because it encodes semantics.
if it really did so, performance wouldn't swing up or down when you change syntactic or symbolic elements of problems. the only information encoded is language-statistical
"rat furry" :3
"(it's short for rationalist)" >:(
it is a little entertaining to hear them do extended pontifications on what society would look like if we had pocket-size AGI, life-extension or immortality tech, total-immersion VR, actually-good brain-computer interfaces, mind uploading, etc. etc. and then turn around and pitch a fit when someone says "okay so imagine if there were a type of person that wasn't a guy or a girl"
good longpost, i approve
honestly i wouldn't be surprised if some AI companies weren't cheating at AI metrics with little classically-programmed, find-and-replace programs. if for no other reason than i think the idea of some programmer somewhere being paid to browse twitter on behalf of OpenAI and manually program exceptions for "how many months does it take 9 women to make 1 baby" is hilarious
data scientists can have little an AI doomerism, as a treat
the upside: we can now watch "disruptive startups" go through the aquire funding -> slapdash development -> catastrophic failure -> postmortem cycle at breakneck speeds
syncthing is an extremely valuable piece of software in my eyes, yeah. i've been using a single synced folder as my google drive replacement and it works nearly flawlessly. i have a separate system for off-site backups, but as a first line of defense it's quite good.
correlation? between the rise in popularity of tools that exclusively generates bullshit en masse and the huge swelling in volume of bullshit on the Internet? it's more likely than you think
it is a little funny to me that they're taking about using AI to detect AI garbage as a mechanism of preventing the sort of model/data collapse that happens when data sets start to become poisoned with AI content. because it seems reasonable to me that if you start feeding your spam-or-real classification data back into the spam-detection model, you'd wind up with exactly the same degredations of classification and your model might start calling every article that has a sentence starting with "Certainly," a machine-generated one. maybe they're careful to only use human-curated sets of real and spam content, maybe not
it's also funny how nakedly straightforward the business proposition for SEO spamming is, compared to literally any other use case for "AI". you pay $X to use this tool, you generate Y articles which reach the top of Google results, you generate $(X+P) in click revenue and you do it again. meanwhile "real" business are trying to gauge exactly what single digit percent of bullshit they can afford to get away with putting in their support systems or codebases while trying to avoid situations like being forced to give refunds to customers under a policy your chatbot hallucinated (archive.org link) or having to issue an apology for generating racially diverse Nazis (archive).
i absolutely love the "clarification" that an email address is PII only if it's your real, primary, personal email address, and any other email address (that just so happens to be operated and used exclusively by a single person, even to the point of uniquely identifying that person by that address) is not PII
Actually, that email exchange isn’t as combative as I expected.
i suppose the CEO completely barreling forward past multiple attempts to refuse conversation while NOT screaming slurs at the person they're attempting to lecture, is, in some sense, strictly better than the alternative
ebu
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i think you're missing the point that "Deepseek was made for only $6M" has been the trending headline for the past while, with the specific point of comparison being the massive costs of developing ChatGPT, Copilot, Gemini, et al.
to stretch your metaphor, it's like someone rolling up with their car, claiming it only costs $20 (unlike all the other cars that cost $20,000), when come to find out that number is just how much it costs to fill the gas tank up once