Oh, you meant interaction as a joint training with images, actions, feedback etc. That would be the next generation I guess.
I am simply thinking of interaction here as similar to learning a language in a classroom. First the teacher provides sample questions/answers, then the teacher asks the students to come up with answers themselves, and tell them which one is better. The end result here is I think ChatGPT is quite good at answering questions and can pass as a human, especially if it's augmented with a fact database, so obviously wrong answers can be pruned.
It did, actually. The model was trained with multiple rounds of reinforcement learning where human judges provided the feedback: first with full answers, and then with ranking of answers as most relevant.
So the model in production is probably frozen, but before that it went through multiple rounds of interaction with the world.
Leverage. Call options at 2000 strike expiring on 9/16/22 cost roughly 1000 now. For each dollar GOOG goes up (or down), the deep in money options' price will probably move roughly one dollar in the same direction, as long as GOOG price doesn't go down too much. So instead of investing on 100 Google shares for 300K dollars, she can buy 3 call options (each call option is for 100 shares) for the same money and makes three times as much if GOOG goes up, and loses three times as much (or more) if it goes down: e.g., GOOG is under 2000 in 9/16, she will lose all 200K dollars.
Essentially, she's bullish on GOOG. She's also rich enough to take the risk to leverage 3 times. She's even more bullish on RBLX though.
This is sad. If the report is correct, Robinhood might be negligent here. I don't know if there's security law required, but Schwab has 4 levels of option tradings [0], and you'd need to apply and get approved. I've investing/trading for more than 10 years now, but they've only given level 0, and rejected my level 1 application. It seems this guy's trade is at level 2.
Everything is factored in the real estate price: the weather, the school district, the night life, the ethnic grocery stores, crime rate etc. and last but not least, the opportunity to change to a new job with much higher comp.
Real estate, while not as liquid as stock market, is quite efficient in my opinion.
> startups have tremendously high variance. Most startups are st. There's a few of them that are really exceptional, and if you land at an exceptional one, you can do really well. If you randomly pick something, you'll probably have a bad time.
Great words of wisdom. How does one find a great one though? Even for YC with their expertise and experience, most of the startups they fund are not great.
That just goes to show that Pearl's approach on causal reasoning is solid. Instead of looking patterns and correlation in data, one could consider building causal graphs from the domain knowledge.
So 600M is the upper bound. Drew Houston owns roughly 25% of the company now, and he probably owned ~75% at when YC invested, for a dilution rate of 3. I'd say YC investment probably has dilution rate of 10, for the real amount of 60M. Not bad, but not Whatsapp scale either.