GPT 3 aur SEO: Kyun AI aapke content ko hamesha ke liye kranti laayega

Hum sabhi ne ab tak iski charcha suni hai.

OpenAI ne Generative Pre-trained Transformer version 3 (sankshep mein, GPT-3 ya GPT 3) ka ek naya version release kiya hai jismein beta API access hai. GPT 3, apne pehle ke version GPT 2 ki tarah hi, ek bada deep neural network hai jo automatically aisi realistic text generate kar sakta hai jisse kisi aam insaan ko aasani se behkaya ja sake. Yeh ek advanced AI hai jo web se insaani writing ki nakal karna seekhta hai.

Yahan GPT 3 dwara generate kiye gaye ek article ka excerpt diya gaya hai:

Second World War ke baad ke saalo mein, Western world ki economy, aur vishesh roop se Europe ki economies, sudharne aur growth dikhane lagi thi. Factriyo, sadko, pulo, shahro aur gharo, port aur airport ka fir se nirmaan shuru ho gaya tha. Europe ki economy poore Western world ke liye growth ka engine ban gayi thi. Desh, companies aur log samriddh hue, aur Europe mein economic growth, badhti mazdoori aur behtar living standards ka ek bada daur shuru hua. Rebuilding aur naye investment ke combination ne Europe ko business karne ke liye ek behtareen jagah bana diya. Companies ke liye, Europe ek bada market tha, jiske members market regulation, infrastructure, investment policy aur culture ke mamle mein lagbhag ekthe the. Firms ne factories lagayin, invest kiya, aur naye markets dhundhe, aur yeh investments kaafi hadd tak debt-funded the.

In results ne bilkul public ko hairan kar diya hai aur kafi hype create ki hai. Generate kiya gaya text acche se padha ja sakta hai aur grammatically sahi hai - lekin GPT 3 sirf ek powerful text generator hi nahi hai. Yeh technology content creation, marketing, aur SEO (Search Engine Optimization) ke baare mein sochne ke tareeqe ko bilkul badal deti hai. Content ke chhote snippets, jaise upar dikhaya gaya hai, kam cost par aasani se banaye ja sakte hain.

SEO experts aur content creators ke roop mein, GPT 3 ko samajhna imperative (bohot zaroori) hai. Kya iska matlab yeh hai ki human writing obsolete ho chuki hai? Kya yeh high-quality copy produce kar sakta hai? Kya yeh kisi doomsday scenario ko ishara karta hai jahan SEO-spam bots unlimited kachra produce karenge?

Halanki in baaton mein kuch sachhai hai, humein lagta hai ki GPT 3 ke aas-paas ki overhype ko thodi aur clarity ki zaroorat hai. SEO aur content writing par text generation technologies ke impact ko samajhne ke liye, humein sabse pehle yeh break down karna hoga ki GPT 3 kya karta hai, iska kya mahatva hai, aur yeh kaise kaam karta hai.

GPT-3 Ki Generality

GPT-3 aur iski purani technologies (GPT aur GPT 2) OpenAI dwara develop kiye gaye general NLP (Natural Language Processing) models par research ki ek line hain. Lekin general hone ka kya matlab hai?

Machine learning ka ek lamba itihaas raha hai aise systems develop karne ka jo sirf ek cheez mein acche hain. In systems ko narrow AI kaha jata hai. Agar aapko ek aisa AI chahiye jo Amazon review ki rating predict kare - toh aapke paas kaafi training data hone par aap aasani se ek model ko train kar sakte hain. Agar aap ek aisa model develop karna chahte hain jo social media par profile picture dekhkar bata sake ki woh kaun hai - toh aap dusre model ko train kar sakte hain jo yeh kaam karega.

Problem yeh hai ki in dono tasks mein se kisi ek par train kiye gaye AI systems kisi aur cheez par kaam karne mein asamarth hote hain - isiliye inhein narrow kaha jata hai. Yeh usi scope tak constrained hote hain jiske liye inhein train kiya gaya hai. AI research ki maujuda manzil aisi general technologies ko dhundhna hai - jo bohot saare kaam kar sakein. Yahan bataya gaya hai ki general technologies game-changers kyun hain.

AI generalists kyun banayein?

Ek aam soch hai - kya specialized experts ko zyada mahatva nahi diya jana chahiye?

Computing ke shuruati dino mein, logo ne specialized computers banaye jo sirf calculation kar sakte the aur ek hi tarah ki problem solve kar sakte the. Sochiye ek specialized calculator ke baare mein jo sirf addition kar sake, aur kuch nahi. Beshak, yeh addition karne mein bohot accha hai aur ise bohot tezi se kar sakta hai, lekin yeh zyada kaam ka nahi hoga.

Iske bajaye, ek aisa computer hona zyada useful hai jo add kare, subtract kare, online jaye, video games khele, aur kafi kuch kare. Modern computers jo von Neumann architecture par based hain, unme yeh general capabilities hoti hain. Baad mein dekhne par, yeh kehna aasan hai ki general-purpose computing manavta ke sabse impactful inventions mein se ek hai.

Yahi principle GPT 3 jaisi AI technologies par bhi apply hota hai. Hum apne systems mein generality chahte hain kyunki yeh humein bina har ek task ko manually engineer kiye, bohot saari problems ko solve karne ki azaadi deta hai. Saath hi, yeh pata chala hai ki general learning approaches se NLP tasks par AI accuracy ko kam se kam 60% tak badhaya ja sakta hai.

Aakhirkar, humans bhi ek tarah ki general intelligence hain. General intelligence humein un skills ko acquire karne mein madad karti hai jinke baare mein humein pehle se pata bhi nahi hota ki woh useful hain. Jo log isme interested hain ki general intelligence ka kya matlab hai, hum unhe aur details ke liye Chollet ka paper On the Measure of Intelligence recommend karte hain.

SEO marketing ke liye, iska matlab hai ki humein pehle se janne ki zaroorat nahi hai ki hum kis tarah ka content produce karna chahte hain. Humein thode alag purpose ke liye ek alag AI create karne ki zaroorat nahi hai.

GPT-3 ek aisa AI system hai jismein general intelligence ki kuch properties dikhti hain (jise kabhi-kabhi Proto-AGI kaha jata hai). For example, hum AI ko character dialogues ke examples dekar use poora karne ke liye keh sakte hain:

Rex future se aaya ek time traveller hai. Ada ek nineteenth-century ki noblewoman hai. Rex: Mujhe lagta hai maine apna time machine aapke garden mein crash kar diya hai. Ada: Pardon me? Aapne kya kaha naujawan?

Yeh kayi tarah ke dusre tasks bhi perform kar sakta hai aur yahan tak ki HTML code bhi generate kar sakta hai. Yeh ek badi baat hai kyunki iska matlab hai ki hum GPT ke sath content se jude bohot se tasks ko solve kar sakte hain.

Toh kya iska matlab yeh hai ki GPT 3 SEO se jude sabhi relevant tasks ko solve kar sakta hai? Kya yeh kisi bhi topic ke liye blog posts ya kisi bhi category ke liye content create kar sakta hai jo hum chahein? Bilkul nahi. Is sawaal ka jawab dene ke liye, humein yeh break down karna hoga ki GPT 3 kaise kaam karta hai.

GPT 3 Kaise Seekhta Hai

Big Data Ka Fayda Uthana

Machine learning models (aur khas kar deep neural networks) data ke bhookhe hote hain aur tabhi acche se kaam karte hain jab aap unhe bohot sara data dete hain. Aakhirkar, data is the new oil.

Lekin data milna mushkil aur costly hota hai. Sabse useful machine learning systems ke liye humans ko har ek data point ko mehnat se label karna padta hai. Labeled data aam taur par kayi applications mein sabse badi mushkil hoti hai kyunki ise ik इकट्ठा karna mehanga hota hai - sochiye Amazon Turkers ki ek fleet ko hire karne ka kya kharch hoga!

GPT 3 web par naturally milne wale text ko model karke apna khud ka training signal generate karke is problem ko solve karta hai. Yeh unsupervised (ya self-supervised) learning naam ka ek machine learning paradigm adopt karta hai. Yeh bina human-labeled data ke seekhne ki azaadi deta hai. Jo log unsupervised learning ke technical details mein jaana chahte hain, unke liye hamare CTO ne yahan ek in-depth analysis likha hai.

Lekin bina labels ke bhi, humein bohot saare data ki zaroorat to hogi, hai na?

Pata chala ki data bilkul hamari naak ke neeche hai. Internet par kayi topics ke baare mein high-quality, acche se likhe gaye articles ka dher hai - aur woh sabhi aasani se accessible hain. GPT ki training technique ki khubsoorti yeh hai ki ise behtar perform karne ke liye bas yeh seekhna hai ki in human-written articles ko kaise predict kiya jaye.

Lekin rukiye - kya web par bohot saara garbage nahi hai? Kya GPT 3 unhe bhi nahi seekh lega?

Yeh sach hai. GPT ke creators ne crowdsourcing ka use karke apne data ko filter karke inme se kuch issues ko kam kiya. Iska ek tareeqa yeh hai ki un URLs ko dekha jaye jo log Reddit par share karte hain, aur sirf un websites ke content aur posts ko crawl kiya jaye jinhe Reddit par badi sankhya mein upvotes mile hain.

Language Generation Ke Dwara Seekhna

Ek baar jab aapke paas data aa jaye, toh aap GPT ko train kar sakte hain. Lekin aap GPT ko un sabhi general capabilities ko paane ke liye kaise train kar sakte hain jinhe hum chahte hain? Ek idea bas text generation karne ka hai. GPT kisi article mein pichle words ke base par agle word ko predict karke natural language generate karna seekhta hai.

Yahi mukhya karan hai ki GPT sirf left se right content generate karta hai (yeh piche ki taraf nahi kar sakta). Is tarah ki learning ko language modeling kaha jata hai.

Yeh bas itna hi aasan hai.

Ek sentence mein agla word kya hoga, iska prediction karke, AI ko apne context ke baaki words ka use karna seekhna chahiye. Yeh implicitly GPT ko kayi dusre important general knowledge ko seekhne ke liye majboor karta hai.

Jo main create nahi kar sakta, use main samajh nahi sakta.

-- Richard Feynman

Agle word ko sahi tarike se predict karne ke liye, aapke paas English syntax aur grammar jaisi basic cheezon ke alawa hamari duniya ke baare mein common sense ki samajh ki bhi zaroorat hoti hai. Isi wajah se, sirf article prediction karne se GPT behad hairatangez human-like behaviors seekh leta hai.

Language generation systems ka machine learning mein ek lamba itihaas raha hai, aur GPT is game mein naya nahi hai. Balki, kuch AI researchers GPT ko ek scientifically novel achievement ke roop mein kam, balki ek impressive engineering feat ke roop mein zyada dekhte hain. Yeh humein ek important lesson sikhata hai ki computing resources par kharch kiye gaye $4+ million USD aur bohot saare data ke combination se hume kya mil sakta hai aur kya nahi.

Toh gya verdict hai?

OpenAI ne humein dikhaya ki AI solutions ko scale karne se hum kaafi aage tak ja sakte hain. GPT, jab iske sabse bade size tak scale kiya jata hai, toh sirf is baat ko observe karke ki humans kaise likhte hain, bohot saari general capabilities nikal sakta hai. Yahi wajah hai ki aap model se itna impressive performance dekhte hain. Google ne haal hi mein GPT ke ek version ko scale kiya hai jise Switch Transformers kaha jata hai jo GPT-3 ke size se 10 guna bada hai.

Yeh kayi AI researchers dwara mehsoos kiya gaya ek bitter lesson hai ki computation aur learning par based solutions, manual human effort ko peeche chhod dete hain. Ek simple generation framework ko scale karke, hume GPT 3 milta hai jo lagbhag ek human ki tarah likhta hai.

Lekin GPT 3 bina limitations ke nahi aata. SEO aur content marketers ke roop mein, in limitations ko janna behad important hai aur yeh is baat ko influence karta hai ki hum is natural language technology ka fayda kaise utha sakte hain.

Text Generation Ki Limitations

Poor World Model aur Factual Correctness

Hype ke bawajood, GPT ke paas hamari duniya ki acchi samajh nahi hai. Is world model ki kami ko dekhne ka ek interesting tareeqa yeh hai ki agar aap GPT ko common sense physics ya real world se juda kuch dete hain. Jaisa ki OpenAI ke technical paper mein bataya gaya hai, ise "Agar main cheese ko fridge mein rakhu, toh kya woh pighal jayega?" jaise sawalon ka jawab dene mein difficulty hoti hai. Yeh clear roop se dusre human concepts jaise puns ko bhi nahi samajh sakta.

Is phenomenon ki ek possible wajah yeh ho sakti hai ki AI ek embodied cognition nahi hai - usne training data ke zariye iske baare mein kayi baar padhne ke bawajood kabhi khud fridge ko nahi dekha ya feel nahi kiya hai. Agar aap apne content marketing ki zarooraton ke liye aankh band karke AI ka use text generate karne ke liye karte hain, toh aapko kuch inconsistencies aur factually galat cheezein milengi.

Unwanted Bias

GPT ko web par training di gayi hai aur, isiliye, yeh usi bias se suffer karta hai jo internet data provide karta hai. Is wajah se, GPT ka direct use karne se inappropriate ya offensive content create ho sakta hai. Is problem ko kam karne ke kuch tareeqon mein offensive filters shamil hain jo inappropriate content ko reject karte hain. Machine learning mein unwanted bias ko kam karna abhi bhi research ka ek active area hai.

Domain Adaptation

Halanki GPT ne language ki ek general samajh seekh li hai, lekin yeh aapke domain ke liye shayad suitable na ho. Recent research se pata chala hai ki GPT-style ke models ko tune aur tweak karne se aur bhi behtar results mil sakte hain.

GPT sirf kuch examples ke sath kaam karta hai, lekin ise badi quantity mein data dene se bilkul behtar results milenge. GPT ki ek aur limitation iski maximum generation length hai, jo ise input ke roop mein bade documents ka use karne ke liye suitable nahi banati.

Practical Efficiency

Halanki abhi kuch kehna jaldbaazi hogi, aisa lagta hai ki OpenAI GPT ka use karne ke liye premium price charge karne ki planning kar raha hai. Yeh solution kuch use cases ke liye mehanga ho sakta hai aur provide ki gayi service SEO ke liye customize nahi hai. GPT ka in-house use karna ya use train karna iske enormously bade parameter size ke karan ek practical challenge hai.

Lekin long run mein yeh issue ek choti chinta hai. Kuch research directions hain jo GPT ko run karne ke zyada efficient tareeqon ko possible banayengi jisse long term cost kam ho jayegi.

GPT-3 SEO Opportunity

Toh GPT-3 ek powerful text generation system hai - lekin is sabka content marketing ke liye kya matlab hai? SEO ke liye content marketing mein kayi steps hote hain. Yeh keyword research, competitor analysis, aur aakhir mein, aapke content ko create karne tak hote hain.

Hum GPT ko mukhya roop se content create karne ke liye use hote dekhte hain, lekin yeh ise akele nahi kar sakta. Technology ki limitations ke karan, yeh bilkul clear hai ki algorithm ko bina kisi control ke chhod dene se acche results nahi milenge. Ek human in the loop ka hona zaroori hai.

Writers Ka Artists Banna

GPT tab sabse accha kaam karta hai jab iska use human writers ke sath ek tool ke roop mein kiya jata hai — writers bina apni voice khoye AI tools ka use kaise karte hain yeh SEO teams ke liye ek core skill banta ja raha hai. Aisa isiliye hai kyunki human writers aisi kayi cheezon mein behtar hote hain jinme AI nahi hota. For example, human writers high-level thinking aur yeh sochne mein behtar hote hain ki kya likhna hai. AI low-level tasks jaise kisi site par web pages ki list se category pages banane mein behtareen hai.

Writing mein kafi mehnat low-level problems jaise grammatical correctness, tone, aur fluency par kharch hoti hai. GPT ke sath, ek human writer ka role ek editor mein badal jata hai. Sochiye ek canvas par broad brush strokes lagane ke baare mein, aur AI image details ko fill karta hai, fir human un details ko tab tak edit karta hai jab tak woh perfect nahi ho jate.

Ek tarah se, yeh behtar hai kyunki writers un cheezon par focus kar sakte hain jo zyada interesting hain - quality content ideas build karna aur writing ke zyada creative side par focus karna. Yeh category pages banane, kisi article mein kitne keywords ki zaroorat hai taaki optimal amount tak pahunch sake ispar focus karne, aur/ya har sentence fluent ho yeh dhyan rakhne se behtar hai.

Humans aur AI Ko Jodne Wale Tools

Upar di gayi baaton ka nishkarsh yeh hai ki humein behtar user experience aur aise tools ki zaroorat hai jo GPT ka fayda uthayein taaki yeh writers ke sath milkar acche se kaam kar sake. Broadly speaking, GPT-style technology ko useful content writing tools ke roop mein realize karne ke kayi tareeqe hain. Yahan AI technologies ke kuch examples hain jo vibhinn tools ke roop mein samne aate hain:

Readability Analysis

Acchi readability ka hona behtareen content develop karne ka ek important part hai. Yeh aapke users ko engaged rakhne aur aapke page par zyada time spend karne mein madad karta hai, jo Google par high rank karne ke liye ek important factor hai. Lekin padhne mein aasan articles likhna kehne se zyada mushkil hai.

Yahan Jenni par, humne ek aisa tool develop kiya hai jo aapke liye yeh kaam karega. Humne GPT 3 ke jaisi technology ka use kiya hai, lekin ise automatic sentence rewrites ke liye adapt kiya hai taaki yeh zyada readable ban sake.

Smart Rephrasing

Paraphrasing kisi source text ko bina directly quote kiye use karne ki kala hai. Jab bhi aap kisi aisi source se jankari le rahe hain jo aapki apni nahi hai, toh aapko specify karna hoga ki aapko woh jankari kahan se mili. Yeh sawaal aksar AI ke sath bhi aata hai; hamara AI writing, plagiarism, aur originality ka breakdown batata hai ki kis cheez ka dhyan rakhna hai.

Upar diye gaye paragraph ko hamari automatic rephrasing AI ka use karke Purdue ki definition se paraphrase kiya gaya tha. Ek AI jo smart rephrase perform karta hai, kisi bhi sentence ko is tarah se likh sakta hai jo source se alag ho ya use alag desired writing styles mein rephrase kar sake.

Jenni mein, humne apne writers par studies ki hain aur paya hai ki rephrasing ko automate karne se writer ka kam se kam 30% time bach sakta hai. Yeh writers ko sentences ki alternative phrasing ke sath experiment karne ki azaadi bhi deta hai, jinme se kuch original writing se zyada smoothly flow kar sakte hain ya unke intent ko behtar tarike se convey kar sakte hain.

Topic Optimization

Kayi SEO experts topic optimization par rely karte hain taaki yeh ensure kiya ja sake ki unka content search engines par high rank kare. Bilkul, kuch search queries ke liye relevant hone ke liye topics ka ek set develop karna important hai, lekin yeh ensure karna ki ek article sabhi topic requirements ko satisfy karta hai, ek bada challenge hai.

Hamare editors pehle topics ko manually optimize karne mein 1-4 ghante spend karte the. Apne article mein topic relevance ko detect karne ke liye AI systems ka use karna aapko apni writing ko sahi track par rakhne mein madad kar sakta hai, jo editors ko irrelevant content ko fir se likhne se bachayega.

Summarization

Jaisa ki humne pehle baat ki, AI low-level tasks mein behtareen hai aur summarization bhi iska exception nahi hai. Jab content writing ki baat aati hai, toh humne dekha ki ek aam task jo writers perform karte hain woh hai dusre text ko summarize karna.

Summarization ek aisa task hai jisme AI systems ne production aur commercial systems mein behtar perform karne ka proof diya hai. Kisi dense block of text ko padhne ke bajaye, kyun na ek AI aapko ek succinct bullet point list de? Isi tarah, agar aapne pehle se hi apni website build kar li hai toh aap indexes ya category pages banane ke liye AI ka use kar sakte hain.

Kya Generated Content Rank Kar Sakta Hai?

Kuch SEO practitioners automated content generation ke use aur Google se penalties milne ke baare mein chintit hain.

Google, kayi dusre search engines ki tarah, apne users ko sabse relevant content deliver karna chahta hai. Toh generated content ke sath sabse badi problem iska generate hona nahi hai, balki iska intent aam taur par spam create karna hota hai. Google ne claim kiya hai ki, jab tak content user ko real value deta hai aur system ko game karne ke liye use nahi kiya jata hai, tab tak generated content bilkul thik hai.

Balki, Forbes jaise kayi bade news aur media outlets pehle se hi content generation technologies ka use kar rahe hain. Yahan key dono worlds ke best - human aur artificial intelligence - ko fuse karke compelling content create karna hai. Internet par valuable knowledge contribute karna yeh ensure karega ki aap top par rank kar sakein bhale hi aapka kuch content generated ho.

AI aur SEO Ka Future

Science aur fiction ke beech ki line GPT jaise cutting-edge AI models ke release ke sath blur hoti ja rahi hai. Sirf ek saal ke time mein GPT 2 aur GPT 3 ke beech quality mein bada sudhaar behad hairatangez hai. Jaise-jaise time bitega, breakfast se pehle jo newspaper aap padhte hain, uske kisi human ya fir aisi cheez dwar likhe hone ki possibility zyada hogi jisne apni life mein kabhi omelet nahi khaya hai.

Yahi wajah hai ki humein lagta hai ki sirf hype se aage badhkar AI technology ki gehri samajhbana important hai. Jo log SEO field mein nahi hain, woh sirf AI ki progress se impress ho sakte hain. Jo log SEO field mein hain aur content create karte hain, unhe top par bane rehne ke liye in tools ke sath adapt hona padega.