In order for a program to be considered intelligent the following questions must be answerable with a ‘yes’.
Is the output of the program passable as human work?
Can the program cite sources inline and create a bibliography of works cited?
Can the program explain the reasoning behind its conclusions?
Can the program respond “I don’t know” when it doesn’t know the answer to a question?
Can the program explain its limitations?
Can the program propose a conclusion that is not present in the training data used to create it?
Disclaimer: I’m an AI novice and may be completely wrong about the conclusions presented in this article. Over the past few years I’ve dabbled in machine learning. I’ve watched introductory videos explaining the underlying concepts, trained an R/C car to drive itself using computer vision, generated art, and experimented with ChatGPT.
Case writes about why complex systems can seem stable, then suddenly collapse all at once and demonstrates how a concept called “attractor landscapes” can be used to understand what’s happening.
Why do many complex systems – cultures, environments, economies – seem stuck (or if good, “stable”) despite lots of effort to change them? And why, when change does come, it seems to cascade (or if bad, “collapse”) all at once?
There’s a tool that can help us understand this: attractor landscapes.
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So, the next time you’re wondering why things are stuck a certain way, think about:
What are the “attractors” of this system?
How “deep” are the valleys? (deeper = harder to escape)
How “wide” are the valleys? (wider = bigger range of attraction)
Can we not just move the ball, but move the hills? (changing the underlying system)
And if you ever find yourself frustrated by the world, remember: for many systems, for long periods of time, nothing much changes. Then, everything changes.
My #1 rule for ventures, especially with friends, is to create an “ejection seat plan” at the beginning. The ejection seat is designed to save friendships and prevent teams from holding on to ideas too long.
Write down a list of milestones that must be achieved in 1, 2, 3, and then every 3 months up to 48 months. Agree that either partner can choose to eject without blame whenever the milestones aren’t met. Agree how much equity will be retained in the event of ejection. Follow the plan.
I credit five inspirations for the ejection seat plan. (1) Tim Ferris’ “dreamline” concept from 4HWW, (2) news stories about “golden parachutes”, (3) my friends who learned this with me the hard way because we didn’t do it, (4) the Stripe Atlas guide to founders equity, (5) my friend who helped me validate that it can work.
Lots of people use Microsoft Project or similar tools to create and analyze project plans. Here is my checklist for creating a project plan in Microsoft Project.
Solomon investigates the hypothesis that companies allow Dilbert to be successful, and pay Dilbert’s author to speak at company events, because the cartoon conditions employees to accept a certain set of working conditions as normal so that they will not seek change. Who knows if it’s true, but it’s pretty interesting.
Asked at 11:00 how he would advise people that aren’t necessarily going into high paying fields Buffet recommends people do what they love. He makes a few notable observations:
A market system does not pay as well in some activities as might seem appropriate given the value of those activities to society
Many people make a fundamental choice between doing something they love or doing something to make money
He can’t recall speaking with someone who spent their whole life doing something they loved and wished in old age they’d made more money instead
The day-to-day reality of how he lives his life really isn’t that different from how most people in the United States live, except for the notable example of traveling by private jet (listen to him explain it because he’s more convincing on this point that I expected)
Asked about Welfare and Social Security at 51:51 (2nd to last question), Buffet challenges the students to think of the world as a lottery they’re born into and to think about what rules it might be worth having in place to take care of the people who draw an unlucky ticket.
On Sunday Freakonomics published an interview with Mark Zuckerberg as part of the Freakonomics series on CEOs and the role of CEO. The Q&A provides broader perspective on the Facebook mission and aspects of how Zuckerberg thinks about connecting people, data, and running a company. It’s interesting to hear Zuckerberg discuss data privacy before the Cambridge Analytica information operations story (the interview was recorded last summer). The full transcript of the interview is posted on the Freakonomics website in addition to the audio.
A few of my favorite highlights:
Information that filters to us through friends is more influential than increased ability to access raw facts
Deciding [as a leader] to let people do things that you disagree with, because on principle you know it’s just going to free up more creativity
Openness and connectedness is not enough to bring people together, a different strategy is needed to achieve “more open, connected, and together”
If the objective is massive change, empowering people is the only way because doing it alone is impossible
Facebook runs multiple versions of the website at any given time to test the impact of new features
“To keep our society moving forward, we have a generational challenge — to not only create new jobs, but create a renewed sense of purpose… by taking on big meaningful projects together, by redefining equality so everyone has the freedom to pursue purpose, and by building community across the world.”
In just under 33 minutes, the founder of Facebook walks through his positive vision of the future and describes the generational challenge facing Millennials built upon three key ideas:
Big meaningful projects
Universal freedom to pursue purpose
Global community
Zuckerberg explains that innovation is incremental and the overnight success is a myth. Ideas develop through iteration.
“I know, you’re probably thinking: I don’t know how to build a dam, or get a million people involved in anything. But let me tell you a secret: no one does when they begin. Ideas don’t come out fully formed. They only become clear as you work on them. You just have to get started… Movies and pop culture get this all wrong. The idea of a single eureka moment is a dangerous lie.”
We often measure an idea against an imagined state of perfection rather than agains real-world alternatives available today.
“In our society, we often don’t do big things because we’re so afraid of making mistakes that we ignore all the things wrong today if we do nothing. The reality is, anything we do will have issues in the future. But that can’t keep us from starting.”
Three quotes on the Millennial generation:
Millennials are already one of the most charitable generations in history. In one year, three of four US millennials made a donation and seven out of ten raised money for charity. But it’s not just about money. You can also give time. I promise you, if you take an hour or two a week — that’s all it takes to give someone a hand, to help them reach their potential.
I taught them [a middle school Boys and Girls Club] lessons on product development and marketing, and they taught me what it’s like feeling targeted for your race and having a family member in prison.
… and when our generation says “everyone”, we mean everyone in the world.
Contrast Dr. Zuckerberg’s view of Millennials with the pessimistic view Simon Sinek has popularized across social media. Contrast Dr. Zuckerberg’s vision of a global community with the pessimistic and isolationist view of President Trump. You’ll quickly understand why I’m betting on the Millennial Generation, and proud to be a part of it.
What should leaders and managers who are expected to serve the current IE graduates expect when they enter into the workforce? With three generations of leadership in place within industry, understanding best practices can be complicated. A panel session of various demographic industrial engineers and leaders assembled by the IISE-LA Professional Chapter to discuss their experiences, frustrations and best practices with this diverse and talented next generation and the expectations associated will address this new issue.
#HackForLA is active on #Slack and meets regularly at Civic Hack Nights. Participating in #HackForLA is a great creative outlet for community members that want to solve community challenges in a non-partisan way. Unlike many (maybe even most) nonprofit organizations, #HackForLA challenges people to volunteer their skills by finding ways to help move projects forward and deemphasizes donations.
Hack for LA brings coders, designers, entrepreneurs, students, government agencies, activists, and other civically engaged individuals together to solve the LA region’s biggest civic challenges.
Hack for LA is the official Los Angeles chapter of Code for America, a national nonprofit that believes government can work for the people, by the people, in the 21st century. At our weekly Civic Hack Nights, we organize groups of volunteers to build technology addressing the LA region’s biggest civic issues. We welcome technologists, government officials, designers, students, activists, entrepreneurs and community members to join us and collaboratively create a better Los Angeles.
