The Artificial Superintelligence (ASI) Alliance, a collaborative organization focused on advancing decentralized artificial intelligence development, has launched Cortex, a decentralized AI model designed to address industry challenges.
Cortex marks the first model launched under the “ASI: Train initiative,” which is focused on creating domain-specific AI solutions for industries like robotics, biotechnology and healthcare.
Unlike general-purpose AI models, Cortex is designed for precision, scalability and adaptability to meet the specific needs of various industries. It focuses on tasks requiring advanced, context-aware problem-solving.
Humayun Sheikh, CEO of Fetch.ai and chairman of the ASI Alliance, told Cointelegraph that this development could reduce the reliance on centralized AI solutions, allowing entities to “train, own and build solutions with decentralized AI-trained models.”
Related: SingularityNET, ASI alliance launch self-learning proto-AGI in Minecraft
Addressing industry-specific needs
Cortex is designed to provide an alternative to current general-purpose AI models, offering high relevance in manufacturing, autonomous delivery and data-driven research.
Sheikh told Cointelegraph that the robotics industry is a “very interesting area at the moment,” adding that the alliance has “several partners who are willing and able to use the Cortex model for inferences.”
“Bio-technology, healthcare, gig economy and research. All these areas require data coming from various research organizations which could, in a combined way, result in step changes in discovery and utilization.”
Related: AI will save us all, but only if it’s decentralized — SingularityNET CEO
Decentralized approach to AI ownership
Cortex will use a decentralized framework to encourage collaboration across various industries and organizations, employing governance-based models to provide an alternative to centralized AI solutions.
The decentralized structure it offers aims to distribute the benefits of AI development more equitably to ensure concentrations of power for AI development do not accumulate and restrict free innovation for developers.
By addressing the limitations of centralized AI systems, this first launch of the ASI: Train initiative could offer specific industries a more inclusive option for collaborative AI development tailored to their specific needs.
Related: Fetch.ai, Imperial College partner to launch AI lab
Self-learning proto-AGI on Minecraft
The ASI Alliance recently launched the first self-learning proto-AGI within Minecraft in coalition with SingulatirtyNET, a decentralized AI network.
The new proto-AGI, dubbed Autonomous Intelligent Reinforcement Inferred Symbolism (AIRIS), could boost the development potential for artificial general intelligence (AGI).
Deploying the new AI technology in Minecraft allows the coalition to witness the capabilities of the proto-AGI as it learns and adapts autonomously, broadening the potential for AI in robotics, automation and smart systems designed to solve real-time problems.
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