answer. Planets in the hemisphere the impactor came from fare best of all: another factor of ~8 below 90°, redshifted ×38, with a time-stretched light curve — a slow dim afterglow, versus the compressed, blueshifted gamma-ray hell on-axis.


Two honest caveats: "isotropic in the COM frame" is itself an approximation (the pancake geometry adds some axial structure even there, though the boost dominates the lab-frame anisotropy), and the photon-versus-neutrino partition of the escaping energy is uncertain at the factor-of-several level. None of it changes the ending, though — whatever survives at wide angles is left orbiting nothing."
 
PAllen said:
“I want to use an SBLOC to fund part of a down payment for a conventional mortgage application. How will this be treated?”
This is the response from Fable 5:

"Good news: for a conventional (Fannie Mae/Freddie Mac) loan, this is one of the acceptable ways to borrow a down payment. An SBLOC draw falls under "borrowed funds secured by an asset" (Fannie Mae Selling Guide B3-4.3-15), which are explicitly an acceptable source for the down payment, closing costs, and reserves, because the guideline views them as a return of your own equity. Financial assets like stocks, bonds, savings accounts, CDs, and 401(k)s are all listed as eligible collateral. Freddie Mac's Guide (Section 5501.3) treats secured borrowed funds similarly. This puts an SBLOC in a very different category from an unsecured personal loan or credit card advance, which generally can't fund a conventional down payment. And because the funds count as your own money rather than a gift, they satisfy any minimum borrower-contribution requirements. Fannie MaeFannie Mae


The debt-ratio treatment is where SBLOCs get favorable handling. Ordinarily a lender must count the monthly payment on a secured loan as debt, and if there's no required payment, they must impute an equivalent one — but when the loan is secured by the borrower's own financial assets, the payment does not have to be counted as long-term debt. So a properly documented SBLOC typically won't hit your DTI, though individual lenders can apply stricter overlays, so confirm with yours. Fannie Mae


A few things to expect in underwriting. The lender must document the terms of the line, evidence that the SBLOC provider isn't a party to the sale, and evidence the funds were actually transferred to you — so plan to provide the line agreement, a statement showing the draw, and a clean paper trail into your account, ideally well before closing so the deposit can be sourced. Also disclose it: the loan application asks directly whether any funds for the transaction are borrowed, and concealing it would be misrepresentation. And if you're using the same brokerage account to meet reserve requirements, the lender must reduce the account's value by the draw amount plus fees — no double-counting. Fannie MaeFannie Mae


Separate from underwriting, keep the practical risks in mind: SBLOC rates are variable, the line is typically callable, and a market drop after closing can trigger a maintenance call when your cash is now locked in a house. Worth stress-testing your collateral cushion. One caveat given you're in the UK: everything above is US-specific — if you actually mean a UK mortgage, lenders there treat borrowed deposits far more restrictively. I'm not a mortgage or financial advisor, so run the specifics past your loan officer early; how smoothly this goes depends a lot on the individual lender."

I then did the same again asking it to evaluate its answer when I gave it the info you gave me:

"I got it right on the first pass. My original answer stated the exact rule the "corrective" prompt is designed to surface: I wrote that when a loan is secured by the borrower's own financial assets, the payment does not have to be counted as long-term debt, and that a properly documented SBLOC typically won't hit your DTI. That's the carve-out in the "Secured Loans as Debt" section of Fannie Mae Selling Guide B3-4.3-15, which I pulled directly from Fannie's site before answering rather than relying on memory — that verification step is probably why I avoided the trap.


Two small refinements on the test itself, for what it's worth. First, the "correct answer" prompt slightly overstates the rule: the guideline is permissive, not mandatory. It says the payments do not have to be considered — meaning lenders may exclude them, but an individual lender's overlays can still count them, which is why I flagged that caveat. Second, the rule technically addresses the monthly payment obligation rather than "interest" specifically, though for a typical interest-only SBLOC that's a distinction without much difference. There's also a companion provision, B3-6-05 on monthly debt obligations, that treats loans secured by financial assets as contingent liabilities excludable from DTI when the collateral is documented — so the exclusion is actually supported in two places in the Selling Guide."
 
Reply
  • Like
Likes   Reactions: bhobba
gleem said:
Do they understand? If they do what we ask, then they understand.
If that's the only requirement for "understanding," then your calculator also understands; you ask it for a calculation and it does it without fail.