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myHerb Academy: Student Prospectus & Handbook
Balancing the Algorithm with the Ecosystem
1. Welcome from the Director
Welcome to myHerb Academy.
We stand at a dual frontier. As the world rushes toward Artificial Intelligence, we face a paradox: the technologies promising to solve our climate crisis are themselves consuming unprecedented amounts of energy. Training a single large language model can emit as much carbon as five cars in their lifetimes.
You are here because you refuse to choose between technological advancement and planetary survival.
At myHerb Academy, we are defining the field of Algorithmic Ecology. We train engineers who can build smart grids, optimize neural networks for low-power devices, and design infrastructure that regenerates rather than depletes.
This document serves as your guide to our cutting-edge curriculum, covering everything from Green AI to Carbon Capture.
Aaron Levin Director, myHerb Academy
2. Our Philosophy & Mission
The AI-Climate Nexus
We believe that AI is a tool, not a savior. Its impact depends entirely on how it is architected. Our mission tackles the environmental impact of the "Fourth Industrial Revolution" on two fronts:
Intelligent Decarbonization: Using AI to optimize renewable energy grids, predict weather patterns for solar/wind, and accelerate material science discovery.
Sustainable Intelligence: Redefining how we build AI—prioritizing "Small Models," sparse computing, and energy-efficient inference over brute-force scaling.
Our Core Pillars
Biomimicry: We look to nature's 3.8 billion years of R&D. How does a forest distribute resources? How does a brain compute on 20 watts? We code with these efficiencies in mind.
Radical Transparency: We demand auditability in AI models regarding their energy and water consumption footprints.
Circular Innovation: Tech must be designed for indefinite loops of reuse, repair, and remanufacturing.
3. Academic Curriculum: The Impact Tracks
Our curriculum integrates the latest trends in tech and sustainability.
Track I: The Intelligent Grid & Renewables
Focus: Smart Grids, Green Hydrogen, and AI Optimization
Module 101: AI-Driven Grid Management: Using machine learning to predict demand spikes and balance intermittent loads from solar and wind sources.
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Module 102: Beyond Lithium: Exploring Green Hydrogen, Sodium-ion batteries, and Kinetic Storage systems.
Module 103: Carbon Capture & Storage (CCS): The physics and chemistry of direct air capture technology and mineralization.
Track II: Sustainable AI & Computing
Focus: Green AI, TinyML, and Hardware Efficiency
Module 201: The Cost of Compute: Quantizing Large Language Models (LLMs) and training "Small Language Models" (SLMs) for edge devices.
Module 202: Green Cloud Architecture: Carbon-aware computing that shifts workloads to regions with excess renewable energy in real-time.
Module 203: TinyML & Edge Computing: Running complex inference on microcontrollers (under 1 milliwatt) to reduce data center reliance.
Track III: Bio-Futures & Circular Economy
Focus: Material Science, Policy, and Urban Mining
Module 301: Urban Mining & E-Waste: Techniques for recovering gold, cobalt, and lithium from discarded electronics to break reliance on conflict mining.
Module 302: Biomimetic Design: Engineering algorithms and cooling systems inspired by termite mounds, mycelium networks, and neural biology.
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Module 303: Digital Passport Policies: Understanding the EU Digital Product Passport and tracking supply chain carbon via blockchain.
4. The Innovation Labs
Students apply theory in our state-of-the-art facilities:
The "Heat-Reuse" Data Hall: An AI training cluster where 98% of waste heat is captured and diverted to warm our campus algae-biofuel ponds.
The Urban Mine: A robotics lab where computer vision systems (trained by students) automate the disassembly of smartphones for recycling.
The Living Wall Interface: A sensor-laden vertical garden that uses plant-microbial fuel cells to power low-energy IoT sensors.
5. Code of Ethics
As a student and future engineer of myHerb Academy, you agree to:
Model Minimalism: We do not use a cannon to kill a mosquito. We do not use Deep Learning when a linear regression will suffice.
Bias & Impact: We acknowledge that energy-intensive AI often disproportionately affects marginalized communities living near data centers and power plants.
Open Science: We contribute to open source Green AI libraries to democratize access to efficient technology.
6. Our Campus Sustainability
We practice what we teach:
Carbon-Negative Operations: We generate more energy than we use, feeding the excess back into the local municipal grid.
Water-Neutral Cooling: We utilize closed-loop rainwater harvesting for our server cooling, rejecting potable water usage for industrial purposes.
7. Next Steps
Enrollment Dates
Spring Cohort: Applications close January 15th.
Autumn Cohort: Applications close August 15th.
Tuition & Grants
We offer the "Algorithmic Stewardship Grant" for students developing open-source tools that measure and reduce software carbon footprints.
Code for the planet. Compile a better future.
Contact Admissions:
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