willis77

Apparently a web search is not the kind of puzzle he wanted to solve.

If you are 25 years old, this is how many weekends you have left in your life (on average):

https://i.imgur.com/MA3YeuX.jpg

Let's spend one on a plane so that we can make it into the gold lounge and get free yogurt-covered raisons!

"I killed a pedestrian on the way home, but so glad I got your text about mac n cheese for dinner! Smells yummy, let's eat!"

> should we be charging people more (effectively punishing them) for something outside of their control?

Car insurers charge young people more money, despite their youth being outside of their control.

I find comments like this unconstructive, and they always surface when people present forecasts. It's easy to play the shoulda-woulda-coulda game with data. "You should account for the breaking strengths of each team's players' ACL tendons. It could affect the outcome if they get injured!" Okay, so what? Did you do it? Does the data exist? Do you have any quantitative evidence of a statistically significant link between the weather and team performance? If you do, do you also have the evidence to show that the game forecast is not rate limited by the error of the weather forecast?

I'm not saying you have to write a thesis to suggest new data sources, but I am saying that "you need to do XYZ" is not a productive piece of advice without the evidence to back it.

One of the things I despise about academia is the need (and sometimes the arrogance to) give every project/idea/framework, no matter its size or importance, some silly acronym.

> "We know being active is important, so your Vessyl connects with popular activity trackers for more accurate net calories and hydration awareness."

Phew, I was worried about this. If I can't sync my Vessyl to my fitbit to my strava profile with nike+ misfit shine integrations, how the hell am I supposed to know exactly how many steps I need to take to optimize my area under the fun curve subject to the constraints that I lose 1.6 pounds but can still eat artisanal cuisine?! The other day I almost went for a walk in the woods, but my Vessyl was dropping its bluetooth connection, so I retreated to the safety of my San Francisco apartment.

This is a tour like being handed a list of animals is a tour of a zoo.

> reminds me of Michael Feynman

Richard Feynman?

* The algorithms must be MIT Open Sourced, so you are also welcome to take the results and make millions with them

* There is no guarantee the algorithms will beat the betting line, so saying they are worth millions is not generally true

* If the authors of such an algorithm find that they are more accurate than the bookies, they can always keep it to themselves and make millions

Unlimited breadsticks

:-/

Considering this is four months old and the only method implemented is still just knn, I think it's disingenuous to (a) call this a library and (b) write in such general terms (admittedly, hindsight is 20/20). I don't mean to detract from the premise behind starting the project, but language like "I couldn't find any comprehensive ML library for Go, so I decided to write one" has a bit more hubris than is warranted.

I remember that case. Semicolon and Sons sued Sammy "Sentence" Splice, saying his single-sentence sagas seemed somewhat salaciously un-salubrious.

I also hope their technical competency beats their writing competency.

Precisely. Publications require data. Data costs time/money/brains. Grants/promotions/tenure/survival cost publications. It's not hard to see that data serves a role as currency, and there is little incentive to give it away as long as publications are what puts bread on the table.

Additionally, the discussion over shared data is usually a cry to improve reproducibility. In this publication-centric world, one can't publish a paper that is just "we reproduced an existing paper", so outsiders look to "poach" new applications or findings from the data.

Also, don't forget that people like to come out on record for/against hot ideas/topics/predictions. In the event they are right, they ride the success all the way to the fame and monetary bank. If they're wrong, such an article is usually forgotten and lost in the sea of bitcoin press.

A lot of the hype has been around using Watson as a medical decision support system, so yes, they do need peer-reviewed papers before "throwing it at hospitals". In medicine, you can't "see if it helps" without a controlled experiment. It's just too subtle to see when it's not helping, and also too late.

You really think they are going to "get an overhaul of the their mobile platform and, as a result, their business" from a three day hackathon? You underestimate Salesforce's size, the complexity of business in general, and about 50 other factors that make an event like this far from a silver bullet overhaul, whatever that means.

It hasn't been solved because it's not one problem. People have different wants and needs and expectations and banks and tax codes and tolerances for entering data, and are lazy when it comes to testing existing options. Why spend hours searching and signing up for trials and learning new UIs when they know how to make a spreadsheet that does what they want?

Your opinion doesn't matter; you have not spent the required 10,000 hours to become a Hacker News comment expert.

Sure, they may have solved the cat problem, but the well-documented challenges of "pug face" and "slobber smudging" makes dog recognition an order of magnitude harder. Some say the Clay Institute is pondering a $1M prize for it.

It's a free country and you are free to measure productivity however you want. That said, is this slow societal descent into short, insincere, 140 character coke-addict emails with expected instant response times a positive thing? I'm not trying to be nostalgic for the letter-writing days of yonder, but nothing says "I don't give a shit" like those emails you get. You know the ones. 18 people are CCd. People just attach whatever they think is relevant without reading what you're asking. People forward whatever to whomever. This guy to BCC. So and so will arrange. Have a look at my calendar and suggest a time. I attached version 2 Final Revised Signed Real Version Final Final. Blah blah blah.

People were productive long before death by instant email papercuts. It's something worth thinking about as you optimize on response time. I find many insta-responses were preventable with better planning in hindsight.

Why is that argument stronger? You think Starbucks hasn't run the numbers/experiments to test whether a warm body on a laptop is better than the same body ducking in and out? I would bet money they have done a frightening amount of analysis on this question.

Also, to your specific point - when people choose restaurants they often go where there's a crowd (the food must be good here), not to an empty restaurant. The situation is a little different because Starbucks is so pervasive, but don't discount the customer draw of a bustling store full of people.

Woah woah woah, not so fast, Doctorate McPhdsosoon. Science is repeatable. See you at lab meeting next Monday morning. Please come prepared with a roadmap for phase 2 trials. These grants don't write themselves, you know.

Obviously chemotherapy causes cancer, because all the people who have chemotherapy end up having cancer.

Gmail previously had 1 type of message compose. Now it has 2. Feel free to choose the one yo--oops, now it has 1. The one you didn't choose.

It's funny to me that people are so quick to poo-poo the complicated modeling done for the Netflix prize. When did production-worthiness become the only important thing? It's like saying Watson was useless because it can't play a concurrent game of Jeopardy with thousands of people on the web.

Just like in research, it turns out that relaxing real-world constraints on a problem is often a great way to make progress. I would not have to search long or far to provide much worse uses of million-dollar grants/projects/big-data-software.

The plural of anecdote is not data.

Have a look for your self:

http://research.google.com/pubs/MachineLearning.html

"Be sure to drink your Ovaltine."