Bhagavad Gita 3.17

*The Evidence Collection*

There is overwhelming evidence of election fraud. Therefore it is the duty of the Executive, Legislative, & Judicial branches to throw out the fraudulent votes & to honor their oath to protect & defend the Constitution of the USA.🇺🇸🦅

A list below.🔻

1/ Navarro Report: The Immaculate Deception - Six Key Dimensions of Election Irregularities -

2/ Analysis of 3,000 U.S. counties shows Joe Biden received 5.6 % more votes in counties using Dominion Voting Systems (Video) -

3/ Antrim Michigan Dominion Voting Systems Forensics Report -

4/ Evidence Grows: ’20 Election Was Rigged -

X : Our executive team is concerned that we need to up our game in order to out innovate Amazon.
Me : Do you map?
X : Yes
Me : Like this?
X : No. What's that?
Me : A map of a tea shop.

X : Why is that a map?
Me : Long story, all to do with how space has meaning. To keep it short, maps help people to focus on user needs, the components involved, to communicate missing components and scenario play ideas like staff becoming robots.

Me : They’re also good for measuring and managing capital flow, making investment decisions, removing bias and getting rid of duplication.
X : I don’t see how that helps with innovation?

Me : Well, innovation is a tricky word because we use it to describe many things. If you’re talking about differentiation with the adjacent unexplored then you’re experimenting in the “uncharted” space e.g. immortality with magic provided by the special custom built kettle.

X : That sounds like nonsense.
Me : A lot of what people think will be the next great innovation is nonsense. Actually, most of it is. That’s the nature of the uncharted space, it’s experimental, high risk and generally results in failure.
X : We need more reliable innovation.

Can we control the output of neural generation systems?
Can we build a better chatbot using this control?
And what makes a good conversation anyway?

Check out the blog post for our NAACL paper:

https://t.co/UAAUxSeA0L

#AI #NLProc #DeepLearning #ConversationalAI @facebookai

This post got a little delayed since the paper's publication, but the intervening time has given me an opportunity to reflect.

So this post has some extra thoughts regarding more recent NLG developments - e.g., pretrained models like GPT(2), and the suitability of beam search.