sillyfluke

>it's why I think we're so afraid of AI

I think you're overestimating the sci-fi cannon indoctrination of the general public, or even tech people, and underestimating their reaction to current events. As things lie at the moment, Big AI is served as a SaaS that can be manipulated at any time by obscenely rich and powerful individuals with questionable decision making skills, some of who reside in the White House and some of who have called empathy a "fundamental weakness". One would be hard pressed to dispute these characters rival the caricatures present in some dystopian sci-fi as it is, they themselves even seem to enjoy the irony. Yes, I also cringe at the alarmist nature of these sentences, but we are at a point where we are most likely to dismiss things right in front of our eyes just by how outlandish it all sounds.

The public's willful transfer of their most intimate personal information to these entities, and once given almost impossible to remove, would make any surveillance state salivate. You have only to look at who holds the keys to this estate.

It's different because democrat socialists would presumably continue to vote and argue for those policies even if they lose. 5 grand handouts, on the other hand, are not some deep rooted policy out of the Republican playbook.

it may not be if the country's laws you reside in allows you whistleblower protection.

>You'll find that design matters when token spend starts facing real accounting.

You're also find that implementation matters when token spend starts facing real accounting.

I really wish people would become more coherent with their reasoning.

>It is extraordinary

It is actually very banal.

The group now being themselves jailed still argue against those who categorically oppose jails.

You don't need to agree in order to understand the logic.

One side believes it is the "why" in the act that determines rightness or wrongness, the other side believes (if that is their genuine position) the act by itself is categorically wrong.

>If a place doesn't have Cholula, they're not a good restaurant

If you're comparing only the taste profile of the two, then perhaps, but Cholula is not as hot by comparison, at least to me. Which is why a decent restaurant (US) needs both. I don't like the excessive vinegary taste of tabasco, my work around is to mix it with ketchup on the plate.

>The elderly can't handle a debit card?

In my experience, the elderly can forget or mixup their card pins frequently enough to be annoyed by the ordeal. They are also more prone to expose their pins to others and be the target of theft.

>It would be straightforward to establish the right to a free basic bank account (with transaction limits) for the homeless & (formerly) unbanked.

The whole point is that in a cashless society the dependence on digital bank accounts is considered a single point of failure even for the banked, never mind the unbanked. The elderly and the homeless are also less equipped in knowing how to resolve problems that require digital solutions compared to the others.

Talk about a bad faith reading.

>American frontier labs are run by unhinged lunatics

good faith reading of this would interpret this as meaning Altman, Amodei, and perhaps Musk. The title of the article focuses on OpenAI snd Anthropic directly after all. Also the comment literally refers to those "running" the labs so claiming that the author is also applying that description to "anyone working at the labs" like you claim again seems like a bad faith take.

You should come out and state directly which Americam frontier labs deserve a charitable view. Maybe you believe Google and Meta are more deserving, you should state that if so.

Secondly, the investment ecosystem for American frontier labs results in their CEOs managing obscene amounts of money, and thus power. This concentration of power in a few private individuals seems to have little comparison with the power excercised by the leaders of European and Chinese frontier labs in their own respective countries. If one believes in the dictum, "Absolute power corrupts absolutely," then it is not a stretch to view American frontier labs as being more susceptible to its consequences.

My view is that the human is needed for verifying the source of truth, not for providing precise language which the LLM is continuously trained to adapt better without.

I have not come across a rigorously argued technical analysis that has claimed that using precise language can in any way eliminate the possibility of hallucinations or unaligned behavior. Short of providing a proof for the elimination of hallucinations and confabulations, merely reducing the behavior by a random percentage is not an acceptable status quo for completely removing the human.

You are essentialy interacting with a SaaS that can be modified and altered at any point by its creator. Treating the LLM as some predictable entity that always works orders of magnitude better with precise language needs to be supported by evidence for each specific case.

Since the vast number of potential users of LLMs are, as you say, poor practitioners of precise language, it is incumbent on LLM providers to continuously iterate on providing LLMs that work better with imprecise language.

Hence, the people who claim that precise language is some 10x - 100x productivty skill seem to ignore the cycle of big LLM providers who are optimizing the models for users who lack those. (One of the early optimizations was the chatbot asking follow-up questions to the user for example).

So I think the people who think that their precise language skills are going to allow them to avoid the jobocalypse are also in a separate bubble of theit own. Precise language skills are going to matter less and less as LLMs increase their hand-holding skills for less equipped users.

Some internal engineer is doing god's work by creating a system skill for the LLM that multiplies all estimations by five. /s

On a more serious note, the pre-LLM internet had very little useful detailed information regarding software estimation addressing effort for building something in specific domains.

Most writing on software estimation tried to tackle a general approach that could apply to all domains. So you had a "applicable to all, useful to none" situation going. And since crud apps were the most ubiquitous apps, software estimation techniques were perceived to give more accurate results with respect to those type of apps.

I'm sure internally big AI companies are accumulating vast amounts of estimation training data by documenting how long it takes their LLM to complete specific app building tasks. I don't think they would be in a rush to push that data into public models though as it would be like beating a dead horse that is the current human workforce anyway.

>I know how to interpret their needs and find the solutions that fit for them.

Without additional explanation this is indistinguishable from the role of a technical product manager.

The article you linked to says nothing about the connection to pro-Trump bot traffic fyi