I've seen him give this great talk before, but IMO the delivery this time feels rushed and a bit disjointed. That said, the last few minutes summarize his powerful "Gretzky Game" idea so succinctly that they're worth the price of admission alone.
I would recommend watching the last 18 seconds of this version (starting at https://youtu.be/ZDM33CMJvp8?t=3452), internalizing the Gretzky Game slide on the screen, backing it up and watching the fuller explanation in the preceding ~3 minutes (starting at 54:18, https://youtu.be/ZDM33CMJvp8?t=3258), and then finally watching a different, more expansive version of the talk like this one, given at Qualcomm: https://www.youtube.com/watch?v=NdSD07U5uBs.
Oddly specific advice, I know, but hopefully helpful to somebody.
Now this right here https://www.youtube.com/watch?v=NdSD07U5uBs?t=1362 is the problem: if you follow the idea of computers as virtualisers where it leads you do not, in the general case, end up with the flat backplane talked about from 23:15 and shown in the accompanying slide. (Actually, this is in turn probably just a symptom of another, more general problem.)
I just realized where the 'V' logo in "Viewpoints Research Institute" came from (you can see it here: [0]):
The diagram comes from the book "The Act of Creation"[1], where Arthur Koestler discusses the common themes in creative acts, including the idea of juxtaposition.
In research, you start with a baseline level of knowledge and do a random walk until you encounter a (not necessarily) totally orthogonal set of ideas. Once you combine the two, boom! Something new is created. A lovely book, that I'd recommend to anyone.
I like the philosophy of going out into the future and bringing it back into the present. I feel like a lot of startups are making an error in failing to do this.
For example, in the not-to-distant future, we won't need parking spaces. You'll just hail the self-driving car (or similar) using your phone. People won't own their own cars.
So if your startup is designed to help people get parking spaces, how much potential is it really going to have? Probably not much.
Similarly, the internet is transforming education. Information is everywhere. A startup focused on helping kids get into college feels a little shortsighted to me. It might provide a useful service to some people today in the context of present challenges, but there's no way it's going to turn into a unicorn.
Anything related to helping people find jobs is also probably a non-starter. Do you imagine a future in which we need everyone to contribute to the extent that it's worth paying them what today we would consider a "fair salary" for their labor? I certainly don't.
Take the salary part out of the job and maybe you have something. What about a platform for helping people find interesting ways to spend their time?
Take the college part out of education and all kinds of possibilities open up. For that matter, take the job training part out too. I've become pretty disgusted as Udacity, Coursera, and edX have gradually shifted toward teaching people "career skills." There are still some good MOOCs out there, but you have to wade through all the "learn these skills to make more money in your career" crap.
What about a platform to foster pure intellectual curiosity? That's what I was hoping these MOOCs would be.
> like the philosophy of going out into the future and bringing it back into the present. I feel like a lot of startups are making an error in failing to do this.
> For example, in the not-to-distant future, we won't need parking spaces. You'll just hail the self-driving car (or similar) using your phone. People won't own their own cars.
You are right about the philosophy. But a thought regarding your specific example: even if self-driving tech were to be available tomorrow, it will take many years for all the cars (the "fleet") to be self-driving. There are about 2B cars on the road, and every year about 100M new ones are made. It would take 20 years to replace the fleet. So the "parking problem" isn't made immediately redundant with the invention of self-driving tech. There is still room (and in my opinion) worthwhile for a startup to solve the parking problem (however they attempt to solve it). Just saying that I wouldn't discourage anyone from attempting this :)
Dr. Kay might also observe that this is an instance of problem solving, which he associates with incrementalism (since the context is already understood), while inventing the future is about problem finding, which requires creating a new context.
That's a good point. I agree with you that, in the short term, there's going to be use for solutions to the parking problem. But how big can it really get?
It's not just self-driving tech. It's the ride-hailing paradigm in general, which the self-driving tech makes incredibly cheap. As soon as it becomes more cost effective to use ride hailing services than to own your own car, those 2 billion cars will all leave the road basically overnight.
We're not going to have to wait for the old cars to die.
> For example, in the not-to-distant future, we won't need parking spaces. You'll just hail the self-driving car (or similar) using your phone. People won't own their own cars.
Why won't people want to own cars? What if people want to drive for the fun of it, or do not care to use self-driving cars? what of motorbikes or even regular bicycles?
In the future people could lounge at the pool all day and have everything done for them by robots.
> Why won't people want to own cars? What if people want to drive for the fun of it, or do not care to use self-driving cars?
Some people will undoubtedly want to pay extra to drive their own car for fun. I imagine that having a driver's license will be like having a pilot's license today.
> what of motorbikes or even regular bicycles?
A bicycle is a lot cheaper than a car, so I imagine that more people will be riding their own bikes than driving their own cars.
> In the future people could lounge at the pool all day and have everything done for them by robots.
Yup. Except for the stuff they want to do themselves.
I think you're "right directionally" (i.e. solve for global optima, not local ones), but you must absolutely consider timing. It's fairly easy to dismiss ideas because they're not going to be the "end game" for humanity, but overlook many viable business opportunities that will be temporary on our way there, but still very profitable.
Moore's law can predict the future, but just predicting the future is probably better as you point out. If only you were right in the same way Moore's law is right.
1. Live in the future: If you live in the present your ideas are going to derived from the present, and therefore will be incremental. Paul graham points to a similar idea in his essay here http://paulgraham.com/startupideas.html
2. Learn the rules and break them like pro: An important idea that says learn deeply about a field (industry or language or medium - whatever) before you go about breaking its rules. This is something that should be discussed more. On one hand, this implies that rules need to be broken carefully by understanding something very well. On the other hand, a certain "naivete" also has been proven to be successful (As he himself says in another portion of this talk). Requires more thinking...
I have to say that I have worked with two geniuses who changed industries (caused a "Disruption"), but while they were "outsiders" they understood the industry they were changing very deeply, and could point to very specific flaws in them (legacy rules) that were ready to be broken.
3. Scientists and engineers working together: I love this specific idea. He points to the Manhattan project and the Radar project as successful examples (and ofcourse, Xerox PARC itself). I also understand why OpenAI is organized the way it is -- they must have taken inspiration from Alan's ideas.
4. Progress is the only important thing: This is very similar to YC's idea of have a metric and grow it by X% week over week. One of the big things (IMHO) that YC cracked was to find way to fund hard tech problems, using this very specific idea that worked very well in software. Break a big problem into small parts and show progress on it every week/month/quarter etc. It is a simple and elegant way to think (and work).
5. Advance something very important: This idea is dedicating your life to an important goal / problem. This idea stirred me the most (for personal reasons). This especially rings true for me, esp when I meet someon who found "overnight success" after toiling aways at something for 10-15 years. This idea requires a lot of reflection. Alan says: "Fix big human problems"
6. Argue for clarity, not to win: An amazingly simple yet powerful message. So much of our interactions would be better if we (if I) did more of this.
3 Sidenotes:
a) I wish he had answered the question about "What caused the regression?" that someone asks (I think Sam) after watching a demo of an early "iPad" from the 1960s. It is really important to understand this. Elon Musk often says that tech advancements don't just happen automatically, some group of smart people need to work together to make it happen. I think something happens that governments, VCs, technologists stop working on advancing tech in some areas. Some of it is explained by lack of a "great adversary" (WW II, Cold War etc), but still it would be great to understand this very deeply. Thiel's famous book also talks about regression in tech, without fully explaining it. It is an important observation, that merits a deep discussion. I would be curious to hear what Alan says. Maybe @Sama can fill in (?)]
b) Special mentions to two ideas, not because of the ideas, but because how he puts them. a) "Fund people not projects" (basically how early stage funding works) - but Alan says, these are "artists are people who do their art because they must". And b) While talking about "build your own tools if you have the chops" he says "...Otherwise you are working the past on some vendor's bad idea of what computing is about". I love how he puts these thoughts across.
c) I recommend the video @_pius links to in the comments: it is called "the power of simplicity". One of the great Alan Kay talks.
Excellent summary. Covers all the key points that I wanted to take away and put it so much better.
For me, the theme that runs through his work and talks is this: (Constantly ask) How to make use of computers to learn and create in ways better than we do currently?
Now yes, the above sentence seems like incremental and not so far out but lot of what he and some of the people he has worked with is trying to answer this.
And I completely agree with him that we haven't fully explored this new digital interface and in some ways have regressed.
His words are truly inspirational and at the same time it is slightly disheartening that I am not working on something great.
Crossposting question from other thread: What's the "Visions: Cosmic and Romantic" that's referred to around 36 minutes into the video? Google doesn't turn up anything.
When Kay says (paraphrasing) 65% of your errors are overhead, he's talking about the difference between say baseball's batting averages and golf.
A batting average of .333 (you hit one ball for every three throws) is considered very good. But you're missing two out of three.
In golf, one wrong swing can ruin you.
The point is, when you're doing new things you should be failing often. If you're not you're playing the wrong game.
(I watch many more Alan Kay videos than I do sports, so I hope I'm describing baseball and golf accurately.)
Alan is saying that in baseball there is a distinction between "failures" and "errors".
In the non-baseball use of the terms, a "failure" would be interpreted as a bad outcome, but in baseball as in research, "failure" is inherent to the game and should not be seen as an embarrassment or a negative outcome. A very good baseball player gets on base only 33% of the time. A very good researcher may fail dozens of times for any eventual success.
Conversely an "error" is when you fail to do something that is technically feasible but you fail to achieve it because of a personal mistake. In baseball an "error" would be an outfielder who misses catching a fly ball. Fly balls are caught 98-99% of the time by professional players, and it's expected that they can catch one anywhere in their area of coverage. A researcher should be able to achieve any outcome which is "technically feasible", such as creating a new software language, creating a new operating system, or creating a new hardware integrated circuit if necessary.
To sum up his statements; Failures in research should be expected, embraced, and motivating. Errors are the real problem, and point to an inability to achieve outcomes which are feasible. And if you are achieving ALL your research goals without any failures then your goals are not big and challenging enough.
A baseball error in fielding is when you drop a fly ball, or miss catching a pass. This happens very rarely, maybe 1-5 times per game (or succeeding ~98.5%).
This is because you're doing something easier, catching a ball. Hitting one though, is very difficult (~20-30% is where most professional players are).
He says the design task is much more difficult, and failure should be seen as overhead for part of the process (i.e. R&D process should be failing often, engineering & delivery process should be succeeding in making software ~98.5% of the time).
I continue to see comments on HN hypercritical of Apple's cash position but I have yet to see any rational or deep thoughts about why it's NOT a good idea for a company or individual's for that matter to have such savings.
You never know what's going to come along in the future, and having a sizeable cash position allows them to act and perhaps hedge against any unforeseen situations. It is really just being financially responsible. Hypothetically what if Apple is planning something huge, something in the healthcare space or transportation... We as outsiders have no idea.
I don't think OPs post was hypercritical of apple's cash position. It simply reinforces the notion that big companies can't use the cash effectively.
To call it hypercritical of apple isn't exactly accurate. It's simply reality. Apple may even be acting more effectively than most by keeping the cash in reserve. You might imagine they're waiting to spend it intelligently and effectively rather than on a slow-moving corporate machine.
As a shareholder I'd approve of such a strategy 100%.
All the comments here about Kay's presentation media are missing a key point... Let's put aside any subjective assessment of whether or not the slides are good or bad. The more interesting thing is how they're made. They're made with a tool in the Squeak Smalltalk environment. I didn't watch this particular presentation but I've watched others Kay has done and the things he's doing with his slides simply aren't possible with PowerPoint or KeyNote.
My guess is he's being covertly meta about his presentations because he really never gets into any detail about the tech he's using to create his presentations.
Unfortunately, to my knowledge, the package he uses for his presentation is not openly available.
It increases friction, even if it doesn't come pletely block communication. In that case, it is similar to an avoidable performance-affecting design flaw that doesn't impact the correctness of th eventual result.
"First of all, that's completely wrong, especially when it comes to startups."
Are you saying his presentations are some kind of startup? It is completely right that aesthetics don't really matter for his presentations. In my experience, aesthetics only matter when trying to sell turds as diamonds. People will use useful things, regardless of aesthetics. Sadly, they'll also use useless things because of aesthetics.
> aesthetics only matter when trying to sell turds as diamonds
When it comes to printed (or any kind of graphical) communication, form and function are very closely tied. The vertical text at 23:15 is (at least to my western eye) super distracting and hard to read, and I have no idea what I should be looking at on the screen.
Aside from the obviously messed up slides, I think everything there was pretty readable. I think odd layouts might actually help remember the content. When you mention the vertical text slide I can picture it almost perfectly in my head. If it had been just another evenly spaced, clearly typed bullet list among 50 others just like it, I would have a harder time recalling it. However, there is a time and place for aesthetics and that's after the functionality has been clearly established, since he's been giving essentially this same talk for tens of years, he probably could put a bit of time into the slides :)
I would recommend watching the last 18 seconds of this version (starting at https://youtu.be/ZDM33CMJvp8?t=3452), internalizing the Gretzky Game slide on the screen, backing it up and watching the fuller explanation in the preceding ~3 minutes (starting at 54:18, https://youtu.be/ZDM33CMJvp8?t=3258), and then finally watching a different, more expansive version of the talk like this one, given at Qualcomm: https://www.youtube.com/watch?v=NdSD07U5uBs.
Oddly specific advice, I know, but hopefully helpful to somebody.