HOP - DML
Health Oracle Protocol (HOP) founding mission was to find a way to allow decentralized machine learning or machine learning peer to peer. The first usecase was performing sport science on swimmers usin competition and training times. From this data the following question was posed: Can an AI produce a better training programme for swimmers than a human coach?
Each swimmer had a smart stopwatch collecting time data and when wearables came along this data was added. Sure, all the data could be pushed to a database in the cloud but the goal of DML is to perform the learning peer to peer. Is this possible? If it is, it starts with sovereign data. This is the core ingredients of machine learning. For a peer to peer network, at least two peers are required to be connected with permissionless access to join. The goal is to learn continuously, when an improvement is verified then all can be notified. There is no demand to collected all data from day one. Learn from the data available and like a baby becoming a toddler to child to an adult; be patient and allow learning and intelligence to emerge with time. Allow a range of learning techniques to be included, a besearch cycle that will conclude for each peer and network of peers if a better AI has been established. Be open ended; give the learning space to explore new techniques, take leaps of faith in new directions. Not all the time but enough to explore new search spaces, concepts, ideas and computational techniques. Be mindful that intelligence at all scales will be need. Tiny bottom up or top down, give enough information for self organization. Lastly, be mindful that this approach needs to be continuously assessed for risks of an AI taking its own path; act like an oracle responding to human.
continuous
Rich Sutton, Toward a better Deep Learning
Artificial intelligence needs better deep learning methods because current algorithms fail in continual learning settings, losing plasticity, forgetting cata…
https://youtu.be/YLiXgPhb8cQ?si=Cug5P6lTVUyaYKvf
Grounded knowledge way to digital gaia intelligence
The Shift from Models to Compound AI Systems
The BAIR Blog
https://bair.berkeley.edu/blog/2024/02/18/compound-ai-systems/
https://youtu.be/vRTcE19M-KE?si=Tb9Y2zAIlvsWPzLG
The Shape of AI to Come! Yann LeCun at AI Action Summit 2025
The Next AI Revolution: Yann LeCun’s Vision Beyond LLMs At the AI Action Summit in Paris, Yann LeCun underscored a fundamental shift in artificial intellige…
https://youtu.be/xnFmnU0Pp-8?si=IKOk17vF_n_wjC2w
Yann LeCun “Mathematical Obstacles on the Way to Human-Level AI”
Yann LeCun, Meta, gives the AMS Josiah Willard Gibbs Lecture at the 2025 Joint Mathematics Meetings on “Mathematical Obstacles on the Way to Human-Level AI.”…
https://youtu.be/ETZfkkv6V7Y?si=MEtqd62lucMTJolR
Don’t invent faster horses - Prof. Jeff Clune
AI professor Jeff Clune ruminates on open-ended evolutionary algorithms—systems designed to generate novel and interesting outcomes forever. Drawing inspirat…
https://youtu.be/mw5WIDGRLnA?si=1lIEpYE5ZVEZq5XX
https://youtu.be/W2uauk2bFjs?si=nodVDB1qmKBXnIeD
https://youtu.be/W2uauk2bFjs?si=nodVDB1qmKBXnIeD
$No Access
LAB
LAB Introduction The LAB’s mission is to create a sovereign intelligence. This will require work to give peers their data and will demonstrate machine learning ‘that works’ on a peer to peer level. Overall, the lab provides the research on all matters small and decentralised. Agenda Intellig…
https://docs.google.com/document/d/1fF3Q2kAWylcGAgWdxrOPvUIGqMXmLN6e1xhexEbqtu8/edit?usp=sharing
Risks to this approach
Seminar with Professor Geoffrey Hinton, at the Royal Swedish Academy of Engineering Sciences (IVA)
Meet Professor Geoffrey Hinton, AI pioneer and 2024 Nobel Prize in Physics Laureate, in a panel discussion on AI development, humanity, and the future, along…
https://youtu.be/lexF-CrhOrE?si=w9zo0WhEXhQ4DAtY