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🚀 Elevate Your AI Innovations at the Solidus AI Tech Hack-AI-Thon! 💡 Ready to turn your AI concepts into profitable solutions? Participate in the Solidus AI Tech Hack-AI-Thon and showcase your skills in developing cutting-edge AI applications. 🔍 What Will YOU Do: ✔Select a Pre-Trained Model: Choose any LLM model of your preference. ✔Deploy an API: Select and deploy an API based on your chosen model. ✔Create an AI Prompt: Develop an AI prompt using providers like GPT or Llama. ✔Provide API Access: Ensure seamless API access for your module. ✔Upload to Marketplace: Publish your API on the Solidus AI Tech Marketplace for users to engage and build new solutions. 🏆 Total Prizes Worth $20,000: 🌟 Top 100 Submissions Featured on Solidus Ai Tech Ltd Marketplace: Stand out among top developers and have your AI solutions highlighted on the AI Marketplace. This is your chance to monetize your skills and drive significant impact in the AI industry. Ready to lead the way in AI innovation?👉 Register Here: https://p.hck.re/hvAx #AI #Hackathon #Innovation #TechCommunity #ArtificialIntelligence #SolidusAITech

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Godwin Josh

Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer

3mo

Hackathons like this are pivotal for pushing the boundaries of AI. For instance, deploying a pre-trained LLM via an API can significantly impact scalability and performance based on the underlying architecture of the model, such as the balance between latency and throughput in models like GPT-4 versus Llama2. Efficient prompt engineering is crucial to harness these models' full potential, especially in scenarios where resource constraints are a factor.You talked about selecting a pre-trained model and deploying an API. If you imagine developing an AI-driven real-time language translation service for a multilingual conference, how would you technically optimize the prompt and API deployment for handling high concurrency and ensuring minimal translation latency? What are your thoughts on this approach?

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