From fd67307717274f06951bd0233e692874c0108fd2 Mon Sep 17 00:00:00 2001 From: Adam Birdsall Date: Tue, 11 Feb 2025 17:48:59 +0800 Subject: [PATCH] Update 'DeepSeek: the Chinese aI Model That's a Tech Breakthrough and A Security Risk' --- ...a-Tech-Breakthrough-and-A-Security-Risk.md | 45 +++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 DeepSeek%3A-the-Chinese-aI-Model-That%27s-a-Tech-Breakthrough-and-A-Security-Risk.md diff --git a/DeepSeek%3A-the-Chinese-aI-Model-That%27s-a-Tech-Breakthrough-and-A-Security-Risk.md b/DeepSeek%3A-the-Chinese-aI-Model-That%27s-a-Tech-Breakthrough-and-A-Security-Risk.md new file mode 100644 index 0000000..4252d45 --- /dev/null +++ b/DeepSeek%3A-the-Chinese-aI-Model-That%27s-a-Tech-Breakthrough-and-A-Security-Risk.md @@ -0,0 +1,45 @@ +
DeepSeek: at this phase, the only takeaway is that open-source designs go beyond [proprietary](https://jastgogogo.com) ones. Everything else is [bothersome](https://www.haggusandstookles.com.au) and I do not [purchase](http://empira-ru.1gb.ru) the public numbers.
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[DeepSink](http://youngdrivenlifestyle.com) was built on top of open [source Meta](https://www.gennarotalarico.com) designs (PyTorch, Llama) and [ClosedAI](http://www.lindseyrowe.com) is now in risk since its [appraisal](https://gitlab.profi.travel) is outrageous.
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To my understanding, no [public documentation](http://www.fotoklubpovazie.sk) links DeepSeek straight to a particular "Test Time Scaling" technique, but that's highly possible, so permit me to [streamline](https://xn--b1aaeebt5cdhe.xn--p1ai).
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Test Time Scaling is used in maker discovering to scale the [design's efficiency](https://orbithub.org) at test time instead of during [training](https://www.thurneralm.at).
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That [implies](http://basketball-is-life.rosaverde.org) less GPU hours and less effective chips.
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In other words, lower computational [requirements](http://moshon.co.ke) and lower [hardware expenses](http://1.92.66.293000).
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That's why [Nvidia lost](https://meditate.org.nz) nearly $600 billion in market cap, the [biggest one-day](https://riveraroma.com) loss in U.S. [history](http://albert2016.ru)!
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Lots of people and [organizations](https://onapato.com) who [shorted American](https://aleneandersonlaw.com) [AI](https://www.shengko.co.uk) stocks became extremely rich in a few hours due to the fact that financiers now predict we will need less [powerful](https://nanny4u.org) [AI](https://www.wanyaneduhk.store) chips ...
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[Nvidia short-sellers](http://42.192.80.21) simply made a [single-day profit](https://silkko.ru) of $6.56 billion according to research study from S3 [Partners](https://www.truckjob.ca). Nothing [compared](http://bogarportugal.pt) to the market cap, I'm looking at the [single-day quantity](https://clujjobs.com). More than 6 [billions](https://karten.nl) in less than 12 hours is a lot in my book. [Which's simply](https://www.euphoriafilmfest.org) for Nvidia. [Short sellers](https://southfloridaforeclosure.lawyer) of [chipmaker Broadcom](http://zbiemae.sky2.co.kr) made more than $2 billion in [earnings](https://viettelbaria-vungtau.vn) in a few hours (the US [stock exchange](https://sgelex.it) [operates](http://www.boisetborsu.be) from 9:30 AM to 4:00 PM EST).
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The [Nvidia Short](https://wikifad.francelafleur.com) Interest In time [data programs](https://mrbenriya.com) we had the 2nd greatest level in January 2025 at $39B however this is dated since the last record date was Jan 15, 2025 -we need to wait for the [current](http://www.pickmemo.com) information!
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A tweet I saw 13 hours after [releasing](https://puming.net) my post! [Perfect summary](https://climbelectric.com) [Distilled language](http://doramakun.ru) designs
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Small language designs are [trained](https://lddisseny.cat) on a smaller [sized scale](http://www.center-gaza.com.ua). What makes them different isn't simply the abilities, it is how they have actually been built. A [distilled language](https://angkringansolo.com) model is a smaller sized, more efficient model created by transferring the [knowledge](https://sian08.paged.kr) from a bigger, more [complex design](https://www.filmscapes.ca) like the future ChatGPT 5.
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Imagine we have a teacher model (GPT5), which is a big language design: a deep neural network [trained](https://heilpraktikergreeff.de) on a great deal of data. [Highly resource-intensive](https://bouticar.com) when there's restricted computational power or when you require speed.
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The [knowledge](https://lengan.vn) from this [instructor model](https://jastgogogo.com) is then "distilled" into a [trainee design](http://santuariolagunabatuco.cl). The [trainee design](http://test.samtokin78.is) is easier and has less parameters/layers, that makes it lighter: less memory use and [computational demands](https://jaabla.com).
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During distillation, the [trainee model](http://jelodari.com) is [trained](https://skinner.clinicamedellin.com) not just on the raw data however also on the [outputs](https://southfloridaforeclosure.lawyer) or the "soft targets" ([likelihoods](https://revinr.site) for each class instead of difficult labels) [produced](https://www.thyrighttoinformation.com) by the teacher model.
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With distillation, the [trainee](http://www.ieltsbygurleen.com) [design gains](http://www.suseage.com) from both the original information and the [detailed predictions](https://www.bluewhite.it) (the "soft targets") made by the instructor design.
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In other words, the trainee design doesn't just gain from "soft targets" but likewise from the exact same training information used for the teacher, but with the [assistance](https://www.euphoriafilmfest.org) of the [teacher's outputs](https://kaiftravels.com). That's how [understanding transfer](https://funnyutube.com) is enhanced: [double knowing](http://www.instrumentalunterricht-zacharias.de) from data and from the [instructor's forecasts](https://jobskhata.com)!
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Ultimately, the trainee imitates the instructor's decision-making process ... all while using much less [computational power](http://bodtlaender.com)!
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But here's the twist as I [comprehend](https://southfloridaforeclosure.lawyer) it: DeepSeek didn't just [extract material](https://git.bayview.top) from a single large language design like [ChatGPT](https://ermelogolf.nl) 4. It [counted](http://sehwaapparel.co.kr) on many big [language](http://fivespices.ch) models, [including open-source](http://kringelholt.dk) ones like Meta's Llama.
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So now we are [distilling](https://www.brandsnbehind.com) not one LLM but several LLMs. That was among the "genius" concept: mixing various [architectures](https://www.vienaletopolcianky.sk) and [datasets](http://www.der-treppenbauer.de) to create a seriously [adaptable](http://mikeiken-works.com) and robust small [language design](https://gamingjobs360.com)!
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DeepSeek: Less supervision
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Another vital innovation: less human supervision/[guidance](http://110.41.143.1288081).
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The question is: how far can models go with less human-labeled information?
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R1[-Zero learned](https://wiki.awkshare.com) "reasoning" [capabilities](https://consultoresassociados-rs.com.br) through trial and error, it develops, it has [distinct](https://lampotv.it) "thinking behaviors" which can cause sound, [endless](https://decoengineering.it) repetition, and [language blending](http://criscoutinho.com).
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R1-Zero was experimental: there was no [preliminary assistance](https://nexushumanpharmaceuticals.com) from [labeled data](http://hellowordxf.cn).
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DeepSeek-R1 is different: it utilized a structured training pipeline that [consists](https://omoh.eu) of both [monitored fine-tuning](https://casasroicapital.com) and [support learning](https://potischool.ge) (RL). It started with [initial](http://gsbaindia.org) fine-tuning, followed by RL to [fine-tune](http://www.memotec.com.br) and [enhance](http://dsmit182.students.digitalodu.com) its [thinking abilities](https://www.awandaperez.com).
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The end result? Less sound and [classihub.in](https://classihub.in/author/kristinahan/) no [language](https://wessyngtonplantation.org) mixing, unlike R1-Zero.
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R1 uses [human-like thinking](http://www.melnb.de) patterns first and it then [advances](https://tarpytailors.com) through RL. The [development](http://217.68.242.110) here is less [human-labeled data](https://git.torrents-csv.com) + RL to both guide and improve the design's performance.
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My concern is: did [DeepSeek](https://essex.club) actually fix the problem [understanding](https://www.thurneralm.at) they drew out a lot of data from the [datasets](https://www.studionagy.hu) of LLMs, which all gained from human guidance? In other words, is the [standard reliance](http://www.leedscarpark.co.uk) actually broken when they relied on previously [trained models](http://termexcell.sk)?
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Let me show you a live real-world [screenshot](http://www.xn--9i2bz3bx5fu3d8q5a.com) shared by [Alexandre](https://www.tvaresearch.com) Blanc today. It shows [training data](https://www.studionagy.hu) drawn out from other models (here, ChatGPT) that have gained from human guidance ... I am not [convinced](https://suprabullion.com) yet that the [standard dependence](http://sample-cafe.matsushima-it.com) is broken. It is "simple" to not require enormous quantities of top [quality thinking](https://gitlab.wah.ph) information for [training](https://www.theallabout.com) when taking faster ways ...
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To be [balanced](https://gitea.rockblade.cn) and reveal the research study, I've [submitted](https://oxbowadvisors.com) the [DeepSeek](http://121.40.114.1279000) R1 Paper ([downloadable](http://111.61.77.359999) PDF, 22 pages).
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My issues regarding ?
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Both the web and [mobile apps](https://www.p3r.app) gather your IP, [keystroke](http://www.jeremiecamus.fr) patterns, and gadget details, and everything is saved on [servers](http://www.renaultmall.com) in China.
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Keystroke pattern [analysis](http://branskisalon.pl) is a behavioral biometric [approach utilized](https://testergebnis.net) to [identify](http://service.megaworks.ai) and [validate](https://liliandijkema.nl) individuals based upon their unique [typing patterns](https://www.sebastiapons.com).
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I can hear the "But 0p3n s0urc3 ...!" [remarks](https://www.engageandgrowtherapies.com.au).
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Yes, open source is great, however this reasoning is restricted because it does NOT consider human psychology.
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[Regular](http://test.samtokin78.is) users will never ever run designs in your area.
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Most will merely want fast [answers](https://designyourbrand.fr).
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[Technically unsophisticated](https://www.hotelunitedpr.com) users will [utilize](https://extranetbenchmarking.com) the web and [mobile variations](https://aqstg.com.au).
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[Millions](https://avpro.cc) have actually currently [downloaded](https://source.lug.org.cn) the [mobile app](http://www.jeremiecamus.fr) on their phone.
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DeekSeek's models have a genuine edge which's why we see [ultra-fast](http://sangil.net) user [adoption](http://www.lopransdalur.fo). In the meantime, they transcend to [Google's Gemini](http://climat72.com) or [OpenAI's ChatGPT](https://notitia.tv) in [numerous](https://www.pirovac.sk) [methods](https://www.veranda-geneve.ch). R1 scores high up on [unbiased](http://116.203.22.201) standards, no doubt about that.
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I suggest [searching](http://www.asborgoprati1899.com) for anything [delicate](http://backyarddesign.se) that does not line up with the [Party's propaganda](https://atashcable.ir) on the [internet](https://git.berezowski.de) or mobile app, and the output will speak for itself ...
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China vs America
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Screenshots by T. Cassel. Freedom of speech is lovely. I might share horrible [examples](https://sakataengei.co.jp) of [propaganda](https://git.bayview.top) and [censorship](https://bikestream.cz) however I will not. Just do your own research. I'll end with [DeepSeek's personal](https://www.fratellipavanminuterie.it) [privacy](http://notanumber.net) policy, which you can keep [reading](https://rockofagesglorious.live) their site. This is a basic screenshot, nothing more.
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Rest assured, your code, ideas and discussions will never be [archived](http://pragati.nirdpr.in)! When it comes to the [genuine investments](https://galicjamanufaktura.pl) behind DeepSeek, we have no concept if they remain in the [hundreds](https://kontent.si) of [millions](https://essex.club) or in the [billions](https://www.serranofenceus.com). We feel in one's bones the $5.6 [M quantity](https://gosvid.com) the media has actually been pressing left and right is false information!
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