- User Onboarding Teardowns — the UX of new users. (via Andy Baio)
- Microsoft’s Productivity Vision — always-on thinged-up Internet everywhere, with predictions and magic by the dozen.
- Machine Learning Done Wrong — When dealing with small amounts of data, it’s reasonable to try as many algorithms as possible and to pick the best one since the cost of experimentation is low. But as we hit “big data,” it pays off to analyze the data upfront and then design the modeling pipeline (pre-processing, modeling, optimization algorithm, evaluation, productionization) accordingly.
- Ten Simple Rules for Lifelong Learning According to Richard Hamming (PLoScompBio) — Exponential growth of the amount of knowledge is a central feature of the modern era. As Hamming points out, since the time of Isaac Newton (1642/3-1726/7), the total amount of knowledge (including but not limited to technical fields) has doubled about every 17 years. At the same time, the half-life of technical knowledge has been estimated to be about 15 years. If the total amount of knowledge available today is x, then in 15 years the total amount of knowledge can be expected to be nearly 2x, while the amount of knowledge that has become obsolete will be about 0.5x. This means that the total amount of knowledge thought to be valid has increased from x to nearly 1.5x. Taken together, this means that if your daughter or son was born when you were 34 years old, the amount of knowledge she or he will be faced with on entering university at age 17 will be more than twice the amount you faced when you started college.
"productivity" entries
Four short links: 2 March 2015
Onboarding UX, Productivity Vision, Bad ML, and Lifelong Learning
Be a squeaky wheel, but always bring oil
Camille Fournier on becoming a “multiplier” — and why multipliers are more effective than managers.
There are times when we all wish we could clone ourselves so we could get more done at work. In a Velocity New York 2014 keynote, Camille Fournier, CTO at Rent the Runway, presented an alternative, practical solution, that she argued is far more effective (not to mention feasible): become a “multiplier” rather than a manager.
Technical skills are important, she said, but they’re not ultimately the bottlenecks you experience later in your career — eventually, time and focus become the main hurdles. To overcome these hurdles, Fournier argued that you need to take a step beyond managing and focusing on creating additive value, and focus on multiplying your value by increasing the effectiveness of the people working around you.