Updates
Aside from the random items I stumble across, I've been intentional this week about seeking out information on culture, leadership, and motivation.
Thanks everyone who sent me links and recommendations this week. If you stumble across something interesting, send it my way! You can send any recommendations to links@houstonp.com.
Books
Steve Jobs by Walter Isaacson - Jobs is a complex and complicated individual. There are so many positive and negative aspects to his personality. Isaacson doesn't pick sides and lays out the history and facts well. If you're at all interested in the life of Jobs and his legacy, this is the book to read.
Drive by Daniel H. Pink - While a little long winded at times, Pink summarizes the key motivators of the modern workplace. Namely, intrinsic motivators drive employee satisfaction, retention, and performance. He groups them into three categories:
- Autonomy
- Mastery
- Purpose
I agree with the high level points made. I've had a hard time explaining why I enjoy or don't enjoy in a role. Autonomy and mastery are personally important to me; I had never read it laid out so well.
Podcasts
Some extraordinary episodes from this week:
Human biases are baked into algorithms. Now what? - Marketplace Tech
Hilary Comes to Town - Not So Standard Deviations
Why Everyone Should See Themselves as a Leader - HBR Ideacast
A Nobel Prize Winner on Rethinking Poverty (and Business) - HBR Ideacast
Why “Connector” Managers Build Better Talent - HBR Ideacast
The Power of Conflict - Masters of Scale
How to set the Drumbeat - Masters of Scale
Disney in a Foxhole - The Information’s 411
Designing Data-Intensive Applications – Reliability - Coding Blocks
Lessons learned from doing data science, at scale, in industry - Linear Digressions
Gavin Baker – Tech and Consumer Growth Investing – Invest Like the Best
Scott Adams: Avoiding Loserthink - The Knowledge Project
Videos
Andreas “Andy” Bechtolsheim: The Process of Innovation”
Conway's Game Of Life in APL - I have zero understanding of what is going on in the APL, but I can appreciate just how succinct the language can be.
The 5/4 Trick - How Harry Connick Jr. tricked an entire audience
Articles
How To Keep Your Best Programmers - If you don't want to take the time to read Drive, then this article and the links found throughout may be your next best bet. Again, the three intrinsic motivators: autonomy, mastery, purpose.
We’ve seen some very compelling words from a handful of people that roughly outline three motivations for departure:
- Frustration with the inversion of meritocracy (“organization stupidities”)
- Diminishing returns in mutual value of the work between programmer and organization
- Simple boredom
- Perception that current project is futile/destined for failure accompanied by organizational powerlessness to stop it
- Lack of a mentor or anyone from whom much learning was possible
- Promotions a matter of time rather than merit
- No obvious path to advancement
- Fear of being pigeon-holed into unmarketable technology
- Red-tape organizational bureaucracy mutes positive impact that anyone can have
- Lack of creative freedom and creative control (aka “micromanaging”)
- Basic philosophical differences with majority of coworkers
An Engineering Team where Everyone is a Leader - Gergely tackles project management, leadership, and autonomy in this post. There's a lot of lessons to be learned from his approach.
The First Non-Bullshit Book About Culture I’ve Read - Turn the Ship Around instantly went on my list after reading this summary.
My Management Lessons from Three Failed Startups, Google, Apple, Dropbox, and Twitter - Kim Scott wrote the book Radical Candor, and this article summarizes a lot of that content. I use her “ruinous empathy” phrase often. If you like this article, I'd recommend going through all of her book.
Want Better Forecasting? Silence the Noise - A lot of content packed into this article on forecasting. I do still have major concerns about bias in modeling, but it's interesting to see how big of an impact noise has on predictions.
150 successful machine learning models: 6 lessons learned at Booking.com - The original paper is good, but Adrian summarizes it perfectly.
My interpretation of them is as follows:
- Projects introducing machine learned models deliver strong business value
- Model performance is not the same as business performance
- Be clear about the problem you’re trying to solve
- Prediction serving latency matters
- Get early feedback on model quality
- Test the business impact of your models using randomised controlled trials (follows from #2)
It’s Official: JPMorgan Chase Is the Riskiest Big Bank in the U.S. - The title is sensationalized, but the content is interesting. I'm not familiar enough with the reporting and metrics the Fed look at to determine systemic risk.
Shrinkflation - Companies would rather change the size and shape of their products rather than change the price.
Novelty and Heresy - Paul Graham seems to be back to writing more.
So it's particularly dangerous for an organization or society to have a culture of pouncing on heresy. When you suppress heresies, you don't just prevent people from contradicting the mistaken assumption you're trying to protect. You also suppress any idea that implies indirectly that it's false.
Inefficient Efficiency - The article provides an intuitive example of latency vs throughput using a coffee analogy.
Coding habits for data scientists - The sooner data scientists can implement these concepts the better.
Keep code clean Use functions to abstract away complexity Smuggle code out of Jupyter notebooks as soon as possible Apply test driven development Make small and frequent commits
Best Practices for Testing Your Shiny App - The context is R's Shiny package, but the practices for testing should be applied to any form of software development. Formal, automated testing isn't done nearly enough in the actuarial profession.
Testing the tune package from tidymodels - analysing the relationship between the upsampling ratio and model performance - A thorough writeup on some of the packages in the tidymodels metapackage. A lot of development is going in to these packages, and articles like this are going to drive its usage more and more. Exciting stuff.
Cost-benefit analysis in R - An easy example to understand the usefulness of R when performing financial analysis.
Designing ggplots - Some slides going over all of the cool stuff you can do using ggplot. Being intentional about explanatory plot design will raise your presentations to a new level. Highly recommend.
The Matrix Calculus You Need For Deep Learning - Understanding the fundamentals and underlying math behind machine learning is important. Ultimately, machine learning and “artificial intelligence” is just math.
Interactive Linear Algebra - I skimmed through a few sections of this, and it seems like a useful book for anyone going through a linear algebra class or wants a refresher on concepts.
Estimating Uncertainty in Machine Learning Models — Part 1 - Most actuaries can understand confidence intervals. This article looks at a regression model, but later articles go over uncertainty in more complex models that aren't as straight forward. Part 2 and Part 3
Relentlessly Simplify - Our lives are filled with so much noise. Take some time to reduce it.
You probably know to ask yourself, “What do I want?” Here’s a way better question - A low quality title for an otherwise good article on success and meaning in life.
What determines your success isn’t “What do you want to enjoy?” The question is, “What pain do you want to sustain?” The quality of your life is not determined by the quality of your positive experiences but the quality of your negative experiences. And to get good at dealing with negative experiences is to get good at dealing with life.
Why Gross Margins Matter - Software as a Service has become a defacto standard in tech startups. Anyone in finance can learn from value metrics among different revenue making business models.
Big Calculator: How Texas Instruments Monopolized Math Class - TI makes 50%+ margin on their calculators that still sell for over $100. That's great for TI shareholders, but there are things more important than profits.
Stoicism and Control - Ending on a philosophical note:
You choose the principles by which you live. You choose who you are. Every day. You are in control. You are powerful. And nobody can ever take this from you.
Seeing Like a Finite State Machine - It will be interesting to see how Henry's conjecture plays out. China is making huge bets in ML, but I don't think they're as naive as Henry is making them out to be. This tweet found in the article though was pure gold:
That's it for this week. Again, if you have anything you want to share or have any comments, shoot me an email at links@houstonp.com.