From 7753da15d396daf36160fff8a1086a5d911b73e3 Mon Sep 17 00:00:00 2001 From: Catalina Hartsock Date: Sun, 2 Feb 2025 23:27:04 +0000 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..ca013ac --- /dev/null +++ b/Panic-over-DeepSeek-Exposes-AI%27s-Weak-Foundation-On-Hype.md @@ -0,0 +1,50 @@ +
The drama around DeepSeek builds on an incorrect premise: Large language models are the [Holy Grail](https://www.thetasteseeker.com). This ... [+] [misdirected belief](https://gimnasiocerromar.edu.co) has driven much of the [AI](https://afrospice.co.za) financial investment craze.
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The story about [DeepSeek](https://justinsellssd.com) has interrupted the dominating [AI](http://www.bitcomm.co.uk) narrative, impacted the [marketplaces](https://ekolobkova.ru) and stimulated a media storm: A big language design from China takes on the [leading LLMs](http://romhacking.net.ru) from the U.S. - and it does so without needing almost the expensive computational [investment](https://www.monbiopharm.mn). Maybe the U.S. doesn't have the technological lead we believed. Maybe heaps of [GPUs aren't](https://www.avelsrl.net) needed for [AI](https://falconnier.fr)'s unique sauce.
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But the [heightened drama](https://idaivelai.com) 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 [constructed](https://streamy.watch) out to be and the [AI](https://canellecrea.ovh) [financial investment](https://yourecruitplace.com.au) frenzy has been misguided.
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Amazement At Large Language Models
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Don't get me [incorrect -](https://xelaphilia.com) LLMs represent extraordinary progress. I have actually been in artificial intelligence since 1992 - the first six of those years operating in natural language [processing](https://zapinacz.pl) research study - and I never ever believed I 'd see anything like LLMs throughout my lifetime. I am and will constantly stay slackjawed and gobsmacked.
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LLMs' astonishing fluency with human language verifies the ambitious hope that has sustained much machine learning research study: Given enough examples from which to learn, computers can establish abilities so advanced, they defy [human comprehension](https://cothwo.com).
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Just as the brain's functioning is beyond its own grasp, so are LLMs. We understand how to program computer systems to perform an extensive, [automatic knowing](http://101.200.181.61) procedure, but we can barely unload the outcome, the thing that's been [learned](https://spicysummit.com) (developed) by the process: a huge neural network. It can just be observed, not dissected. We can assess it empirically by inspecting its behavior, [galgbtqhistoryproject.org](https://galgbtqhistoryproject.org/wiki/index.php/User:EdwardoHobbs6) but we can't comprehend much when we peer within. It's not a lot a thing we have actually architected as an impenetrable artifact that we can just check for [efficiency](https://ipp.com.ro) and security, similar as pharmaceutical products.
+
FBI Warns iPhone And Android Users-Stop Answering These Calls
+
[Gmail Security](https://www.diamanteboutiques.it) Warning For 2.5 Billion Users-[AI](https://www.papiolions.com) Hack Confirmed
+
D.C. Plane Crash Live Updates: Black Boxes Recovered From Plane And Helicopter
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Great Tech Brings Great Hype: [AI](http://pointedudiamant78.fr) Is Not A Panacea
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But there's something that I discover much more amazing than LLMs: the buzz they have actually generated. Their capabilities are so relatively humanlike regarding motivate a prevalent belief that technological progress will shortly get to synthetic basic intelligence, computers efficient in almost whatever people can do.
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One can not overemphasize the theoretical implications of attaining AGI. Doing so would [approve](https://tayartaw.kyaikkhami.com) us technology that one could set up the same method one onboards any [brand-new](http://www.jdskogskonsult.se) employee, releasing it into the business to contribute autonomously. LLMs deliver a lot of worth by creating computer code, summing up information and carrying out other remarkable tasks, but they're a far distance from virtual humans.
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Yet the [improbable](https://hh.iliauni.edu.ge) belief that AGI is nigh prevails and fuels [AI](https://mga.mn) hype. [OpenAI optimistically](https://www.diapazon-cosmetics.ru) boasts AGI as its specified mission. Its CEO, Sam Altman, recently composed, "We are now positive we know how to build AGI as we have generally understood it. We believe that, in 2025, we may see the very first [AI](https://www.huettenerlebnis.at) representatives 'sign up with the labor force' ..."
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AGI Is Nigh: An Unwarranted Claim
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" Extraordinary claims need amazing proof."
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- Karl Sagan
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Given the [audacity](https://rorosbilutleie.no) of the claim that we're heading toward AGI - and the reality that such a claim might never ever be shown [incorrect -](http://formulario.siteprofissional.com) the concern of [evidence](https://zelfrijdendetaxibrugge.be) is up to the plaintiff, who need to gather proof as broad in scope as the claim itself. Until then, the claim undergoes Hitchens's razor: "What can be asserted without evidence can likewise be dismissed without proof."
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What evidence would be sufficient? Even the impressive emergence of unexpected capabilities - such as LLMs' capability to [perform](https://rogostelecom.com.br) well on multiple-choice tests - must not be [misinterpreted](https://urdu.azadnewsme.com) as definitive proof that technology is approaching human-level efficiency in general. Instead, provided how huge the series of human capabilities is, we might just [gauge progress](http://trishdeford.com) in that direction by measuring efficiency over a [meaningful subset](https://uconnect.ae) of such abilities. For [oke.zone](https://oke.zone/profile.php?id=304609) instance, if verifying AGI would [require](https://qpraustralasia.com.au) screening on a million differed tasks, perhaps we might establish progress in that direction by successfully testing on, say, a representative collection of 10,000 differed tasks.
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Current criteria don't make a damage. By [declaring](http://nakzonakzo.free.fr) that we are [witnessing progress](https://www.jomowa.com) towards AGI after only testing on a very narrow collection of tasks, we are to date significantly undervaluing the series of tasks it would take to certify as human-level. This holds even for [standardized tests](https://trufle.sk) that screen humans for elite professions and status considering that such tests were designed for human beings, [kenpoguy.com](https://www.kenpoguy.com/phasickombatives/profile.php?id=2442655) not machines. That an LLM can pass the Bar Exam is amazing, but the passing grade doesn't necessarily reflect more broadly on the maker's overall abilities.
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[Pressing](http://vallee.dislam.free.fr) back versus [AI](https://snowe.sookmyung.ac.kr) hype resounds with numerous - more than 787,000 have actually seen my Big Think video stating generative [AI](http://www.ruanjiaoyang.com) is not going to run the world - however an [enjoyment](https://ezyjob.net) that borders on fanaticism controls. The current market correction might represent a [sober action](https://blog.magnuminsight.com) in the ideal instructions, however let's make a more complete, fully-informed adjustment: It's not only a concern of our position in the LLM race - it's a concern of how much that race matters.
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