
The Jim Rutt Show EP130 Ken Stanley on Why Greatness Cannot Be Planned
01:28:50
No Free Lunch Theorem
- No optimization algorithm excels at all problems.
- Specializing in some areas makes you weaker in others.
The Myth of the Objective
- Modern Western culture overemphasizes objectives.
- This hinders exploration and serendipitous discovery.
Pickbreeder and Unintentional Discovery
- Pickbreeder, an image breeding website, demonstrated how objectives limit discovery.
- Interesting images emerged when users weren't aiming for specific targets.
Get the Snipd Podcast app to discover more snips from this episode
Get the app 1 chevron_right 2 chevron_right 3 chevron_right 4 chevron_right 5 chevron_right 6 chevron_right 7 chevron_right 8 chevron_right 9 chevron_right 10 chevron_right 11 chevron_right 12 chevron_right 13 chevron_right 14 chevron_right 15 chevron_right 16 chevron_right 17 chevron_right 18 chevron_right 19 chevron_right 20 chevron_right 21 chevron_right 22 chevron_right 23 chevron_right 24 chevron_right 25 chevron_right 26 chevron_right 27 chevron_right 28 chevron_right 29 chevron_right 30 chevron_right 31 chevron_right 32 chevron_right 33 chevron_right
Introduction
00:00 • 2min
The No Free Lunch Theorem
01:54 • 2min
Is There a Guaranteed Right Answer?
03:55 • 2min
The Alternative to Open Endedness
06:08 • 2min
Getting Better and Better at Making Nails?
08:29 • 2min
Pickbreeder - A Very Interesting Example of Objective-Based Behavior
10:20 • 4min
The Art Generator
14:14 • 4min
The Room of All Images
18:08 • 3min
The Robotic Mouse in the Maze
21:09 • 3min
How to Solve a Maze Using Simple Algorithms
24:24 • 2min
The Chinese Finger Trap
26:36 • 3min
The Warning to Be Sceptical of Objectives in Life
29:10 • 2min
Innovation in the Business Technology Space
30:58 • 4min
Computers Are Not Planned
34:52 • 2min
Johnny Depp
36:48 • 2min
College Professors and Computers in the '80s
38:30 • 2min
Interestingness in the Book
40:24 • 6min
I Don't Give a Damn About Things That Aren't Interesting
46:10 • 2min
How to Trust Your Intuition
48:11 • 4min
Using a Novelty Search Algorithm on a Computer
52:39 • 2min
How Does a Novelty Search Work?
55:03 • 3min
Increasing Complexity and Information Accumulation Are Good Tells
57:34 • 3min
Is a Novelty Search a Good Idea?
01:00:23 • 2min
Using a Novelty Driven Search
01:02:34 • 2min
How to Unshackle Education?
01:04:18 • 4min
How to Foster Diversity Intentionally in a Systemic Way
01:08:13 • 2min
Is There a System of Peer Review?
01:10:19 • 3min
Is There a Risk-Reward Trade-Off?
01:12:51 • 2min
Education Is a Great Example of Social Innovation
01:14:52 • 2min
Is There a Meta Heuristic in AI?
01:17:01 • 4min
The Objective Fallacy Is Just Another Way of Trying to Be Objective
01:21:13 • 3min
The Journal of Artificial Intelligence
01:24:24 • 2min
The Myth of the Objective by Ken Stanley
01:26:41 • 2min
Ken Stanley and Jim talk about his wide-ranging book Why Greatness Cannot Be Planned: The Myth of the Objective...
Ken Stanley and Jim talk about his wide-ranging book Why Greatness Cannot Be Planned: The Myth of the Objective. They cover the no free lunch theorem, exploitations vs exploration, the myth & issues of objectives, the room of all images & adjacent possible, the problems & dynamics of deception, the power of serendipity, gradients of interestingness, intuition & novelty search, social change & innovation, emergent education & AI insights, incrementalism, risk & reward, Ken's unique journal idea, and much more.
Episode Transcript
Ken's Site
Why Greatness Cannot Be Planned: The Myth of the Objective
JRS: EP25 Gary Marcus on Rebooting AI
Ken Stanley leads a research team at OpenAI on the challenge of open-endedness. He was previously Charles Millican Professor of Computer Science at the University of Central Florida and was also a co-founder of Geometric Intelligence Inc., which was acquired by Uber to create Uber AI Labs, where he was head of Core AI research. He received a B.S.E. from the University of Pennsylvania in 1997 and received a Ph.D. in 2004 from the University of Texas at Austin. He is an inventor of the Neuroevolution of Augmenting Topologies (NEAT), HyperNEAT, novelty search, and POET algorithms, as well as the CPPN representation, among many others.
