Kya AI Copywriters ko replace karega? AI Content Writing ka Vikas aur Bhavishya

Jaise-jaise text generation aur machine learning advance ho rahe hain, is baat par bahut charcha ho rahi hai ki kya content writers ko un dheron AI copywriting tools dwara replace kar diya jayega jo autocomplete functionality offer karte hain.

GPT-3, Rytr, Jarvis, Shortly, CopyAI, Frase, etc. - market mein autocomplete ke sath aane wale naye products ki list endless hai. In sabhi products mein ek "Write for me" button hota hai. Aap us button par click karte hain, aur ek paragraph text bahar aa jata hai.

Yeh lagbhag kisi jadoo jaisa lagta hai.

Ek artificial intelligence researcher ke roop mein, main pichle 5 saalon se is area mein hone wale breakthroughs ko follow kar raha hoon - aur yeh behad dilchasp hai ki kaise ek aisi cheez jo aapke text messages ko autocomplete karne ke tarike ke roop mein shuru hui thi, aaj ek aisi technology ban gayi hai jo lagbhag poore novels likh sakti hai.

Lekin kya iska matlab yeh hai ki AI copywriters ko replace kar sakta hai - kya human writing purani ho chuki hai? ‍Iska jawab complicated hai.

Is sawal ka jawab dene ke liye, hamein sabse pehle parda uthakar dekhna hoga ki content writing ke liye autocomplete really kaise kaam karta hai. Is jankari ke sath, hum is artificial intelligence technology ke fayde-nuksan ko samajh sakte hain, aur yeh pata laga sakte hain ki market mein in sabhi AI writing tools ke hone se kya copywriters ko chinta karne ki koi zarurat hai.

How Autocomplete Evolved for Content Writing

GPT-3 jaise naye artificial intelligence breakthroughs ke aas-paas chal rahe hype ke beech, yeh bhoolna aasan hai ki predictive text technology (autocomplete aur autocorrect) pichle kuch dhashkon mein kaise evolve hui hai.

Haan, yeh wahi feature hai aapke purane iPhone 5 par jo aapko "iz" se "is" par autocorrect karta hai, aur isi tarah Google aapko aapki search ke liye (kabhi-kabhi hilarious) completions suggest karta hai.

Counting on N-Grams to Write For You

Aapko hairani ho sakti hai, lekin autocomplete technology ka itihas 1948 tak jata hai. Tab se, isne content writers ko spellcheck karne aur unki writing ko correct karne mein madad ki hai.

Aaiye autocomplete ke shuruati dino par ek nazar dalte hain.

Kayi shuruati autocomplete systems ek language model ke concept par based the. Yeh aam taur par ek aisa model tha jo words ki history ke basis par agle word ko predict kar sakta tha.

Sabse pehla language model, jise sabse pehle reference kiya tha Claude Shannon ne, use n-grams model kaha jata tha. N-grams ka ek application yeh predict karna tha ki aap jo text type kar rahe hain usme words ke ek set ke aane ki kitni sambhavna hai.

Toh udaharan ke liye, agar aap type karte hain "Can you please come" (the history words), toh n-grams model predict karega ki agla word "here" aane ki high probability hai (for example, 80% chance). Aapka phone tab aapko "here" word ke sath aapke phrase ko autocomplete karne ka option dega.

N-grams ko kaise pata chalta hai ki kaun se words aane ki zyada sambhavna hai?

Aap high-quality text ke corpus (jise training data bhi kaha jata hai) mein "Can you please come here" phrase kitni baar aaya hai, use count karke ek n-grams model bana sakte hain. Agar yeh phrase bahut baar aata hai, toh iska matlab hai ki "here" ek correct completion hone ki sambhavna hai - nahi toh, yeh ek unlikely phrasing hai.

Yeh occurrence count corpus ke sabhi possible phrases par apply hota hai, aur iska result ek "table of counts" ke roop mein nikalta hai.

Upar diye gaye example mein, pehli row ka count sabse zyada hai kyunki yeh human written language mein sabse zyada baar aata hai. Last row esoteric English mein likhi gayi hai aur modern language mein zyada nahi aati, isliye iska count kam hai.

Is table ke sath, jab bhi koi type karta hai, toh program is table ko dekhega taki sabse highest count wale phrase ko match kar sake. Yeh best match asal mein is baat ka prediction hota hai ki agla word kya hona chahiye. Yeh match program ko aapko likelihood ka ek estimation dene ki permission bhi deta hai (for example, corpus ke basis par correct completion ka 80% chance).

Aur bas ho gaya - dheron autocomplete tools ke peeche ka jadoo words ko count karne par hi tika hai!

Ek behad simple shabdo mein kaha jaye toh, is tarah aap ek aisa model banate hain jo kuch history words ke basis par agle sabse zyada likely word ko predict kar sake. Yeh autocorrect aur autocomplete systems ke kaam karne ka foundation hai.

Toh kya copywriters ko ek n-grams model se replace kar diya jayega?

Bilkul nahi.

N-grams ke sath ek fundamental problem hai - yeh language ko ek sparse tarike se represent karta hai. Simple shabdo mein kahein toh, iska matlab hai ki agar aapke paas bahut saara data hai, toh aapka table bahut bada ho jata hai. Wahin par GPT jaise neural networks apna kaam shuru karte hain.

Going beyond a table with GPT

Aaj hum jo use kar rahe hain, woh n-grams model ke baad se bahut aage badh chuka hai.

Autocomplete ke liye modern artificial intelligence neural networks par depend karti hai, jo n-grams models se kahin zyada powerful hain. Halanki yeh zyada sophisticated hain, phir bhi neural networks statistical counting ke usi fundamental principle par depend karte hain.

Sabse powerful GPT-3 (Generative Pre-trained Transformer v3) OpenAI dwara develop kiya gaya ek bada neural network language model hai aur ab yeh market mein haal hi mein release hue sabhi autocomplete writing tools ki back-bone hai. GPT-3 natural language processing (NLP) ke us trend ka hissa hai jo bade pre-trained neural networks ki taraf badhne ka hai.

GPT-3 ke sath, hum ab sabhi possible phrases ko store karne ke liye naively table ka use nahi karte, balki hum iske neural network ke weights mein iska ek compressed summary store karte hain. Yeh hamein billions of phrases aur sentences par models ko train karne ki permission deta hai jise ek single table mein fit karna impossible hota.

‍Toh GPT-3 aapke liye kaise likhta hai?

N-grams ki tarah hi, jab aap koi word ya phrase type karte hain, toh GPT-3 us corpus of text ke basis par jise lekar use train kiya gaya tha, aapke sentence ko complete karne ke liye sabse likely word dhoodhne ki koshish karega.

Lekin yeh wahin nahi rukta. Ek baar jab yeh predict kar leta hai ki aap agla kaun sa word type karne wale hain, toh yeh ise ek loop mein chalayega aur tab tak agle word ko predict karta rahega jab tak ki isne ek paragraph na likh diya ho. Is tarah yeh aapke liye ek paragraph "generate" karta hai.

Lekin rukiye - agar GPT-3 sirf pehle se likhe gaye content se derive hui probabilities ko hi dekhta hai, toh kya iska matlab yeh hai ki GPT-3 sirf wahi repeat karta hai jo usne padha hai, ya yeh actually creative hai?

Yeh ek mushkil philosophical sawal hai jo aaj-kal AI-generated content ke baare mein hone wali discussions mein छाया hua hai.

Misconceptions about AI Content Writing

Kya AI Content Writing Creative Ho Sakti Hai?

Kayi critics ne note kiya hai ki GPT-3, baki sabhi AI models ki tarah, sirf wahi text generate kar sakta hai jo usne pehle dekha hai. Unka daawa hai ki AI writing mein creativity ki kami hoti hai aur yeh tools sirf regurgitated content ko spam karne ke liye ache hain.

Halanki yeh view pehle sahi hua karta tha, lekin ab yeh poori tarah se sach nahi hai.

Yeh claim karna aasan hai ki 1948 ka ek n-grams model aasani se existing content ko repeat karega kyunki yeh literally apne saare training data ko ek table mein store karta hai aur un phrases ko dekh kar text "generate" karta hai jo usne pehle dekhe hain.

Lekin chunki GPT-3 apne training text ka ek highly efficient compressor hai, isliye yeh written content ke rules aur patterns ko develop karne ke liye forced hai - yeh humesha apne memory mein store kiye gaye training data keexact sentence ko yaad nahi rakhta.

Halanki kuch sentences verbatim generate ho sakte hain, lekin produce kiye gaye dheron phrases naye hote hain. Generated text ka ek quick Google search aapko dikha dega ki yadatar generations original hote hain.

Aap is baat par vishwas karte hain ya nahi ki GPT-3 (ya koi bhi AI model aur AI Tools) original writing produce kar sakta hai, yeh debate ka vishay hai, aur yeh is baat par depend karta hai ki aap originality ko kaise define karte hain. Aakhirkar, humans ne bhi pehle ke mahan kamon se sikha hai aur Shakespeare ke spin-offs banaye hain, toh kya humans really itne original hain?

Wahin jab modern AI aisa text produce karta hai jo shayad market mein maujood text se milta-julta ho, toh yeh aisa text bhi produce kar sakta hai jo aapko hairan kar de.

Yeh human copywriters aur content editors par depend karta hai ki woh is surprise ka sabsay zyada fayda kaise uthate hain.

Autocomplete ka behtar use karne ke liye writers ko sabse ache AI-generated text ko filter aur choose karna chahiye, ya ise writer's block ko todne ke liye ek inspiration ke roop mein use karna chahiye.

Can AI Content Writing Have Emotion?

AI content writing ko lekar ek chinta yeh bhi hai ki yeh soulless, unemotional text produce karega.

Yeh ek aur broad statement hai jisme nuance ki kami hai - aur shayad yeh hamari science fiction ki is soch se aaya hai ki AI bina feelings wale tin-can robots hote hain.

Ek baar phir, n-gram jaise simple AI models ke emotional text produce karne ki sambhavna kam hogi kyunki unme representational power ki kami hoti hai - unke paas sikhne ki ek practical limit hoti hai.

Lekin chunki GPT-3 zyada context ke sath text ke ek bade corpus se sikhta hai, isliye yeh aksar writing ke sentiment aur tone ko nakal kar sakta hai. Iska matlab hai ki agar aap "I'm feeling sad today" jaisa phrase type karte hain, toh AI model generated text mein us sentiment ko reflect karne ke liye sabse appropriate words dhoodhne ki koshish karega.

(Upar jo paragraph aapne abhi padha hai, use Jenni AI dwara bina kisi edit ke poori tarah se autocomplete kiya gaya tha. Isne pichle paragraphs se mere tone aur writing style ko match karna sikh liya hai.)

ICLR 2020 mein published ek study dikhati hai ki neural text generators dheron baar parrot bhi kar sakte hain aur repetitive hona shuru ho sakte hain. Halanki, parroting karna emotion hone ke jaisa nahi hai.

Ek writer ke roop mein, aapko abhi bhi apni writing ke overall tone aur emotion ka dhyan rakhna hoga. Halanki AI aisa text produce kar sakta hai jo human sentiment ko mirror karta hai, lekin uske paas is baat ka empirical experience nahi hai ki human hona kya hota hai - yeh ek embodied intelligence nahi hai.

Yaad rakhein, n-gram models ki tarah hi, GPT-3 ko text ke ek corpus par train kiya jata hai (mostly internet se aur ek human copywriter dwara produce kiya gaya).

Isne aisi koi aur cheez nahi dekhi ya experience nahi ki hai jo ek typical human karta hai - yeh kabhi nahi jaan payega ki ek cheeseburger ka taste kaisa hota hai, na hi yeh poori tarah se empathize kar sakta hai. OpenAI ke mutabik, yeh physical world se related sawalon ke jawab accurately nahi de sakta, jaise ki "If I put cheese into the fridge, will it melt?".

Yeh aane wale kuch saalon mein modern language models ki ek inherent limitation hai - kam se kam tab tak jab tak AI ko ek physical body nahi mil jati.

Content writing ke liye, is limitation ko samajhna critical hai.

Iska matlab hai ki content writing ke liye AI ki power ka sach mein fayda uthane ke liye, hamein AI model ko sahi direction mein steer karne ke liye guidance aur feedback dene ki zarurat hai.

Why AI + Human Is the Future of Content Writing

Yeh drawbacks kayi logon ko AI content writing ke advances ko lekar skeptical bana sakte hain ya darr paida kar sakte hain ki hamara future spam content se bhara hoga.

Iske viprit, main ek behad bright future dekhta hoon.

1996 mein, jab IBM ke AI system ne chess ke game mein haraya tha, toh yeh socha gaya tha ki chess ka game solve ho gaya hai aur ab koi chess players nahi bachenge.

Halanki, jo hua woh tha log AI ke moves ko study karke naye chess strategies sikhne lage. Ek similar phenomenon tab par bhi hua jab DeepMind ke AlphaGo ne Lee Sedol ko haraya, jo 2016 mein Go ke duniya ke best player the.

AI mein success ka matlab hai ki humans ko adapt aur change hona hoga - aur yeh change uncomfortable ho sakta hai lekin yeh aam taur par behtari ke liye hota hai. Halanki AI humans ko kuch tasks mein hara sakta hai, lekin humans behtar generalists hain, aur hum apni overall productivity ko augment karne ke liye AI ko incorporate karna sikh sakte hain.

Yeh content writing ke liye bilkul sach hai, jahan copywriters ko apne content mein ek high-level content strategy, company ke vision aur brand, aur audience ki samajh ko integrate karne ki zarurat hoti hai.

Isliye main ek aise future ko predict karta hoon jahan hamare paas dono worlds ka best hoga - humans aur AI milkat kaam karenge taaki aur bhi higher quality content produce kiya ja sake.

Will Copywriting Be Obsolete Tomorrow?

Technology ke exponential development ke sath, is baat par hairan na hona mushkil hai ki - kya future mein content writer ki job risk par hai?

Agar hum pichle saalon mein language model ke improvement ke trend ko dekhein, toh yeh saaf hai ki AI text ko autocomplete karne mein behtar aur behtar hota ja raha hai. Ek common benchmark jaise WikiText-103 par AI ki perplexity (error ka measurement) pichle 3 saalon mein 40 se ghatkar 10 ho gayi hai - yeh ek 4x improvement hai!

Is exponential growth ko agar hum aage badhayein, toh agle 5 saalon mein, hum autocomplete technology ki quality mein aage aur 10x improvement ki umeed karte hain.

Iskar matlab hai ki agar aap apni SEO content writing ke liye sirf low-value work produce karte hain - existing content ko rewrite karna, templates ko fill karna, listicles ko copy/paste karna, ya dusre logo ke content ko spin karna - toh jawab hai haan - aap doomed hain.

Toh, iska serious aur passionate copywriters ke liye kya matlab hai?

Don't "Write for Me", "Write with Me"

Ek reason hai ki hum ab typewriters ka use nahi karte. Woh isliye kyunki content writing sirf ek paper par ink lagane ke baare mein nahi hai.

Ek reason hai ki hum ab manually grammar check nahi karte. Woh isliye kyunki grammar ek technicality hai aur aapke content ka sachha dil nahi.

User search intent ko satisfy karna aur aapke specific niche mein subject matter experts ke roop mein dekha jana aapke readers ko baar-baar wapas layega. Woh organically aapke articles ko ek bade scale par share karenge aur google search engine rankings mein aapke article ko upar shoot karne mein madad karenge.

Technology ke sath hum kaise likhte hain, isme is saare evolution ke bawajood, writer hi content ke vision ka in-charge hota hai. Replacement ke bajaye augmentation hi key hai.

Agar AI low-level work ko remove karne ke liye yahan hai, toh ek copywriter ke roop mein, aapko higher-value work karne ke liye apne methods ko shift karna hoga. Yeh sochne ka samay hai ki aap kaun sa content produce kar rahe hain.

Har din 7.5 million blogs publish hote hain aur aapke content ko needs hat-ke dikhna hoga.

Aapka kaam aapki marketing strategy, audience, aur content ke beech ke dots ko connect karna hai - unique information, research, aur ideas lekar aana - aur ise ek aisi story ke roop mein present karna jo dusro ne nahi batayi ho. Ek aisi story jo attention grab karti hai aur aapke readers ko piece ke end tak engaged rakhti hai.

Iska matlab hai ki writing ab paper par words likhne ke mechanics ke baare mein kam aur un ideas ke baare mein zyada hogi jise aap convey karna chahte hain aur storytelling ki art ke baare mein hogi.

Hamein apne liye likhne ke liye AI par depend hona band karna hoga, balki apne sath likhna hoga.

Agar aapke job mein aapke reader ke sath empathize karna shamil hai taaki high-quality, engaging content produce kiya ja sake jo aapki audience ke sath resonate kare aur real value provide kare - toh aapka role safe hai.

How Jenni can Help

Jenni mein, hum humans aur AI ke beech is integration ko jitna ho sake utna seamless banane ke liye kadi mehnat karte hain - aur isliye humne apne GPT-3 based autocomplete system ko dhyan se design kiya hai taki yeh aapke raste mein na aaye, balki aapko - content creator ko - driver ki seat par rakhe. Humesha!

March 2022 ke mutabik, humne "Write for Me" functionality ko phase out karne ka decision liya hai - aap jante hain, woh button jise aap press karte hain, aur yeh magically aapke liye ek paragraph likh deta hai. Shocking!

Aisa isliye hai kyunki humne dheron user case studies ke zariye pata lagaya hai - naye users jinhe "Write For Me" buttons ka access diya gaya tha, unme se aadhe se zyada ne apne content ka lagbhag 80% produce karne ke liye is par click kiya - jisme se zyadatar low quality ka tha.

Is button ka incentive user ke liye spam create karne ke liye niyat bahut aasan hai, aur yeh aapko aapki story ke author hone se rokta hai.

Iske bajaye, Jenni ab aapke likhte samay aapko actively suggestions dekar aur aapke content creation process ke sath seamlessly integrate karke aapki madad karega.

Yeh kisi bhi writer's block ko todne mein bahut madad karega, aur aapke craft mein fun aur passion ko wapas lekar aayega.