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Soumya

Stealth • 1m

💡An Idea to Change the Game for AI Startups: Making AI Processing Faster, Cheaper, and Effortless Running AI models like ChatGPT, DALL·E, or AlphaCode is a computing monster—they need massive power to function, which makes them expensive to operate. Imagine paying for thousands of GPUs to generate a single conversation or image! As more people use them, the costs grow quickly. For small startups, these expenses can be a big hurdle. The Problem: Huge Compute Costs: Running these models requires powerful hardware, which is expensive. Storage & Data: Training and maintaining these models requires a lot of storage, which adds to the overall cost. Ongoing Expenses: Regular updates and fine-tuning demand continuous computing power. the solution in written below cmt👇🏻

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Yash Barnwal

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🦾AI model training comes with significant costs. This chart highlights the estimated expenses for training top AI models like Google’s Gemini 1 and OpenAI’s ChatGPT-4 in 2023. These costs, calculated using both cloud computing and amortized hardware

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Shuvodip Ray

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AI relies on robust data management across 7 key components to build effective AI models: 1. sources, 2. ingestion, 3. storage, 4. transformation, 5. analytics, 6. governance and security, and 7. orchestration.

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sabarinath B

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Which technology, semiconductor or quantum computing, is expected to have a greater impact on AI development in the future?

6 replies7 likes
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Karunakar CH

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Revenue, Costs, and Profit: The Foundation of Business When running a business, understanding how money flows is crucial. The three essential elements are: Revenue: The total income from selling goods or services. Costs: Expenses incurred to operate

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Karan Sahu

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With just 15 global companies producing foundational models, it's clear how complex and capital-intensive this field is. The AI boom favors industry giants with resources and tech advantages, while startups refining these models to make money contend

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4 replies5 likes
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Mr BIZENIUS

Stealth • 2m

OpenAI has for months been working with Broadcom to create an AI chip for running models, which could arrive as soon as 2026, reports Reuters. Meanwhile, OpenAI plans to use AMD chips through Microsoft's Azure cloud platform for model training.

1 replies3 likes

pathak yash

Stealth • 1m

🚀 Transforming Data Storage with Quantum Computing | By Yash Pathak Imagine a future where quantum chips seamlessly connect to modern databases like MongoDB, revolutionizing the way we store, process, and secure data. With quantum computing, we unl

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Mohammed Zaid

Stealth • 3m

Researchers are developing AI models to predict the onset of diseases like Alzheimer’s and Parkinson’s. These models analyze patterns in medical data to identify early signs, potentially leading to earlier and more effective treatments.

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Mohit Singh

Stealth • 8m

Meta, formerly Facebook, has unveiled two new open-source AI models called Llama 3 8B and Llama 3 70B, with 8 billion and 70 billion parameters respectively. 🚀 These models outperform some rivals and spark debate over open versus closed source AI de

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NANDHA

Stealth • 2m

Which market do you prefer?. and why?. consider all the aspects while running a business. (finance, customer acquisition, costs, profit, sales, future growth etc... all) please justify, why? thank you.

10 replies4 likes
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