Saturday, October 10, 2015

Accelerated Learning: 20 hours vs 10000 hours

Accelerated Learning: How To Get Good at Anything in 20 Hours - YouTube

No need for 10000 hours (that is a full time job for 5 years!).
That is needed for an expert level performance. Promoted by book Outliers, it could be misunderstood since most people don't need to be experts to start becoming successful. This book suggest that even 20 hours may be sufficient to make a start learning something, A good way how to do this:
  1. Clearly decide what you want
    very specific goal, "target performance level"
  2. "Deconstruct" the skill: find specific small enough sub-skills,
    Practice them one at the time, most important skills first;
    same applies for both cognitive and motor skills, while practice may be different;
    important to practice before going to sleep for "consolidation";
    "imaginary" practice reinforces skills only when combined with real practice
  3. Learn enough to self-correct: research the skill just enough
    to be able to deconstruct and find most important sub-skill
    but not so much that it becomes a barrier for practice
    Skim a few books, DVDs, courses
  4. Remove barriers for practice; make it easy to practice what you want and not get distracted; instead of lot of willpower forcing change, alter the environment 
  5. Practice at least 20 hours, to make sure you push-trough early frustration,
    and do what you really want to do by investing enough time to start well.
    Mind is not accurate in estimating time; 20 hours is 2x20 minutes a day for a month
The barriers are not intellectual, most people are smart enough, the barriers are emotional. 

The First 20 Hours: How to Learn Anything . . . Fast!: Josh Kaufman: 9781591845553: Books

IPv4 Addresses: no more available?

most enterprises and cloud providers are still using IPv4
but mobile and IoT is moving to IPv6

No More IPv4 with Ed Horley @ RunAs Radio

America runs out of IPv4 Addresses as IPv6 Usage Rises @ InfoQ

xkcd: Map of the Internet
Map of the Internet

IoT: Semantic Sensors

Semantic Sensors « Pete Warden's blog
"tiny, cheap, all-in-one modules that capture raw noisy data from the real world, have built-in AI for analysis, and only output a few high-level signals."