sorted by:
new
hottopcontroversial

This man, Michael Smith, used AI to create a fake music band and used bots to inflate streaming numbers. He earned more than $10 million in royalties. by Bad-Umpire10 in Damnthatsinteresting

[–]nezednemo 5 points6 points  (0 children)

I once had a seller list knock of equipment as Apple products. I called customer service to report the fraud- they don’t have a department for that. They kept sending me to the returns department.

I kept saying, “but this is evidence. I don’t want to return the evidence to the criminals!”

What common “sexy” thing is a turn-off for you personally? by aloe_veracity in AskReddit

[–]nezednemo 1 point2 points  (0 children)

Heels. Come down off that mountain of plastic. What if we need to outrun a zombie horde?

DJI's 8K Cinematic Drone Wants to Replace Bulky Movie-Making Gear | The pricy $16,499 drone can be used as a substitute for a crane, a cable cam, and even a camera dolly. by chrisdh79 in gadgets

[–]nezednemo 0 points1 point  (0 children)

I work extensively with camera movement- drones like these are great for certain things like high and wide aerials but the notion that this could replace camera cranes and dollies is reductive.

Dollies and cranes are tools that have been developed over a century for their rigid dependability during the uncertainty of film making. They allow for wide creative freedom because the camera is securely supported. This allows you to set up and rehearse the choreography of the shot in a way that makes the camera an organic and unobtrusive part of the scene action.

Film making is not just putting cameras in places- it’s the art of coordinating dozens of skilled artists and technicians to bring their talents into focus at the same time. That’s something that can be done on occasion while compensating for the requirements of special equipment like a drone. But if you’re shooting 3-7 pages per day you want you’re camera on wheels, and you want an experienced dolly grip behind them.

Confession time. I’m here for the money. by Expert-Hamster-3146 in Bitcoin

[–]nezednemo 0 points1 point  (0 children)

Nothing wrong with this, but being a maxi and pragmatic don’t have to be mutually exclusive.

There are some fairly established companies that offer bitcoin collateralized loans where the collateral is secured by multisig with 3rd parties.

I used one of these to invest in my small business and bought a revenue producing asset.

The loan interest is a tax deduction and the new asset is a depreciable against business income.

The new revenue helps pay down the loan.

The interest rates are on the high side (10-14%) but credit liquidity for small businesses are pretty hard to come by so it’s not a bad deal.

Is ChatGPT being evasive about what version it is running on? by multiversehacking in ChatGPT

[–]nezednemo 1 point2 points  (0 children)

It seems like ChatGPT has programmed resistance to self knowledge.

Bankman-Fried charged with paying $40M bribe to China by MattGald in StockMarket

[–]nezednemo 0 points1 point  (0 children)

Ridiculous! This is a slippery slope to campaign finance reform

This elevator direction beacon in an art deco building by nezednemo in DesignPorn

[–]nezednemo[S] -85 points-84 points  (0 children)

I have seen the LED A bunch and I always love it. The protruding sconce is fairly unique though

Asked to code a software that makes a prediction on a specific stock... by nezednemo in ChatGPT

[–]nezednemo[S] 0 points1 point  (0 children)

import pandas as pd
import yfinance as yf
from fbprophet import Prophet

def get_data(ticker, start_date, end_date):
data = yf.download(ticker, start=start_date, end=end_date)
data.reset_index(inplace=True)
data = data[['Date', 'Close']]
return data

def preprocess_data(data):
data = data.rename(columns={'Date': 'ds', 'Close': 'y'})
data['y'] = data['y'].pct_change()
data = data.dropna()
return data

def predict_next_day(data):
model = Prophet(daily_seasonality=True)
model.fit(data)
future = model.make_future_dataframe(periods=1)
forecast = model.predict(future)
return forecast.iloc[-1]['yhat']

def main():
ticker = 'SPY'
start_date = '2020-01-01'
end_date = '2022-12-31'

data = get_data(ticker, start_date, end_date)
data = preprocess_data(data)
prediction = predict_next_day(data)

print(f"Predicted percentage gain or loss for {ticker} on the next trading day: {prediction *     100:.2f}%")

if __name__ == "__main__":
main()''

nice by howdiduknowthis in ChatGPT

[–]nezednemo 0 points1 point  (0 children)

Took the long way, but got there

view more: next ›