Blog Posts

April 21st, 2023
  • Machine Learning
  • Speculation

What are we going to do when the machines are better than us at everything?

Pace of AI has been insane. Humans have challenges. Health, alertness, impairment, dietary needs, bathroom breaks, repetitive strain injuries etc. Robots just go as long as the electrons flow. But what about the mind? Certainly, we will be more creative than the robots, right? Nope. Not only can a program generate art in seconds (what […]

April 20th, 2023
  • Tesla

3 Ways Tesla Can Advertise Without Giving Money to MSM

April 5th, 2023
  • Code Fun

Flag to Top

Objective: Get flag to top. MVP pieces needed: Additionally:

April 4th, 2023
  • Machine Learning

Notes for – Building makemore Part 5: Building a WaveNet

Homework:

March 30th, 2023
  • Midi
  • Music

Test01.mid

March 29th, 2023
  • Speculation
  • Tesla

Is Tesla building a fleet?

If you look at Tesla’s quarterly numbers, lately you can see that lately, the gap between production and deliveries is widening. Undelivered cars are increasing. There have been explanations for this. ie: The cars are en route to customers, there aren’t enough ships to transport them all. The end-of-quarter push no longer makes sense. Perhaps, […]

March 27th, 2023
  • Machine Learning

Notes for – Building makemore Part 4: Becoming a Backprop Ninja

makemore: becoming a backprop ninja¶ swole doge style In [52]: # there no change change in the first several cells from last lecture In [53]: import torch import torch.nn.functional as F import matplotlib.pyplot as plt # for making figures %matplotlib inline In [54]: # read in all the words words = open('names.txt', 'r').read().splitlines() print(len(words)) print(max(len(w) for w in […]

March 24th, 2023
  • Machine Learning

Jungle Beats

I could have the baddest jungle beats. Why do I not have them yet? Because I have not trained my neural net.

March 21st, 2023
  • Investing
  • Machine Learning
  • Speculation
  • Tesla

Tesla Stock Prediction 2023-03-21

In [483]: # This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python # For example, here’s several helpful packages to load import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) # Input data files […]


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