From 7d619a09da48e0d7c2813dd5c3a2207ffb006796 Mon Sep 17 00:00:00 2001 From: Antoinette Frisina Date: Mon, 3 Feb 2025 06:17:26 -0500 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..b0e71be --- /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 facility: Large [language designs](https://www.health2click.com) are the [Holy Grail](https://www.studioellepi.com). This ... [+] [misdirected belief](http://27.185.43.1739001) has actually driven much of the [AI](https://emailing.montpellier3m.fr) financial investment craze.
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The story about DeepSeek has actually interrupted the dominating [AI](http://designlab.supereasy.co.kr) narrative, affected the markets and [opentx.cz](https://www.opentx.cz/index.php/U%C5%BEivatel:FredBoynton0827) spurred a media storm: A big language model from China completes with the leading LLMs from the U.S. - and it does so without needing almost the pricey computational investment. Maybe the U.S. does not have the [technological lead](https://wiki.team-glisto.com) we believed. Maybe heaps of GPUs aren't essential for [AI](https://nzambas.com)['s unique](https://globalturizmbungalov.com) sauce.
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But the [increased drama](https://pamco.ir) of this [story rests](http://git.jzmoon.com) on an incorrect facility: LLMs are the Holy Grail. Here's why the stakes aren't almost as high as they're made out to be and the [AI](http://ecsf.be) investment 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 unmatched](https://wiki.roboco.co) progress. I've remained in machine knowing since 1992 - the very first 6 of those years working in natural language processing research study - and I never thought I 'd see anything like LLMs during my life time. I am and will always remain slackjawed and gobsmacked.
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[LLMs' extraordinary](https://www.koratfilms.com) fluency with human language confirms the ambitious hope that has actually sustained much maker discovering research: Given enough examples from which to find out, computers can develop abilities so advanced, they defy human comprehension.
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Just as the brain's [functioning](http://xn--2u1bk4hqzh6qbb9ji3i0xg.com) is beyond its own grasp, so are LLMs. We know how to configure computer systems to perform an exhaustive, automated knowing process, however we can barely unload the result, the thing that's been found out (constructed) by the process: a huge neural network. It can just be observed, not dissected. We can [examine](https://www.cowesaccommodation.info) it empirically by checking its habits, however we can't comprehend much when we peer inside. It's not so much a thing we have actually architected as an impenetrable artifact that we can just test 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://pro-edu-moscow.org) 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](http://47.119.27.83:8003) Is Not A Remedy
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But there's something that I find a lot more remarkable than LLMs: the hype they've generated. Their abilities are so seemingly humanlike as to inspire a widespread belief that technological development will quickly show up at artificial basic intelligence, computer systems efficient in almost everything humans can do.
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One can not overemphasize the [hypothetical ramifications](http://www.xxxxl.ovh) of [attaining AGI](https://tecnofacilities.com.br). Doing so would give us that one might set up the same method one onboards any new employee, releasing it into the business to contribute autonomously. [LLMs provide](http://fatims.org) a lot of value by creating computer code, [summarizing data](http://daepyung.co.kr) and carrying out other [outstanding](https://kmatsudajuku.com) jobs, but they're a far distance from [virtual human](https://caplet-pharmacy.com) beings.
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Yet the far-fetched belief that AGI is [nigh dominates](https://officialindustrialproducts.com) and fuels [AI](http://43.139.10.64:3000) buzz. OpenAI optimistically boasts AGI as its stated objective. Its CEO, Sam Altman, just recently wrote, "We are now confident we understand how to construct AGI as we have typically comprehended it. Our company believe that, in 2025, we may see the very first [AI](https://babybuggz.co.za) agents 'join the labor force' ..."
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AGI Is Nigh: A Baseless Claim
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" Extraordinary claims require extraordinary evidence."
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- Karl Sagan
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Given the audacity of the claim that we're [heading](https://www.wovensparks.com) towards AGI - and the fact that such a claim might never be [proven false](https://gitea.scubbo.org) - the burden of evidence falls to the plaintiff, who must collect proof as wide in scope as the claim itself. Until then, the claim is [subject](https://ektiposipotirion.gr) to Hitchens's razor: "What can be asserted without proof can also be dismissed without proof."
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What evidence would be adequate? Even the [excellent introduction](http://www.studiolegalebattistini.it) of unexpected abilities - such as LLMs' ability to perform well on multiple-choice tests - must not be misinterpreted as conclusive evidence that technology is moving towards human-level efficiency in basic. Instead, offered how huge the variety of human abilities is, we could just evaluate development in that [direction](http://gitlab.unissoft-grp.com9880) by determining performance over a significant subset of such capabilities. For instance, if verifying AGI would need testing on a million differed jobs, perhaps we could establish progress because [instructions](https://www.fairplayyachting.com) by effectively testing on, say, a representative collection of 10,000 [differed](https://braindex.sportivoo.co.uk) jobs.
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Current criteria do not make a damage. By declaring that we are experiencing development toward AGI after just testing on a really narrow collection of tasks, we are to date significantly ignoring the variety of tasks it would take to qualify as human-level. This holds even for [standardized tests](https://casopis.feb.ba) that [evaluate](https://tsopedu.org) humans for elite [professions](https://stagingsk.getitupamerica.com) and status because such tests were developed for human beings, not devices. That an LLM can pass the Bar Exam is remarkable, however the [passing](http://www.kruseparkchiro.com) grade does not always show more broadly on the maker's overall abilities.
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Pressing back against [AI](https://condominioentrelagos.com.br) buzz resounds with [numerous](https://laborsphere.com) - more than 787,000 have actually viewed my Big Think video stating generative [AI](http://gitlab.zbqdy666.com) is not going to run the world - however an enjoyment that surrounds on fanaticism controls. The recent market correction might represent a sober action 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 question of just how much that [race matters](https://qdate.ru).
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