[curtesy Serge Ramelli]
Occasional Musings
by Murali Jayapala
Avoiding the false proxy trap [S. Godin]
A notable thing to keep in mind. Often we come up with various metrics to measure performance… but they are most of the times proxies for something else. Important to keep in mind the “something else”.
Seths Blog
via Avoiding the false proxy trap.
Sometimes, we can’t measure what we need, so we invent a proxy, something that’s much easier to measure and stands in as an approximation.
TV advertisers, for example, could never tell which viewers would be impacted by an ad, so instead, they measured how many people saw it. Or a model might not be able to measure beauty, but a bathroom scale was a handy stand in.
A business person might choose cash in the bank as a measure of his success at his craft, and a book publisher, unable to easily figure out if the right people are engaging with a book, might rely instead on a rank on a single bestseller list. One last example: the non-profit that uses money raised as a proxy for difference made.
You’ve already guessed the problem. Once you find the simple proxy and decide to make it go up, there are lots of available tactics that have nothing at all to do with improving the very thing you set out to achieve in the first place. When we fall in love with a proxy, we spend our time improving the proxy instead of focusing on our original (more important) goal instead.
Gaming the system is never the goal. The goal is the goal.
The Acute Heptagram of Impact [S. Godin]
Seths Blog
via The Acute Heptagram of Impact.
Not as catchy a title as Maslow’s Hierarchy of Needs, but I hope you’ll walk through this with me:
I can outline a strategy for you, but if you don’t have the tactics in place or you’re not skilled enough to execute, it won’t matter if the strategy is a good one.
Your project’s success is going to be influenced in large measure by the reputation of the people who join in and the organization that brings it forward. That’s nothing you can completely change in a day, but it’s something that will change (like it or not) every day.
None of this matters if you and your team don’t persist, and your persistence will largely be driven by the desire you have to succeed, which of course is relentlessly undermined by the fear we all wrestle with every day.
These seven elements: Strategy, Tactics, Execution, Reputation, Persistence, Desire and Fear, make up the seven points of the acute heptagram of impact. If your project isn’t working, it’s almost certainly because one or more of these elements aren’t right. And in my experience, it’s all of them. We generally pick the easiest and safest one to work on (probably tactics) without taking a deep breath and understanding where the real problem is.
Feel free to share the AHI, but please don’t have it tattooed on your hip or anything.
Waiting for all the facts [S. Godin]
Seths Blog
via Waiting for all the facts.
A very useful piece of advice from Seth Godin
“I’m just going to wait until all the facts are in…”
All the facts are never in. We don’t have all the facts on the sinking of the Titanic, on the efficacy of social media or on whether dogs make good house pets. We don’t have all the facts on hybrid tomatoes, global warming or the demise of the industrial age, either.
The real question isn’t whether you have all the facts. The real question is, “do I know enough to make a useful decision?” (and no decision is still a decision).
If you don’t, then the follow up question is, “What would I need to know, what fact would I need to see, before I take action?”
If you can’t answer that, then you’re not actually waiting for all the facts to come in.
Comparison of 24-105L IS with kit lens 18-55mm IS II
Recently, I pulled the trigger and upgraded from my kit lens 18-55mm IS II to 24-105mm L lens. Here is some initial comparison in semi-controlled environment. In all of these pics, the kit lens under exposed the pics compared to 24-105mm. Already a good start..
A more thorough comparison can be found here at the digital picture.
[Iso chart comparison @digital picture]
[distortion chart comparison @digital picture]
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- 24-105L vs 18-55 IS II @ 24mm f/10
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- 24-105L vs 18-55 IS II @ 24mm f/4
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- 24-105L vs 18-55 IS II @ 24mm f/5.6
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- 24-105L vs 18-55 IS II @ 50mm f/10
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- 24-105L vs 18-55 IS II @ 50mm f/5.6
Finally a whole cell computational model
An entire organism is modeled in terms of its molecular components
Complex phenotypes can be modeled by integrating cell processes into a single model
Unobserved cellular behaviors are predicted by model of M. genitalium
New biological processes and parameters are predicted by model of M. genitalium
Summary
Understanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication. In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions. We conclude that comprehensive whole-cell models can be used to facilitate biological discovery.
More info [The Science Direct Link] [The Cell.com Link]
Is Society Becoming Over-Medicalized? (Ivan Oransky)
An interesting talk @TEDMED 2012 by Ivan Oransky.
Also, interesting interview in medgadget: [Interview Transcript here]
Interesting interview with Stephen Wolfram [theeuropean-magazine]
Here is an interesting interview with Stephen Wolfram of Mathematica, WolframAlpha from theeuropean-magazine. Couple questions that I found interesting in the interview.
The European: The New York Times Magazine recently published a profile of Craig Venter, who led the team that decoded the human genome. Two things about it struck me as very interesting: One, he argued that the main challenge for innovation is not to do more, but to spread the benefits of innovation around the globe. Two, the best way to do that is through private enterprises and not through academic research. What’s your take on that?
Wolfram: I was an academic for a while, but I really like energetically doing projects. What I tried to do is build a very efficient mechanism to turn ideas into things. Right now, entrepreneurial companies seem to be the best way to do that. I look at my friends in academia and think: “Wow, things moved so slowly there in the last 25 years!” When we hire academics to work on WolframAlpha or Mathematica, the biggest shock for them is always how quick everything moves. We sit down, and an hour later we have decided what we are going to do and moved on. We can do crazy projects! If you want an immediate impact on the world, that’s what you need.
The European: So there are limits to the intrusiveness of data searches that violate personal privacy. Is there a similar limit where we might say: Even if it were technologically possible to automate most everyday processes, we should not do so for the sake of intuition or creativity.
Wolfram: It’s interesting that you mention creativity. We did an experiment a few years ago where we randomly plucked music from the universe of possible musical arrangements, and it actually sounded quite decent. I have been hearing from composers that they use that website for inspiration, which is the exact opposite of what I had expected. But the question remains what we humans should do if everything became automated. The answer, I think, is that we figure out what we should do. Let’s assume that everything is automated and wonderful. What do you choose to do in that case? As humans and as individuals, we have certain purposes that we are trying to achieve and which cannot be automated. Highly advanced artificial intelligence can be programmed to have a particular purpose but it cannot answer the question of what’s the right purpose to have. I find it highly interesting to figure out how human purposes evolved and how technology might affect them. At different times in history, we have said that our purpose is religion, or maximizing pleasure, or maximizing money. Some of the purposes we have today would seem rather bizarre from a historical perspective. Imagine a paleolithic ancestor trying to figure out why someone would walk on a treadmill indoors! So when lots of things are automated and possible, what purposes will we value? My personal and rather bizarre answer is that future generations will return to the wisdom of the ancients. The times we live in right now mark the first time in human history that data is permanently recorded on a large scale, so future generations can study us and say: “These people lived finite lives and had to make tough choices. So maybe those choices can tell us something about what it means to be human, and about what endpoints our idea of progress should aspire to.”
More of this here: [The Link]