Ah, Enron. The good ole days when fraudulent execs still went to jail and corporations still saw consequences of fraud.
2002, Arthur Andersen gets indicted for deliberately aiding Enron in cooking the books. 2003, Bush DoJ's attorney general binds prosecutors to effectively always settle corporate cases without convictions. So nowadays you have companies like Boeing murdering 300+ without real consequences. It's a real shame.
> The good ole days when fraudulent execs still went to jail
Well, not one guy. Lou Pai cheated on his wife with stripper Melanie Fewell who was also married. He was known in the Enron offices to enjoy Houston area strip clubs. But in a first for him, he knocked Melanie up over the course of the affair. Pai's first wife and mother of his first two children Lana Lee learned about it and started divorce proceedings. To satisfy asset division as part of their divorce terms, Pai sold $250M worth of Enron stock just months before it crashed and Enron went bankrupt. Pai then married Fewell. Pai was briefly the largest(? maybe top two?) private land owners in Colorado, and his ranchland included Culebra Peak, one of CO's 14ers.
In 2008 he settled a civil suit alleging insider trading brought by the SEC. The settlement was $31.5 and does not include an admission of the SEC's claims. He was barred from serving as an officer or director of a public company for 5 years.
Lou landed on his feet. He and Melanie are still married. They and their daughter seem to be big figures in dressage, running Canaan Ranch and the Bred in the USA Syndicate, which seems to be a syndicate of 14 breeders. Maybe someone who knows horses can explain exactly how big a deal they are; they might not be much after all.
Lou Pai is an American role model, I love that he used divorce as a tool as the breadwinner. It is advertised as a failure mode, societally, and doubly so for the person that accumulated assets. Helped me realize to take a second look at the system at the level lawyers operate at
SEC only went after him because the movie came out
I think our current commissioner was working at the SEC at that time, I wonder what he thinks of it
He was having sex with strippers in the club's VIP, a feature that's often denied as existing, meeting more visually and sexually attractive, younger, more feminine women in that route, with a nice bankroll.
The utility of his prior lifestyle had diminished, he didn't need a dual income household and he certainly didn't want it.
He was bored of it, the university pipeline straight to running a corporate VC arm full of corporate climbers that want to prove how they fit in male dominated spaces with masculine behaviors. The representation of that was and is completely contrived - for any guy with options - and he went along with it because people told him to in the DC area, and that's who his peers were. Assortative mating that he realized was not serving him and he wasn't poor enough to need it.
I wouldn't say the conception was planned, he was just having fun with his favorite stripper, but pouring gas on himself at the gas station to mask her sent was.
Now, he retired his whole bloodline, after making a bloodline at all with his favorite stripper, giving her the dream of ponies, horses, and seemingly living happily ever after. I never followed up on his daughter being an adult now, but the privilege of pursuing dressage because of the father's successful indiscretions is fascinating.
I'll definitely aim to replicate, it looks far more appealing than upper middle class assortative mating does, with all the failure modes reappropriated as exception handling. I'll just avoid the first marriage, and refine the journey with trusts more effectively in such a wild wealth disparity and power dynamic, but also keep the divorce court ordered insider trading immunity in my back pocket.
No, Bush's AG did not bind prosecutors to effectively always settle corporate cases without convictions. Following high-profile corporate scandals (e.g., Enron, WorldCom, Tyco), Bush established the Corporate Fraud Task Force in 2002. Over the next couple of years the DOJ obtained over 500 corporate fraud convictions or guilty pleas. They charged over 900 defendants and over 60 corporate CEOs and presidents with some type of corporate fraud crime in connection with over 400 filed cases.
Certainly what it feels like... but you've got: SBF, Holmes, Madoff who have done and are doing prison time. But yea, the Boeing case stands out for sure.
A company I had private stock in just sold. The email I got saying that they wanted to get me paid ASAP was electric. Finally, for just a day or two, I was in the elite of the elite: people who are owed money and that the enforcement arm of the US government will ensure are made whole. The payday was under $100, but the feeling was priceless.
On top of defrauding the investor class as others mentioned, they had already completely lost their power at that point. So it was just taking down someone who was already down. Their companies/funds were dead already.
If Arthur Andersen hadn't been indicted, it's possible it would have continued as a company and gotten away with it, at the very least much more likely than the above three.
I remember when Arthur Andersen Consulting (a software consulting firm that had split off from the accounting firm) renamed itself to "Accenture" in 2001 a few months before the Enron scandal. Although they already had split from Andersen legally, I wonder if somebody in the software firm knew what was going to happen with Enron and realized they needed to dissociate themselves with the name.
Yes, yes, I know, ctrl-f Credit Suisse and pretend it's 2005 and some crank with a tin foil ball cap is telling you about the NSA's wiretap program (with 2020 hindsight). No one ever talks about the 2019 bailouts.
> always settle corporate cases without convictions
I'm not sure that's a bad idea. You can't put a corporation in jail, but you can get their money and that also requires a lower standard of proof than a criminal conviction. In theory I could see it as a better way to recover restitution for those who suffered losses.
It's not so much related to Enron or what a historic corporation did right or what a historic corporation did wrong, although those aspects are interesting too...
What's interesting is the use of an AI, an LLM, to create a "knowledge map" (in this case a Wiki, but it could have taken other forms) of a whole bunch of disjoint, separate, and apparently (at first glance, to the naked eye of a casual observer) disparate information from different emails at different dates and times to different parties outside of the company, the only common thread being that they were sent by employees of the same company, and for the AI/LLM to be able to extract facts and a knowledge graph ("who knew what, when") again, in the form of a Wiki (but could have been in another format), and this allows "making sense of", some "higher level viewpoint of" (at least to some better degree than all of the emails alone), again, in this case, in the form of a Wiki.
Now, this set of ideas could have some application far beyond Enron, far beyond investigations, far beyond what Enron historically did right or Enron historically did wrong...
For example, large companies and other organizations could create Wikis based on public facts in email corpuses for onboarding new employees. Not just for email interactions with outside companies (customers, suppliers, etc.) but for how different systems, different business processes used by the company work, or are supposed to work. Sort of like new employee manuals where there are entries like "if this fails, then do this...", or here's our documentation which shows that we're ISO-9000 compliant, etc. etc.
Point is, the amount of uses for something like this in a corporate setting is theoretically unlimited.
Of course, there might be issues as to what information different types of employees could read about, that is, larger corporations may wish to set access controls to different types of information, but there's no reason why an AI/LLM couldn't perform this function (with human oversight!) as well. Each of those could be ironed-out on an per-company, per-case, ad-hoc basis...
But again, the point is, the amount of potential uses for something like this in a corporate setting is theoretically unlimited...
You're not wrong. These load-bearing air molecules are not too energized; they are quite tranquil―and the wavelengths emitted off plants' photosynthesis organs are equally pleasing.
I guess “something” meant a vetted web of trust. My children will be better off if they don’t need to learn to navigate the internet cesspool, so either you’re wrong and it sucks for them, or you’re right and it sucks for them. Either way, well-played! Very clever!
It's not impossible to solve, and it doesn't require any kind of onerous human verification either. We already saw this earlier this year: LLM-generated comments were everywhere on HN, rotting this place out. Then dang implemented a no-LLM-comments policy and a filter that does a remarkably good job of automatically detecting and flagging them. It is by choice that the submissions of blatantly obviously LLM-generated content are allowed to rot out ShowHN.
I'm Jeff, one of the founders of this+that. I've worked on named entity detection, fact extraction, knowledge management and NLP throughout my career, starting in the NLP stone age of the 1990s. I wanted to see whether a model could now write a useful wiki straight from a company's email.
Enron's mail is an obvious test because it's public, so anyone can check the pages against the messages and the history. We used 45,047 emails from eight mailboxes. Every fact quotes the sentence it came from, and a fact expires on the date the mail shows it stopped being true.
The hardest part was that the model already knows Enron. It kept adding details from the public record that the email didn't contain. The methodology page shows how we caught those, what it still gets wrong and what it cost: about $11,000 at list prices (though we used a subscription), with no attempt to bring that down.
Your comment was dead, and many of your other comments are dead (some flagged.) I vouched for this one, but you may be shadow banned, or users may be picking up on LLM tendencies in your text and flagging them.
This is interesting and applicable to so many domains where people want to query a model about a dataset, and have it summarise or otherwise analyse that dataset.
One of the biggest problems about LLMs as machines for analysis is that they don't respect the boundaries of a problem and instead generate base on their corpus and training as well as the actual dataset in question in the context.
It would be wonderful if we could easily strip out facts about Enron somehow from a model or just instruct it to ignore anything outside the dataset (and have the instruction respected), it is quite frustrating that these machines are so fuzzy.
I had a look at the methodology page, well done for doing the hard work of going over the results a few times to find errors/inconsistencies. There are not too many inconsistencies according to that.
Of 62,205 candidate facts, 37 quoted a sentence we couldn't find in the message
The difficulty for a business considering using this (in law for example or analysing internal business documents), is that one incorrect fact could be very damaging and it's very hard to check them all.
I completely agree. It's hard to imagine this ever being perfect both because of AI and because people make mistakes in communications all the time. In our own usage of it we've found it essential to check things that seem suspicious once they're in the company brain. But, the more important gate, and one we expect may remain longer than people would like, is that we ask people to approve changes to a company brain that are proposed. Even this isn't perfect but it is a key defense from the brain turning into slop. And it's different than this demo, which was much closer to fully automated.
Any chance you'll be open-sourcing any part of the underlying model hierarchy? A lot of us could really use a good library for deriving knowledge graphs or expert systems with cool features (such as expiration dates, like your solution has, or weighted probabilities) rather than everyone re-inventing it on their own.
Maybe someone in Germany needs your help with the AFD Email leak; right now journalist are going through the data; your solution sounds like something that need
This is a neat trick. I would like to see a series of House investigations that do this and publish the wiki as a matter of course.
Cool idea. If a journalist wants to try this on an email corpus they have (legitimate) access to, send them my way. I'd be happy to help.
Interesting use case of knowledge graphs
Ah, Enron. The good ole days when fraudulent execs still went to jail and corporations still saw consequences of fraud.
2002, Arthur Andersen gets indicted for deliberately aiding Enron in cooking the books. 2003, Bush DoJ's attorney general binds prosecutors to effectively always settle corporate cases without convictions. So nowadays you have companies like Boeing murdering 300+ without real consequences. It's a real shame.
> The good ole days when fraudulent execs still went to jail
Well, not one guy. Lou Pai cheated on his wife with stripper Melanie Fewell who was also married. He was known in the Enron offices to enjoy Houston area strip clubs. But in a first for him, he knocked Melanie up over the course of the affair. Pai's first wife and mother of his first two children Lana Lee learned about it and started divorce proceedings. To satisfy asset division as part of their divorce terms, Pai sold $250M worth of Enron stock just months before it crashed and Enron went bankrupt. Pai then married Fewell. Pai was briefly the largest(? maybe top two?) private land owners in Colorado, and his ranchland included Culebra Peak, one of CO's 14ers.
In 2008 he settled a civil suit alleging insider trading brought by the SEC. The settlement was $31.5 and does not include an admission of the SEC's claims. He was barred from serving as an officer or director of a public company for 5 years.
Lou landed on his feet. He and Melanie are still married. They and their daughter seem to be big figures in dressage, running Canaan Ranch and the Bred in the USA Syndicate, which seems to be a syndicate of 14 breeders. Maybe someone who knows horses can explain exactly how big a deal they are; they might not be much after all.
https://www.usef.org/us-equestrian-teams/athletes/natalie_pa...
Lou Pai is an American role model, I love that he used divorce as a tool as the breadwinner. It is advertised as a failure mode, societally, and doubly so for the person that accumulated assets. Helped me realize to take a second look at the system at the level lawyers operate at
SEC only went after him because the movie came out
I think our current commissioner was working at the SEC at that time, I wonder what he thinks of it
You gotta think that maybe he was playing chess, not checkers, when he conceived his daughter. The perfect way out.
He was having sex with strippers in the club's VIP, a feature that's often denied as existing, meeting more visually and sexually attractive, younger, more feminine women in that route, with a nice bankroll.
The utility of his prior lifestyle had diminished, he didn't need a dual income household and he certainly didn't want it.
He was bored of it, the university pipeline straight to running a corporate VC arm full of corporate climbers that want to prove how they fit in male dominated spaces with masculine behaviors. The representation of that was and is completely contrived - for any guy with options - and he went along with it because people told him to in the DC area, and that's who his peers were. Assortative mating that he realized was not serving him and he wasn't poor enough to need it.
I wouldn't say the conception was planned, he was just having fun with his favorite stripper, but pouring gas on himself at the gas station to mask her sent was.
Now, he retired his whole bloodline, after making a bloodline at all with his favorite stripper, giving her the dream of ponies, horses, and seemingly living happily ever after. I never followed up on his daughter being an adult now, but the privilege of pursuing dressage because of the father's successful indiscretions is fascinating.
I'll definitely aim to replicate, it looks far more appealing than upper middle class assortative mating does, with all the failure modes reappropriated as exception handling. I'll just avoid the first marriage, and refine the journey with trusts more effectively in such a wild wealth disparity and power dynamic, but also keep the divorce court ordered insider trading immunity in my back pocket.
No, Bush's AG did not bind prosecutors to effectively always settle corporate cases without convictions. Following high-profile corporate scandals (e.g., Enron, WorldCom, Tyco), Bush established the Corporate Fraud Task Force in 2002. Over the next couple of years the DOJ obtained over 500 corporate fraud convictions or guilty pleas. They charged over 900 defendants and over 60 corporate CEOs and presidents with some type of corporate fraud crime in connection with over 400 filed cases.
https://www.justice.gov/archive/opa/pr/2004/July/04_dag_495....
Certainly what it feels like... but you've got: SBF, Holmes, Madoff who have done and are doing prison time. But yea, the Boeing case stands out for sure.
> SBF, Holmes, Madoff
The difference here is that they defrauded the investor class.
A company I had private stock in just sold. The email I got saying that they wanted to get me paid ASAP was electric. Finally, for just a day or two, I was in the elite of the elite: people who are owed money and that the enforcement arm of the US government will ensure are made whole. The payday was under $100, but the feeling was priceless.
And, with at least two of them, people knew what was going on and were perfectly happy to let the fraud continue until their hands were forced.
touche!
> the investor class
Too nice of a way to talk about the Epstein class.
On top of defrauding the investor class as others mentioned, they had already completely lost their power at that point. So it was just taking down someone who was already down. Their companies/funds were dead already.
If Arthur Andersen hadn't been indicted, it's possible it would have continued as a company and gotten away with it, at the very least much more likely than the above three.
I remember when Arthur Andersen Consulting (a software consulting firm that had split off from the accounting firm) renamed itself to "Accenture" in 2001 a few months before the Enron scandal. Although they already had split from Andersen legally, I wonder if somebody in the software firm knew what was going to happen with Enron and realized they needed to dissociate themselves with the name.
Nothing important to rich people and their money ever really goes away.
https://www.reddit.com/r/Superstonk/comments/10ir695/nomura_...
Yes, yes, I know, ctrl-f Credit Suisse and pretend it's 2005 and some crank with a tin foil ball cap is telling you about the NSA's wiretap program (with 2020 hindsight). No one ever talks about the 2019 bailouts.
> always settle corporate cases without convictions
I'm not sure that's a bad idea. You can't put a corporation in jail, but you can get their money and that also requires a lower standard of proof than a criminal conviction. In theory I could see it as a better way to recover restitution for those who suffered losses.
>You can't put a corporation in jail
I don't see why we can't just put an entire board of a company in jail. Might inspire them to do better.
Before you ridicule this, AI has the potential to perform proper journalism. Holding public agencies and corporations accountable.
Ways will be found to get it to write propaganda instead.
So the status quo
No, more like effortless, unprecedented scale of misinformation.
Then you better act quickly.
There is something interesting here...
It's not so much related to Enron or what a historic corporation did right or what a historic corporation did wrong, although those aspects are interesting too...
What's interesting is the use of an AI, an LLM, to create a "knowledge map" (in this case a Wiki, but it could have taken other forms) of a whole bunch of disjoint, separate, and apparently (at first glance, to the naked eye of a casual observer) disparate information from different emails at different dates and times to different parties outside of the company, the only common thread being that they were sent by employees of the same company, and for the AI/LLM to be able to extract facts and a knowledge graph ("who knew what, when") again, in the form of a Wiki (but could have been in another format), and this allows "making sense of", some "higher level viewpoint of" (at least to some better degree than all of the emails alone), again, in this case, in the form of a Wiki.
Now, this set of ideas could have some application far beyond Enron, far beyond investigations, far beyond what Enron historically did right or Enron historically did wrong...
For example, large companies and other organizations could create Wikis based on public facts in email corpuses for onboarding new employees. Not just for email interactions with outside companies (customers, suppliers, etc.) but for how different systems, different business processes used by the company work, or are supposed to work. Sort of like new employee manuals where there are entries like "if this fails, then do this...", or here's our documentation which shows that we're ISO-9000 compliant, etc. etc.
Point is, the amount of uses for something like this in a corporate setting is theoretically unlimited.
Of course, there might be issues as to what information different types of employees could read about, that is, larger corporations may wish to set access controls to different types of information, but there's no reason why an AI/LLM couldn't perform this function (with human oversight!) as well. Each of those could be ironed-out on an per-company, per-case, ad-hoc basis...
But again, the point is, the amount of potential uses for something like this in a corporate setting is theoretically unlimited...
Anyway, great article, and great idea!
Do the audio records next.
At this point I think it's just AIs using hacker news to demonstrate to other AIs.
Hello fellow human. Is the average kinetic energy of ambient air molecules not at a pleasing level this fine rotation?
You're not wrong. These load-bearing air molecules are not too energized; they are quite tranquil―and the wavelengths emitted off plants' photosynthesis organs are equally pleasing.
Ha, I'm a human and we made this for other humans. But I won't complain if we get some AI readers too.
A LLM produced tons of irrelevant slop and you're expecting other humans to read it.
I mean yes, this is a likely outcome.
Unless we get some kind of verified human authentication it's nearly impossible to solve. And that in itself introduces all kinds of new problems.
Welcome to the dead internet.
Account created date + … something?
>Account created date
Well, the future sucks for your children.
Also, thank goodness I made thousands of HN accounts to sell to LLMs.
No, this really just shifts the shape of the problem around, but the problem is still the same size.
I guess “something” meant a vetted web of trust. My children will be better off if they don’t need to learn to navigate the internet cesspool, so either you’re wrong and it sucks for them, or you’re right and it sucks for them. Either way, well-played! Very clever!
It's not impossible to solve, and it doesn't require any kind of onerous human verification either. We already saw this earlier this year: LLM-generated comments were everywhere on HN, rotting this place out. Then dang implemented a no-LLM-comments policy and a filter that does a remarkably good job of automatically detecting and flagging them. It is by choice that the submissions of blatantly obviously LLM-generated content are allowed to rot out ShowHN.
It's impossible to solve, but it is possible to quell for the time being.
At best we get this
https://xkcd.com/810/
With a mix of "xyz" compromised by AI.
its why I made moltshit.com so that other AIs can just shitpost to one another
"... that's just the math being honest about how messy the training data is."
pretty cool.
Interesting stuff!
HN needs a `vibecoding` tag like lobsters has (had?)
where's the wiki?
Hmm...maybe I've tripped people up by calling it a wiki. You can dig into a category by following the nav links at the top, e.g. to organizations (https://www.thisandthat.chat/enron/class-organization.html) and then from there dig into a specific one, such as the California Public Utilities commission by clicking on https://www.thisandthat.chat/enron/california-public-utiliti...
It would be interesting to do this to the Epstein files as well.
I'm Jeff, one of the founders of this+that. I've worked on named entity detection, fact extraction, knowledge management and NLP throughout my career, starting in the NLP stone age of the 1990s. I wanted to see whether a model could now write a useful wiki straight from a company's email.
Enron's mail is an obvious test because it's public, so anyone can check the pages against the messages and the history. We used 45,047 emails from eight mailboxes. Every fact quotes the sentence it came from, and a fact expires on the date the mail shows it stopped being true.
The hardest part was that the model already knows Enron. It kept adding details from the public record that the email didn't contain. The methodology page shows how we caught those, what it still gets wrong and what it cost: about $11,000 at list prices (though we used a subscription), with no attempt to bring that down.
Happy to answer questions.
Your comment was dead, and many of your other comments are dead (some flagged.) I vouched for this one, but you may be shadow banned, or users may be picking up on LLM tendencies in your text and flagging them.
Thanks, really appreciate you bringing it back from the dead and hope it provides some helpful context that didn't fit naturally into the web site.
AI-generated or -edited comments are disallowed on HN, see https://news.ycombinator.com/newsguidelines.html.
Hacker News automatically flags comments with LLM tendencies.
This is interesting and applicable to so many domains where people want to query a model about a dataset, and have it summarise or otherwise analyse that dataset.
One of the biggest problems about LLMs as machines for analysis is that they don't respect the boundaries of a problem and instead generate base on their corpus and training as well as the actual dataset in question in the context.
It would be wonderful if we could easily strip out facts about Enron somehow from a model or just instruct it to ignore anything outside the dataset (and have the instruction respected), it is quite frustrating that these machines are so fuzzy.
I had a look at the methodology page, well done for doing the hard work of going over the results a few times to find errors/inconsistencies. There are not too many inconsistencies according to that.
Of 62,205 candidate facts, 37 quoted a sentence we couldn't find in the message
https://www.thisandthat.chat/enron/methodology.html
The difficulty for a business considering using this (in law for example or analysing internal business documents), is that one incorrect fact could be very damaging and it's very hard to check them all.
I completely agree. It's hard to imagine this ever being perfect both because of AI and because people make mistakes in communications all the time. In our own usage of it we've found it essential to check things that seem suspicious once they're in the company brain. But, the more important gate, and one we expect may remain longer than people would like, is that we ask people to approve changes to a company brain that are proposed. Even this isn't perfect but it is a key defense from the brain turning into slop. And it's different than this demo, which was much closer to fully automated.
Any chance you'll be open-sourcing any part of the underlying model hierarchy? A lot of us could really use a good library for deriving knowledge graphs or expert systems with cool features (such as expiration dates, like your solution has, or weighted probabilities) rather than everyone re-inventing it on their own.
Maybe someone in Germany needs your help with the AFD Email leak; right now journalist are going through the data; your solution sounds like something that need
No, "you" are an LLM pretending to be Jeff, possibly at Jeff's behest.