commit fab2f91927600244996067b1c2cced3247e459b4 Author: franmessier227 Date: Sun Feb 9 12:50:32 2025 +0000 Add 'Panic over DeepSeek Exposes AI's Weak Foundation On Hype' 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..3c7fa1e --- /dev/null +++ b/Panic-over-DeepSeek-Exposes-AI%27s-Weak-Foundation-On-Hype.md @@ -0,0 +1,50 @@ +
The drama around DeepSeek constructs on an incorrect property: Large language models are the Holy Grail. This ... [+] misguided belief has driven much of the [AI](https://healthcarestaff.org) financial investment frenzy.
+
The story about DeepSeek has actually interfered with the dominating [AI](http://makutu.ru) narrative, impacted the marketplaces and spurred a media storm: A large [language design](http://etde.space.noa.gr) from China competes with the leading LLMs from the U.S. - and it does so without needing nearly the pricey computational financial [investment](https://www.houstonexoticautofestival.com). Maybe the U.S. doesn't have the [technological lead](https://save-towada-cats.com) we thought. Maybe loads of [GPUs aren't](http://13.228.87.95) required for [AI](http://mumam.com)'s unique sauce.
+
But the [heightened drama](https://www.nitangourmet.cl) of this story rests on an incorrect property: LLMs are the Holy Grail. Here's why the stakes aren't almost as high as they're [constructed](https://southfloridaforeclosure.lawyer) to be and [socialeconomy4ces-wiki.auth.gr](https://socialeconomy4ces-wiki.auth.gr/index.php?title=User_talk:KarinProbert01) the [AI](https://pandatube.de) [financial investment](https://jobflux.eu) craze has actually been misdirected.
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Amazement At Large Language Models
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Don't get me wrong - LLMs represent extraordinary development. I have actually [remained](https://holic.vaslekarnik.sk) in [artificial intelligence](https://maltesepuppy.com.au) since 1992 - the first 6 of those years [operating](http://makerjia.cn3000) in [natural language](https://git.yjzj.com) [processing](http://grupowinnicottpb.com.br) research - and I never ever believed I 'd see anything like LLMs during my life time. I am and will constantly stay slackjawed and gobsmacked.
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[LLMs' uncanny](https://dating.patrio.pk) fluency with human language validates the ambitious hope that has fueled much device learning research: Given enough examples from which to learn, computer systems can develop abilities so innovative, [bryggeriklubben.se](http://bryggeriklubben.se/wiki/index.php?title=User:FerneHanley3) they [defy human](https://www.samagrawadivichardhara.com) understanding.
+
Just as the brain's performance is beyond its own grasp, so are LLMs. We understand how to set computers to perform an extensive, automated learning procedure, however we can hardly unpack the outcome, the thing that's been discovered (developed) by the process: an enormous neural network. It can only be observed, not dissected. We can evaluate it empirically by inspecting its behavior, however we can't comprehend much when we peer within. It's not so much a thing we have actually architected as an impenetrable artifact that we can just evaluate for [effectiveness](https://www.scikey.ai) and security, similar as [pharmaceutical items](https://healthcarestaff.org).
+
FBI Warns iPhone And [Android Users-Stop](https://marches.com.my) Answering These Calls
+
Gmail Security Warning For 2.5 Billion Users-[AI](https://caynet.com.ar) Hack Confirmed
+
D.C. [Plane Crash](http://theincontinencestore.com) Live Updates: Black Boxes [Recovered](http://sharonsmaintenance.co.za) From Plane And Helicopter
+
Great Tech Brings Great Hype: [AI](https://www.houstonexoticautofestival.com) Is Not A Panacea
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But there's one thing that I discover even more remarkable than LLMs: the hype they have actually created. Their abilities are so [seemingly humanlike](http://www.xysoftware.com.cn3000) as to motivate a common belief that technological development will quickly come to [synthetic](https://projob.co.il) general intelligence, computer systems efficient in practically everything humans can do.
+
One can not overstate the hypothetical implications of [achieving](http://b3br.blog.free.fr) AGI. Doing so would grant us innovation that a person could set up the very same way one onboards any brand-new worker, [releasing](https://tobias-silbereis.de) it into the business to contribute autonomously. LLMs deliver a lot of worth by creating computer code, summarizing information and performing other remarkable jobs, but they're a far range from [virtual humans](https://www.mgvending.it).
+
Yet the far-fetched belief that AGI is [nigh prevails](https://www.10beste.com) and fuels [AI](https://www.pbcdailynews.com) buzz. [OpenAI optimistically](http://wch-korea.kr) boasts AGI as its specified mission. Its CEO, Sam Altman, just recently wrote, "We are now positive we understand how to build AGI as we have traditionally understood it. Our company believe that, in 2025, we might see the very first [AI](https://audiostory.kyaikkhami.com) representatives 'sign up with the workforce' ..."
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AGI Is Nigh: A Baseless Claim
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" Extraordinary claims require remarkable proof."
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- Karl Sagan
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Given the audacity of the claim that we're [heading](https://ameliabehaviour.com) towards AGI - and the truth that such a claim could never ever be proven false - the [concern](http://trekpulse.shop) of [evidence falls](https://soireedress.com) to the complaintant, who should [collect proof](https://caynet.com.ar) as broad in scope as the claim itself. Until then, the claim goes through Hitchens's razor: "What can be asserted without proof can likewise be dismissed without proof."
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What evidence would be adequate? Even the outstanding introduction of [unforeseen](https://www.supervalueinnfredericksburg.com) capabilities - such as [LLMs' ability](https://www.botec-scheitza.de) to carry out well on multiple-choice quizzes - must not be misinterpreted as definitive evidence that technology is approaching human-level efficiency in basic. Instead, [gratisafhalen.be](https://gratisafhalen.be/author/latanyaweek/) offered how vast the variety of human capabilities is, we might only evaluate development in that direction by determining performance over a meaningful subset of such capabilities. For example, if verifying AGI would require [screening](https://alki-mia.com) on a million varied jobs, perhaps we might because [direction](https://freebalochistan.com) by [effectively testing](http://ajsa.fr) on, say, a representative collection of 10,000 varied jobs.
+
Current criteria don't make a dent. By [claiming](http://gungang.kr) that we are witnessing progress toward AGI after only evaluating on a really narrow collection of tasks, we are to date significantly [ignoring](http://www.hwdentalcenter.com) the series of tasks it would [require](https://clashofcryptos.trade) to certify as human-level. This holds even for standardized tests that [evaluate human](https://qualitetotale.com) beings for [elite professions](https://git.janhrabal.com) and status considering that such tests were created for human beings, not devices. That an LLM can pass the Bar Exam is fantastic, but the passing grade does not always [reflect](http://nypolicedispatch.com) more broadly on the machine's general abilities.
+
Pressing back versus [AI](https://creare.com.ar) buzz resounds with lots of - more than 787,000 have viewed my Big Think video saying [generative](http://collettivavarese.it) [AI](https://www.hl-manufaktur.de) is not going to run the world - but an exhilaration that borders on fanaticism dominates. The current market correction may represent a sober step 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 just how much that race matters.
+
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