spyhi

To be fair, it’s the horsepower of a mouse, but all devoted to a single task, so not 100% comparable to the capabilities of a mouse, and language is too distributed to make a good comparison of what milestone is human-like. But it’s indeed surprising how much that little bit of horsepower can do.

A senior engineer can work through a hard problem assigned to a junior engineer, resulting in a well-implemented hard feature and a less junior engineer. Just because a junior engineer is working on it doesn’t mean by default it’s an easy problem—how are you going to grow your engineers otherwise?

Fractional opacity mixing with pure black is still not the most physically accurate shadow, because in the real world ambient light is mixed in with shadow, and also the color of the object casting shadow (and the surface the shadow is cast on) also creates color casts on a second light bounce from off-angle ambient light hitting an object, which influences shadow color in a way that's not "black on top of surface color." The algorithm for blending drop shadows doesn't take these things into account. https://willkempartschool.com/the-secret-to-painting-realist...

The link above also has an example of the use of multiple shadows to create a more naturalistic feel, namely that in the real world we are accustomed to, one source of light creates multiple kinds of shadows because of reflections from clouds, objects, etc.

This is all linked to physical realism, to help carry over our expectations of what the world looks like into a (in this case) digital space.

I am surprised to find this comment so high up when so much of it is so categorically wrong I almost wonder if you're saying opposite things as a joke.

Perhaps the most egregious is your position on black shadows being the best and physically most realistic color to blend with, when in reality pure black doesn't exist in nature almost at all, it's just how our brains process things and if you actually use pure black then things will look subtly wrong--I know because I used to do that and learning to stay away from black where possible after taking a basic design course was one of the things that best improved the feel of my designs. Like, there's decades of research in the arts, sciences, and design community about this! It works for a reason.

For the sake of brevity, I'll leave this blog post here that explains it better and more in depth: https://ianstormtaylor.com/design-tip-never-use-black/

Not only did NASA help create and enable SpaceX, they were one of the primary early customers, with about half of SpaceX’s revenue coming from government contracts. [1] Apparently government is involved with all space entrepreneurship to some degree or another.

One thing that people also aren’t pointing out is that Space is considered a multi-trillion dollar market for whoever can access it due to the Wild West “if you can reach it, it’s yours” resource policies, which is why it attracts so much investment for long term projects. Many sectors that need investment in fundamental research don’t have those properties (untapped, unclaimed resources you can look to the sky and see), and therefore don’t attract the same kind of money.

[1] https://www.theverge.com/2019/6/18/18683455/nasa-space-angel...

Yeah, but the original point you were responding to was endorsing the idea that “you should invest time in optimizing/performance last, and focus on making something people want to use first.” I’m saying your point that videogames have to be performant at the end is irrelevant to the point at hand because that’s exactly what the games industry does, they prototype without care to optimization to make something worth optimizing—i.e. something internal stakeholders reasonably believed there would be a market for.

Yeah, but even in the old days the developers would still be prototyping. Internal stakeholders are still stakeholders, and it’s developers optimizing for things other than speed. Nintendo devs famously build nothing until Mario’s jump (the MVP) feels right.

Ehhh, I don't think your example disproves the idea you're responding to. Perhaps video games MUST deliver performance in the end, but often game prototypes are not performant at all for the sake of rapid experimentation, and are only optimized towards the end of development once all the systems are set in stone...which is what's being advocated for here.

Sublicensing is what legally enables things like rich media link previews (the kind you see on Facebook and Twitter) or APIs to exist. Yeah, theoretically they could use that to sell content, but in practice it's generally used to make the web more interoperable.

If you think about it, it kind of makes sense. OP is in a situation where he haas much more money than time, however due to his position in the world, he can see many opportunities--generally this is true for professional investors, too. For a normal person, pursuing one means there is an opportunity cost, but for an investor it makes sense to buy a slice of the action in an opportunity they believe in. Being a proper investor (mentoring, introductions) also takes time, so that's another disincentive from OP's perspective to being a founder vs a funder.

Also, investors have things thing about inventing the future by funding it. Generally, individually or as a group, they'll decide something is going to be the next big thing and start cultivating deals in that area. One you can see happening in real time is space: Randomly in the last couple of years, investors have put together huge funds around space ventures, even though serious commercialization still seems to be a ways off. Even OP referenced it in his blog post.

As for why a founder vs a compensated product owner? Because a founder presumably has spent a lot of time thinking about the problem and is intrinsically motivated to solve it--so much so that they've done all the legwork to assemble a team and gather enough data to be investment-worthy. If as an investor you're wrong about the opportunity in this space, it's a whole lot of risk and cost and time you don't have to take on yourself. By advertising a pot of money, instead of searching for the right person, the hope is that the right person and team will eventually come to your door.

I went to school for CS, and decided to add on a BBA since I could do it basically for free. Prior to school, I was extensively read in the category of books you describe. While you're not wrong that you can get most knowledge from reading famous business books and using some intuition, you also don't know what you don't know, and that little bit has outsized value because it is important, non-intuitive, and hard to find--I suspect it's the secret sauce everyone keeps to themselves and isn't talked about by virtue of being relatively boring. Sure, you could read it in any old textbook, but you probably wouldn't think to.

I'm not sure what you're trying to get at...are you trying to say business people are smarter than OP gives them credit for?

"I very quickly realized that" <- Implying a prior assumption that was proven false

"very smart people" <- The set of very smart people OP has met, which hinges on perspective

"often" <- The key phrase here, implying that it is generally (but not always) true

"have very little knowledge of finance and business." <- The assumption at hand

I'm assuming OP thinks of STEM people as the definition of "very smart," based on his description of his degree, and his feelings about coding. OP may have assumed that since his knowledge is comparatively trivial for STEM people to learn, the knowledge might be widespread among what he thinks of as smart people, and was surprised when this valuable knowledge wasn't. In my experience, the average kind of person I'm assuming OP would consider "very smart" is either averse to business, or didn't bother learning business because it took time away from the hard problems they were more interested in, even though they easily could have.

More generally, the total set of obviously and profoundly smart people is bound to be (much) bigger than the set of obviously and profoundly intelligent people with knowledge of finance. Are there smart business people? Absolutely. But it's probably a small percentage when compared with the total set of Very Smart People. Also, at least in my school, the smartest people tend to go into harder disciplines, so that may further dilute the numbers of finance knowledge among the pool of Very Smart People.

So, there are multiple ways OP's statement can be true without being specifically about the capacity of intelligent people to learn finance through study or experience.

Marketing class- 2 lessons, if you are going to put years into a project, do a marketing plan. Also, learned how incredibly important marketing is.

This was exactly why I chose to do a BBA alongside my CS degree. If I was gonna make something, I wanted to make sure it would have some impact on the real world. I tell people: CS is a tool for solving problems, but business is a tool for finding them.

I think you're misunderstanding what he's trying to say. He's not saying that knowing finance has anything to do with being smart--if anything, it's the opposite: Of the people he considers smart, he noticed knowledge of finance isn't widespread. Perhaps the average smart person doesn't find the problem interesting enough.

For what it's worth, I was one of those people. I didn't go for my undergrad until 8 years into my adult life (I'm a veteran), but I had done extensive reading about business to the point that most of my BBA (which I was taking as a bonus alongside CS) felt like review. Except for finance. I knew the basics, but even undergrad courses revealed that my knowledge was very shallow. I think it's just something that people don't expect to have that much complexity. I wouldn't have thought to learn it if I hadn't been forced to take it in school, but I took as many finance courses as I could once I realized the knowledge deficit.

Is finance hard? The sophisticated stuff can be, but generally in comparison to engineering it's not. But nonetheless, nearly none of the computer scientists in my class or in my professional circles have bothered to learn...probably because they're more interested in compilers ;)

Oh man, all the questions you just asked only highlight exactly why an MBA is so beneficial for mid-career people haha! I'm an adult student doing concurrent CS and business degrees after a long time dabbling in both, and in both cases the value of college was in the things I wouldn't have thought to learn or wouldn't have thought were valuable, especially in places where the signal-to-noise ratio is really low and snake oil is everywhere, like the marketing example you just gave.

Just as a small example, why do you need to read financial report at all? Because that is the language of investors and managers. Why read financial reports for some random company? Benchmarking, so you can tell investors and stakeholders "this is how well we are doing vs comparable companies." A template generator won't help you with this kind of analysis, and those services you mention won't help you if you can't really understand them.

I'm not saying you need an MBA to be a good business person, and I felt like my BBA (which I'm told is mostly the same material as an MBA, at least at my school) only confirmed that my instincts and self-learning after 8 years in the workforce was pretty good...but man, those little bits I didn't know and hadn't thought to learn (especially around finance and proper marketing) were the ones that have ended up mattering the most.

Oh hey Dr. Johnson, fancy seeing you here!

Here is an example of TechFolios in the wild [1] which I built while I was in his class. https://spyhi.github.io/

(I’ve let it fall a bit out of date since the class, but this thread is good inspiration!)

It isn't anymore, if it ever was. https://arstechnica.com/tech-policy/2016/02/happy-birthday-i...

Yelp seems to be the superior product since it has more reviews while having no financial benefit from manipulating reviews.

This is a dubious claim.

There have been periodic blowups about Yelp offering to manipulate how reviews are presented for money. [1][2] Yelp portrays this as advertising [3], like putting a "favorite" review "above the fold" so to speak, but many business owners consistently tell the same story about extortion over negative reviews.

I never paid it much attention before, but recently someone I personally know mentioned that her boss (at the time) was paying to remove negative Yelp reviews, so ¯\_(ツ)_/¯

Point is, even if they aren't directly deleting negative reviews, reviews are their main product and pressure over negative reviews seems to be at the very least a sales tactic, so don't be so sure they have no financial benefit from manipulating at least certain aspects of reviews--it's not inconceivable.

[1] https://thenextweb.com/insider/2009/02/20/yelp-remove-bad-re... [2] https://www.searchenginejournal.com/yelp-filter-positive-rev... [3] https://www.quora.com/Does-Yelp-remove-negative-reviews-in-e...

University of Hawaii at Manoa. I'm finishing up an undergrad degrees in CS and Business (started school at 30 after time in the military, so another success story for this thread), but I have a few friends in the masters program who came from other disciplines, which is how I know about this, though it's also listed on their site.

http://www.ics.hawaii.edu/welcome/academics/graduate-degree-...

I don't know how it is in other schools, but at mine you can get a masters in CS even if you didn't do your undergrad in CS. They just have you take the core undergrad CS courses, which is about 1-1.5 years of work. With an ME, it might not even be that long. You should look into that before going for a second bachelor's.

the goal with having this tech on the phone that the phone won't need to communicate with servers to do this sort of processing?

Yeah, that's basically it. In short, the operations listed are pretty computationally intensive on a CPU, but pretty easy to parallelize for the data structures that are commonly used in machine learning (matrices and tensors). I presume that, by creating an API, Google can abstract out these common ML operations to work on the most efficient hardware on the device, whether a GPU or custom ML hardware such as Apple's Neural Engine. In theory, this should make on-device machine learning and inference more power-efficient, and could reduce reliance on server communication, improving privacy and probably making lightweight ML applications feel faster.

I think you may be conflating two ideas. You seem to be talking about green thinking, where most of the thread is talking about using automation to even out the grid when energy consumption is below minimum production levels, which may very well happen during the day and at unpredictable times in a solar-heavy grid. Sure, we can adopt green habits now (especially since negative prices are still a rare problem), but it doesn't actually address the discussion at hand.

Same. I've generally been pretty bearish on IoT appliances since the usual features seem to be a) contrived, b) net inconveniences, and/or c) primarily of benefit to commercial entities rather than consumers (i.e. buy milk reminders). This, on the other hand, is something that's difficult to do without automation and is pretty beneficial to everyone involved--the more I think of it, the more I like it. Really hope as negative energy costs become more of a "problem" we see manufacturers start drifting towards this use case.

Seems like a great IoT opportunity. Smart-appliances that are able to detect prices on a public energy marketplace, or receive a signal from energy companies, so that they can turn on their high-energy processes when the grid needs some evening out.

Also, not mentioned on that list is DJI, which is pretty dominant in the drone space, and it was only founded in 2006. I know it's not a software startup, but you'd be hard-pressed to say it's not a tech company.

I lived in Texas for a while and we had fire ants on our property every so often. One time I was taking out the trash, and a lone ant got on my hand, but was just wandering around aimlessly. I watched it for probably a full two minutes, and then completely out of the blue it decided to bite me. Only years later did I learn that the behavior you mentioned is what I was seeing.

I've been thinking about this a lot lately--I'd really love in-email applications, especially with Web Assembly working its way into viability. Being able to act on stuff without leaving my inbox would be fantastic. Unfortunately, lots of potential for abuse and also the fact that email protocol is so entrenched.

Here is a link to the actual CSS used on the blog post. https://github.com/ericdouglas/ericdouglas.github.io/blob/ma...

I'm gonna try pointing to the relevant CSS, but be warned, I am not a CSS wizard. I am also probably not a smart man, posting about CSS on HN while not being a wizard.

The relevant classes seem to be .sidebar, .sidebar-toggle, .motion-element, and .posts-expand, the last of which seems to control the transforms and durations. This is where my knowledge breaks down, since I'm not sure how they .sidebar or .motion-element trigger .posts-expand or any of the other animation CSS. Hopefully someone can help fill in the rest! ¯\_(ツ)_/¯

True to their tradition, the legal disclaimer on the announcement is about half as long as the announcement itself!

Nice, I never knew what it was called. Thanks!