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The answer is artist Will Hulsey...
Will Hulsey was the undisputed king of the animal attack pulp cover. You name it, he'd paint it attacking you in a pool of stagnant water.
Very little is known about Will Hulsey, but he worked on a number of men's pulp magazines in the 1950s and early 1960s including Man's Life, True Men, Guilty, Trapped and Peril.
Their audience was ex-GIs: during WWII the US Council of Books in Wartime had given away over 122 million books to American servicemen to read; this led to a post-war surge in paperback and magazine sales amongst these newly enthusiastic readers.
As a result the 1950s saw a raft of men's pulp magazines being published to tap into this market - almost 200 different titles!
I'll begin with the ancient history ... and it goes way back. Because modern humans - and before that, the ancestors of humans - almost certainly originated in Ethiopia. 🇪🇹 (sub-thread):
The famous \u201cLucy\u201d, an early ancestor of modern humans (Australopithecus) that lived 3.2 million years ago, and was discovered in 1974 in Ethiopia, displayed in the national museum in Addis Ababa \U0001f1ea\U0001f1f9 pic.twitter.com/N3oWqk1SW2— Patrick Chovanec (@prchovanec) November 9, 2018
The first likely historical reference to Ethiopia is ancient Egyptian records of trade expeditions to the "Land of Punt" in search of gold, ebony, ivory, incense, and wild animals, starting in c 2500 BC 🇪🇹
Ethiopians themselves believe that the Queen of Sheba, who visited Israel's King Solomon in the Bible (c 950 BC), came from Ethiopia (not Yemen, as others believe). Here she is meeting Solomon in a stain-glassed window in Addis Ababa's Holy Trinity Church. 🇪🇹
References to the Queen of Sheba are everywhere in Ethiopia. The national airline's frequent flier miles are even called "ShebaMiles". 🇪🇹
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The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.
They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.
When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.
Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.
It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
Published a new essay: The red flags and magic numbers that investors look for in your startup’s metrics – 80 slide deck included!
This was a deck that I created on my (longish) interview process with @a16z. It was a long path, starting with meeting folks at the firm 10 years ago. But the purpose of the deck was to explain how I would use my superpower in an investing context
Here's what I explain in the deck. As investors (whether angel or VC) we're often confronted with an up-and-to-the-right graph. Is it going to go up? Or down?
One solution to forecast these growth curves is the Growth Accounting Framework, where you add up New+Reactivated and subtract churned users. In each time period that gives you the difference in monthly actives.
The problem with this is that it's a lagging metric, not a leading one. We need to go one level deeper and look at the underlying loops that drive these numbers, to understand the quality.
Please add your own.
2/ The Magic Question: "What would need to be true for you
3/ On evaluating where someone’s head is at regarding a topic they are being wishy-washy about or delaying.
“Gun to the head—what would you decide now?”
“Fast forward 6 months after your sabbatical--how would you decide: what criteria is most important to you?”
4/ Other Q’s re: decisions:
“Putting aside a list of pros/cons, what’s the *one* reason you’re doing this?” “Why is that the most important reason?”
“What’s end-game here?”
“What does success look like in a world where you pick that path?”
5/ When listening, after empathizing, and wanting to help them make their own decisions without imposing your world view:
“What would the best version of yourself do”?