There was already a lot of ML bullshit from the big data bubble ~ 2010 and before ChatGPT, together with all of the fuss about data scientists. But now it’s a 100 times worse.

The link doesn’t work for me.

Even if the initial intention is positive, I think this degree of dependency on external services is not realistic even if mega corps were not as bad as they are currently.

Could be that the unusual characters make the comment less readable.

Most gamers don’t want to get involved with PC building and just want something as convenient as a console to play their Steam games with good performance on a big screen. This can be priced quite above what a nerd would be able to build by himself with PCPartPicker.

There are conventional definitions of the poverty line. In France, it is defined by the national institute of statistics as:

The poverty threshold is conventionally set at 60% of the population’s median standard of living. It corresponds to a disposable income of €1,288 per month for a single person and €2,705 for a couple with two children under 14 years old. https://www.insee.fr/fr/statistiques/5759045

I looked for the original article, abstract:

Human capital—encompassing cognitive skills and personality traits—is critical for labor market success, yet the personality component remains difficult to measure at scale. Leveraging advances in artificial intelligence and comprehensive LinkedIn data, we extract the Big 5 personality traits from facial images of 96,000 MBA graduates, and demonstrate that this novel" Photo Big 5" predicts school rank, compensation, job seniority, industry choice, job transitions, and career advancement. Using administrative records from top-tier MBA programs, we find that the Photo Big 5 exhibits only modest correlations with cognitive measures like GPA and standardized test scores, yet offers comparable incremental predictive power for labor outcomes. Unlike traditional survey-based personality measures, the Photo Big 5 is readily accessible and potentially less susceptible to manipulation, making it suitable for wide adoption in academic research and hiring processes. However, its use in labor market screening raises ethical concerns regarding statistical discrimination and individual autonomy.

The PDF is downloadable here: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=2eia4X4AAAAJ&sortby=pubdate&citation_for_view=2eia4X4AAAAJ%3A_FxGoFyzp5QC

I don’t have the time nor the expertise to read everything to understand how they take into account the bias that good looking white men with educated parents are way more likely to succeed at life.

Kim Kardashian compressed with AI so her butt protrudes from her back.

Resistance networks who hid and smuggled targets out of reach at the very least.

Does that mean I will have more choice in which surveillance agency I want to be spied by?

But it also doesn’t need to be as exact as SQL, which removes some kind of complexity.

It would not be a fully determining schema that could apply to random outputs, I would guess this is impossible for natural language, and if it is possible, then it may as well be used for procedural generation. It would be just enough to make an LLM output be good enough. It doesn’t need to be perfect because human output is not perfect either.

You seem to imply we can only use the raw output of the LLm but that’s not true. We can add some deterministic safeguards afterwards to reduce hallucinations and increase relevancy. For example if you use an LLM to generate SQL, you can verify that the answer respects the data schemas and the relationship graph. That’s a pretty hot subject right now, I don’t see why it couldn’t be done for video game dialogues.
Indeed, I also agree that the consumption of resources it requires may not be worth the output.

I am using them as a side tool for development. I think LLMs are already very performent for web knowledge search (e.g. replacing a search on stackoverflow), suggestions, explanations and error detection. Although is it worth the resources consumption? Not sure, but I can’t afford not staying on top of the tooling available for my job. However, I agree, in my experience, the edit/agent modes are not efficient for coding, for now.

Generating secondary dialogues for a video game is quite a lower quality requirement than software engineering. So I think it could work there. It requires sounding natural, not being exact, LLMs are good at this.

I think it could work to give dynamic and varied answers to secondary characters given good prompts and other guardrails to preserve the immersion. As long as the core elements of the games are not AI generated slope, and developers are honest about where it was used.

My cousin in Darwin, OP also means original post, I got the joke. The comment was about the science behind, so that’s what I replied about.

It’s not clear apparently. https://en.wikipedia.org/wiki/Junk_DNA.
Although OP seems to confuse non-coding DNA (the ~98%) and junk DNA. Some non-coding DNA has clearly identified roles, so it should be well below 98% of junk, and there’s a lot left to explore.

I guess your job market as a scientist is even worse than for IT engineers right now. So I would keep looking for a new job while keeping my head down at the current one until I can safely secure a new one. There’s also a possibility that your problems at 2 months will get better after 6 months once you get to know all your colleagues better and make some allies.

It will keep happening. LLMs are the perfect tools for those huge meat grinding consulting companies. Their industry is all about looking good, not factual quality, just like LLMs.

bUt It’S sTaBLe FoR neiGH

which meme