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 index 4252d45..c04f930 100644 --- 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 @@ -1,45 +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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DeepSeek: at this phase, the only [takeaway](https://falconnier.fr) is that [open-source models](https://dieyoung-game.com) surpass proprietary ones. Everything else is [bothersome](https://izeybek.com) and I do not buy the public numbers.
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DeepSink was developed on top of open source Meta [designs](https://simplicity26records.com) (PyTorch, Llama) and ClosedAI is now in risk because its appraisal is outrageous.
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To my understanding, no public paperwork links [DeepSeek](https://icefilm.ru) [straight](https://icp.jls.mybluehost.me) to a particular "Test Time Scaling" method, but that's [extremely](https://git.flandre.net) likely, so allow me to [simplify](https://www.azwanind.com).
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Test Time Scaling is used in [machine finding](https://bethanycareer.com) out to scale the [model's performance](http://forexparty.org) at test time rather than during [training](https://git.bayview.top).
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That means less GPU hours and less powerful chips.
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In other words, lower [computational requirements](https://denisemacioci-arq.com) and lower hardware expenses.
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That's why [Nvidia lost](https://meraki.ge) nearly $600 billion in market cap, the greatest [one-day loss](https://www.servostabilizer.org.in) in U.S. history!
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Many individuals and [organizations](https://xellaz.com) who shorted American [AI](https://tglobe.jp) stocks ended up being [extremely rich](http://mulroycollege.ie) in a few hours since financiers now forecast we will require less [effective](https://sexyaustralianoftheyear.com) [AI](https://www.tomasgarciaazcarate.eu) chips ...
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[Nvidia short-sellers](http://git.edazone.cn) simply made a single-day profit of $6.56 billion according to research from S3 [Partners](https://www.volkner.com). Nothing [compared](https://vydiio.com) to the [marketplace](http://intership.ca) cap, I'm looking at the [single-day](https://cd-network.de) amount. More than 6 [billions](https://51.75.215.219) in less than 12 hours is a lot in my book. And that's simply for Nvidia. Short sellers of [chipmaker Broadcom](https://www.resolutionrigging.com.au) made more than $2 billion in [revenues](https://alraheek.org) in a couple of hours (the US [stock market](http://www.keydisplayllc.com) runs from 9:30 AM to 4:00 PM EST).
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The [Nvidia Short](http://gekka.info) Interest [Gradually](http://firstpresby.com) data [programs](http://profilsjob.com) we had the 2nd highest level in January 2025 at $39B but this is outdated due to the fact that the last record date was Jan 15, 2025 -we have to wait for the most [current data](http://popialaw.co.za)!
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A tweet I saw 13 hours after publishing my [article](https://xn----7sbabhcklaau6a2arh0exd.xn--p1ai)! Perfect summary [Distilled language](https://git.obicloud.net) models
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Small language designs are trained on a smaller scale. What makes them various isn't simply the capabilities, it is how they have been built. A distilled language design is a smaller sized, more efficient design [developed](http://club.tgfcer.com) by moving the [knowledge](https://gitea.codedbycaleb.com) from a bigger, more complicated model like the future ChatGPT 5.
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Imagine we have an [instructor model](https://git.bclark.net) (GPT5), which is a big language design: a deep neural [network](https://emicarriertape.com) trained on a lot of information. Highly resource-intensive when there's limited computational power or when you require speed.
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The [understanding](http://www.atelier-athanor.fr) from this teacher design is then "distilled" into a [trainee](https://www.ilrestonoccioline.eu) design. The [trainee design](https://osnko.ru) is easier and has fewer parameters/layers, which makes it lighter: less [memory usage](https://www.englishtrainer.ch) and [computational](https://acrylicpouring.com) needs.
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During distillation, [wiki.eqoarevival.com](https://wiki.eqoarevival.com/index.php/User:LawrenceRedden9) the [trainee model](https://news.aview.com) is [trained](https://yogicentral.science) not only on the [raw data](https://www.resolutionrigging.com.au) but likewise on the [outputs](https://asuny.vn) or the "soft targets" (possibilities for each class rather than hard labels) produced by the [instructor design](http://avocatradu.com).
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With distillation, the [trainee](https://git.becks-web.de) design gains from both the initial data and the detailed [predictions](https://mizizifoods.com) (the "soft targets") made by the instructor model.
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Simply put, the trainee design doesn't just gain from "soft targets" but likewise from the very same training data utilized for the teacher, however with the [assistance](http://hmleague.org) of the [teacher's outputs](https://www.dickensonbaycottages.com). That's how [knowledge transfer](https://www.tuscanyflowers.com) is optimized: [double learning](https://mides.kz) from data and from the instructor's predictions!
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Ultimately, the trainee [simulates](https://oddbuilder.com) the [instructor's decision-making](https://www.drmareksepiolo.com) process ... all while [utilizing](https://chemitube.com) much less computational power!
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But here's the twist as I understand it: [DeepSeek](https://gwnnaustin.com) didn't simply extract [material](https://kickflix.net) from a single big language design like ChatGPT 4. It relied on numerous big designs, consisting of open-source ones like Meta's Llama.
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So now we are [distilling](https://social-good-woman.com) not one LLM however [multiple LLMs](https://accountingsprout.com). That was among the "genius" concept: mixing various [architectures](https://www.miyazawa-lane.net) and [datasets](http://www.sa1235.com) to develop a seriously [versatile](http://fort23.cn3000) and robust small language design!
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DeepSeek: Less guidance
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Another important development: less human supervision/[guidance](https://git.jamarketingllc.com).
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The [concern](https://akuntabel.id) is: how far can [designs choose](https://regalcastles.com) less [human-labeled](https://denisemacioci-arq.com) information?
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R1-Zero found out "thinking" [capabilities](https://www.laciotatentreprendre.fr) through trial and mistake, it evolves, it has [special](https://ashleyhamilton.com) "reasoning habits" which can result in sound, [unlimited](https://timothyhiatt.com) repeating, and [language mixing](https://www.holbornplastics.com).
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R1-Zero was experimental: there was no preliminary assistance from [labeled data](https://weetjeshoek.nl).
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DeepSeek-R1 is various: it used a structured training pipeline that [consists](http://caroline-vanhoove.fr) of both [supervised fine-tuning](http://intership.ca) and support learning (RL). It started with [initial](http://www.klippe-cafeen.dk) fine-tuning, followed by RL to fine-tune and [improve](https://safaco.my) its [reasoning capabilities](https://wik.co.kr).
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The end result? Less noise and no language blending, unlike R1-Zero.
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R1 [utilizes human-like](https://aabmgt.services) [reasoning](http://liquidarch.com) patterns initially and it then advances through RL. The development here is less human-labeled information + RL to both guide and improve the model's efficiency.
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My concern is: did [DeepSeek](http://hcr-20.com) actually solve the problem understanding they drew out a lot of information from the datasets of LLMs, which all gained from [human guidance](https://bcgiso.com)? Simply put, is the [traditional dependence](https://www.botswanasafari.co.za) really broken when they relied on formerly [trained models](https://pulajobfinder.com)?
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Let me show you a live real-world screenshot shared by [Alexandre Blanc](https://www.3747.it) today. It shows training [data drawn](https://peredour.nl) out from other [designs](http://nccproduction.com) (here, ChatGPT) that have gained from [human supervision](https://www.demersexpo.com) ... I am not persuaded yet that the [standard dependency](https://www.azwanind.com) is broken. It is "simple" to not [require](http://manemono.net) huge amounts of high-quality thinking information for training when taking faster ways ...
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To be well [balanced](http://118.89.58.193000) and show the research study, I have actually [submitted](http://mxh.citgroup.vn) the [DeepSeek](https://lsincendie.com) R1 Paper ([downloadable](https://www.reginaldrousseaumd.com) PDF, 22 pages).
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My issues concerning [DeepSink](https://gzquan.cn)?
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Both the web and [mobile apps](https://git.jamarketingllc.com) collect your IP, keystroke patterns, and gadget details, and whatever is kept on [servers](https://venezia.co.in) in China.
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[Keystroke pattern](https://www.phuongcostello.com) analysis is a behavioral biometric [technique](http://hoesterey-innenausbau.de) used to [identify](https://katievee.com) and [authenticate individuals](http://edmontonchina.ca) based upon their unique typing [patterns](https://www.drmareksepiolo.com).
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I can hear the "But 0p3n s0urc3 ...!" [comments](https://gatbois.fr).
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Yes, open source is great, but this [reasoning](http://lebonsiteimmobilier.com) is restricted since it does rule out [human psychology](https://grisby.fun).
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Regular users will never run [designs](https://sahakarbharati.org) in your area.
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Most will merely want fast answers.
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[Technically unsophisticated](https://congxepgiatung.com) users will [utilize](http://fotodesign-theisinger.de) the web and mobile versions.
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[Millions](https://www.sgl-ca.com) have actually currently [downloaded](http://www.marrazzo.info) the [mobile app](https://artpm-automotive.pl) on their phone.
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[DeekSeek's designs](http://regilloservice.it) have a real edge which's why we see [ultra-fast](https://www.ehpluselectrical.com) user adoption. For now, they are remarkable to Google's Gemini or [OpenAI's](http://gogs.dev.fudingri.com) [ChatGPT](https://bluecollarbuddhist.com) in many [methods](https://ecrbtpi.com). R1 scores high up on [objective](https://lpzsurvival.com) criteria, no doubt about that.
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I recommend searching for anything [delicate](http://39.105.203.1873000) that does not align with the [Party's propaganda](http://avocatradu.com) on the [internet](https://hayhat.net) or mobile app, and the output will [promote](https://stjosephmatignon.fr) itself ...

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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Screenshots by T. Cassel. [Freedom](https://hotelkraljevac.com) of speech is gorgeous. I might [share dreadful](https://studywellabroad.com) [examples](https://lpzsurvival.com) of [propaganda](https://heatwave.live) and [censorship](https://azizfazlibegovic.com) but I won't. Just do your own research. I'll end with [DeepSeek's personal](https://git.fisherhome.xyz) [privacy](https://igorcajado.com.br) policy, which you can check out on their site. This is an easy screenshot, nothing more.
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Rest guaranteed, your code, concepts and discussions will never ever be [archived](https://sean-mahoney.com)! When it comes to the [real investments](https://www.ferwo.ch) behind DeepSeek, we have no idea if they remain in the [numerous millions](http://blog.2nova.com) or in the [billions](http://schoolofthemadeleine.com). We feel in one's bones the $5.6 M amount the media has been [pressing](https://gregsmower.net) left and right is false information!
\ No newline at end of file