As summer holidays start my kids and I kicked off a project that unfolded over the course of 6 weeks. As usual, we decided to do something wild that we have no idea how to do… yet… We decided to build AI's that we will personally train to become digital twins of ourselves.
Here is the conclusion of this amazing project:
For more information see the full blog series here:
I'VE BEEN ACQUIRED! PoLP, my collective Intelligence work has been acquired by Nolej a French AI company. I'm joining as a late Co-Founder and US CEO to lead the US team first to push our Nolej AI, A powerful AI tool that allows anyone to take any content, be it text, webpages, videos, or audio, and then autogenerate interactive learning content from it in minutes. And then to develop our Nolej Graph and Nolej protocol which together create a Collective Intelligence Engine to rapidly accelerate learning and innovation, more on that soon. I'm really excited for this adventure to continue, now together with such a super Team
Here is a recent podcast I did with Scott Meyer, founder of Ed3.gg
“Cutting edge topics and emerging fields aren’t taught in school. They move too fast. @BodoHoenen has a solution: decentralized education where every learner is a teacher.”
It's humbling to be confronted with a truth that is so self-evident and yet so far from what we know to be true. But what we KNOW and what is TRUE may not always agree.
Opportunity
Proof of learning could happen as you learn, each step you take with no added effort. All we need are learner’s learning, and teachers teaching, no middlemen.
Problem
Proof of learning is critical to getting anywhere in life. But today’s systems that prove learning are cumbersome, “One-sized-fits-all”, and inaccurate, especially over time.
We are embarking on an exciting journey with a as yet loosely connected group of innovators to Build AIs to help us learn and teach anything. Accessible through any web browser, in AR or VR. A guide to the metaverse and all human knowledge. Think VR/AR, our learning map project + AI.
Learn more here: superreality.com
Here is a video we created about our project:
Can you guess what this project is all about? You will get to know soon :)
DO YOU WANT TO JOIN ME ON A PRETTY COOL PROJECT?
I’ve been building a "Google maps" for learning using various methods, and I'd like to test out another method, This time with a clear and pretty easy-to-develop initial MVP. I'm looking for a Machine learning engineer and someone with Front end development experience, to join me and some others in this pretty fun little project, that could go far!
Here is a recent guest lecture I gave on open innovation, the Learning map, the Doing map, and how they helped my daughter fix her paralyzed arm. This is a shortened version of the lecture that covers the main points.
I've been working for several years within Open innovation, and for the last year, I've been writing a book about it. To do further research for the book I'm interviewing a whole bunch of scientists, thinkers, and innovators from around the world. We will be discussing open innovation, collective intelligence, computer science, machine learning, artificial intelligence, and practical applications of those to solve real-world challenges. Much like everything else I do, I'll be releasing these research calls openly as a podcast for anyone to watch.
I hope you will enjoy this journey of learning with me as we explore some deep rabbit holes together.
You can subscribe to this Research Podpost here:
Exploring Open Innovation with Bodo Hoenen
If we can openly share all the things we have learned, and then share all the things we can do with what we have learned, we can rapidly accelerate the good we can do in the world. This is a guest lecture I gave over zoom at the L'École LDLC University. I hope you can find some inspiration here.
I'm thinking of starting a video podcast, focusing on how to build a Super Collective Intelligence. So yea, it won't be interesting to many, but it will be for a small few
We will start from the ground up, with each episode focusing on a specific part that would be needed, which then becomes a brick on top of which future episodes would be built on. The goal here is to discuss and come out of each episode with tangible, practical ways to apply what we had discussed. As a seed, we could follow the topics presented in the book I'm writing, on the same topic (dev4x.com/project-sci), and I'm confident that the discussions will quickly lead down interesting paths.
To get this going, I'm looking for a few like-minded friends who want to join me. Each discussion will likely span 2 hours, of which an hour will be used and posted. I'll aim to have two or three guests who are specialists in the given topic for that episode. And while I do have a little funding for this project, this will likely go towards marketing and possibly video editing.
Any takers !? message me.
I'm in the process of writing a book, I was planning to spend the year writing it and releasing the first draft at the end of the year, but I decided I would release the first few chapters here as a work in progress, and use this as an opportunity to build a project around this work sooner. What I am about to share below is a draft, but it's a good start. I hope you could enjoy this: Here
This is the powerful story of how the connected world empowered my daughter to build a brain-controlled exoskeleton for her paralyzed arm.
For 25 years I’ve suffered from cluster headaches. Several years ago I found a way to stop them, which is when I originally posted this. Since then many people have read this, tried the same, and successfully stopped their headaches.
The story of how my 5-year-old daughter and I built a robotic exoskeleton for her paralyzed arm. After learning there were no treatments we could afford, and only a 2% chance of recovery, we decided to leverage Open Social Innovation to build our own solution. A year later, leveraging the collective intelligence of experts around the world we built an exoskeleton, 100X cheaper, 10X lighter, and one that enabled her motor neurons to repair themselves! Today she can move, unassisted and has recovered 60% of her strength! This is our story:
We are off to Paris to prepare for the launch of the Learning Planet assembly together with UNESCO and the CRI.
There are more than 200 million students in higher education. Most students feel disengaged from the learning process but are highly concerned about world’s biggest problems and want to act.
This is the time to involve everyone in developing sustainable solutions. This is the time for building a learning planet.
Want to learn more: https://www.learning-planet.org/
HOW To build a Google maps for learning:
There are a number of ways we can create a “Google maps” for learning, and a GPS that runs on it to guide you to any learning goal. Here I’ll describe three methods I have tried over the years, their pros and cons, and why the best results will come by combining all three methods.
The Background:
Where these insights come from
+8 years of work on this problem
+6 Prototypes and working apps
+2,000 1-on-1 in-depth youth interviews conducted in many settings, refuge camps in Africa, homes in the middle east, k12 classrooms in the US, maker spaces in India, Colledges in Japan…
+10,000 Hours of user research, experiences, successes, and failures
Key Insights from past prototypes/research
Static Maps
Young kids loved this!
High cost to design
Can only work for maps that work off known learning destinations and linear learning paths
Hybrid Maps (Static)
(Static map background, dynamic path layer)
The map’s background does not convey any useful information, and therefore quickly becomes boring.
Kids were initially excited about the map but then became really disappointed!
Hybrid Maps (Styled)
(Styled Map background, dynamic path layer)
Simple to implement and create different “themes”
There is no map feel to this, little reward for learners to explore new regions on the map
Abstract maps
Simple to implement
Quickly becomes boring
No reason to explore and discover new things
Treemaps
Good metaphor and a great way to represent past learning, but not future learning.
How we learn is not in tree-like branches, but rather a highly connected web, that quickly breaks this metaphor.
Treemaps cannot be used to explore anything but traditional linear learning paths
Learn more about this prototype here.
Lens-based maps
Easily implemented
Easily skinned to suit any learner, can use procedural generation to design maps for kids to adults
Can scale in real-time to accommodate new competencies and paths as we generate them.
Learn more about this here.
Three METHODS:
METHOD 1 - BUILDING FROM STANDARDS
An approach we can use to build the learning map is to build it from extracting nodes from standards, like the US common core standards, European educational standards, or national curricula. Here we have pretty well-defined standards we can convert into nodes. This method was tested when we were running the Moonshot Education Project, explained in this blog post: one-size-does-not-fit-all-overcoming-our-factory-education
Pros
Easy to generate maps for traditional education and domains
Easy for existing providers to leverage map
Cons
Not scalable
Does not work for non-traditional domains
Does not allow for cross-domain path generation
Method 2 - BUILDING FROM EXISTING MATERIAL
One approach we can use to build this Learning Map is to build it from deconstructing existing courses, curricula, online programs, textbooks, lectures or any other pre-packaged learning paths. In this method, we leverage the expertise of educationalists who have created courses, online learning programs, youtube videos or lectures to define not only the nodes, but also the links between them. We then use this as a “seed” to create the start of the map. Here, in this illustrated example I’ll describe this approach.
Pros
Rapidly generate maps for any domain that has existing content
The map becomes a new channel for existing content and content producers
Cons
Building an automated pipeline to deconstruct content is complex.
Method 3 - BUILDING FROM ONTOLOGIES
A third approach to building the learning map is to build it from an ontology like Wikipedia. Like building from standards, this is relatively easy as it again has well-defined structured data, however, in this approach, there are no learning paths within the ontology. Projects like the we.learn project by the CRI are leveraging this method and using learner-generated paths to augment a map built on a Wikipedia ontology.
Pros
Rapidly generate a Map of all human knowledge
This map is continually updated, and we could both leverage the Wikipedia community AND contribute to it too!
Cons
Links do not have directional information, there is no Path information.
Why we need to do all three
We need to do all three approaches in parallel so that we cover all available knowledge and educational material.
2. We need to do all three methods to get the greatest data coverage, metadata, relationship data, ML Data.
3. Why we need all three methods as its the only way we can get all required features
If you want to work on this with me reach out!
HACKAHEALTH Geneva
14th-15th April 2018
Join us at the Geneva HACKAHEALTH event where various differently-abled people will come together to develop assistive devices, then publish the work as open source so that others can do the same.
We will continue on the journey of Chiara, Lorelei, Eric and Yariv as they hack their own health
If you are a Maker, Designer, Developer or Engineer interested in learning new skills, developing some cutting-edge solutions or just having fun with like-minded hackers, join us.