Did we get dietary saturated fats all wrong? The #HADLmodel provides a new understanding and an opportunity to get it right. THREAD👇👇👇
@simondankel @kariannesve

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Get a cup of coffee.

In this thread, I'll help you understand the basics of Binomial Thinking.

The future is always uncertain. There are many different ways it can unfold -- some more likely than others. Binomial thinking helps us embrace this view.

2/

The S&P 500 index is at ~3768 today.

Suppose we want to predict where it will be 10 years from now.

Historically, we know that this index has returned ~10% per year.

If we simply extrapolate this, we get an estimate of ~9773 for the index 10 years from now:

3/

What we just did is called a "point estimate" -- a prediction about the future that's a single number (9773).

But of course, we know the future is uncertain. It's impossible to predict it so precisely.

So, there's a sense of *false precision* in point estimates like this.

4/

To emphasize the uncertainty inherent in such predictions, a better approach is to predict a *range* of values rather than a single number.

For example, we may say the index will return somewhere in the *range* of 8% to 12% (instead of a fixed 10%) per year.

5/

10 years from now, this implies an index value in the *range* [8135, 11703]:

https://t.co/xvP6tVlIaE
Quite a surprise. Ferguson isn’t qualified to comment on such things. He lacks understanding of basic biological concepts, partly explaining why his predictions are often so extreme.

That said, I’ll take him as an ally. It’s clear we’re already at herd immunity. How can I be sure? London had a huge peak of excess deaths in spring. The timing of peak deaths showed clearly that the pandemic was self-limiting. Recall much debate about whether the interval...

...between lockdown & peak deaths was long enough for lockdown to have been the cause of reducing deaths? The answer was “no”. But it was close & I can understand people thinking “well, it’s close, so perhaps it was lockdown that did it?”, thereby establishing a foundational...

...myth favoured by those who genuinely believe lockdown saves lives (it clearly doesn’t).
I’ll get to London & here immunity. But those wavering about the evidence about lockdown in spring really will benefit from cogitating on this graph.

In blue are the 30 trusts with the earliest date of peak deaths in spring. In red, the 30 with the latest peak deaths. For me, this is proof that national lockdown, which began Mar 23, played no role whatsoever in turning the pandemic. You’ll see some areas had peak daily...

Next up at #enigma2021, Sanghyun Hong will be speaking about "A SOUND MIND IN A VULNERABLE BODY: PRACTICAL HARDWARE ATTACKS ON DEEP LEARNING"

(Hint: speaker is on the

In recent years ML models have worked from research labs to production, which makes ML security important. Adversarial ML research studies how to mess with ML

For example by messing with the training data (c.f. Tay which became super-racist super-fast) or by foiling ML models by changing inputs in ways humans can't see.

Prior work considers ML models in a standalone, mathematical way
* looks at the robustness in an isolated manner
* doesn't look at the whole ecosystem and how the model is used -- ML models are running in real hardware with real software which has real vulns!

This talk focuses on hardware-level vulnerabilities. This is particularly interesting because these can break cryptographic guarantees (because those are outside of their threat models)
e.g. fault injection attacks, side-channel attacks

Neonicotinoids and why they need to stay banned 🐝

#SciComm #ScienceTwitter #SaveTheBees #ClimateEmergency #ClimateCrisis

Neonicotinoids were banned by the EU in 2018 following multiple scientific studies which proved their severe detrimental impact on pollinators. Effects from neonics include reduced immune function, reduced foraging capabilities, and impaired cognition in bees.

The government has approved neonics for emergency use as a seed treatment on sugar beet. Yields have been impacted by beet yellows, transmitted by aphids. They argue that, because sugar beet does not flower and will not attract pollinators, the risk from neonics is acceptable.

Since the ban on neonics in 2018, the infection rate of beet yellows has increased year on year. Aphid populations have been proliferating due to mild winters, with no agrochemicals to solve the problem.

Sounds like a good case for neonics, right?

But this is the start of a vicious cycle. Climate change isn't going away. Winters will continue to get milder, resulting in the need for more and more pesticides to combat growing pest problems. Inevitably, this won't be the last time neonics are authorised for emergency use.