How to Invent the Future II - Stanford CS183F: Startup School

Xerox made a ROI of 20000% on the laser printer alone [1]. A better version lecture Alan did for Ycombinator startups [2] but doesn't focus on the return of investment. Xerox did shrink a bit since then. [1] link [2] ▶ this video

I'll repeat my answer to the previous iteration[1] of this question from a couple of weeks ago: ---- You might find something of use in some of this stuff: link link link link link link link ---- In addition, the two videos on "How to Invent the Future" by Alan Kay might be inspirational to you (or anybody else thinking about this topic): Part I - link Part II - ▶ this video Actually, this entire playlist is quite interesting, even if you're not looking to launch a startup right now - ▶ this video [1]: link

If I was really truly stuck for an idea and could not get anything to pop into mind, here's something I might try: Apply the "take an old idea and reinvent it in light of newer discoveries, new technology, or in application to a new problem" approach. To do that, read about old ideas in some area of interest to you, that didn't catch on, or were abandoned for whatever reason. Use Google, Wikipedia, Sci-hub, old print magazines, old newspapers, whatever it takes. Look at things through a lens of "Could I resurrect this idea with a new twist that wasn't available when it was first proposed?" Do that for enough "things" there's a chance it'll spark something. Extra hint: if you're looking for a startup idea specifically, Google for one of the multiple lists of "startup ideas that never work" that are out there. Of course it should go without saying to be very cautious about jumping into a project where many other people have failed with the same idea: there's probably a good reason for their failure. But IF you can find a new angle or hook that's "just right" maybe you can succeed. Or the whole exercise may actually bring a completely different idea to mind. Try to be open minded with this stuff. Also, find the two video series[1][2] that Alan Kay did on "Inventing the Future" and watch those. He shares a lot of great ideas in those. [1]: link [2]: ▶ this video

Counterpoint is that they picked one thing (laser printing) out of the dozens of ideas coming out of PARC and capitalized on it to the point that they were found to be a monopoly [0] and forced to license their patents [1]. Watch Alan Kay's "How to Invent The Future" talks from Stanford about this [2] and he talks in more depth. I don't think any company could have built products around all of the ideas that came out of there and been successful, they would have been focused on too many things. [0] link [1] link [2] link and ▶ this video

I don't know that I can say I'm particularly good at this, but to the extent that I do have any original / good ideas, I think a big part of it is this: 1. Know at least a little bit, about a lot of stuff. 2. Know a lot about at least a few things. 3. Constantly trawl for new "stuff" (eg, read books, magazines, the web, watch documentaries, etc.) 4. Think about how to combine different bits of the "stuff" you have in your head. Take notes, write down lots of ideas, even if they're dumb at a first glance. Keep chewing on things, and eventually the penny drops and you see some connection between things that makes sense. 5. Related to that, and I don't do this well enough myself, is "spend a lot of time thinking about the kinds of problems people have". I've read a few books on creativity / innovation / etc., but I'm not sure I can say any of them specifically helped, although a few of the ideas may have been useful without my being consciously aware of it. I read some of the Lateral Thinking book and I vaguely recall thinking it seemed somewhat useful. YMMV. link I also recommend Alan Kay's video series on "How To Invent The Future". Part I: link Part II: ▶ this video Another thing: I think sometimes ideas come out that are "ahead of their time" and seemingly die on the vine, or just get left behind. But sometimes when the environment changes, those ideas become ripe to get re-invented. There's a book title Rethink that sorta deals with this idea. link Anyway, I think there's

Yeah, I think you have a point. I'm not sure existing data is enough to generate ideas about all potential new products though, since behavior is shaped by what things/ideas/knowledge we have access to today. That is, what data is going to tell you that somebody wants a product that they can't even imagine yet? So I'd think consumer behavior data / demographic data / etc. is a useful guide, but I'm not sure it's sufficient in and of itself. All of that said, Alan Kay said something interesting in a set of lectures[1][2] he did a year or so ago. He brought up the idea of basing new product ideas on "Human Univerals", or universal aspects of human nature that really don't vary. A writer named Donald Brown wrote a book literally titled Human Univerals [3] which catalogs a number of these (a lot of them are pretty obvious though: food, shelter, sex, etc.). Kay suggested reading this book, pick one of the human univerals, and figure out a way to use technology to address that. [1]: link [2]: ▶ this video [3]: link

>Please elaborate I'd love to but what do you want me to elaborate on? We started making EDA tools and simulators (CAD, SYM FAB as Alan Kay says) and designing a wafer scale integration to run parallel Squeak Smalltalk (David Ungar's ROARVM) in 2007 and we are still working on it in 2024 so I estimate 30,000 hours now. I call that very ambitious too. >Also, have you checked out the OpenROAD[1] project? It’s a pretty impressive No it is not pretty impressive EDA software, OpenROAD software quality is like Linux, " a budget of bad ideas" as Alan Kay typifies it. Openroad is decades old sequential program code, millions of lines of ancient C, C++ and bits of Python programs written in the very low level C language, riddled with bugs and pathes. The tools are bolted together with primitive scripts and very finicky configurations and parametric rules. Not that the commercial proprietary EDA software is any better, that usually is even worse but because you don't see the source code you can't see the underlying mess. Good EDA tools should be written by just a few expert programmers and scientists in just a few thousand lines of code and run on a supercomputer. So the first ambitous goal is to learn how to write better software (than the current dozens of millions of lines of EDA software code). Alan Kay explains how [1-3]: [1] link [2] link [3] ▶ this video The second ambitous goal is to (learn to) design ultra low power transistor and free space optics. Learn from the best quantum

Kay himself does regularly describe the Arpanet as one of the inspurations for OO, and the modern interbet browser as an incomplete implementation of the same ideas: ▶ this video

Location: Europe, Brazil Remote: preferred Technologies: Custom Supercomputers (always cheaper than existing hardware, especially Wafer Scale Integration running on solar, starting at $100K), P4/openflow proframmable terabit linespeed routers, custom chip design and IP, custom terabit optical internet and solar battery energy providers, EV chargers and datacenters, Smalltalk and other late bound encapsulating object languages, massively parallel distributed message passing VM's, compilation and load balancing adaptive JIT compiling to bare metal, FPGA, ASIC and wafer scale integration, million core reconfigurable processors. Single app program bit-identical VM software, deploy on most platforms with native GUI. Cheap independent scientist and inventor, can do research on demand and publish papers Resumé/CV: link link and papers on request link email: morphle at ziggo dot nl +31 6 1742 8596 Whatsapp, Signal, Facetime, Skype I built the first internet provider, built chips, built the next generation Enernet (decentralized peer-to-peer internet for Energy). Its faster to have an interactive chat than for me to write about our methodologies, list all my skills and predict what our community of scientist and programmers can do for your startup or company. We built entire software and hardware systems from scratch because that is faster, cheaper and quicker time-to-market than using legacy operating systems, as described by Alan Kay in the YCombinator Startupschool lectures a

Alan Kay had an interesting talk about designing for the future. One part was on building a company to appeal to basic instincts vs creating tools and systems to benefit people. ▶ this video There are universal human traits that have negative impacts on people over the long-term but are craved during the short-term. These are like legal drugs. If you can use a few of these traits and tie them to an addictive feedback loop, then you probably have a product that's successful (and totally evil). It's concerning that some of the bestselling books in the startup bubble are about how to create these addictions in people. It would be nice if there were more tools and systems companies for helping humanity grow. I guess most modern day big companies are like a mix of the two. For every major social network there are usually some awesome engineering tools that get open sourced. It's harder to create a tools only or systems only kind of company but they're definitely nice since they expand the way we all think.

I don't think there's one simple, straight-forward, cookie-cutter answer to this. There are a lot of different ways you could approach this, depending on ... stuff. But to start... I would say you should begin not by thinking in terms of identifying a problem, but by thinking in terms of identifying a candidate problem. That is, some hypothesis that you can then turn around and try to validate. (I won't get all Popperian here and point out that you can really only invalidate hypotheses, but instead will just lean on our intuitive notion of what it means to validate a hypotheses). Once you have a candidate hypotheses (or two, or three, whatever) there is a somewhat straight-forward process for how to validate it and (potentially) turn it into a business. That process is laid out and explained in The Four Steps to the Epiphany and The Startup Owner's Manual . Anyway, back to our "candidate hypotheses". The most obvious way to generate one is from personal experience. Eg, if you have worked as, say, a surgeon, you will probably already know a lot about what problems surgeons face. OTOH, if you think you want to sell to a certain domain, but you don't have actual experience in that domain, you could make it a point to cultivate personal relationships with people who are in that domain, as well as doing a deep-drive into "the literature" of that domain, taking classes, watching videos, etc. But at the end of the day, if you're going to try to build a business selling something to,

. Internet was still relatively new. I mean, if your approach is "find problem, add Internet, equals solution" then yeah, you're probably going to find it a tough row to hoe these days. But I'd challenge you to broaden your thinking and be more imaginative. There's a lot more to creating solutions that "mix in some Internet". Think about the staggering array of things you can do today, with almost no up-front investment at all, using AWS, GCE, Azure, etc., that would have cost millions 20 years ago. You can deploy a virtual super-computer running in AWS and throw it at a problem for crying out loud. Consider too the range of awesome open-source / free software packages that are out there, and all the capabilities they enable. Consider cheap, small, embeddable single-board computers, inexpensive software-defined-radio, cheap webcams, accelerometers, gps chips, and other sensors. Consider all the Open Data that's out there already, and everything streaming in minute-by-minute (see, SDR and receiving satellite data right off the air in real-time). Consider the 8+ billion people in the world who are mostly all potential customers given how interconnected we are with the internet and global payment systems. Look at how much easier it is now to get content in front of potential customers with Facebook, Reddit, Twitter, Google, LinkedIn, etc. Consider that you can prototype a physical item with a cheap 3D printer, using Open Source OpenSCAD software, ship a prototype off to an injec