Nice points. I have two kids under 6 right now and was starting to worry about how smart phones might replace computers for most of what they do and thus never expose them to an easy to program platform. What's really exciting for them is the abundance of hobbyist computers and embedded project kits available now. They're going to grow up in a world where simple microcontroller-style projects are completely accessible to them. Makes me almost want to be 6 again!

Today, I can teach my kids some basic UI programming with HTML/CSS/Javascript (not much harder than VB) to get them familiar with high level concepts. I can also get them a BrickPi or any other embedded(ish) system and teach them how hardware works and how to interface with external devices. What a great time to learn technology!

Millennials, by and large, got shafted when it comes to learning how computers work. Most of them went to school when Java was the only language being taught and Linux was becoming too complicated to easily understand for the casual user. When they started working, a little Javascript and CSS got them really far. There weren't many opportunities to really understand how the full stack works. And, with the rise of social media and apps, their exposure to technology was more social than technical. As others in this thread have pointed out, being able to use a simple UI on an iPhone doesn't make you the technology whiz that the media keeps saying you are.

Millennials can still catch up, but I think the next generation is the one that's really going to be primed to do amazing things.

-Chris

I don't think it's that computers and machine learning really trump an exact model. It's more that manual curated semantic information is difficult to do well and even when done well is simply the curator's interpretation of the key points. Ontologies and controlled vocabularies (necessary to make semantic solutions work) are always biased towards their creators view of the world. Orthogonal interpretations rarely fit with the ontologies and require mapping between knowledge systems. Rather than simplifying things, this just creates another layer of abstraction and meta-data that now must be managed.*

Machine learning, on some level, basically admits this flaw in structured knowledge representation and punts. Instead, it provides tools for querying knowledge bases and finding patterns in them. I think the latter part is just as flawed as manual curation, but the query tools combined with a human are incredibly powerful.

A simple example: Yahoo originally indexed and categorized the Web. When I interviewed there in '96 (and, silly me, turned down the offer), they had a room full of people that did just that. Google, on the other hand, used a graph algorithm combined with standard text search methods to leverage the structure of the web to give good search results. Yahoo eventually bailed on manual curation and we learned how to leverage Google's approach to search to mine knowledge.

tl;dr: manual and automated curation will never properly capture human's representation of knowledge. Instead, better tools plus the human brain will improve our ability to leverage knowledge.

-Chris

*and there's that old saying: every software problem can be solved with another layer of abstraction.

I was going to make a similar post...

It's my understanding that the current almond tree bubble is driven by (wall street?) investors who noticed the price mismatch in water and are using it to make a quick buck, the rest of the state me damned. Of course, these funds have deep pockets and probably can lobby effectively to keep prices where they are until they cash out.

Seems very much like a variation on ENRON but with water instead of gas.

Feeding a troll here, I know...

I'm pretty sure I had more Legos than you growing up. But, I didn't make the Legos, I built with them. I also was never under the delusion that my lego skillz would translate to a job building lego buildings. It was a fun, creative activity that required allow no learning and occupied most of my childhood.

The current push for everyone to program is the exact opposite of that. Learning to program for all but us autodidactics requires coursework and commitment. Sure, once you can do it it's a lot of fun. But, to keep the lego analogy going, it's like require a basic understanding of mechanical engineering before being allowed to use Legos (sorry Susan Williams - they'll always be Legos, not lego bricks).

Bricks are also a fundamental building block of our modern world. But I'll be damned if I know how to make one.

Not everyone needs to know everything. I love to code but I also appreciate that my friends who build houses for a living could give a shit about learning to code.

I'm amazed that people on a tech forum don't get that.

It's a statistical computing environment. R is much closed to what VB was pre-VB6 - a loosely defined domain specific language with lots of libraries aimed at a specific task. It's not really a general purpose programming language and not a great one to learn if you want to learn to program.

If you do a lot of number crunching and want to move beyond Excel, R is a great choice (as is matlab, s-plus, or any of the others aimed at analytics).

If you do analytics AND want to learn to program, go Python and NumPy/Pandas.

If you just want to learn to program, VB, JavaScript, Python, Java are all good. Just find what you'd like to program and see what languages people are using.

And yes, at some point, pick up a few more languages if you find you like programming.

-Chris

A few random thoughts on this:

Influencing people by having instant recall is a classic sales trick. Old school sales people wrote notes in their Rolodex to remember spouse's names, birthdays etc,. Today, Salesforce, Zoho, and the like (hell, even linkedin) handle this role. However, as soon as you realize that the sales person remembered something using a CRM rather than actually remembering it, that interaction quickly becomes awkward. In the past, sales techniques like these weren't well known outside of sales circles. Nowadays, everyone knows about them and they're less effective. The value in the technique is that people weren't aware it was being used and mistook the sales person remember personal details as actual friendship, rather than just a sales trick. Same will happen with timelines - we'll quickly sort those who use it as a gimmick and those who are sincere.

Another angle is the fitbit/life tracking. You know who obsessively tracks everything they do in hopes of improving themselves? People who obsessively track everything in hopes of improving themselves. The rest of us don't. Those people will always be around and will use these tools, the rest of us won't.

More importantly on the personal side of things: anyone who's accumulated a lifetime's worth of photos knows you never really go back an look at them in an detail. Sure, once in a while you'll reminisce, but you never do the detailed analysis of your past that these data hoarding stories predict. Instead, you live your life in the present, learning from the past with an eye toward the future. A few million years of evolution has made our brains very good at that. Every attempt to document and catalog our lives externally has failed to really live up to what our brain already does (hint: we likely don't have perfect recall for evolutionarily important reasons).

From the corporate side, data will be tracked as long as it can be traced back to profits. Right now, most of the profits are going to companies selling big data analysis services. It's only a matter of time before their customers move on to the next marketing trend.

trl;dr: live in the present and stop trying to cheat nature. :)

-Chris

ps: yes, the government collecting all this data is scary as hell. Voting can help fix that (at least in America - it'll take a few elections, but it's possible).

This. Most of the workforce would benefit from basic education in all aspects of business. Sales, marketing, finance, project management, business development, etc.

In our neck of the corporate world (software), too few employees understand how business actually functions and what it really takes to make a business work. The current culture of "just build an app and you're set for life" leaves out many of the key steps needed to build a business. As a result, most promising applications go no where and most "successful" exists are really just acqui-hires (making the entrepreneur just a well paid headhunter, which has nothing to do with coding ability).

Simple things like knowing how to develop top down and bottom up models of a market would help app developers understand who their users are and how they might generate revenue to continue to fund their app. Even something as simple as understanding that revenue is actually necessary for success is lost on most developers I know.

-Chris

C'mon! Every programmer worth their salt knows that Control belongs to the left of 'a'. 'Mouse' is cute, but stick that on the bottom (and not where the Meta key goes!).

I'll go back to Emacs now...

-Chris

... not a programming test. Recursion is a key concept in CS and is the foundation of many techniques and principles. Sure, no one uses it in practice that often, but that doesn't mean you shouldn't know it if you're learning CS.

If you want to train people for job interviews, send them to a trade program. If you want them to understand the field, you have to teach them the fundamentals.

I never use the central limit theorem directly when doing stats, but knowing how it underlies the methods helps provide a better understanding of results.

-Chris

I have a Ph.D. and am now fully qualified to teach university courses. The funny thing about that is that in the course of getting my Ph.D., I never once had to take a course on how to teach or even teach/TA a course (I was a research assistant the whole time I was in grad school).

I'm an outlier on not having to teach/TA a course in grad school (I did TA an undergrad, though) , but I don't know of any graduate programs that require actual training for teaching.

The person cited in the summary is just as qualified as most Ph.D.s. :)

As for the big bucks, two of my good friends from grad school (both computer scientists) spent their first two years working for free waiting for tenure track positions to open up. They get decent salaries now, but over the course of their careers, it's not what I'd call big bucks.

-Chris

Data scientists are this bubble's web masters. 'Nuff said.

For the sake of this discussion, mosquito borne malaria is a warm weather problem. Increased deaths from cold weather, which was the parent's straw man, occur when it's really cold (sub freezing). Mosquitos die when it freezes. Sure, they can be a problem even when it's cold, but not when it's deadly cold.

-Chris

How about just remove the camera? That's the creepiest part of Google Glass.

I'm all for exploring the potential of having a display in my line of site for getting information on demand or for AR applications. You don't need a camera for either of those. For AR, the GPS in the phone gives you position, accelerometers in the headset give you orientation, and public database of roads and buildings gives the apps spatial awareness. If you want to be able to highlight people or cars, they could 'opt in' to a location sharing feature that publishes their coordinates.

Battery life would probably be much better w/o the camera as well.

-Chris

31,000 extra deaths due to cold weather and the flu in 2013:

http://www.dailymail.co.uk/new...

584,000 deaths due to malaria in the same year:

http://www.who.int/features/fa...

Malaria is transmitted by mosquitoes, which rely on warm weather to live. And that's just one warm weather related cause of death that will go up as the planet warms. :. A warming planet will be a deadlier planet than a cooling planet.