Multiverse AI Launches Breakthrough Miniature High-Performance Models
A pioneering European AI startup has unveiled groundbreaking micro-sized AI models named after avian and insect brains, demonstrating that powerful artificial intelligence doesn't require massive scale.
Multiverse Computing's innovation centers on ultra-compact yet capable models designed specifically for edge computing applications. Dubbed "ChickBrain" (3.2 billion parameters) and "SuperFly" (94 million parameters), these miniature neural networks represent a significant leap forward in efficient AI deployment.
"Our compression technology allows these models to operate directly on personal devices," explained founder Román Orús in an exclusive TechCrunch interview. "Imagine having conversational AI capabilities running natively on your smartwatch without cloud dependency."
The Spanish quantum computing specialist firm has attracted substantial investment, securing €189 million this June alone. Their proprietary "CompactifAI" technology leverages quantum-inspired algorithms to dramatically reduce model sizes while maintaining - and in some cases improving - performance metrics.
Notably, ChickBrain demonstrates superior performance to its source model (Meta's Llama 3.1 8B) across multiple benchmarks including mathematical reasoning (GSM8K, Math 500) and general knowledge assessment (GPQA Diamond). Meanwhile, SuperFly's insect-scale footprint enables voice interface capabilities for IoT appliances using minimal processing power.
The company collaborates with major tech manufacturers and offers flexible deployment options:
- Direct integration into consumer electronics
- AWS-hosted API services with competitive pricing
- Specialized compression for existing ML implementations
Multiverse's client roster includes chemical giant BASF, financial services provider Ally, and industrial leader Bosch, demonstrating the technology's cross-industry applicability.

Comparative performance metrics show ChickBrain outperforming its source model across multiple cognition benchmarks
This breakthrough in model efficiency arrives as the tech industry increasingly prioritizes on-device processing advantages including privacy preservation, latency reduction, and offline functionality.
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Comments (2)
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Interesting concept! I'm curious how these tiny models compare to larger ones in real-world tasks. Are they really as efficient as claimed? 🤔
A pioneering European AI startup has unveiled groundbreaking micro-sized AI models named after avian and insect brains, demonstrating that powerful artificial intelligence doesn't require massive scale.
Multiverse Computing's innovation centers on ultra-compact yet capable models designed specifically for edge computing applications. Dubbed "ChickBrain" (3.2 billion parameters) and "SuperFly" (94 million parameters), these miniature neural networks represent a significant leap forward in efficient AI deployment.
"Our compression technology allows these models to operate directly on personal devices," explained founder Román Orús in an exclusive TechCrunch interview. "Imagine having conversational AI capabilities running natively on your smartwatch without cloud dependency."
The Spanish quantum computing specialist firm has attracted substantial investment, securing €189 million this June alone. Their proprietary "CompactifAI" technology leverages quantum-inspired algorithms to dramatically reduce model sizes while maintaining - and in some cases improving - performance metrics.
Notably, ChickBrain demonstrates superior performance to its source model (Meta's Llama 3.1 8B) across multiple benchmarks including mathematical reasoning (GSM8K, Math 500) and general knowledge assessment (GPQA Diamond). Meanwhile, SuperFly's insect-scale footprint enables voice interface capabilities for IoT appliances using minimal processing power.
The company collaborates with major tech manufacturers and offers flexible deployment options:
- Direct integration into consumer electronics
- AWS-hosted API services with competitive pricing
- Specialized compression for existing ML implementations
Multiverse's client roster includes chemical giant BASF, financial services provider Ally, and industrial leader Bosch, demonstrating the technology's cross-industry applicability.

This breakthrough in model efficiency arrives as the tech industry increasingly prioritizes on-device processing advantages including privacy preservation, latency reduction, and offline functionality.
Base44 Unveils Proprietary AI Model to Bolster Defensibility in Vibe Coding Platform
Base44, the vibe coding platform acquired by Wix for $80 million just a year ago — when it was merely six months old with a team of eight — has begun deploying its proprietary AI model to help users build applications using natural language.This deve
Multiverse Computing Launches Free Compressed Generative AI Model
Large language models face a significant challenge: their immense size. Spanish startup Multiverse Computing is tackling this problem by creating compressed models designed to bridge the gap between the capabilities of cutting-edge AI and what busine
Secret Tracking Data Exposes Theft of AI Models
A new method can invisibly watermark models like ChatGPT in seconds without retraining, leaving no trace in standard outputs and resisting all practical removal attempts. The key distinction between watermarking and 'copyright-baiting' is that waterm
Interesting concept! I'm curious how these tiny models compare to larger ones in real-world tasks. Are they really as efficient as claimed? 🤔





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