GenAI se paisa kaun kama raha hai?

Generative AI, GenAI revenue, AI startups, Accenture GenAI, OpenAI revenue, AI investments, AI productivity gains, AI customer support, AI recommendation systems, LLM infrastructure, Hugging Face, Llama AI, AI agents, SaaS workflows, AI market opportunities

Accenture ne is quarter mein Generative AI se $600M se zyada kama liya hai ($2.4B annualized). Is number ko samajhne ke liye, 2023 mein OpenAI ne $1.6B revenue kamaya tha.

Bohot se enterprises GenAI experiments ke promising early results dekh rahe hain aur plan kar rahe hain ke 2024 mein apna kharcha 2x se 5x tak badhaayenge taake zyada workloads production mein deploy kar saken.

Yeh ek badi opportunity hai un founders ke liye jo AI startups build kar rahe hain:

1.     Jo enterprises ke AI-centric strategy ko dhyan mein rakh kar unke pain points solve karte hain.

2.     Jo productized services build karte hain jo is naye investment wave ko capture karte hain.

Revenue Multiple ek company ke valuation ko uske revenue ke hisaab se measure karta hai. Control aur customizability ki wajah se enterprises open-source aur self-hosted LLMs mein interested hain.

Hugging Face ne is ecosystem mein apni jagah bana li hai. Llama ek de facto standard ban gaya hai LLMs ke liye, kyun ke Meta ne pehla strong LLM source available karaya aur iske benefits enjoy kar raha hai. Competitors bhi aisa hi kar rahe hain, jaise Google, Apple, Mistral, Stability, Databricks aur doosre apne models open-source kar rahe hain.

January 2024 tak, chatbots LLM apps ka 46% the. Customer support chatbots aur recommendation systems (jahan chat interface user input ke basis par recommendations refine karta hai) do primary customer-facing use cases hain jo enterprises dekh rahe hain.

Sabse bada impact productivity gains ka raha hai - “A Dollar Saved is A Dollar Earned”. Yeh upar diye gaye use cases ek of three ways mein build kiye gaye hain:

·        Internal teams solutions build karte hain

·        Consultancies productized services use karte hain

·        Product companies one-fit solutions bechti hain

·        ROI zyada productivity ki wajah se hai jo AI generate karta hai.

Yeh badalne wala hai, AI agents ab explode hone wale hain. 2024 woh saal hai jab hum simple wrappers se aage jaayenge aur complex tasks ko AI ke through agentic workflows se accomplish karenge.

Zyada AI apps workflow apps hain jo ek sequence of actions ko execute karte hain taake final state tak pahuchein. SaaS apps workflow wrappers hain ek database ke upar, simple shabdon mein.

Humne bohot saare workflows chahiye the toh humne bohot saare SaaS apps build kiye. Sab ne user inputs liye aur workflows execute kiye - workflows jo customers ko chahiye end result tak le jaate hain.

Ab, AI agents jo workflows execute kar sakte hain (aur jald hi complex workflows flawlessly execute kar sakte hain), jab AI agents desired end results denge, SaaS apps ki zarurat nahi rahegi workflows design karne ke liye. Toh, agents aayenge, workflows chale jaayenge.

Phir, kis ke paas moat hoga? Ek strong moat ke liye business mein teen core competencies zaroori hain:

·        Product innovation

·        Operational Excellence

·        Customer Intimacy.

Generative AI apps ke liye, yeh Data ya Infra ho sakta hai. Agar aap ek LLM Infra company hain jaise Langchain, Pinecone ya LlamaIndex, aapke paas achha chance hai. 2023 mein, enterprises ne $1.1B+ LLM infra stack par kharch kiya — jo generative AI mein sabse bada naya market bana aur startups ke liye massive opportunity hai.

Total funding $10B+ se zyada hai March 2024 tak (excluding $1B+ raises). Ya phir ek company jo data rakhti hai jo kisi aur ke paas nahi hai ya replicate karna mushkil hai, jaise Character AI.

Aap GPT wrapper products ke saath bhi achha kar sakte hain. FormulaBot, SiteGPT ache early examples hain. Mobile app segment mein, apps jo companionship provide karti hain jaise Character AI bohot achha kar rahi hain.

Overall, ChatGPT yahaan winner hai, apni all-rounder tool hone ki wajah se.

Conclusion mein, Agar aap sirf start kar rahe hain aur aapke paas limited funds hain, toh AI services par bet karein, phir Productized AI Services aur Consultancy. Agar aapke paas funds aur experience hain, toh apne idea ko validate karein aur ek strong product build karein specific use case ke liye with end customer in mind. Agar paise aur talent aapke problems nahi hain, toh R&D mein massive invest karein, high-quality data ko acquire karein, compute ko hoard karein, aur new architectures ko explore karein both software aur hardware mei.