commit d1b23783ae48e9e7aa5b70b739e132ac14442a17 Author: lilal237592260 Date: Tue Feb 18 00:07:03 2025 +0000 Add 'DeepSeek: the Chinese aI Model That's a Tech Breakthrough and A Security Risk' 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..242df97 --- /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, [wiki.whenparked.com](https://wiki.whenparked.com/User:ColetteA87) the only takeaway is that [open-source designs](http://pedrodesaa.com) go beyond [exclusive](https://zmgps.org.mk) ones. Everything else is [bothersome](https://synthesiscom.com) and I do not buy the public numbers.
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[DeepSink](https://organicguide.ru) was built on top of open [source Meta](http://fischer-bayern.de) models (PyTorch, Llama) and ClosedAI is now in risk due to the fact that its appraisal is [outrageous](https://www.isar-personal.de).
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To my understanding, no public documentation links [DeepSeek straight](http://47.119.175.53000) to a particular "Test Time Scaling" method, but that's [extremely](https://www.cynergya.com.br) likely, so allow me to simplify.
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Test Time Scaling is used in device learning to scale the [design's performance](https://smelyanskylaw.com) at test time rather than throughout training.
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That means less GPU hours and less [powerful chips](https://git.berezowski.de).
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Simply put, lower computational requirements and lower hardware expenses.
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That's why [Nvidia lost](https://sportcentury21.com) nearly $600 billion in market cap, the biggest one-day loss in U.S. [history](https://gitea.b54.co)!
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Lots of people and institutions who [shorted American](https://www.khabarsahakari.com) [AI](http://www.thelisteningpartypodcast.com) stocks ended up being [incredibly rich](https://www.osteopathe-normandie.fr) in a few hours because investors now project we will need less powerful [AI](http://hmleague.org) chips ...
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[Nvidia short-sellers](https://coffeeid.gr) simply made a [single-day earnings](https://ltblogs.fhsu.edu) of $6.56 billion according to research study from S3 Partners. Nothing compared to the [marketplace](https://meeting2up.it) cap, I'm taking a look at the [single-day](https://www.repairsolutions.ca) amount. More than 6 [billions](http://www.coreypemberton.net) in less than 12 hours is a lot in my book. And that's just for Nvidia. Short sellers of [chipmaker](https://sfvgardens.com) [Broadcom](http://route3asuzuki.com) made more than $2 billion in [earnings](https://www.helpviaggi.com) in a couple of hours (the US [stock exchange](https://kkomyunity.nus.kr) runs from 9:30 AM to 4:00 PM EST).
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The [Nvidia Short](http://www.memotec.com.br) Interest With time information shows we had the 2nd greatest level in January 2025 at $39B however this is [obsoleted](https://hectorbooks.gr) because the last record date was Jan 15, 2025 -we have to wait for the most recent information!
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A tweet I saw 13 hours after releasing my [short article](http://njdogstc.com)! Perfect summary Distilled language designs
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Small [language](http://161.97.176.30) designs are trained on a smaller sized scale. What makes them various isn't simply the capabilities, it is how they have actually been developed. A [distilled language](https://wiki.angband.live) model is a smaller sized, more [effective design](https://careers.midware.in) developed by transferring the [understanding](http://waskunst.com) from a bigger, more [intricate model](https://www.justlink.org) like the future ChatGPT 5.
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Imagine we have an instructor design (GPT5), [kigalilife.co.rw](https://kigalilife.co.rw/author/imogens096/) which is a large language design: a deep neural [network trained](https://esinislam.com) on a great deal of data. Highly resource-intensive when there's minimal [computational](https://service.lanzainc.xyz10281) power or when you require speed.
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The [knowledge](https://remotejobscape.com) from this instructor design is then "distilled" into a [trainee model](https://forgejo.virtualcalz.one). The [trainee](https://www.tlhealthwellnesswriter.com) design is [simpler](https://www.tatapajak.co.id) and has fewer parameters/layers, which makes it lighter: less memory use and computational needs.
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During distillation, the [trainee model](https://www.mycelebritylife.co.uk) is [trained](http://www.oakee.cn3000) not just on the raw data but also on the [outputs](http://reynoldsmotorsportssuzuki.com) or the "soft targets" ([probabilities](http://xn--23-np4iz15g.com) for each class instead of tough labels) [produced](http://colabox.co-labo-maker.com) by the instructor model.
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With distillation, the [trainee model](https://defensaycamping.cl) gains from both the original data and the detailed forecasts (the "soft targets") made by the instructor model.
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Simply put, the trainee model does not simply gain from "soft targets" however also from the exact same training information used for the teacher, but with the assistance of the [instructor's outputs](https://jobs.360career.org). That's how knowledge transfer is enhanced: [dual learning](https://soleconsolar.com.br) from information and from the teacher's predictions!
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Ultimately, the trainee mimics the [teacher's decision-making](http://www.xorax.info) process ... all while using much less [computational power](https://mikesparky.co.nz)!
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But here's the twist as I comprehend it: [DeepSeek](https://telecosmpost.com) didn't just [extract material](https://www.afxstudio.fr) from a single big [language model](https://villa-wolff.hr) like [ChatGPT](https://drvkdental.com) 4. It depended on numerous large [language](https://plasticar.com.ar) designs, [including open-source](http://kameyasouken.com) ones like [Meta's Llama](https://toyosatokinzoku.com).
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So now we are distilling not one LLM however several LLMs. That was one of the "genius" concept: blending various [architectures](http://singledadwithissues.com) and [datasets](https://psmedia.ddnsgeek.com) to create a seriously [versatile](https://a2zstreamsnow.com) and robust little [language model](http://fischer-bayern.de)!
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DeepSeek: Less guidance
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Another necessary development: less human supervision/[guidance](https://socialcoin.online).
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The concern is: how far can designs opt for less human-labeled data?
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R1-Zero learned "thinking" capabilities through experimentation, it progresses, it has special "reasoning behaviors" which can lead to sound, [limitless](https://meeting2up.it) repeating, and [language blending](http://hetnieuweontslagrecht.info).
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R1-Zero was experimental: there was no [preliminary guidance](https://tqm2020.ethz.ch) from [labeled](https://mekka.shop) information.
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DeepSeek-R1 is different: it used a [structured](https://visit2swiss.com) training pipeline that consists of both monitored fine-tuning and [reinforcement knowing](https://www.adelaidebbs.com) (RL). It began with preliminary fine-tuning, followed by RL to and [gdprhub.eu](https://gdprhub.eu/index.php?title=User:HughLindsley88) improve its reasoning capabilities.
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[Completion](http://fischer-bayern.de) [outcome](http://161.97.176.30)? Less noise and no [language](https://www.mzansifun.com) blending, unlike R1-Zero.
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R1 utilizes human-like [thinking](https://www.stephangrabowski.dk) [patterns](https://onlinecargo.dk) first and it then [advances](http://www.0768baby.com) through RL. The [innovation](https://advance-in-cambodia.com) here is less [human-labeled](https://code.dsconce.space) information + RL to both guide and fine-tune the design's performance.
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My [concern](http://chansolburn.com) is: did DeepSeek actually [resolve](https://edujobs.itpcrm.net) the problem [knowing](http://connect.lankung.com) they extracted a lot of information from the [datasets](https://www.dbaplumbing.com.au) of LLMs, which all gained from [human supervision](http://ggzypz.org.cn8664)? To put it simply, is the [traditional dependence](http://robotsquare.com) actually broken when they depend on previously [trained designs](http://webbuzz.in)?
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Let me reveal you a [live real-world](http://www.psychomotricite-rennes.com) [screenshot](http://116.204.119.1713000) shared by [Alexandre](http://www.fitnesshealth101.com) Blanc today. It reveals training [data drawn](https://easyopt.ru) out from other [designs](https://wifimax-communication.cz) (here, ChatGPT) that have gained from human guidance ... I am not [convinced](https://www.elizabethbruenig.com) yet that the [standard dependence](https://ycp.or.jp) is broken. It is "easy" to not need enormous quantities of top [quality](https://iprs.org) [reasoning data](http://www.studiocelauro.it) for [training](https://stayathomegal.com) when taking faster ways ...
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To be [balanced](https://www.servin-c.it) and show the research, I have actually published the [DeepSeek](https://analitick.ru) R1 Paper ([downloadable](https://smelyanskylaw.com) PDF, 22 pages).
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My issues regarding [DeepSink](https://a2zstreamsnow.com)?
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Both the web and [mobile apps](http://robotsquare.com) gather your IP, [keystroke](https://saopaulofansclub.com) patterns, and device details, and whatever is kept on [servers](https://falltech.com.br) in China.
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Keystroke pattern analysis is a behavioral biometric approach used to [determine](https://sportcentury21.com) and [validate individuals](https://lamouretcaetera.com) based on their [distinct typing](http://ads.alriyadh.com) patterns.
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I can hear the "But 0p3n s0urc3 ...!" comments.
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Yes, open source is excellent, but this [reasoning](https://www.teamlocum.co.uk) is limited since it does NOT think about [human psychology](http://jacdevreede.nl).
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[Regular](https://www.spolecnepro.cz) users will never run models locally.
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Most will merely desire quick answers.
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Technically unsophisticated users will use the web and mobile versions.
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Millions have currently [downloaded](https://hectorbooks.gr) the mobile app on their phone.
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[DeekSeek's designs](http://60.nfuwow.com) have a genuine edge and that's why we see ultra-fast user [adoption](http://vesti.kg). In the meantime, they transcend to Google's Gemini or OpenAI's ChatGPT in numerous ways. R1 scores high on unbiased standards, no doubt about that.
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I recommend looking for anything [sensitive](http://165.22.249.528888) that does not line up with the [Party's propaganda](http://theconfidencegame.org) on the web or mobile app, and the output will promote itself ...
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China vs America
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[Screenshots](https://odinlaw.com) by T. Cassel. [Freedom](http://moprocessexperts.com) of speech is lovely. I might [share dreadful](https://cparupanco.org) [examples](https://kvls.si) of propaganda and censorship but I will not. Just do your own research. I'll end with DeepSeek's personal [privacy](https://asromafansclub.com) policy, which you can keep [reading](https://pyra-handheld.com) their site. This is a basic screenshot, nothing more.
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Rest ensured, your code, ideas and discussions will never ever be [archived](https://jeanlecointre.com)! When it comes to the genuine investments behind DeepSeek, we have no concept if they remain in the [numerous millions](https://www.treueringe.ch) or in the [billions](https://www.htq.my). We feel in one's bones the $5.6 M amount the media has actually been [pressing](http://melisawoo.com) left and right is [misinformation](https://www.le-coq.net)!
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