Casey Neistat is an observer of the modern world (e.g. NYC bike lane obstructions), and he has sage advice about avoiding basic embellishments.
Sage from creator Casey Neistat
Author Archives: Neal Mueller
68 bits of unsolicited advice from a 68 year old co-founder of Wired
My favorite part is that Kevin teaches most readers a new word, with the last word on his list –– “Pronoia” is a neologism coined to describe a state of mind that is the opposite of paranoia..
Here are 3 of of my favs from his list:
1- Being enthusiastic is worth 25 IQ points.
2- Don’t be the best. Be the only.
3- Promptness is a sign of respect.
This list reminded me of the sunscreen song, which is also good.
Read MoreOn self-driving cars
We’re a decade from self-driving cars. When I write self-driving I mean a car that drives you around while you sleep, which is level-4 and level-5. Since I think we have 10 years until that, in the meantime let’s talk about level 1, 2 and 3 in a granular way.
Continue reading “On self-driving cars” Read MoreVideo– First year of life for six Swainson’s Hawks
This mapped graphical visualization of six Swainson’s Hawks from Data is Beautiful caught my attention.
Via reddit
Continue reading “Video– First year of life for six Swainson’s Hawks” Read MoreVideo– 3D animation of my route on Mount Everest
In-depth– Spend analysis of 6 years 686 rides and $12,041 spent on Uber
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 MoreMars mission will take 6 years roundtrip including prep
eBay Adds to Machine Learning Hype
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.
Simple questions you should ask to help reduce AI hype
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 Salesforce
Continue reading “Simple questions you should ask to help reduce AI hype”
Read MoreVideo– Excellent product description by Chevy from 1937
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.
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