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architectonic
·6 माह पहले·discuss
Yes and another that uses a fixed ridiculous combination like 1 2 3 4 5 6 7 8 9. This is my favorite way for bringing the odds nearer to mind.
architectonic
·8 माह पहले·discuss
Yes I can confirm that,we had resorted to a multilingual embedding model back in the day. https://link.springer.com/chapter/10.1007/978-3-031-77918-3_...
architectonic
·9 माह पहले·discuss
How much computing power would one need to get this working completely local running a half decent llm fine tuned to sound like santa with all tts, stt and the pipecat inbetween?
architectonic
·10 माह पहले·discuss
I enjoy this AI generated album https://open.spotify.com/album/6C6PJzxkHctvk1ibKM2zMx?si=YgL...
architectonic
·पिछला वर्ष·discuss
How do the quality and prompt adherence compare to Suno v4?
architectonic
·2 वर्ष पहले·discuss
I have created a simple geogebra Applet applying your method step by step: https://www.geogebra.org/m/enztf4s6
architectonic
·2 वर्ष पहले·discuss
That's called the stability of the algorithm. The first algorithm is not stable whereas the second with the logarithm is.

Another example: compare the two algorithms, that are actually pure-mathematically equal:

  def fc(x): 
      return sqrt(x+1) - sqrt(x)
  def fd(x): 
      return 1/(sqrt(x+1) + sqrt(x))

For large values of x (1e16 for example) plot the results and see the difference.

  xs = np.linspace(10\*14,10\*16,10000) 
  plt.figure(figsize=(8, 6), dpi=120) 
  plt.plot(xs,[fc(x) for x in xs]) 
  plt.plot(xs,[fd(x) for x in xs])