Eco Repharse

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  Eco Rephrase

About the project EcoRephrase is a revolutionary NLP tool that rewrites sentences with different tones while minimizing energy consumption — blending cutting-edge quantum computing with eco-conscious AI to drastically reduce carbon footprints in language processing.

Inspiration Our inspiration comes from witnessing the skyrocketing energy demands of modern AI models, which threaten the planet's health. We wanted to create a system that doesn’t sacrifice language quality but fights climate change by rethinking how AI can be smarter and greener — a nature hero standing up against energy-hungry AI giants.

What it does EcoRephrase intelligently rephrases sentences into tones like formal, friendly, professional, or persuasive — but unlike conventional AI tools, it integrates quantum algorithms to optimize tone selection and sentence variation efficiently, saving computational energy and CO₂ emissions.

This results in natural, diverse, tone-aware paraphrases that are both powerful and planet-friendly.

How we built it We combined: -Sentence Transformers for efficient semantic embeddings. -A QUBO-based tone classifier solved via quantum-inspired methods and optionally quantum hardware, ensuring eco-efficient tone detection. -An energy-aware scoring system that tracks CPU use, runtime, and estimates CO₂ emissions saved compared to classical AI. -Python’s async capabilities for fast, scalable processing. -A modular architecture letting quantum computing guide sentence optimization, with classical fallbacks for reliability.

Challenges we ran into -Integrating quantum algorithms seamlessly with NLP workflows. -Balancing tone accuracy and paraphrase diversity without heavy transformer use. -Implementing eco-metrics for realistic carbon footprint estimation. -Ensuring robustness with limited quantum hardware access and fallback solvers.

Accomplishments that we're proud of -Creating a hybrid quantum-classical system that actively reduces computational energy in paraphrasing. -Designing a novel QUBO tone classifier that can leverage actual quantum hardware or simulate quantum annealing. -Delivering natural, tone-aware paraphrases with measurable energy savings. -Building an open, extensible platform bridging AI, quantum computing, and environmental responsibility.

What we learned -Quantum computing can meaningfully contribute to real-world NLP tasks, especially for optimization problems. -Efficient embeddings and smart scoring reduce the need for massive models. -Measuring energy and CO₂ impact is critical and feasible in AI projects. -Collaboration between disciplines — AI, quantum, sustainability — unlocks new possibilities.

What's next for EcoRephrase -Integrate with real quantum annealers and test on live quantum hardware. -Expand the paraphrase dataset and tone variety. -Develop a user-friendly web app and API for broader access. -Explore other eco-aware NLP tasks, like summarization and translation. -Partner with climate organizations to promote green AI awareness.

Built With

• and-seamless-integration.-sentence-transformers-(all-minilm-l6-v2)-?-lightweight-yet-powerful-embedding-model-enabling-efficient-semantic-understanding-with-minimal-energy-consumption.-qiskit-?-ibm?s-open-source-quantum-computing-framework
• async-processing
• python
• qaoa
• qiskit
• qubo
• vercel