A quick and easy way to figure out if your startup is solving the problem that really matters. Just update a Google Sheet.
“Fall in love with the problem not the solution, and the rest will follow.” That’s the advice from Uri Levine just before he sold his startup Waze to Google for $1.1 billion.
Is your startup building a solution looking for problem? How do you know that you’re solving the right problem?
The coronavirus pandemic is rapidly evolving. I believe that we all have the desire to contribute and help others but there is no easy way to find, sort and take advantage of all the amazing and resourceful people that are willing to help devote their time and energy to dampening this crisis.
To help people find the resources and relief that they need I’ve created a real-time Google sheet where you can find the latest resources, by category and by geography.
Here you will find everything including free mental health chat services, pro-bono legal and financial counseling, first-come/first-serve…
A crowdsourced book project powered by people and robots.
Today I’m announcing a new project where we will be writing a book about the future of work.
This will be a story where people from all walks of life get to tell their versions of what they think the future of work will be for them.
Hopes, fears, ideas and inspirations.
From the autoworkers whose jobs are dwindling due to automation to the accountant where software is literally crunching-out their world to freelancer tasks being increasingly mimicked by AI.
Imagine that you are a programmer with a brilliant idea for the next tech unicorn. Perhaps you’re trying to build the next great startup that no one else has thought of. You have even coded-up a proof-of-concept but then realize that you are in over your head. There are bugs, you’re pressed for time since this is just a side-gig, you’re flying solo and you’re frustrated with asking question after question on coding forums.
I started with Github, a free web platform for uploading, sharing and collaboratively working on open-source code — but it was tedious at first to gain…
W e just launched AlgoHive, an open-source project to crowdsource the prediction of cryptocurrency prices and automate crypto trading.
We are now sharing our vision towards where our project is headed. In short we’d like to make our group learnings and breakthroughs more accessible, transparent and easier to contribute.
To that end I have laid out a plan that accomplishes the above while providing a lot more structure to our efforts. AlgoHive is a free open-source community and will always be as far as I am concerned.
To that end I have been approached by several people in the AI…
Imagine living on an island that is not only advancing the adoption of cryptocurrency and blockchain technology, but is actually pumping millions of dollars into seeing this nascent industry prosper.
Welcome to Taiwan, a nation state in Asia that will soon be the crypto capital of the world.
Serious about innovation, Taiwan is a hotbed for tech startups focusing on blockchain, AI and IoT. There is now a proliferation of major startup accelerators and incubators that are making this a reality. …
What best predicts whether the price of Bitcoin will go up or down? What if there was an algorithm that could predict this at least a day in advance? This is what we’re building at the AlgoHive project and will be sharing how step-by-step.
Just a quick refresher this project began with my initial post on how I created a Bitcoin prediction algorithm that produces a 29% positive return:
W e now live in a world where the most valuable assets are no longer physical. While virtual assets have been in existence for years it’s only recently that these digital goods have emerged as a new asset class.
Now with the combination of blockchain technology virtual assets have the opportunity to no longer be limited to traditional use cases such as gaming.
In today’s sharing economy as more assets, both physical and virtual are tokenized a new kind of protocol is necessary to ensure security, transparency, ownership, liquidity and shared use.
TL;DR: This is the second article in my series on how I created an algorithm to predict the price of Bitcoin. In this article I am sharing all of my lessons learned and proposing a novel approach.
In my last article I created an algorithm that predicts the Bitcoin (BTC) price with a 29% investment return rate over 90 days. I shared that although I was initially impressed with my basic formula, I would not be satisfied until I was able to consistently repeat this performance over a longer period of time.
The simple formula uses a combination of price…