The BepiColombo mission launched in October 2018 will enter orbit around Mercury on December 5, 2025. Here’s an incredible animation of its 9 gravity assists past Earth (once), Venus (twice) and Mercury (six times).Read More
This wonderful illustration from July 2019 National Geographic explains one of Elon Musk’s greatest space innovations – rocket reuse.Continue reading “SpaceX Falcon 9: How Elon Musk’s Rocket Is Winning the Reusability Race” Read More
This mapped graphical visualization of six Swainson’s Hawks from Data is Beautiful caught my attention.Read More
What I learned from my Uber data
I save $703/month using Uber versus owning 2 cars (🚙🏎). I’ve spent $12,041 on 686 Ubers over 6 years. By comparison, car ownership cost $11,783 per year, most of it depreciation. What could $703/month buy you? Well, four years of $703/month and you’ll save enough to climb Mount Everest 🏔 unguided. Or you could buy a shiny new laptop every 3 months. More details below. Continue reading “In-depth– Spend analysis of 6 years 686 rides and $12,041 spent on Uber”Read More
Photo credit National Geographic Magazine, November 2016.
Earlier this week I blogged about 5 simple questions you can ask to determine AI hype.
Today I saw something with more hype than I would expect from a respected tech company. “eBay determines this price through a machine learned model of the product’s sales prices within the last 90 days.”
In my opinion this price prediction is not machine learning. It’s just math. It’s not a machine learned anything. It fails 1-5 of Stephen’s tests.
As Machine Learning captures our imagination, it’s important to separate the material from the hype. Here are 5 simple questions you should ask to help reduce AI hype:
- “How much training data is required?”
- “Can this work unsupervised (= without labelling the examples)?”
- “Can the system predict out of vocabulary names?” (i.e. Imagine if I said “My friend Rudinyard was mean to me” – many AI systems would never be able to answer “Who was mean to me?” as Rudinyard is out of its vocabulary)
- “How much does the accuracy fall as the input story gets longer?”
- “How stable is the model’s performance over time?”
source: Stephen Merity of SalesforceRead More
Skip to 3:01 to learn how the automobile differential allows a vehicle to turn a corner while keeping the wheels from skidding. It’s a brilliant product break-down using language and concepts to conceptualize the product features into something that everyone understands and wants to buy.Read More