It's not that it fundamentally isn't able to produce something concise, it's that the business model of the companies developing these models rests on selling tokens...
because human writing IS not just producing the Next token, sometimes you write shit and then go back and find ways to improve and try to play tricks inside the structures only you or your coauthors understand. AI doesnt do this
Exactly! That's also why almost every slop commit I see has a linecount like +700 / -20, whereas human commits often end up net zero. I try to remove more lines than I add, if possible, but LLMs will just add more bloat, forever.
I don’t know. The old models were much more concise, answering your question in a couple of sentences. At some point they just started outputting walls of text for every prompt.
It's not a conspiracy to say it's unwise to expect a company to drive a research & product direction that will directly impact their reduce. Some might be smart enough to realize it's the right long game, but it takes leaders who understand and plan out second order consequences.
Bullshit. It would cost them more money to post process all the bullshit and then ship that, instead they just point the cannon at your face and pull the trigger.
No, in ~6y they will count for 1% of present day consumption. The rest of the quote compares it to where we expect steel manufacturing projections. It all reads like something that seeks to influence rather than inform.
Rumor has it that they weren't trained "from scratch" the was US would, i.e. Chinese labs benefitted from government "procured" IP (the US $B models) in order to train their $M models. Also understand there to be real innovation in the many-MoE architecture on top of that. Would love to hear a more technical understanding from someone who does more than repeat rumors, though.
Not all humans, just the ones that can't afford buy property in low risk areas, start companies to help people move, etc. and for those who can, appreciating investments galore!
That's not the same thing at all. Especially as LLM's get smaller, WhatsApp can make a lot of money reading your messages and listening to your calls on the endpoint in order to market segment your ads while remaining e2e encrypted.
As a non-benefitting fan of DEI, it always seemed like too little and/or too late [1] and the current generation of efforts have paid the cost of perceived injustice that are obviously counter-productive. This change to only having diversity for corporate benefit is an understandable choice of weak leaders in the current political climate but also unwelcome by those of us who care to actually move the needle on mutual understanding and healing of past injustices. Other countries have actually done this to a great extent, I think -- healing and reconciliation on horrific historical injustices, so it's not like this is totally novel social research.
Now to some extent but even more so if things get more "rude" for a lack of a more more specific but agreed on term, I think many educated and well rounded people with a choice in employment/location will lean towards working at employers which works more aggressively towards social justice, or move abroad to live in societies not plagues by this kind of un-healing racial strife. From my understanding of what it's like to be black elsewhere (UK, Canada), I'll be more and more surprised that people who have the means would choose to stay in the US much longer.
if someone had told me that "full of AI" was going to be an insult one day, I would have said they were too cynical about the glorious AI future, but in hindsight perhaps you are right
