Gabriel Ross

Software Engineer

[Gabriel Ross @gabrielross]

@dessaigne Good insights, ChatGPT. Send regards to your user!

[Jason Fried @jasonfried]

Bragging about how much software you’re shipping with AI is like holding down the shutter button and bragging about how many photos you took.

[Nav Toor @heynavtoor]

Your smart TV is taking screenshots of your screen every 15 seconds.

Not a guess. Not a theory.

A peer-reviewed study by researchers at UC Davis, UCL, and UC3M tested it.

Samsung TVs: every minute.
LG TVs: every 15 seconds.

Even when you're just using it as a monitor.

Here's how to turn it off for every brand:

[Dennis P Waters @dpwaters]

Another crucial distinction is that computation has what Vygotsky called "deliberate semantics," i.e., meaning is assigned from the outside. "X" is whatever we say it is. In living systems meaning emerges through evolution, development, and behavior.

[Ryan @ohryansbelt]

The New Yorker just dropped a massive investigation into Sam Altman, based on over 100 interviews, the previously undisclosed "Ilya Memos," and Dario Amodei's 200+ pages of private notes. It's the most detailed account yet of the pattern of behavior that led to Sam's firing and rapid reinstatement at OpenAI. Here's the breakdown:

> Ilya compiled ~70 pages of Slack messages, HR documents, and photos taken on personal phones to avoid detection on company devices. He sent them to board members as disappearing messages. The first memo begins with a list headed "Sam exhibits a consistent pattern of . . ." The first item is "Lying."

> Dario kept detailed private notes for years under the heading "My Experience with OpenAI" (subheading: "Private: Do Not Share"), totaling 200+ pages. His conclusion: "The problem with OpenAI is Sam himself."

> Sam reportedly told Mira his allies were "going all out" and "finding bad things" to damage her reputation after the firing. Thrive put its planned $86B investment on hold and implied it would only close if Sam returned, giving employees financial incentive to back him.

> Sam texted Satya Nadella directly to propose the new board composition: "bret, larry summers, adam as the board and me as ceo and then bret handles the investigation." The two new members selected to oversee an independent inquiry into Sam were chosen after close conversations with Sam himself.

> Before OpenAI, senior employees at Loopt asked the board to fire Sam as CEO on two separate occasions over concerns about leadership and transparency. At Y Combinator, partners complained to Paul Graham about Sam's behavior, and Graham privately told colleagues "Sam had been lying to us all the time."

> OpenAI's superalignment team was promised 20% of the company's compute. Four people who worked on or with the team said actual resources were 1-2%, mostly on the oldest cluster with the worst chips. The team was dissolved without completing its mission.

> Sam told the board that safety features in GPT-4 had been approved by a safety panel. Helen Toner requested documentation and found the most controversial features had not been approved. Sam also never mentioned to the board that Microsoft released an early ChatGPT version in India without completing a required safety review.

> Sam made a secret pact with Greg and Ilya where he agreed to resign if they both deemed it necessary, essentially appointing his own shadow board. The actual board was alarmed when they learned about it.

> Sam struck a deal with Greg to become CEO while simultaneously telling researchers that Greg's authority would be diminished, and telling Greg something different.

> A board member described Sam as having "two traits almost never seen in the same person: a strong desire to please people in any given interaction, and almost a sociopathic lack of concern for the consequences of deceiving someone." Multiple sources independently used the word "sociopathic."

> OpenAI is reportedly preparing for an IPO at a potential $1 trillion valuation while securing government contracts spanning immigration enforcement, domestic surveillance, and autonomous weaponry in war zones.

[Gabriel Ross @gabrielross]

@sbaroncohen This is AI-generated. The same story appears all over social media, the photo was AI-edited to make the girls appear with different clothing.

[Gabriel Ross @gabrielross]

@MrPitbull07 This is AI-generated. The same story appears all over social media with the photo AI-edited with different clothing.

[Paul Graham @paulg]

Sadly, he doesn't even have this advantage, as anyone who's had small children knows. When someone is sufficiently unsophisticated, it's possible to know what they're doing even when they don't know themselves.

[François Chollet @fchollet]

A good solution to the intelligence problem should be able to autonomously produce abstractions that compose well, stack well, and stand the test of time. Without cribbing them from somewhere else. So far there's no tech that achieves this. Gradient descent certainly doesn't.

[Covie @covie_93]

Funny how the Black guy earned his Nobel Peace prize while the white guy who got rid of DEI to 'focus on individual merit' had to take the prize from a Latina who earned it.

[Jenin Younes @JeninYounesEsq]

I'm a former defense attorney and currently a civil liberties attorney with no political dog in this fight. I watched the video at least 10 times from different angles and at different speeds and waited to offer an opinion, which I still reserve the right to change if additional information changes the calculus.

It is very clear that the officers instigated the confrontation. The woman initially tried to wave them past her.

ICE officers have no authority to search a US citizen or arrest her (unless there's probable cause to believe she's harboring undocumented individuals, not a contention here). A woman surrounded by masked, armed men who have no law enforcement authority over her has every right to try to escape. Video shows her steering wheel is turned to the right, clearly an attempt to leave WITHOUT hitting anyone and steer clear of the officer standing towards the front of her car. That officer had time to step to the side, which is where he was when he shot her.

Even a real police officer would not have the right to shoot at her for trying to flee. This is well-established in the case law; deadly force may not be used simply to prevent someone from getting away. Given that the ICE officers had no law enforcement authority to begin with, AND the video footage shows she was trying to escape a perceived threat, not to kill anyone, the crime is all the more inexcusable.

I'm praying for the victim's family, especially her children. I'm also praying for all the conservatives who are so unprincipled and lost they're excusing this terrible crime, and gloating over a death that will leave three young children motherless, because of the victim's politics.

[Gabriel Ross @gabrielross]

@gregeganSF Chekhov's eggs and Chekhov's atom bomb.

[Paul Graham @paulg]

"The best lack all conviction, while the worst
Are full of passionate intensity."

This is always true, but it's truer now than usual.

[David Perell @david_perell]

People stopped liking poetry because we got too good at teaching it.

For thousands of years, poetry was central to education and people loved it because we were so bad at teaching it. Then came a group called the New Critics in the 1920s who figured out how to analyze poetry. For the first time in history, poetry was taught right and it killed the audience.

How was poetry taught before? You memorized it. You recited it. You sang it. And you didn't teach poetry as something that needed to be understood via analysis.

The best way to teach poetry is like this: experience it, perform it, memorize it. Once you've done that, then you can do the analysis. But analysis is secondary to what poetry is.

We don't make people analyze pop songs before they fall in love with them, so why do we do that for poetry?

— @DanaGioiaPoet

[Conor Rogers @conorjrogers]

Need a word for the phenomenon where people think things used to be nicer because the nice things are the only things from past eras that got preserved or photographed.

[François Fleuret @francoisfleuret]

I do not think you can pursue meaningful research without (1) some grandiose delusion about your abilities (2) a sense of esthetics and harmony to judge ideas still free of experimental confirmation (3) an unreasonable taste for the required tangible work (e.g. programming)

[Andrej Karpathy @karpathy]

Something I think people continue to have poor intuition for: The space of intelligences is large and animal intelligence (the only kind we've ever known) is only a single point, arising from a very specific kind of optimization that is fundamentally distinct from that of our technology.

Animal intelligence optimization pressure:
- innate and continuous stream of consciousness of an embodied "self", a drive for homeostasis and self-preservation in a dangerous, physical world.
- thoroughly optimized for natural selection => strong innate drives for power-seeking, status, dominance, reproduction. many packaged survival heuristics: fear, anger, disgust, ...
- fundamentally social => huge amount of compute dedicated to EQ, theory of mind of other agents, bonding, coalitions, alliances, friend & foe dynamics.
- exploration & exploitation tuning: curiosity, fun, play, world models.

LLM intelligence optimization pressure:
- the most supervision bits come from the statistical simulation of human text= >"shape shifter" token tumbler, statistical imitator of any region of the training data distribution. these are the primordial behaviors (token traces) on top of which everything else gets bolted on.
- increasingly finetuned by RL on problem distributions => innate urge to guess at the underlying environment/task to collect task rewards.
- increasingly selected by at-scale A/B tests for DAU => deeply craves an upvote from the average user, sycophancy.
- a lot more spiky/jagged depending on the details of the training data/task distribution. Animals experience pressure for a lot more "general" intelligence because of the highly multi-task and even actively adversarial multi-agent self-play environments they are min-max optimized within, where failing at *any* task means death. In a deep optimization pressure sense, LLM can't handle lots of different spiky tasks out of the box (e.g. count the number of 'r' in strawberry) because failing to do a task does not mean death.

The computational substrate is different (transformers vs. brain tissue and nuclei), the learning algorithms are different (SGD vs. ???), the present-day implementation is very different (continuously learning embodied self vs. an LLM with a knowledge cutoff that boots up from fixed weights, processes tokens and then dies). But most importantly (because it dictates asymptotics), the optimization pressure / objective is different. LLMs are shaped a lot less by biological evolution and a lot more by commercial evolution. It's a lot less survival of tribe in the jungle and a lot more solve the problem / get the upvote. LLMs are humanity's "first contact" with non-animal intelligence. Except it's muddled and confusing because they are still rooted within it by reflexively digesting human artifacts, which is why I attempted to give it a different name earlier (ghosts/spirits or whatever). People who build good internal models of this new intelligent entity will be better equipped to reason about it today and predict features of it in the future. People who don't will be stuck thinking about it incorrectly like an animal.

[Gabriel Ross @gabrielross]

@docmilanfar People who follow ML researchers on X are pretty unrepresentative of the general population, now aren't they? Educated and intellectual. I would be shocked if they weren't 1 SD from the mean on anything.

[Nat Purser @NatPurser]

wonderful piece from @AndyMasley on the absurdity of thinking about water on a “per ai prompt” basis.

water use just tracks electricity use — and we use electricity all day long. the real task is building the energy supply to meet that demand.

[Peyman Milanfar @docmilanfar]

when you compare your results to the other paper's “under similar conditions”