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Exposed: The Truth Behind Volkai โ Is It Truly India Made AI? So, I recently dug into the buzz around Volkai, the AI company gaining fame as Indiaโs very own innovation in the AI space. Everyone's been hyping it up for being completely built from scratch right here. But here's what I found: Volkai is actually fine-tuned on Gemma by Google, a sophisticated AI framework. While fine-tuning is totally valid and part of AI development, claiming to have built the entire system independently? That's a whole different narrative. Thereโs no shame in building on existing frameworks itโs how many great products are made! But transparency matters. When you're creating a national brand, honesty earns long-term respect. What are your thoughts on this! #Volkai #NotindianAI
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Fine-Tuning: The Secret Sauce of AI Magic! Ever wonder how AI gets so smart? Itโs all about fine-tuning! Imagine a pre-trained model as a genius with general knowledge. ๐ง โจ Fine-tuning takes that genius and hones its skills for a specific task, li
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I recently used Gemma 3 and it's groundbreaking Gemma 3 is Googleโs super light open-weight AI model thatโs free to use for building apps, including commercial ones. It is multimodal , runs efficiently on laptops or even mobile devices, and allows
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Hiring AI/ML Engineer ๐ Join us to shape the future of AI. Work hands-on with LLMs, transformers, and cutting-edge architectures. Drive breakthroughs in model training, fine-tuning, and deployment that directly influence product and research outcom
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India should focus on fine-tuning existing AI models and building applications rather than investing heavily in foundational models or AI chips, says Groq CEO Jonathan Ross. Is this the right strategy for India to lead in AI innovation? Thoughts?
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I have started a series to make it easy for people to, simply understand the latest AI trends here: https://open.substack.com/pub/jainnivedit/p/fine-tuning?utm_source=share&utm_medium=android&r=5l6i8y Think of it Finshots for AI, looking for feedbac
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"A Survey on Post-Training of Large Language Models" This paper systematically categorizes post-training into five major paradigms: 1. Fine-Tuning 2. Alignment 3. Reasoning Enhancement 4. Efficiency Optimization 5. Integration & Adaptation 1๏ธโฃ Fin
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The โEntry-Levelโ AI Engineer Job Description of 2025 ๐จ HR today: > โWeโre looking for someone who knows Python, OOP, NumPy, Pandas, SQL, Advanced Excel, Power BI, ALL ML/DL models, every AWS service, LangChain, Docker, Kubernetes, LLM fine-tuning
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