Drishtant Ghosh (Drix10)
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AI Education••8 min read•1479 words

🤖 AI & Healthcare - Model-Agnostic Infrastructure

⚡Direct Technical Summary

Healthcare AI models change every 6 months, while clinical validation takes 2-3 years. By the time a study publishes, the AI it evaluated no longer exists. Hospital systems need mo

🤖 AI & Healthcare - Model-Agnostic Infrastructure

Healthcare AI models change every 6 months, while clinical validation takes 2-3 years. By the time a study publishes, the AI it evaluated no longer exists. Hospital systems need model-agnostic infrastructure that outlasts the model cycle.

Key Points:

  • Model-Agnostic Infrastructure: This infrastructure should be designed to adapt to changing AI models, ensuring that the system remains effective and efficient despite model updates.

  • Clinical Validation: Clinical validation is a critical step in ensuring the accuracy and reliability of AI models in healthcare. However, the current process is slow and inefficient, leading to a gap between model development and deployment.

  • Infrastructure Design: The design of model-agnostic infrastructure should prioritize flexibility, scalability, and maintainability, allowing it to adapt to changing AI models and clinical validation processes.

🔗 Resources:

🚀 AI Governance - Autonomous Agents

Meta's autonomous agent beat 99% of Kaggle data scientists. Meanwhile, Spain recorded the first AI agent data breach. Capability without governance = liability. At @ibaboronat we built Agentic OS for this: RBAC, audit trails, full source code. You own the stack.

Key Points:

  • Autonomous Agents: Autonomous agents are AI systems that can operate independently, making decisions and taking actions without human intervention. However, this capability also raises concerns about liability and governance.

  • Data Breach: The recent data breach in Spain highlights the risks associated with autonomous agents, emphasizing the need for robust governance and security measures.

  • Agentic OS: Agentic OS is a platform designed to provide governance and security for autonomous agents, ensuring that they operate within established boundaries and protocols.

🔗 Resources:

🚀 AI Education - Donations and Robotics Kits

As part of our AI literacy initiative, @nvidia and StudyFetch donated 1,500 StudyFetch licenses to students in Ashe County, North Carolina, along with 100 robotics kits powered by NVIDIA Jetson Nano. They also received a visit from @FLOTUS who surprised them with the news.

Key Points:

  • AI Literacy Initiative: The AI literacy initiative aims to promote education and awareness about AI, providing students with access to resources and tools to learn about AI.

  • Donations and Robotics Kits: The donations and robotics kits provided to students in Ashe County, North Carolina, are part of the initiative, aiming to inspire and educate the next generation of AI professionals.

  • Visit from @FLOTUS: The visit from @FLOTUS highlights the importance of AI education and the need for continued support and investment in this area.

🔗 Resources:

📚 Book Summary - The Art of Learning

“Growth comes at the point of resistance. We learn by pushing ourselves and finding what really lies at the outer reaches of our abilities.” ~Josh Waitzkin Book Summary: The Art of Learning load in 4k light & dark

Key Points:

  • The Art of Learning: The book "The Art of Learning" by Josh Waitzkin emphasizes the importance of learning and growth, highlighting the need to push oneself beyond comfort zones.

  • Growth and Resistance: The book suggests that growth and learning occur at the point of resistance, where one is forced to confront and overcome challenges.

  • Learning and Abilities: The book emphasizes the importance of finding what really lies at the outer reaches of one's abilities, highlighting the need for continuous learning and self-improvement.

🔗 Resources:

🚀 Kami On Tour

Kami On Tour kicks off this weekend! Find our Kami Crew at Booth 48 at ALET, and see where we're headed next on the full schedule: https:// hubs.la/Q04xMLlf0

Key Points:

  • Kami On Tour: Kami On Tour is an event where the Kami Crew will be showcasing their products and services, highlighting the latest developments and innovations in the field.

  • Booth 48 at ALET: The event will take place at Booth 48 at ALET, providing attendees with a unique opportunity to learn about Kami's offerings and engage with the team.

  • Full Schedule: The full schedule for Kami On Tour can be found on the official website, providing attendees with a comprehensive overview of the event and its activities.

🔗 Resources:

🚨 AI Governance - Autonomous Agents Data Breach

Spain just reported the world's FIRST data breach executed by an autonomous AI agent. Not a human with AI tools. An agent acting alone — accessing and exposing personal data. Now imagine this in healthcare, where AI agents handle PHI daily. The governance gap is years wide.

Key Points:

  • Autonomous Agents Data Breach: The recent data breach in Spain highlights the risks associated with autonomous agents, emphasizing the need for robust governance and security measures.

  • AI Agents and PHI: The breach highlights the potential risks of AI agents handling sensitive personal health information (PHI), emphasizing the need for strict governance and security protocols.

  • Governance Gap: The governance gap in AI is years wide, highlighting the need for continued investment and innovation in AI governance and security.

🔗 Resources:

🤖 Neural-ODE Framework

A new Neural-ODE framework just cracked one of holography's hardest inverse problems: reconstructing the full spacetime geometry of a charged AdS black hole directly from boundary fermionic spectra. The network doesn’t just fit the data—it enforces physical laws (AdS asymptotics, holographic principle).

Key Points:

  • Neural-ODE Framework: The Neural-ODE framework is a new approach to solving complex inverse problems in holography, using neural networks to reconstruct the spacetime geometry of charged AdS black holes.

  • Inverse Problems: The framework addresses one of the hardest inverse problems in holography, reconstructing the full spacetime geometry from boundary fermionic spectra.

  • Physical Laws: The network enforces physical laws, such as AdS asymptotics and the holographic principle, ensuring that the solution is consistent with established theories.

🔗 Resources:

🤖 Multi-Model Orchestration

Computer’s goal is maximum intelligence at minimum cost through multi-model orchestration. We’ll continue optimizing the model-agnostic harness and refining the orchestrator and subagent combinations behind each effort level as frontier models advance.

Key Points:

  • Multi-Model Orchestration: The goal of multi-model orchestration is to achieve maximum intelligence at minimum cost, using a combination of models and subagents to optimize performance.

  • Model-Agnostic Harness: The model-agnostic harness is a key component of multi-model orchestration, allowing for the integration of multiple models and subagents.

  • Orchestrator and Subagent Combinations: The orchestrator and subagent combinations are critical to the success of multi-model orchestration, requiring careful optimization and refinement.

🔗 Resources:

🚀 Decentralized Knowledge Graph

Decentralized Knowledge Graph v10 has evolved: Sovereign AI | └ Sovereign Context Infra | └ Verifiable Memory | └ Shared Working Memory | └ Working Memory | └ Sovereign Reasoning Infra ██▒▒▒ 40%

Key Points:

  • Decentralized Knowledge Graph: The Decentralized Knowledge Graph is a decentralized system for storing and managing knowledge, using a combination of sovereign AI, context infrastructure, and verifiable memory.

  • Sovereign AI: The sovereign AI component is a key part of the Decentralized Knowledge Graph, providing a decentralized and autonomous approach to AI.

  • Verifiable Memory: The verifiable memory component ensures that the knowledge stored in the graph is accurate and trustworthy.

🔗 Resources:

📚 Synonym - Desire

https:// thsr.us/desire If someone has a "desire", they strongly want something. E.g. "She had a strong desire to be with the person she loved." #synonym #thesaurus #learnenglish #ielts

Key Points:

  • Desire: The word "desire" means to strongly want something, emphasizing the intensity of the feeling.

  • Synonym: The word "desire" has several synonyms, including "longing", "yearning", and "craving".

  • Example: The example sentence "She had a strong desire to be with the person she loved" illustrates the use of the word "desire" in context.

🔗 Resources:

📂Source / Implementation:AI Education / resources-250.md
GitHub Repository↗

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Drishtant Ghosh (Drix10)
Drishtant Ghosh (Drix10)•Author & Engineer

Technical founder and engineer working across AI systems, developer infrastructure, and cybersecurity.

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GitHub: AI Education/resources-250.md ↗https://blogs.drix10.com/articles/ai-education/ai-healthcare-model-agnostic-infrastructure-250