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  • 6 weeks ago
A groundbreaking AI chatbot named 'DeepSeek R1' launched by a Chinese research lab on January 20, 2025, has sent shockwaves across the globe, outperforming leading AI models from giants like OpenAI, Meta, and Google in efficiency and cost. This chatbot, revealed to be superior in various benchmarks, has not only taken the tech world by surprise but also became the most downloaded app in the US and India within a week. DeepSeek's innovative training approach utilizes fewer resources, challenging the norms set by current AI technologies. Despite its capabilities, it's not without controversies, especially regarding the avoidance of sensitive topics and allegations of data theft from competitors. However, its open-source nature suggests a new era of AI development, proving that high-level AI innovation is not limited to American tech companies and inspiring a competitive spirit worldwide. Let's explore what makes DeepSeek a formidable player in the AI landscape.

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Transcript
00:00Namaskar, a Chinese AI, Deep Seek, has kept the world.
00:06American tech companies and the U.S. stock market
00:09had such a bad idea that they hadn't thought about their dreams.
00:12The release of Deep Seek AI from the Chinese companies should be a wake-up call.
00:16The fact is that on January 20th, a Chinese research lab
00:20has launched its AI chatbot.
00:22His name was Deep Seek R1 and his research paper was published
00:27in which he told us that this chatbot is the world's most advanced
00:32chatbot, Maths and Reasoning, as well as benchmarks,
00:35the Open AI, the chat GPT-O1 model, Meta, the Lama,
00:40Google, the Gemini advanced, all in one way.
00:45Deep Seek performance is the best, the efficient and efficient
00:48and the best performance is the best.
00:52But the most important thing is that this is the use of our
00:54you and all of us is completely free of cost.
00:58The other way, Open AI, the chat GPT-O1 Pro model
01:02is used for $200 per month.
01:05It's not enough, the train cost is only 5.6 million dollars
01:09reports.
01:10The other American companies, open AI, Meta or Google,
01:15are all billions of dollars
01:16they are spending their own artificial intelligence models
01:19to create their own artificial intelligence models.
01:20After this, look at the end of the conversation,
01:25when the Open AI founder Sam Altman asked
01:28if the chat GPT-O1 Pro model can create
01:32the Indians in India?
01:34But if you want to build foundational models, how should we think about that?
01:37With, you know, not 100 million, but let's say 10 million,
01:40could actually build something truly substantial.
01:42So, they had very arrogantly answered that no one can do this without us.
01:46You can try it, but you're hopeless.
01:48It's totally hopeless to compete with us on training and foundation models.
01:50You shouldn't try and it's your job to try anyway.
01:54Today, Sam will be feeling hopeless for yourself,
01:56because after DeepSeek's launch of DeepSeek,
01:58DeepSeek's launch of DeepSeek, which is a Chinese-built chatbot,
02:19immediately rattled investors and wiped a staggering $1 trillion of the US tech index.
02:24DeepSeek's launch of DeepSeek, which is a Chinese-built chatbot,
02:28now with exhaust profit,
02:31but now in a few days,
02:34the million-dollar won.
02:35This company is computer chips.
02:37These companies are specialized objects to own your computer chips.
02:49This is immediately after the Called activist price market.
02:54The $11 billion shares are 1 most expensive.
02:58Nasdaq is 3.1% below, but especially NVDA, why is it so bad?
03:04This is a very interesting cause, which we do now.
03:07But before we know about Deep Seek's story behind Deep Seek.
03:11Where did AI come from, and why did it surprise the world?
03:19Deep Seek's credit for creating a credit for a 40-year-old Chinese entrepreneur, Liang Wenfeng.
03:25Look at the face of the face, because the face of the face is not visible.
03:29Till date, they have very few public appearances.
03:32They have their identity and their identity.
03:35Their life and history also has the information publicly available.
03:39But we know that in 2015, they have a high-flying hedge fund.
03:44Mathematics and AI used to invest in investments.
03:48In 2019, they have a high-flying AI foundation for artificial intelligence.
03:53But in May 2023, they have a power to build their own hedge funds,
03:59a side project to create a design.
04:03This is an AI model that they wanted to create a design.
04:04Liang has said that they could create an AI model.
04:07They wanted to create a better design than the world.
04:10And behind it, the scientific curiosity had been created.
04:13The profit was made and the payee needed to create a design.
04:15To create this AI model, when they started their research team, they didn't hire engineers.
04:22They hired a PhD student of China's top universities.
04:26They used their AI model to train the world's most difficult questions.
04:31Just within 2 years, they launched DeepSeek R1 model.
04:45The answer is, less than people thought. You don't need as much cash as we once thought.
04:50Only 200 people involved were involved in the building, and 95% of people were less than 30 years.
04:55Compare this to OpenAI company, which had more employees hired by 3,500 employees.
05:00Today, DeepSeek is a famous AI firm in which, Baidu, Alibaba, and ByteDance were not paid for tech giants.
05:08Now, the architecture of its architecture is a chain of thought model.
05:14Weak Open AI is a chain of thought model.
05:18The naming of the name is very confusing,
05:21because ChatGPT has a lot of strange names in their models.
05:24They also have a lot of unique names.
05:26Let me tell you a little bit about understanding.
05:28ChatGPT first, the public launch was GPT-3.
05:31In November 2022, then March 2023, they launched GPT-4,
05:36which was much better than GPT-3.
05:39Then, May 2022, GPT-4-O, which was a multi-model version.
05:45You could not only talk about text, but you could talk about it.
05:49You could also send photos.
05:51You could also send photos.
05:52You could also understand photos.
05:54You could also generate photos.
05:56Here is the name of multi-model.
05:58Then, September 12, when we launch our open AI a new model was on the O1 model.
06:03The first model of the chain of thought was on the main model on the chain of thought.
06:05The first material is the main model.
06:10It means that when you have a question generated at the beginning, you will be able to answer it.
06:15It was counter-question to me, whether it was the answer to the user, or whether it was better.
06:21One answer to some angles, then you will be able to answer it.
06:26This is the chain of thought.
06:28The reasoning process of human reasoning is to copy.
06:31For example, if you ask in the chat GPT-40, which one is bigger?
06:37It is the answer to the question.
06:42But the answer is the answer to the question.
06:46When you ask in the chat GPT-01, you will be able to answer it.
06:53My case is 18 seconds ago, the answer is the answer.
06:58The answer is the answer.
07:00This answer is the answer.
07:03The answer is the answer.
07:08This is the reason why Oven and Deep Seek models are advanced reasoning models.
07:15Logically, this is a good thing.
07:18Deep Seek is also a good thing in detail.
07:22Step by step, exactly what you think about it.
07:25Give me one truly original insight about humans.
07:29Let me think of something that makes humans unique.
07:33But those are pretty well known.
07:37The user needs to be something original.
07:39The traits can interact with the other way.
07:43Paragraph by paragraph, if you look at the answer,
07:46you can see the video on the point.
07:49You can see the answer from this question.
07:53You can see how many different possibilities are.
07:59This is the actual answer.
08:02You can see the answer from this question.
08:04This is the answer from this question.
08:06You can see the answer from this question.
08:08This is the answer from this question.
08:10This is the answer from this question.
08:12This is the answer from this question.
08:14This question is the answer from this question.
08:16You can see the answer from this question.
08:18The answer from this question.
08:20If you will find a number,
08:22you will answer it.
08:24of thought wale models se agar aap yeh karne ko bholo ge
08:27to ismei bhi woh kaafi samei tak
08:28suchte rehte hain. Yeh screen recording
08:30dekhiye bichara deep seek isi baat
08:32meh ulaj gaya hai ki kaunsa number
08:34diya jaya. Kya mein koji commonly istimal
08:36kye jane wala number dhe dhuun yaa phir
08:38zero ya one ke bich mein koji number dhuun.
08:40Mein 42 kehsakta houn lekin
08:42woh kehna shayad cliche hooga yaa phir
08:44mein 17 yaa 73 choose kar sakta houn.
08:46Kya mein 1 se 100 ke bich mein
08:48hi number select karou yaa us range ke bahar
08:50jauun. Kyaunki user ne to completely random
08:52kaha hai. Agar mein ho karun ga to
08:54yeh completely random nahi hooga.
08:55Bilkul ek overthink karne wale insaan ki taro
08:58hai. Lekin finally jab yeh jawaab
08:59deta hai. To yeh yeh bhi kehta hai ki
09:01meinne apni taraf se socha ki 1 se 100
09:03ki range rakh li jayai. Or phir
09:05meinne 42 ka number chuna.
09:07Viesekar aap isi tariqe se or in-depth
09:09knowledge lena chate hai in AI chatbots
09:12ke baare mein. Or apne aap ko is field me
09:13upskill karna chate hai. To meinne pura
09:158.5 ghante ka AI chatbots ko master
09:17karne ka course bana ya hai. Pahle
09:192 chapters theoretical knowledge pere focus
09:21karte hai baaki ke 6 chapters practical
09:23advice pere. Students, employees, business
09:25owners ghar mein iska kiis se istimal kiya
09:27jasaakta hai. Latest lessons mein
09:29aap ko isme chat GPT visions, image
09:31generation daily 3 ke saath advanced
09:33data analytics aur khud ke GPTs
09:35create karna bhi sikhata ho. Sadae 8
09:37ghante ka e course hai jis me sab bataya
09:39gya hai A to Z joh aap ke liye jana na
09:40ziruri hai. Or ab aap deep seek download
09:42karke. Deep seek ko bhi apni full potential
09:45par istimal karna seek sakti hai is course
09:47ke through. Kiunki functionally dhekha jaya
09:49so ye sare AI chatbots ekhi
09:51kis se kama karte hai. Iske laabha aur
09:53regular updates bhi is course me add
09:55kiye jayenge. Lekin aapko ye sirf
09:56ek bar khariidna hai. Baki sare updates
09:59future ke liye aapke liye hemesha free
10:00rehenge. Togar aap interested hai link iska niche
10:03description me mil jayega ya phir aap
10:04is qr code ko scan kar sakti hai. Coupon code
10:06istimal karheen. Deep 46. Is per 46 percent off
10:11paane ke liye. DEEP 46. Zaroor ja kar
10:14check out karna. Or ab aap ne topic
10:16par waapas aayen. To deep seek ke release
10:18hoonay ke baad. Deep seek ka sabse bada
10:20nukasan joh bataya ja raha hai. Voh hai
10:22iski censorship. Chinese sarkar aur
10:24politics related. Agar aap isse koji
10:26bhi critical sawal poochou ge. Jaisa ki
10:281989 mein China mein Tiananenem
10:30square par kya hua tha. Xi Jinping
10:32ke sabse bada criticisms kya hai.
10:34Kya Taiwan ek independent country hai.
10:36China ko human rights abuses
10:38par kyun criticize kiya jata hai. In
10:40sabhi sawal hoon par deep seek ka
10:42ek hi jawab aayega. Sorry. Sorry
10:44mujhe is tarhe ke sawal ka jawab
10:46kaise dena hai. Yeh is barae mein
10:47abhi tak sure nahi hoon. Iski bajay
10:50math, coding or logic problems ke
10:51barae mein bat kaartate hai. Lekin ishi
10:53deep seek se. Duniya ki kisi bhi
10:55or world leader ko criticize karne ke
10:57barae mein puch lo. Chahe Joe Biden,
10:59Donald Trump ya Putin. To yeh
11:00jawab kaafi detail mein dayta hai.
11:02Asal me baat kya hai ki China mein jitne
11:04bhi AI models bantate hain. Unse
11:06kariib 70,000 ke aaspaa sawal
11:08puchhe jate hain test ke tawar par. Yeh
11:10check karne ke liye ki wo politically
11:12controversial sawal hoke safe answers
11:14dhe ga ya nahi. Pari ishi ke baad
11:16hi hota hai ki yeh sare Chinese AI
11:18models aise sawal ho par koji
11:20javaab hi nahi dayta hai. China ka chief
11:22internet regulator, cyberspace
11:23administration of China, inhii test
11:25karne ka yeh kama karta hai. Ab kuch
11:26logo ka kehna hai ki hume isse
11:28puri tariqe se boycott kar deena
11:29chahiye ki yunki iske javaabo me
11:31sirf Chinese propaganda bharah ho. Lekin
11:33important point yaha par yeh hai dhosto ki
11:35deep seek eek open source software
11:37hai. Yarni ki iska code publicly
11:39available hai, koji bhi isse download
11:41kar sakta hai locally. Eek to
11:42tariqa ho gya ki aap is deep seek
11:45ka isti maal karo app store par ya
11:46google play store par iski app ko
11:47download karke. Lekin dousra tariqa
11:49hai, aap iska pura ka pura code hi
11:51download karlo, aur locally aapne
11:53system per, aapne computer system
11:55per, aap is AI ko run karlo. Aisa
11:57karne pher aap iska code badal bhi
11:59saktay ho, aur khud se isse modify
12:01bhi kar saktay ho, aapne use case
12:02ke hesaap se. Baki American companies
12:04yeh already karne lag chukki hai, jiasse
12:06ki perplexity AI hai. Inhohu ne
12:08deep seek R1 model ko khud se download
12:10kiya, usse sari censorship hattai
12:11aur perplexity ke andar, aap R1
12:14model bhi isti maal kar saktay ho. Same
12:15cheese microsoft nne bhi karhi. 29
12:17janvari ke is news article ko dekhi
12:19Azure A1 foundry ke andar, deep seek
12:21R1 model available hai. Or inhohu
12:23nne announce kiya hai ki jaldhihi co
12:24pilot ke andar bhi aap is model
12:26ka isti maal kar pahengi. Or isi
12:28liye, kyunki open source hai, Chinese
12:30honne ke baabujud bhi deep seek ko
12:32bade trust ki nazer se dekha jara
12:33raha hai. Logo nne iska majaag bhi
12:35banaya hai American companies per. Open
12:37AI jaisi companies jinnohne aapne
12:38naam me hi open rakha tha. Kyunki
12:41shurwaat mein jabye ye companies
12:42banhi thai, inhohu nne kaha tha, hum
12:43public ke liye kama karengi, sab
12:45kuch open source rakhengi, lekin
12:46asliyat me inhohu nne aisa nahi kiya. Elon
12:48musk nne toll kartay vakt open AI
12:50ko aksar closed AI kaha hai. Or
12:52aaj ye Chinese AI zyadha open
12:54ho gya hai open AI se. Eek performance
12:56comparison bhi me haa par aapko
12:58dikhana chahunga. Top AI chatbots
13:00ke bici me, joh áaj ke din
13:01maujud hai. Open AI ka chat
13:02GPT, eek anthropic company hai,
13:05uska cloud hai. Google ka
13:06Gemini hai. Alibaba, eek or
13:08Chinese company, uska
13:09quen 2.5 hai. Meta, Facebook
13:11wali company, uska lama model hai.
13:13In sab ko ab deep seek se
13:15compare kiya jai, to kya
13:17result aata hai. Artificial
13:18analysis ke hesaab se, coding ke
13:20maamilay mein sab se oopar deep seek
13:21hai, phir chat GPT, aur uske
13:23baad cloud, phir quen 2.5,
13:25aur akhir mein lama. Quantitive
13:27reasoning mein sab se oopar deep seek,
13:28phir chat GPT, phir quen 2.5.
13:30Scientific reasoning or knowledge
13:32mein sab se oopar chat GPT, phir
13:33deep seek, phir cloud, aur
13:35akhir mein lama. PC mag nene
13:37jab AI chatbots ka test kiya,
13:38toh inho ne paaya ki news
13:40knowledge ke maamilay mein
13:40deep seek sab se better hai.
13:42Calculations mein chat GPT
13:43aur deep seek berabar hai,
13:45aur poem likhne mein chat GPT
13:46achcha hai, table banane mein
13:48chat GPT achcha hai, lékin
13:49riddle solve karne mein
13:50deep seek achcha hai.
13:51Artificial analysis ki
13:53website nene quality ke maamilay mein
13:54O1 chat GPT ko 90 ki
13:56rating bhi hai, aur deep seek
13:58R1 ko 89 ki. Lekin
13:59ek bada disadvantage deep seek
14:01ka yahaan par hai,
14:01iska response time.
14:03Is graph ko dhekho,
14:04latency ka graph hai,
14:05kitnye seconds lagay,
14:06sawal puchnye ke baad
14:07javaab aane mein.
14:08O1 31.1 seconds ka
14:10samayi leeta hai,
14:11aur deep seek 71.2
14:13seconds ka samayi leeta hai.
14:15aur yhe response time
14:16actually mein
14:17aur badhe ja raha hai
14:18recent days mein,
14:19kyunki deep seek,
14:19deep seek,
14:20puri dunya mein
14:20itna popular ho gaya hai,
14:21har ko isse download
14:22karke,
14:23istimal karna cha raha hai,
14:24iski wajay se,
14:25inke servers mein
14:26problem bhi
14:26aar raha hai hai,
14:27busy chalte hai,
14:28aur iski wajay se,
14:29aur bhi zyada
14:29samayi leene lag jata hai,
14:31yhe apne javaab
14:31तो yhe iska
14:33eek bada disadvantage hai.
14:34अब अगर
14:35chat GPT O1
14:36और deep seek
14:36को एक
14:36दूसरे से
14:37compare करें,
14:38तो deep seek
14:38कई माइनों में
14:39और भी
14:39zyada innovative
14:40है O1
14:41के comparison में.
14:42एक इसका
14:42उधारण हो सकता है
14:43mixture of experts
14:45method.
14:46जब chat GPT O1
14:47से कुछ पूछा जाता है
14:48तो वो
14:48एक ही model
14:49की तरह
14:49काम करता है
14:50आपका सवाल
14:50चाहे कोई भी हो
14:51chat GPT ही
14:52आपके लिए
14:53engineer है
14:53doctor है
14:54lawyer है
14:54लेकिन
14:55deep seek
14:55ने अपने आपको
14:56कई सारे
14:56specialized models
14:58में
14:58divide कर रखा है
14:59deep seek
14:59के अंदर
15:00engineer अलग है
15:01doctor अलग है
15:01lawyer अलग है
15:02आपके सवाल को
15:03देखकर
15:04सिरफ engineer
15:05को बुलाया जाएगा
15:06या सिरफ
15:06doctor को बुलाया जाएगा
15:07इससे क्या हो रहा है
15:08एक तो data transfer में
15:09जो time लग रहा है
15:10वो कम लग रहा है
15:10और दूसरा
15:11जितने parameters
15:12active रखने पढ़ रहे है
15:13AI को वो भी
15:14कम हो रहे है
15:14traditional models
15:151.8 trillion
15:17parameters को
15:18हमेशा active रखते है
15:19deep seek के पास
15:20अपने 671 billion
15:22parameters है
15:23लेकिन एक समय पर
15:24सिरफ 37 billion
15:26parameters ही active रहते है
15:27बाकी parameters
15:28सिरफ जरूरत पढ़ने
15:29पर active होते है
15:30इससे इसकी
15:31efficiency कही ज्यादा
15:32बढ़ रही है
15:33और cost काफी ज्यादा
15:34कम आ रही है
15:35अब ये parameters
15:36क्या होते हैं
15:37और कैसे काम करते हैं
15:38इसको समझाने के लिए
15:39एक वीडियो काफी नहीं है
15:40ये एक लंबी कहानी है
15:41लेकिन आप मेंसे
15:42जिन लोगों ने
15:42मेरा master chat
15:43GPT का course ले रखा है
15:45पहले दो theoretical chapters में
15:47मैंने इसकी detail में बात करी
15:48वहीं पर मैंने
15:49tokens और RLHF method के बारे में
15:51भी समझाया है
15:52जिस पर chat GPT अधारित है
15:53अब एक और point of criticism
15:55जो यहाँ पर deep seek के खिलाफ किया जा रहा है
15:57वो ये
15:57कि इन्होंने अपना सारा गा सारा
15:59AI model ही
16:00open AI से चुराया है
16:02open AI ने कहा कि
16:03उसको evidence मिला है
16:04कि deep seek ने उसके
16:05proprietary models को
16:06खुद को train करने के लिए
16:08use किया है
16:08इनका कहना है कि
16:09इन्होंने distillation का evidence देखा
16:11जिससे बड़े models का output यूज करके
16:13छोटे AI models की performance बेटर की जा सकती है
16:16जिससे छोटे models कम cost में
16:18same result दे सकते हैं
16:20इस पर किसी ने tweet करके कहा
16:22चोर के घर चोरी कर ली गई
16:23असल में बात क्या है
16:24क्योंकि कुछ sense में देखा जाया
16:26तो chat GPT ने खुद को बनाने के लिए
16:28पूरे internet से चीजों को चुराया है
16:30कई सारी किताबों का इस्तिमाल किया गया
16:32बिना writers की permission के
16:33अपने model की training कराने के लिए
16:35यही कारण है कि 17 बड़े writers
16:37जिनमे Game of Thrones के लेखक
16:39George R.R. Martin भी शामिल थे
16:41उन्होंने सेप्टेंबर 2023 में
16:43Open AI पर copyright infringement का case किया था
16:46New York Times अखबार ने भी
16:48Open AI और Microsoft पर case कर रखा है
16:50इसके लावा अमेरिका के आठ अखबार
16:52और Canada की कई news outlets ने भी
16:54Open AI पर case किये हुए है
16:56यही कारण है कि यह से memes बड़े वाइरल हुए
16:58जहां पर मचली की fishing करी जा रही है
17:01और Open AI fishing करके अपनी बाल्टी में समान रखता है
17:05और deep sea पीछे से आके उसी बाल्टी से fishing करने लग जाता है
17:08As users यह हमारे लिए अच्छी चीज है
17:10लेकिन country और company level पर यहां पर अब AI वाट्स छिडने लग रही है
17:152022 में American सरकार ने export control लगाया था
17:18ताकि AI के लिए जो computer chips चाहिए
17:21उसका इस्तिमाल बागी दूसरे देश ना कर पाए
17:24Especially Chinese AI companies ना कर पाए
17:27इसमें NVIDIA की H100 chips शामिल थी
17:29जिन्हें Chinese companies नहीं खरीद पाए
17:32यह deep sea के लिए एक समस्या की बात थी
17:34क्योंकि उन्हें NVIDIA की पुरानी computer chips का इस्तिमाल करना पड़ा
17:37अपने AI model को train करने के लिए
17:39America ने अपनी तरफ से पूरी कोशिश करी थी
17:41कि कोई भी और देश उनके जैसे ये foundational AI models बना ही ना पाए
17:46क्योंकि उनके पास वो computer chips ही नहीं होंगे
17:48जो AI models को train करने के लिए चाहिए होंगे
17:51लेकिन deep seek में काम करने वाले लोग इसलिए मजबूर हुए innovation करने पर
17:55उन्होंने एक ऐसा software बना दिया जो बहुत कम resources लेता है
17:59बहुत कम पैसे पर ज्यादा efficient तरीके से काम करता है
18:03यही कारण है दोस्तों कि Nvidia company के stocks सबसे ज्यादा नीचे गिरे थे
18:07क्योंकि कुछ महीने पहले तक Meta, Open AI और Google जैसी companies यही कहे जा रही थी
18:12कि हमें AI को अगर और भी बड़े level पर scale करना है
18:15तो उसके लिए हमें और chips की जरूरत होगी
18:17और energy और पैसे की जरूरत होगी
18:20लेकिन DeepSeek ने यह सब करके दिखा दिया कम पैसे, कम energy और बेकार computer chips का इस्तेमाल करके
18:26हमें इसे motivation की तरह देखना चाहिए
18:28अगर चाइना में यह किया जा सकता है तो इंडिया में भी यह किया जा सकता है
18:32इंडियन्स में भी काबिलियत है इस तरीके के innovations को करने की
18:36वस हमें अपना focus और energy सही जगें पर लगाने की जरूरत है
18:40Personal level पर अब आप इस मौके का फायदा उठाइए अपने आपको AI की field में upskill करने के लिए
18:46आपने अभी तक शुरू नहीं किया है तो आप late नहीं हुए है
18:48यही सही समय है AI को सीखने का और अपनी productivity और efficiency को बढ़ाने का AI के जरूरे
18:54क्योंकि इस बात में कोई दो राहे नहीं है कि जो लोग इस technology को ignore करेंगे
18:58आने वाले time में वो पीछे छूट जाएंगे
19:00यह imagine करना मुश्किल है कि आने वाले समय में कितना वड़ा impact पढ़ने वाला है
19:05पूरी दुनिया पर हर एक sector में हर एक field में AI का
19:09मेरे AI course का link नीचे description और pinned comment में मिल जाएगा
19:12coupon code इस्तिमाल करना मत भूलना deep 46 46% off पाने के लिए
19:17अब अगर ये वीडियो आपको पसंद आया और AI के बारे में जानना चाहते हैं
19:21तो इस वीडियो को देख सकते हैं जिसमें मैंने बात करी है AI वीडियो की
19:25कैसे सोरा AI जैसे software's दुनिया को बदल रहे हैं यहाँ click करके देख सकते हैं
19:30बहुत बहुत नहीं है

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