The video discusses the role of algorithms in shaping our digital world. Algorithms are responsible for deciding what content we see, how much we pay for a product, and even what videos we watch. They are used in various sectors, including social media, banking, stock trading, and more.
The video then delves into the creation of these algorithms, or "algorithmic BOTS". These BOTS are built by humans, but the complexity of many problems makes it challenging for humans to write simple instructions. Therefore, BOTS are designed to solve these problems.
The video introduces the concept of a "Builder BOT" and a "Teacher BOT". The Builder BOT randomly connects modules in the BOT's brain, while the Teacher BOT tests the student BOTS. The process involves repeated testing and building, with the best performing BOTs being kept and the rest being discarded. This process continues until a BOT emerges that can perform the desired task.
The video concludes by emphasizing that while we can guide these BOTS with the tests we create, we are increasingly in a position where we are used by tools that we do not fully understand. This is a reality we need to accept as we continue to rely on algorithmic BOTS in our daily lives.
1. Algorithms are used on the internet to bring content to users, such as videos and tweets .
2. These algorithms take note of user interactions, such as clicks and opening a tweet book .
3. Algorithms are also used in banking to monitor transactions and detect fraud .
4. The stock market is full of algorithms trading with each other .
5. Algorithmic BOTS are built by giving them instructions that humans can explain .
6. Many problems are too big and hard for a human to write simple instructions for, leading to the creation of BOTS .
7. There are a gazillion financial transactions a second, and ones that are fraudulent .
8. There are octillion videos on YouTube, and it's impossible to tell which ones a user should see as recommendations .
9. Algorithmic BOTS give answers to these questions, not perfect answers but much better than a human could do .
10. Companies that use these BOTS don't want to talk about how they work because the BOTS are valuable employees and their brains are built as a trade secret .
11. The current hotness is on any particular site and how the bots work is a bit at an l and a waves will be so .
12. To get a bot that can do this sorting, you don't build it yourself. You build a bot that builds BOTS and a bot that teaches bots .
13. The teacher BOTS can't tell a bee from a three, but the human gives teacher bot a bunch of B photos and three photos and an answer key .
14. The teacher BOTS can test the student BOTS, and the student BOTS that survive are just lucky .
15. By combining enough lucky BOTS and keeping only what works, a student bot will eventually emerge who can tell a bee from a three in a photo .
16. The wiring in the student bot's head is incredibly complicated and while an individual line of code may be understood, clusters of codes general-purpose vaguely grasp the whole .
17. The student bot is very good at exactly only the kinds of questions it's been taught .
18. The human overseer can do is give it more questions to make the test even longer .
19. Companies are obsessed with collecting data more data equals longer tests equals better BOTS .
20. When you get the are you human test on a website, you are not only proving that you are human, but you are also helping to build the test .
21. Building a test for figuring out what's in a photo or on a sign or filtering videos requires humans to make correct banoffee tests .
22. There is another kind of test that makes itself, tests on the humans .
23. The student bot gets to be the algorithm because it's point one percent better than the previous bot at the test the humans design .
24. Behind the scenes, there are tests to increase user interaction or set prices just right to maximize revenue .
25. If it's testable, it's teachable .
26. We are increasingly in a position where we use tools or are used by tools that no one not even their creators understand .
27. We can only hope to guide them with the tests we make and we need to get comfortable with that as our algorithmic bot