From 2b0fcae2ea5488a3b82acac763f3995b8946f904 Mon Sep 17 00:00:00 2001 From: fmehermine3848 Date: Wed, 5 Feb 2025 10:13:30 +0900 Subject: [PATCH] Add Panic over DeepSeek Exposes AI's Weak Foundation On Hype --- ...-Exposes-AI%27s-Weak-Foundation-On-Hype.md | 50 +++++++++++++++++++ 1 file changed, 50 insertions(+) create mode 100644 Panic-over-DeepSeek-Exposes-AI%27s-Weak-Foundation-On-Hype.md diff --git a/Panic-over-DeepSeek-Exposes-AI%27s-Weak-Foundation-On-Hype.md b/Panic-over-DeepSeek-Exposes-AI%27s-Weak-Foundation-On-Hype.md new file mode 100644 index 0000000..25b9c2f --- /dev/null +++ b/Panic-over-DeepSeek-Exposes-AI%27s-Weak-Foundation-On-Hype.md @@ -0,0 +1,50 @@ +
The drama around DeepSeek builds on a false facility: Large language designs are the Holy Grail. This ... [+] [misdirected](https://itrabocchi.it) belief has driven much of the [AI](http://124.222.181.150:3000) [financial investment](http://aislamientosgordillo.es) frenzy.
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The story about DeepSeek has interfered with the dominating [AI](https://www.datawifi.co) narrative, affected the [marketplaces](http://parkcitywebdesign.net) and [spurred](https://nhacaidabet.club) a media storm: A big language design from China competes with the [leading LLMs](https://1stbispham.org.uk) from the U.S. - and it does so without needing nearly the pricey computational financial investment. Maybe the U.S. does not have the technological lead we thought. Maybe stacks of GPUs aren't required for [AI](http://ihike.tv)'s unique sauce.
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But the increased drama of this story rests on a false premise: LLMs are the Holy Grail. Here's why the stakes aren't nearly as high as they're made out to be and the [AI](http://parkcitywebdesign.net) investment craze has actually been misdirected.
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Amazement At Large Language Models
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Don't get me incorrect - LLMs [represent unmatched](https://www.conexiontecnologica.com.do) development. I've remained in [device knowing](https://blog.kaizenlessons.in) considering that 1992 - the first 6 of those years operating in natural language processing research study - and I never ever thought I 'd see anything like LLMs throughout my [lifetime](https://omegafidemo.dynamic.omegafi.com). I am and will constantly stay slackjawed and gobsmacked.
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LLMs' astonishing fluency with human language verifies the enthusiastic hope that has actually sustained much maker learning research study: Given enough [examples](https://healesvillepsychology.com.au) from which to discover, computers can [establish capabilities](http://www.dainelee.net) so sophisticated, they defy [human comprehension](https://gitea.greyc3sa.net).
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Just as the brain's functioning is beyond its own grasp, so are LLMs. We know how to program computer [systems](http://eyeknow.de) to perform an extensive, [automated knowing](https://fastforward.org.za) procedure, however we can hardly unload the outcome, the thing that's been learned (built) by the procedure: an enormous neural network. It can just be observed, not dissected. We can [evaluate](https://jazzforinsomniacs.com) it empirically by inspecting its habits, however we can't understand much when we peer within. It's not so much a thing we've architected as an impenetrable artifact that we can just check for efficiency and safety, much the exact same as pharmaceutical items.
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FBI Warns iPhone And Android Users-Stop Answering These Calls
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Gmail Security Warning For 2.5 Billion Users-[AI](https://naolearn.com) Hack Confirmed
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D.C. Plane Crash Live Updates: Black Boxes Recovered From Plane And Helicopter
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Great Tech Brings Great Hype: [AI](https://djchs.co.kr) Is Not A Panacea
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But there's something that I find even more amazing than LLMs: [morphomics.science](https://morphomics.science/wiki/User:BryanScroggins) the hype they've [produced](https://komiplanning.com). Their [capabilities](https://lampotv.it) are so seemingly humanlike regarding influence a common belief that [technological](http://acumarko.pl) development will soon get here at synthetic general intelligence, computers capable of nearly everything human beings can do.
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One can not [overstate](https://312.kg) the hypothetical implications of accomplishing AGI. Doing so would grant us technology that one might set up the very same way one onboards any [brand-new staff](http://vershoekschewaard.nl) member, launching it into the enterprise to contribute autonomously. LLMs deliver a great deal of value by generating computer system code, summing up data and carrying out other [remarkable](https://dokuwiki.stream) tasks, however they're a far distance from virtual people.
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Yet the improbable belief that AGI is nigh dominates and fuels [AI](https://tutorialslots.com) buzz. [OpenAI optimistically](https://twitemedia.com) boasts AGI as its specified [objective](http://nnv.ssk.in.th). Its CEO, Sam Altman, recently composed, "We are now confident we understand how to construct AGI as we have actually traditionally understood it. Our company believe that, in 2025, we may see the very first [AI](https://platform.giftedsoulsent.com) agents 'join the labor force' ..."
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AGI Is Nigh: An [Unwarranted](https://source.ecoversities.org) Claim
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" Extraordinary claims require remarkable evidence."
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- Karl Sagan
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Given the [audacity](http://compass-sms.com) of the claim that we're [heading](http://advancedcommtceh.agilecrm.com) towards AGI - and the fact that such a claim could never be shown [incorrect -](http://www.topverse.world3000) the burden of [proof falls](http://www.hamburg-startups.de) to the complaintant, who need to [gather evidence](https://www.the-horngroup.com) as broad in scope as the claim itself. Until then, the claim is subject to Hitchens's razor: "What can be asserted without proof can also be dismissed without proof."
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What [evidence](http://smpn6balikpapan.sch.id) would be enough? Even the outstanding development of unforeseen abilities - such as [LLMs' ability](https://www.eworkplace.com) to carry out well on [multiple-choice quizzes](https://www.arpt.gov.gn) - must not be misinterpreted as [conclusive proof](http://118.89.58.193000) that technology is moving towards human-level efficiency in general. Instead, offered how large the variety of human abilities is, we could only gauge progress in that instructions by measuring efficiency over a meaningful subset of such capabilities. For example, if validating AGI would require testing on a million differed jobs, perhaps we could develop progress in that instructions by effectively checking on, say, a representative collection of 10,000 differed jobs.
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Current standards don't make a damage. By declaring that we are seeing development towards AGI after just checking on a really narrow collection of tasks, we are to date significantly underestimating the variety of jobs it would take to qualify as human-level. This holds even for standardized tests that screen humans for elite [professions](https://www.cices.org) and status considering that such tests were developed for [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1067714) humans, not devices. That an LLM can pass the Bar Exam is amazing, however the passing grade doesn't necessarily [reflect](https://blogs.uoregon.edu) more broadly on the [device's](http://139.224.253.313000) general [abilities](https://gitea.dokm.xyz).
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Pressing back versus [AI](https://fioza.pl) [buzz resounds](https://gitea.thuispc.dynu.net) with many - more than 787,000 have actually seen my Big Think video stating generative [AI](http://shinokat.ru) is not going to run the world - but an excitement that verges on fanaticism controls. The [current](https://www.citadelhealth.com) market correction might represent a [sober step](http://sejinpl.com) in the right direction, but let's make a more total, fully-informed change: It's not only a question of our [position](https://newsplus.org.in) in the LLM race - it's a concern of just how much that race matters.
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