10. Virus 
Tried airplane mode, then switched hub off at the wall. No effect. When the laptop was used, same thing – Ivan says it is light. Wise Ole Techie once observed of me: ‘Man who likes conspiracy theories will always find the answer he seeks.’
Just entered day seven.
6. Guess which member of the team sent this one along
5. Virus 
Really have to do this one and sad if you can’t access it. I’ve a limited time at the screen, it’s burning into the point in the throat, my eyes and fingers, so this will be quick.
This thread is amazing. What a case study in using bait (Roger Stone) to clear out 4 corrupt prosecutors, 1 corrupt US DC Attorney (Lieu), expose a corrupt DC judge (Jackson) AND expose a deep state plant juror (Tomeka Hart) in one fell swoop. #StableGenius 😎 https://t.co/fekxLSTOcK
— ConservativeMom ⭐️⭐️⭐️ (@conservativma) February 13, 2020
I’ll need to rely on you to get access to Tucker Carlson’s report below, it’s truly a must watch.
My concession to the saccharine day for those still in the game, especially long term spouses, this day is for you:
During my time in Russia, they didn’t initially have a grip on what this ‘American’ ‘holy’ day was about but I’d say neither do the Americans and isn’t it German anyway?
Are the biggest big tech companies monetizing their big datasets? I think the answer in 2020 is ‘sort of’, and doesn’t involve particularly advanced statistics.
At amazon, even really good product recommendations aren’t (I suspect) driving sales growth more than fast shipping.
For FB & G, my ML questions are:
Does ML improve the quality of their core offering (search for G, feed for FB)
Does it improve the performance of ads? (for any stakeholder)
Does it enable development of new things that diversify their product offering
For me, the answers are no, maybe, and no. G search has gotten worse as they’ve focused on recency in the index, gotten more tolerant of synonyms, and gotten less strict about quoted phrases. And no, they haven’t diversified – their core revenue stream is still ads and in G’s case that income may be drying up.
Machine learning, eh?