Hacker News: riphay

New comment by riphay in "The demographic future of humanity: facts and consequences [pdf]"

riphay — Tue, 12 Aug 2025 03:47:59 +0000

Link to the keynote presentation, fills a lot of the gaps in the slides: https://www.youtube.com/watch?v=f7_e_A_vFnk

New comment by riphay in "Lyft Crashes Below IPO Price"

riphay — Mon, 01 Apr 2019 19:10:59 +0000

The banking syndicate takes on some risk in order to facilitate trading in a successful IPO. Usually to compensate for this risk the IPO price is (slightly) less than what they believe the stock will trade at. This way the IPO investors and the banks can make a bit of money for bearing this risk.

It's usually seen as unsuccessful and a bad-news story when a stock falls below its IPO price. Even though Lyft might have taken the max from investors, it will diminish its ability to raise further equity and its bankers will lose the trust of the IPO investors.

New comment by riphay in "China Once Looked Tough on Trade. Now Its Options Are Dwindling"

riphay — Tue, 18 Sep 2018 16:49:52 +0000

Yes, but they are paid by the importer and (usually) passed on to the consumer. In effect they become a subsidy for local industry paid by consumers.

New comment by riphay in "Tesla Faces U.S. Criminal Probe Over Musk Statements"

riphay — Tue, 18 Sep 2018 16:40:14 +0000

Long is short-hand for anyone benefiting from the price of the stock rising. This includes people who own the stock outright, have bought on credit, own call options, have sold put options, etc.

New comment by riphay in "Apple's best product is now privacy"

riphay — Fri, 14 Sep 2018 17:28:06 +0000

I think his point about the "happy accident" is that iAds failed and that's part of why Apple is now "pro privacy."

New comment by riphay in "Poaching Tesla"

riphay — Mon, 10 Sep 2018 06:04:00 +0000

My point was that I don't think there's a ton of productivity to be lost by smoking 1 puff in the middle of the night vs. smoking a whole joint in the middle of the day.

The "X" in this case has too wide of a range of interpretation to jump the gun on hypocrisy.

New comment by riphay in "Poaching Tesla"

riphay — Sun, 09 Sep 2018 07:03:29 +0000

You're absolutely right; but I have a hard time believing this depresses stock valuations with so much smart money out there (by ~20% no less!).

Otherwise I think there's a serious market opportunity to be exploited.

New comment by riphay in "Poaching Tesla"

riphay — Sun, 09 Sep 2018 06:35:47 +0000

He took one puff of weed on a casual podcast at ~11 p.m. local time. Not certain this is the canary in the coal mine some people are making it out to be... but I guess volatile stocks will find reasons to be volatile?

New comment by riphay in "How to be a Manager – A step-by-step guide to leading a team"

riphay — Tue, 05 Jun 2018 21:25:11 +0000

Great article, bookmarked for future reference!

I work for a small consulting firm focused on improving productivity and building innovation systems within small-medium sized businesses. And having strategic plans, vision, values is hugely important in building a focused innovation program. It's become routine in my engagements to spend significant time defining goals and values where the companies had none previously! This sort of exercise is valuable for firms at any stage and size in my opinion.

New comment by riphay in "Keurig to Acquire Dr Pepper Snapple in Largest Soft-Drink Deal Ever"

riphay — Tue, 30 Jan 2018 01:10:35 +0000

When one company buys another it has to assume it's debt.

Enterprise value = equity + debt - cash on hand (and other adjustments sometimes)

So if a company has financed its growth with debt, you still have to pay for that if you're acquiring them so it adds to the valuation.

New comment by riphay in "Amazon is in exploratory talks with generic-drug makers"

riphay — Fri, 01 Dec 2017 18:54:03 +0000

Couldn't agree more. Reminds me of the concept of the "company store" (https://en.wikipedia.org/wiki/Company_store)

New comment by riphay in "Building A.I. That Can Build A.I"

riphay — Mon, 06 Nov 2017 17:10:03 +0000

This is really great. I actually struggled to find ML solutions for a large relational data set at a previous employer. Ended up figuring out a way to flatten the data, but was not ideal. Glad that people are working on this, keep it up!

New comment by riphay in "Some Excel users pop F1 off their keyboards (2012)"

riphay — Sat, 23 Sep 2017 00:51:04 +0000

Former banker, and to this day I remove the F1 key from my keyboards because I still use excel heavily. Never really crossed my mind to remove winhelp.exe or anything else. This was a simple solution to a simple problem, didn't need anything more complicated.

And if I ever need to access the help function, I'd just stick a pen in the socket and hit the membrane.

New comment by riphay in "Ford disguised a man as a car seat to research self-driving"

riphay — Wed, 13 Sep 2017 18:17:24 +0000

Really interesting study, would have liked to see some preliminary or even anecdotal findings discussed in the article.

I've seen some Youtubers pranking drive-through windows in the same way and they're pretty funny at the very least.

New comment by riphay in "Most Female and Male Occupations Since 1950"

riphay — Wed, 13 Sep 2017 16:46:43 +0000

Seems to be a few as other comments have pointed out. But the female labour-force participation rate at the start of the dataset would make it difficult for individual job categories to switch from majority female to male over this particular time span.

New comment by riphay in "iPhone X"

riphay — Tue, 12 Sep 2017 21:57:15 +0000

This is a great point, and why I'd like to see more features being locked without a passcode. The move in iOS 11 to restrict device imaging without a passcode is a great step in this direction.

Perhaps we can see more customization as to what biometrics unlock and what they don't?

New comment by riphay in "AI Playbook"

riphay — Mon, 15 May 2017 22:09:33 +0000

This is a great point, and I think I fall into that bucket you describe. I have just enough information to be dangerous.

There does seem to be a lack of available tools even for someone with a well-defined problem with available labelled data to validate implementing machine learning to a problem. I think that there's a need out there for a software with a GUI that can accept data and let you try some ML approaches with it and take the coding out of it - and it doesn't seem like it would be insanely difficult to build.

New comment by riphay in "India Is Winning Its War on Human Waste"

riphay — Wed, 26 Apr 2017 18:37:47 +0000

Don't mix up "Romans" and "Europeans." A better question is if the residents of Rome and other cities that had public facilities went back to the bucket or if they continued to use and maintain the public toilets. The rest of Europe likely never had public facilities to begin with, and the fall of the Empire might have delayed that technology transfer I suspect.

New comment by riphay in "The Cavendish Banana Will Soon Be Gone"

riphay — Thu, 16 Mar 2017 16:51:30 +0000

For those who want to take a deep dive in the world of bananas, great article about what different people are trying to do about the problem (from 2011):

http://www.newyorker.com/magazine/2011/01/10/we-have-no-bana...

Ask HN: Machine Learning for Relational Data

riphay — Tue, 24 Jan 2017 19:48:50 +0000

I've been dabbling in machine learning and trying to find a way to apply it to some of the data at work. I work in a custom fabrication / construction company and I'm trying to build a regression tool with Tensorflow to predict fabrication time at a piece-level using time data at a higher "project-level." A simplified model of what I'm looking at:

Project-level data: Special requirements [Feature], Time taken by various departments [welding, painting, shipping, etc.] [LABELS]

Piece-level Data: Type of piece [F], Weight [F], Length [F], # of attachments [F], [Desired output time] (does not exist historically)

Attachment-level Data: Type [F], Length [F], Weight [F]

All of the classification and regression examples I've been able to find are for "flat" non-relational data. Some of the features can be flattened (such as requirements), crucially the existing labels cannot be flattened without making very broad assumptions (i.e. distributing the time among the pieces by their weight).

Are there any examples anyone is aware of that could help me build a framework for this problem? Is ML even the right approach for this? Thank you for your help.

(edited for clarity)

Comments URL: https://news.ycombinator.com/item?id=13474815

Points: 1

# Comments: 1