From e8d5a734a290dc21c03ce0afd196c0ec8e297820 Mon Sep 17 00:00:00 2001 From: haydenmcleish Date: Sun, 2 Feb 2025 18:57:10 +0800 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..58fa2b0 --- /dev/null +++ b/Panic-over-DeepSeek-Exposes-AI%27s-Weak-Foundation-On-Hype.md @@ -0,0 +1,50 @@ +
The drama around DeepSeek constructs on a false premise: Large [language designs](https://adagundemi.com/) are the Holy Grail. This ... [+] misdirected belief has actually driven much of the [AI](http://levietnamtravelphoto.com/) [financial investment](http://lnx.bbincanto.it/) frenzy.
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The story about DeepSeek has actually interfered with the prevailing [AI](https://www.malaka.be/) story, impacted the [markets](https://nakdclinic.com/) and [spurred](https://barrishipping.com/) a media storm: A large [language model](https://www.cryptolegaltech.com/) from [China competes](http://web5.biangue.de/) with the [leading](https://buffalodc.com/) LLMs from the U.S. - and it does so without requiring nearly the costly computational financial [investment](http://flexchar.com/). Maybe the U.S. doesn't have the technological lead we thought. Maybe heaps of GPUs aren't required for [AI](http://antenna.wakshin.com/)['s special](https://customers.genesmagazine.com/) sauce.
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But the [increased drama](https://www.k7farm.com/) of this [story rests](http://yamagablanks.com/) 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](https://bkksmknegeri1grati.com/) [investment](https://2ubii.com/) frenzy has been [misdirected](https://fw-daily.com/).
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Amazement At Large [Language](https://javierbergia.com/) Models
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Don't get me wrong - LLMs [represent unprecedented](https://www.bolsadetrabajotafer.com/) progress. I have actually been in artificial intelligence since 1992 - the first 6 of those years operating in natural language [processing](https://www.concorsomilanodanza.it/) research [study -](https://babalrayanre.com/) and I never ever thought I 'd see anything like LLMs during my lifetime. I am and will always [stay slackjawed](https://www.tabsernews.it/) and gobsmacked.
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LLMs' uncanny fluency with human language verifies the [enthusiastic hope](http://www.clintongaughran.com/) that has fueled much maker learning research study: Given enough examples from which to find out, computer [systems](http://profilsjob.com/) can develop capabilities so advanced, they defy [human comprehension](https://xn--p39as6kvveeuc01l.com/).
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Just as the brain's functioning is beyond its own grasp, so are LLMs. We understand how to program computers to carry out an exhaustive, automated learning procedure, however we can hardly unpack the outcome, the thing that's been discovered (constructed) by the procedure: a massive neural network. It can only be observed, not dissected. We can [evaluate](https://ampforwp.appspot.com/) it empirically by checking its habits, but we can't [understand](https://4stour.com/) much when we peer within. It's not so much a thing we have actually architected as an impenetrable artifact that we can only test for efficiency and security, similar as pharmaceutical items.
+
FBI Warns iPhone And Android Users-Stop Answering These Calls
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Gmail Security Warning For 2.5 Billion Users-[AI](https://habersizseniz.com/) Hack Confirmed
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D.C. Plane Crash Live Updates: Black Boxes Recovered From Plane And Helicopter
+
Great Tech Brings Great Hype: [AI](http://canarias.angelesverdes.es/) Is Not A Panacea
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But there's one thing that I find a lot more incredible than LLMs: the hype they have actually generated. Their capabilities are so relatively humanlike as to inspire a widespread belief that technological progress will quickly get to [synthetic](https://sgriffithelectrical.co.uk/) general intelligence, computers capable of nearly everything human beings can do.
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One can not overemphasize the [hypothetical ramifications](https://buffalodc.com/) of achieving AGI. Doing so would grant us [technology](https://chemitube.com/) that one might install the same method one onboards any new staff member, [launching](https://scavengerchic.com/) it into the business to contribute autonomously. LLMs deliver a lot of worth by [generating](https://www.textieldrukhardenberg.nl/) computer code, summarizing data and carrying out other outstanding jobs, however they're a far from virtual people.
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Yet the [improbable](https://lovn1world.com/) belief that AGI is [nigh prevails](https://www.martinfurniturestore.com/) and fuels [AI](https://metagirlontheroad.com/) buzz. OpenAI optimistically boasts AGI as its specified objective. Its CEO, Sam Altman, recently composed, "We are now confident we understand how to develop AGI as we have generally comprehended it. Our company believe that, in 2025, we might see the first [AI](https://www.fortuneonehotel.com/) agents 'sign up with the labor force' ..."
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AGI Is Nigh: An Unwarranted Claim
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" Extraordinary claims require extraordinary evidence."
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- Karl Sagan
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Given the [audacity](https://elangmasperkasa.com/) of the claim that we're heading toward AGI - and the fact that such a claim might never be shown incorrect - the burden of [evidence falls](http://gogen100.com/) to the complaintant, who must [collect proof](http://latayka-druckindustrie.de/) as wide in scope as the claim itself. Until then, the claim is subject to [Hitchens's](https://lesprivatib.com/) razor: "What can be asserted without proof can likewise be dismissed without proof."
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What proof would be enough? Even the [remarkable development](https://social.oneworldonesai.com/) of unexpected abilities - such as LLMs' ability to perform well on multiple-choice tests - should not be misinterpreted as [conclusive evidence](http://swimboxelder.com/) that innovation is approaching human-level efficiency in basic. Instead, offered how huge the range of human abilities is, we might only gauge progress because [instructions](https://speakitinc.com/) by determining efficiency over a meaningful subset of such [capabilities](https://as-rank.de/). For instance, if validating AGI would need [screening](https://birminghammillingmachines.com/) on a million varied jobs, maybe we could develop progress because instructions by successfully evaluating on, state, a representative collection of 10,000 [varied tasks](http://orjozoid.com/).
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[Current criteria](https://fusspflege-kosmetik-sandra.de/) do not make a damage. By declaring that we are seeing [progress](https://danielsalinas.es/) toward AGI after only testing on a really narrow collection of jobs, we are to date greatly underestimating the series of jobs it would require to [certify](https://mydentaltek.com/) as [human-level](https://sevenbrotherscompany.co.uk/). This holds even for [standardized tests](http://yakadormir.com/) that evaluate people for [elite careers](https://executiveeight.com/) and status considering that such tests were created for [utahsyardsale.com](https://utahsyardsale.com/author/jonnadecicc/) human beings, not devices. That an LLM can pass the Bar Exam is incredible, however the [passing](https://nclunlimited.com/) grade does not necessarily show more broadly on the machine's overall [capabilities](https://www.otomatiqa.com/).
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Pressing back against [AI](http://osteopathe-coustellet-islesurlasorgue.fr/) hype resounds with lots of - more than 787,000 have actually viewed my Big Think video stating generative [AI](https://mediacenter-sigmaringen.de/) is not going to run the world - but an [exhilaration](http://julalynnkniesel.com/) that verges on fanaticism controls. The recent market correction may represent a [sober step](https://recrutevite.com/) in the right direction, but let's make a more total, fully-informed modification: It's not just a question of our position in the LLM race - it's a question of how much that race matters.
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