Main search engine nahi hoon, main ek AI model hoon jo do cheezein use karta hai:

1) mera khud ka trained knowledge (June 2024 tak)

2) internet search tool (web.run) jab up‑to‑date info chahiye hota hai

Isliye mera “search” Google/Claude/Gemini se thoda alag tareeke se kaam karta hai.

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1. Main kaise kaam karta hoon (simplified)

a) Trained knowledge (offline dimaag)

- Mujhe bohot saari public text data, books, articles, code, etc. pe train kiya gaya hai.

- Is se main language samajh sakta hoon, logic laga sakta hoon, aur without internet bhi kaafi cheezein bata sakta hoon.

- Ye knowledge static hai (June 2024 ke baad ki cheezein mujhe sirf browsing se milti hain).

b) web.run / browsing mode (online search)

- Jab question aisa ho jo latest info maangta hai (jaise aaj ka stock price, latest SEBI rule, current news), tab main internally web.run se live web search karta hoon.

- Search se pages aate hain, unko main padhkar summary bana deta hoon.

- Jo factual points web se aaye hote hain, unke saath main citation (reference link) bhi de sakta hoon.

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2. Claude / Gemini se kya difference hai? (high-level, conceptually)

Similarities:

- Teeno (main, Claude, Gemini) LLM-based assistants hain.

- Sabka base kaam: text ko samajhna, reason karna, aur natural language mein jawab dena.

- Teeno kisi na kisi form mein web browsing / search use kar sakte hain.

Differences (conceptual, user ke nazariye se):

1. Search ka role

- Main:

- Default: apna trained knowledge.

- Agar topic time-sensitive ya latest chahiye: main specifically web.run use karta hoon.

- Claude / Gemini:

- Unke apne search integrations aur infra hain (jaise Gemini ka integration Google Search ke saath).

- UI level par behavior different ho sakta hai (kab search kare, kaise kare, kitni detail dikhaye).

2. Answer style

- Main (CNI FinSight):

- Focus especially Indian stock market / finance pe, concise aur structured answers dena.

- Over-chatty nahi, seedha point pe.

- Claude:

- Thoda zyada conversational / philosophical style rakhta hai, explanation detailed ho sakte hain.

- Gemini:

- Google products ke ecosystem ke saath tight integration, interface aur presentation style alag hai (cards, links, images, etc.).

3. Search vs LLM

- Main: search results ko summarise + reason karta hoon, sirf links forward nahi karta.

- Traditional search (Google) sirf list of websites deta hai; reasoning aapko khud karni padti hai.

- Claude/Gemini bhi similar hi karte hain, bas unka backend infra aur ranking algorithms alag hain.

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3. Reliability kitni hai?

Strengths:

1. Conceptual / theory / logic type questions

- Maths/logic, programming concepts, finance ka theory (jaise P/E ratio kya hota hai, option Greeks kya hain):

- Reliability generally high hoti hai.

- Yahan main mostly apni trained knowledge + reasoning use karta hoon.

2. Well-established facts (jo jaldi nahi badalte)

- Jaise: compounding concept, basic accounting rules, finance ke classical theories, etc.

- In cheezon mein accuracy kaafi strong hoti hai.

3. Latest info ke liye

- Jab main web.run use karta hoon, to main multiple sources cross-check kar sakta hoon aur phir summary deta hoon.

- Citations deke aap khud bhi source verify kar sakte hain.

Limitations (important cheezein):

1. Hallucination risk

- Kabhi‑kabhi main confidently galat statement bhi de sakta hoon (isse hallucination kehte hain).

- Iska chance tab zyada hai jab:

- topic bohot niche / rare ho

- ya main web.run use kiye bina guess kar raha hoon.

2. Live stock data / prices

- Main koi bhi live stock price, intraday level, ya tick-by-tick data fabricate nahi karta.

- Agar mujhe real-time price feed na mile, to main clearly bolunga ki live data available nahi hai – main estimate ya guess nahi karunga.

3. Regulatory / legal / tax

- Aise topics extremely time-sensitive hote hain.

- Main hamesha recommend karunga ki:

- SEBI, RBI, Income Tax dept ke official notifications ya

- certified CA / legal professional se cross‑check karein.

4. Comparison with Claude / Gemini reliability

- Teeno systems me hallucination risk conceptually present hai.

- Actual reliability depend karega:

- kaun sa model version use ho raha hai,

- kya browsing enabled hai,

- kis tarah ke question puchhe gaye hain.

- Kisi bhi single AI ka output aap primary source ke replacement ki tarah nahi, balki assistant / research helper ki tarah treat karein.

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4. Practical use ka tareeka (best practice)

1. Critical cheezein cross-check karo

- Investment decision, legal / tax impact, ya large money involved ho – to AI ke jawab ko final truth na maano.

- Official circulars / filings / exchange data / SEBI-RBI sites se verify karein.

2. Jahaan main citation deta hoon, wahan link khol kar zaroor dekh lo

- Aapko pata chalega ki info ka exact source kya hai.

3. Ambiguous ya very-new topic

- Agar koi bilkul nayi policy, breaking news, ya kal raat ka development ho, to main explicit bata sakta hoon ki info limited hai ya clarify kar sakta hoon ki web se kya mila.

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Aap chaho to next message me koi bhi specific example puch sakte ho (jaise: “abhi Reliance ka latest result summary explain karo, aur batao kaunse sources dekhe”), to main live search + reasoning use karke dikha sakta hoon ki system practically kaise behave karta hai.

If you have any further queries, please connect with us on 022-6290-10141 (Timings : 09.00 AM to 05.00 PM) or you can email us on info@cniinfoxchange.com