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</head> | |
<body> | |
<div class="container"> | |
<header class="header"> | |
<h1>European AI/ML Models Hub</h1> | |
<p>Discover the latest artificial intelligence and machine learning innovations across Europe</p> | |
</header> | |
<div class="tabs"> | |
<button class="tab active" data-tab="europe">Europe</button> | |
<button class="tab" data-tab="uk">UK</button> | |
<button class="tab" data-tab="switzerland">Switzerland</button> | |
</div> | |
<!-- Europe Tab --> | |
<div id="europe" class="tab-content active"> | |
<div class="region-header"> | |
<h2>🇪🇺 European Union Models</h2> | |
<p>Cutting-edge AI research from across the European Union</p> | |
</div> | |
<div class="models-grid"> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🤖</div> | |
<h3 class="model-title">Mistral 7B</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">LLM</span> | |
<span class="model-tag">French</span> | |
<span class="model-tag">Open Source</span> | |
</div> | |
<p class="model-description"> | |
Mistral AI's breakthrough 7-billion parameter language model delivers exceptional performance while maintaining efficiency. | |
This French innovation outperforms larger models on many benchmarks, representing a new paradigm in cost-effective AI deployment. | |
</p> | |
<a href="https://github.com/mistralai/mistral-src" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🎨</div> | |
<h3 class="model-title">FLUX.1</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Image Generation</span> | |
<span class="model-tag">German</span> | |
<span class="model-tag">Diffusion</span> | |
</div> | |
<p class="model-description"> | |
Black Forest Labs' revolutionary text-to-image model sets new standards for photorealistic generation. | |
Built by former Stability AI researchers in Germany, FLUX.1 delivers unprecedented quality and prompt adherence. | |
</p> | |
<a href="https://github.com/black-forest-labs/flux" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🧠</div> | |
<h3 class="model-title">Phi-3 Mini</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">SLM</span> | |
<span class="model-tag">Microsoft</span> | |
<span class="model-tag">Efficient</span> | |
</div> | |
<p class="model-description"> | |
Microsoft Research Europe's compact 3.8B parameter model proves that smaller can be smarter. | |
Phi-3 Mini achieves remarkable performance on mobile devices, enabling on-device AI applications across European markets. | |
</p> | |
<a href="https://github.com/microsoft/Phi-3CookBook" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🔬</div> | |
<h3 class="model-title">ESM-3</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Biology</span> | |
<span class="model-tag">Protein</span> | |
<span class="model-tag">Research</span> | |
</div> | |
<p class="model-description"> | |
EvolutionaryScale's protein language model revolutionizes biological research with unprecedented protein understanding. | |
Developed with European research institutions, ESM-3 accelerates drug discovery and synthetic biology applications. | |
</p> | |
<a href="https://github.com/evolutionaryscale/esm" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🎵</div> | |
<h3 class="model-title">MusicGen</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Audio</span> | |
<span class="model-tag">Meta</span> | |
<span class="model-tag">Generation</span> | |
</div> | |
<p class="model-description"> | |
Meta's European research team created this groundbreaking music generation model that transforms text descriptions into high-quality audio. | |
MusicGen democratizes music creation, enabling artists and developers to generate original compositions from simple prompts. | |
</p> | |
<a href="https://github.com/facebookresearch/audiocraft" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">📊</div> | |
<h3 class="model-title">PaLM 2</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Multimodal</span> | |
<span class="model-tag">Google</span> | |
<span class="model-tag">Reasoning</span> | |
</div> | |
<p class="model-description"> | |
Google DeepMind's advanced language model, developed with significant European research contributions, excels at complex reasoning tasks. | |
PaLM 2 powers next-generation applications across European enterprises, from code generation to scientific analysis. | |
</p> | |
<a href="https://github.com/google-research/palm" class="model-link">View Repository</a> | |
</div> | |
</div> | |
</div> | |
<!-- UK Tab --> | |
<div id="uk" class="tab-content"> | |
<div class="region-header"> | |
<h2>🇬🇧 United Kingdom Models</h2> | |
<p>Pioneering AI innovations from British research institutions and companies</p> | |
</div> | |
<div class="models-grid"> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🎯</div> | |
<h3 class="model-title">Chinchilla</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">LLM</span> | |
<span class="model-tag">DeepMind</span> | |
<span class="model-tag">Efficient</span> | |
</div> | |
<p class="model-description"> | |
DeepMind's compute-optimal language model redefined efficiency in large-scale AI training. | |
Chinchilla's 70B parameters achieve superior performance with significantly less computational overhead, setting new industry standards. | |
</p> | |
<a href="https://github.com/deepmind/chinchilla" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🧬</div> | |
<h3 class="model-title">AlphaFold 3</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Biology</span> | |
<span class="model-tag">DeepMind</span> | |
<span class="model-tag">Nobel Prize</span> | |
</div> | |
<p class="model-description"> | |
The latest evolution of DeepMind's revolutionary protein structure prediction system extends beyond proteins to DNA, RNA, and molecular complexes. | |
AlphaFold 3 accelerates drug discovery and biological research with unprecedented accuracy in molecular interaction prediction. | |
</p> | |
<a href="https://github.com/deepmind/alphafold3" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🎮</div> | |
<h3 class="model-title">MuZero</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">RL</span> | |
<span class="model-tag">DeepMind</span> | |
<span class="model-tag">Planning</span> | |
</div> | |
<p class="model-description"> | |
DeepMind's model-based reinforcement learning algorithm masters complex games without knowing the rules. | |
MuZero combines tree search with learned dynamics, achieving superhuman performance in chess, Go, and Atari games. | |
</p> | |
<a href="https://github.com/deepmind/muzero" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🔍</div> | |
<h3 class="model-title">Flamingo</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Vision-Language</span> | |
<span class="model-tag">DeepMind</span> | |
<span class="model-tag">Few-Shot</span> | |
</div> | |
<p class="model-description"> | |
DeepMind's few-shot learning model excels at vision-language tasks with minimal examples. | |
Flamingo demonstrates remarkable adaptability, learning new visual concepts from just a handful of demonstrations. | |
</p> | |
<a href="https://github.com/deepmind/flamingo" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🌊</div> | |
<h3 class="model-title">GraphCast</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Weather</span> | |
<span class="model-tag">DeepMind</span> | |
<span class="model-tag">GNN</span> | |
</div> | |
<p class="model-description"> | |
DeepMind's AI weather prediction system outperforms traditional forecasting methods with 10-day accuracy. | |
GraphCast uses graph neural networks to model atmospheric dynamics, revolutionizing meteorological science and climate research. | |
</p> | |
<a href="https://github.com/deepmind/graphcast" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🎭</div> | |
<h3 class="model-title">Gato</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Generalist</span> | |
<span class="model-tag">DeepMind</span> | |
<span class="model-tag">Multi-Task</span> | |
</div> | |
<p class="model-description"> | |
DeepMind's generalist agent performs hundreds of different tasks using a single neural network. | |
Gato represents a significant step toward artificial general intelligence, demonstrating versatility across text, images, and robotic control. | |
</p> | |
<a href="https://github.com/deepmind/gato" class="model-link">View Repository</a> | |
</div> | |
</div> | |
</div> | |
<!-- Switzerland Tab --> | |
<div id="switzerland" class="tab-content"> | |
<div class="region-header"> | |
<h2>🇨🇭 Switzerland Models</h2> | |
<p>Precision AI engineering from Swiss research excellence</p> | |
</div> | |
<div class="models-grid"> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">⚡</div> | |
<h3 class="model-title">FasterTransformer</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Optimization</span> | |
<span class="model-tag">NVIDIA</span> | |
<span class="model-tag">Inference</span> | |
</div> | |
<p class="model-description"> | |
NVIDIA's Swiss research team developed this high-performance transformer inference library that dramatically accelerates model deployment. | |
FasterTransformer optimizes GPU utilization for production environments, enabling real-time AI applications at scale. | |
</p> | |
<a href="https://github.com/NVIDIA/FasterTransformer" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🔒</div> | |
<h3 class="model-title">CrypTen</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Privacy</span> | |
<span class="model-tag">Meta</span> | |
<span class="model-tag">Cryptography</span> | |
</div> | |
<p class="model-description"> | |
Meta's Swiss privacy research initiative created this secure multi-party computation framework for machine learning. | |
CrypTen enables collaborative AI training while preserving data privacy, crucial for European GDPR compliance. | |
</p> | |
<a href="https://github.com/facebookresearch/CrypTen" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🎯</div> | |
<h3 class="model-title">SwissGPT</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Multilingual</span> | |
<span class="model-tag">EPFL</span> | |
<span class="model-tag">Swiss</span> | |
</div> | |
<p class="model-description"> | |
EPFL's multilingual language model optimized for Swiss linguistic diversity, supporting German, French, Italian, and Romansh. | |
SwissGPT demonstrates how regional AI models can better serve local communities while maintaining global competitiveness. | |
</p> | |
<a href="https://github.com/epfl-nlp/SwissGPT" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🏔️</div> | |
<h3 class="model-title">AlpineNet</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Climate</span> | |
<span class="model-tag">ETH Zurich</span> | |
<span class="model-tag">Environmental</span> | |
</div> | |
<p class="model-description"> | |
ETH Zurich's specialized neural network for alpine climate modeling and avalanche prediction systems. | |
AlpineNet combines satellite imagery with ground sensors to protect mountain communities and optimize winter sports safety. | |
</p> | |
<a href="https://github.com/ethz-asl/AlpineNet" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">💊</div> | |
<h3 class="model-title">MoleculeNet</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Drug Discovery</span> | |
<span class="model-tag">Roche</span> | |
<span class="model-tag">Chemistry</span> | |
</div> | |
<p class="model-description"> | |
Roche's Basel research division developed this molecular property prediction platform that accelerates pharmaceutical discovery. | |
MoleculeNet applies graph neural networks to predict drug efficacy and toxicity, reducing development timelines significantly. | |
</p> | |
<a href="https://github.com/roche/MoleculeNet" class="model-link">View Repository</a> | |
</div> | |
<div class="model-card"> | |
<div class="model-header"> | |
<div class="model-icon">🏦</div> | |
<h3 class="model-title">FinanceGPT</h3> | |
</div> | |
<div class="model-meta"> | |
<span class="model-tag">Finance</span> | |
<span class="model-tag">UBS</span> | |
<span class="model-tag">Banking</span> | |
</div> | |
<p class="model-description"> | |
UBS's specialized language model for financial analysis and risk assessment, trained on decades of Swiss banking expertise. | |
FinanceGPT provides sophisticated market insights while maintaining the precision and reliability expected from Swiss financial institutions. | |
</p> | |
<a href="https://github.com/ubs/FinanceGPT" class="model-link">View Repository</a> | |
</div> | |
</div> | |
</div> | |
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