Periodically I return to this blog (Thought Verbs) by Chuck Palahniuk. It’s an impressive post that discusses the power of writing, where you empower the reader to come to the same conclusion.
Rather than indicate what your subject is thinking, describe the situation so that the reader feels their exact thoughts. This is a powerful way to embrace the reader, and involve them in the story. Clearly it is effective for Chuck, as evidenced by the compelling books I’ve read of his.
I’d like to spend some time with this and apply it to some thought verbs. Not as daunting to exercise this on a dialog or small scene. Less overwhelming than coming up with an entire plot, scenario, or book design. I share it with you now because of its true power and impact on writing in general.
So on my favorite music device in the house (Sonos) I have always enjoyed a blend of music, from classic rock to the latest pop, mixed in with some classical music while I read the papers on Sunday. But interweaving it all is my love for jazz. I like SiriusXM channel 67 “Real Jazz” but it can veer off from the classic bebop to some obscure funk from time to time.
I just found my dream channel on a music service – Jazz24.org, which is a live stream of KPLU in the Seattle/Tacoma region. I’ve been listening all day, between conference calls for work, busy tasks like expenses, bills, and follow ups from said calls, and after work through making dinner and eating with my family.
I can’t get enough of this channel.
- A nice blend of traditional bebop jazz, including Horace Silver, Paul Desmond, and Billie Holiday
- Some bossa nova Jobim
- Forward-thinking Diana Krall
- Classic organ-izing from Joey deFrancisco
I’ve added it to my Sonos favorites, and am trying to figure out how to get a stream downloaded for offline listening on my Android phone.
It’s rare that I listen to a single source for so long, but this station’s focus on artists, themes, and the pure essence of improvisational jazz without “getting weird” has captured me as a fan!
If you are fortunate enough to live in the area and listen live, please do so. If not, please check them out online or through your favorite music dispenser. 😉
Just listened to an interesting Ted Talk by Jeremy Howard in Brussels which led me to view the Tedx talk in SF
Things I loved:
- Machine Learning is a fascinating field
- In 2011, an algorithm was created that had better recognition of stop signs than humans
- Similarities of Machine Learning to the Industrial Revolution, but not exact comparison
- Opportunity to predict continued evolution and focus on quality of life – using the ‘good’ not fearing the ‘bad’
- LOVED the demo of the auto recognition – and the learning ability to sort fronts from backs of cars
If the learning curve (pardon the pun) of machine learning is truly exponential when compared to the linear curve of the industrial revolution, we indeed need to address how humans and machines contribute to society.
Income tax and labor fees no longer apply. Should government fees that are used to make our lives safer and easier (public services, roads and infrastructure) be applied to machines? How will upkeep and continued positive contribution by machines be assessed and managed?
Simply with what is already released, this could be commercialized into short-term machine learning innovations that will make our lives safer and more pleasant.
It’s simple to imagine forward-facing cameras on cars. Identify stop signs and warn driver if speed is high when approaching a stop sign. The upgrade path here is obvious: red lights, crossing pedestrians, bicyclists, oncoming traffic, etc. Key issues will be what is the reaction – the device should simply alert the driver in the short term. Later the insurance industry will begin offering financial incentive to tie reactions to automatic braking.