When your challenge goes beyond what traditional integrators and dev shops can deliver — our PhD-led research team turns cutting-edge science into your competitive edge.
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Our team analyzed nine frontier tech domains, identifying differentiation opportunities most enterprises overlook — and why PhD-level R&D is the key advantage.
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當 30% 新程式碼由 AI 生成，軟體工程正經歷最深刻的方法論變革。從 Brooks 本質複雜性框架出發，探討研發團隊如何重新思考架構決策、技術債管理與知識沉澱。
Karpathy 提出的 vibe coding 到底能不能用在正式產品？六階段工作流拆解 + McKinsey、MIT Sloan 研究佐證，企業研發團隊的四層 AI 協作架構——從直覺寫碼到品質治理的完整策略。
從 Deep Compression 到 DeepSeek-V3，深度解析五大模型效率技術如何組合出 10-100 倍的端到端加速。附 Google Colab 線上實作：CV 剪枝+量化、LLM QLoRA、擴散模型三技術疊加。
打開 AI 黑箱——LIME、SHAP、Grad-CAM 三大可解釋性技術完整解析，附 Google Colab 實作：文字情感分類 × SHAP 解釋、影像分類 × Grad-CAM 視覺化。EU AI Act 合規必讀。
2026 年 AI 技術走向何方？一篇掌握生成式 AI、AI Agent、量子運算、TinyML 等九大領域最新突破與成熟度評估。解析企業不可忽視的技術壁壘與差異化佈局機會——附免費成熟度對照表下載。
Harvard、McKinsey 研究證實：早期掌握 AI 的人享有顯著先行者紅利。三大雙向槓桿策略——向下快速習得數位技能、向上深化專業壁壘，附具體行動建議與 ROI 數據佐證。
Meta Intelligence is not your typical software company. We are a PhD-led technology R&D consultancy, focused on frontier challenges that traditional integrators and dev shops cannot deliver.
Our methodology is rooted in academic rigor — literature review, hypothesis testing, rapid prototyping, production-grade delivery — ensuring every solution has a solid theoretical foundation.
From concept to product, from 0 to 1 — this isn't outsourcing. It's a technology research partnership.
Recognized by Taiwan's Ministry of Economic Affairs, Ministry of Digital Affairs, and Ministry of Culture across multiple Green Tech Startup competitions.
We don't just write code — we research problems, design algorithms, and build systems. Nine domains where we deliver differentiated competitive advantage.
Custom LLM fine-tuning, RAG pipelines, multi-agent systems. Domain-specific AI tailored to your industry knowledge.
Industrial defect detection, medical imaging, multimodal understanding. Making machines truly see your domain.
Advanced statistics, causal inference, and ML-driven forecasting. From demand prediction to dynamic pricing.
Smart contracts, zero-knowledge proofs, supply chain provenance. Secure decentralized apps from cryptographic first principles.
TinyML, Edge AI, digital twins. Sensor-to-cloud architecture that makes smart manufacturing real.
Multilingual text analysis, knowledge graphs, semantic search. Turning unstructured data into queryable knowledge.
Quantum algorithm research, hybrid quantum-classical computing. The frontier for simulation, pricing, and optimization.
Enterprise AR/VR/MR, 3D spatial understanding, digital twin visualization. Immersive solutions for next-gen platforms.
Genomic analysis, protein structure prediction, drug screening. Transforming biology into computable models.
From research hypothesis to production deployment — real results delivered for our clients.
Built a generative AI design collaboration tool for a fashion startup, reducing product photography from days to minutes with a six-month phased launch strategy.
Compressed deep learning models to under 256KB for production line sensors, achieving sub-10ms defect detection — replacing manual inspection.
Built a multilingual financial regulation knowledge graph with LLM integration for automated tracking and impact assessment, cutting compliance analysis from weeks to hours.
Edited by Prof. Hungyi Chen with global experts from BIS, NUS, and Cambridge. Published by Palgrave Macmillan.
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Edited by Prof. Hungyi Chen with scholars from Cambridge, Sydney, Monash, and Glasgow. Published by Palgrave Macmillan.
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A systematic analysis of the six most common failure modes in enterprise LLM adoption, with a research-driven three-phase deployment methodology.
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Benchmarking QAOA and VQE algorithms for portfolio optimization against traditional Monte Carlo methods.
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Complete documentation of the PyTorch-to-ARM-Cortex-M pipeline, with benchmarks for quantization, pruning, and distillation.
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Based on ADB and World Bank data, analyzing enterprise investment trends in AI, Blockchain, and Quantum Computing across Asia-Pacific.
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Understand your business context, pain points, and goals. Define problem boundaries and success metrics.
PhD-level literature review and feasibility assessment. Design the optimal solution path.
Rapid proof-of-concept to validate the technical approach and business value at minimal cost.
Productionize research into production-grade solutions. Complete with knowledge transfer and training.
"True innovation isn't chasing technology trends — it's finding the precise connection between a problem and its solution. Our mission is to apply academic depth to find that unique answer for every client."
Whether it's an emerging idea or a defined project, we're happy to start with a complimentary consultation. One conversation could be the breakthrough you need.
