On Bayesianism, the Many Worlds Interpretation, and personal identity.
Some thoughts worked out in a letter to a friend, which is the kind of thing you do when off Twitter for a glorious week. (🧵)
Is there a fact of the matter as to whether the cat is alive before you open the box?— Avraham Eisenberg (@avi_eisen) November 8, 2020
I would say not, and all your references to how the world "is" are similarly incoherent.
Wait so you disagree with 'quantum splitting means that that there are futures where you become the next US president and futures where you murder your family and futures where you spontaneously combust' takes?— Peli Grietzer (@peligrietzer) November 8, 2020
Can you defend this distinction between past and future splits?— Avraham Eisenberg (@avi_eisen) November 8, 2020
You mentioned personal identity, are you going to argue that personal identity splits even if we're unaware of any differences?
My issue is what forks \u201cspace\u201d itself? Obv we need a QG theory, but MWI assumes some background independence or metaphysical substrate in which alternative quantum states can resolve.— U.S.O.U.S. (@hyperauxetic) November 8, 2020
You think there's a fact of the matter about whether you are Classical Simon1 or Classical Simon2? My instinct is that there isn't, if they are qualitatively identical to each other— Peli Grietzer (@peligrietzer) November 8, 2020
If both have the exact same memories and you can't tell which one "you" are, then from your perspective there shouldn't be a fact of the matter as to which one you are. At least, that's my view on personal identity. What's the argument against?— Avraham Eisenberg (@avi_eisen) November 8, 2020
Not sure how that's relevant to personal identity.— Avraham Eisenberg (@avi_eisen) November 8, 2020
Simon, I don't mean to distract you from your brilliant thread, here, but what would you say to a Meillassouxian-type committed to an arche-fossil as the basis of absolute contingency?— NAF Loves Meillassoux (@LovesNaf) November 8, 2020
Not sure this is what you\u2019re looking for, but Tegmark uses cosmic rays causing cancerous mutations as one example of quantum splitting have observable macro effects.— Matt Clancy (@mattsclancy) November 8, 2020
More from Simon DeDeo
In this case, it's a theory about compensation: the worse one's luck is, the more likely it is to see a reversal. On the surface, it's irrational. The more bad luck you have, the more you accumulate evidence that the system is rigged.
But there's also an anthropic component. If the luck is bad enough, it starts to become inconsistent with your survival. You've accumulated evidence for correlations in the environment, but these correlations (may be) inconsistent with (people like you) being in this environment.
An example. You're in a city where everyone takes public transport. You encounter a string of bad delays. It's reasonable to conclude they'll end—otherwise people wouldn't take public transport. It's unlikely that you happened to show up right when the network collapses.
Of course, that's a bad heuristic in a casino, which relies on a constant influx of losers. But in other environments, particularly with persistent populations and no evidence for sudden changes in the underlying laws, it makes sense.
It was pretty simple to do—Apple Time Machine backups let me do it with one click.
That first tweet captures, in two pictures, how badly Apple has “lost the plot” (to quote @wylieprof). On the right is the Apple MagSafe adapter, from 2013. On the left, what I had “upgraded” to.
Thanks, Apple! I really was nostalgic for worrying about yanking my computer off the table.
Oh and I really appreciated not knowing if my computer was charging. What was great was the little whoop sound you used, so that the speaker before me could be informed I was charging my laptop.
This is the first deletion, back in 2014. A bit hard to read between the lines, but the basic story that an admin had Stickland's page "speedy deleted"—i.e., deleted without debate. The method was something called Copyright Jujitsu.
In particular, the admin had the page deleted not because of notability, but because it included a photograph of Strickland that had ambiguous copyright status. This is a method that people developed to get rid of content they didn't want, but also didn't want to debate.
"Copyright Jujitsu" because it is usually used against spam from companies; a PR officer uploads promotional material to Wikipedia. Instead of debating whether it's neutral, the admin can say "we'd love to have it, but the material appears to violate your company's copyright".
Usually the PR office and the IP office are separate in a company, and the idea of releasing promotional material under public domain is such a legal nightmare that the PR person goes away.
Put another way, the editors who built the dominant nodes in this network...
...have little overlap with the ones who made this much more recent managerial flowchart.
Internet time runs at hundred-fold speed—the difference between the people who painted what's in the Uffizi, and the people in charge of keeping those paintings from deteriorating. Very different tasks, and (one presumes) very personalities as well. @PaulSkallas?
Imagine for a moment the most obscurantist, jargon-filled, po-mo article the politically correct academy might produce. Pure SJW nonsense. Got it? Chances are you're imagining something like the infamous "Feminist Glaciology" article from a few years back.https://t.co/NRaWNREBvR pic.twitter.com/qtSFBYY80S— Jeffrey Sachs (@JeffreyASachs) October 13, 2018
The article is, at heart, deeply weird, even essentialist. Here, for example, is the claim that proposing climate engineering is a "man" thing. Also a "man" thing: attempting to get distance from a topic, approaching it in a disinterested fashion.
Also a "man" thing—physical courage. (I guess, not quite: physical courage "co-constitutes" masculinist glaciology along with nationalism and colonialism.)
There's criticism of a New York Times article that talks about glaciology adventures, which makes a similar point.
At the heart of this chunk is the claim that glaciology excludes women because of a narrative of scientific objectivity and physical adventure. This is a strong claim! It's not enough to say, hey, sure, sounds good. Is it true?
More from Data science
- 📦 Product
- 🔢 Data
- 🤖 Modeling
- 📝 Scripting
- 🛠 API
- 🚀 Production
More details (lessons, task, etc.) here: https://t.co/xmMm9XGK9j
Questions that this thread will answer:
- What is it?
- Who is this course for?
- What is the format?
- What makes this course unique?
- Why constrain to open source tools?
- What are my qualifications?
- Why is this free?
- What are the
What is it?
Putting ML in Production: a guide and code-driven case study on MLOps. We will be developing and deploying Made With ML's first ML service, from Product → ML → Production, with open source tools.
This ML service will act as a foundation for all future ML features and subsequent iterations. The first feature is tagifai - multilabel classification of tags for a project. We'll discuss the need and utility of this feature in the first lesson.
Who is this course for?
- ML developers looking to become end-to-end ML developers.
- Software engineers looking to learn how to responsibly deploy and monitor ML systems.
- Product managers who want to have a comprehensive understanding of the different stages of ML dev.
Our long overdue paper on generalized word shift graphs is finally here!
So what are they?
If we have two texts, there are many ways we can compare them. Weighted averages are a particularly useful measure because they're flexible and interpretable
Proportions, Shannon entropy, the KLD, the JSD, and dictionary methods can all be written as weighted averages
But weighted avgs are also slippery. When we try to compress complex phenomena like happiness, surprise, divergence, or diversity into a single number, it can be unclear what we're measuring
If the measure goes up, what does that mean? Why did it do that? Can we trust it?
Very often, that's the end of the line and we're left with an uneasy feeling in the pit of our stomach that our weighted avg is actually picking up a data artifact or some other unintended peculiarity
Word shift graphs help us address those concerns
First, word shifts look under the hood of weighted averages to see what's going on
All weighted averages are a sum of contributions from individual words. We can pull out those words, and rank which ones contribute the most to the difference between two texts
https://t.co/EwwOzgfDca : Deep Learning framework in Java that supports the whole cycle: from data loading and preprocessing to building and tuning a variety deep learning networks.
https://t.co/J4qMzPAZ6u Framework for defining machine learning models, including feature generation and transformations, as directed acyclic graphs (DAGs).
https://t.co/9IgKkSxPCq a machine learning library in Java that provides multi-class classification, regression, clustering, anomaly detection and multi-label classification.
https://t.co/EAqn2YngIE : TensorFlow Java API (experimental)
Here is a compilation of resources (books, videos & papers) to get you going.
(Note: It's not an exhaustive list but I have carefully curated it based on my experience and observations)
📘 Mathematics for Machine Learning
by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong
Note: this is probably the place you want to start. Start slowly and work on some examples. Pay close attention to the notation and get comfortable with it.
📘 Pattern Recognition and Machine Learning
by Christopher Bishop
Note: Prior to the book above, this is the book that I used to recommend to get familiar with math-related concepts used in machine learning. A very solid book in my view and it's heavily referenced in academia.
📘 The Elements of Statistical Learning
by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie
Mote: machine learning deals with data and in turn uncertainty which is what statistics teach. Get comfortable with topics like estimators, statistical significance,...
📘 Probability Theory: The Logic of Science
by E. T. Jaynes
Note: In machine learning, we are interested in building probabilistic models and thus you will come across concepts from probability theory like conditional probability and different probability distributions.
It's technically brilliant, combining BERT, seq2seq, and Transformer XL
It's also a wonderful example of leveraging and customizing the fastai framework in a deep & thoughtful way.
Here's the full set of blog posts diving in to this
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Risks of bat-borne zoonotic diseases in Western Asia
Duration: 24/10/2018-23 /10/2019
2. Bat Virus Database
Access to the database is limited only to those scientists participating in our ‘Bats and Coronaviruses’ project
Our intention is to eventually open up this database to the larger scientific community
3. EcoHealth Alliance & DTRA Asking for Trouble
One Health research project focused on characterizing bat diversity, bat coronavirus diversity and the risk of bat-borne zoonotic disease emergence in the region.
4. Phelps, Olival, Epstein, Karesh - EcoHealth/DTRA
5, Methods and Expected Outcomes
(Unexpected Outcome = New Coronavirus Pandemic)
Why is this the most powerful question you can ask when attempting to reach an agreement with another human being or organization?
A thread, co-written by @deanmbrody:
Next level tactic when closing a sale, candidate, or investment:— Erik Torenberg (@eriktorenberg) February 27, 2018
Ask: \u201cWhat needs to be true for you to be all in?\u201d
You'll usually get an explicit answer that you might not get otherwise. It also holds them accountable once the thing they need becomes true.
2/ First, “X” could be lots of things. Examples: What would need to be true for you to
- “Feel it's in our best interest for me to be CMO"
- “Feel that we’re in a good place as a company”
- “Feel that we’re on the same page”
- “Feel that we both got what we wanted from this deal
3/ Normally, we aren’t that direct. Example from startup/VC land:
Founders leave VC meetings thinking that every VC will invest, but they rarely do.
Worse over, the founders don’t know what they need to do in order to be fundable.
4/ So why should you ask the magic Q?
To get clarity.
You want to know where you stand, and what it takes to get what you want in a way that also gets them what they want.
It also holds them (mentally) accountable once the thing they need becomes true.
5/ Staying in the context of soliciting investors, the question is “what would need to be true for you to want to invest (or partner with us on this journey, etc)?”
Multiple responses to this question are likely to deliver a positive result.
Vishnu puran has twenty three thousand shlokas. It has the power to destroy all your sins. In its first part it contains the dialogue between Parashar rishi and Maitrey rishi.
The main topics discussed here are Aadikaraan sarg, origin of devtas, Samudra manthan, the vansh of Daksh, stories of Dhruv and Pruthu, Prachetas analysis, Prahlads story, the distribution of different powers to the various sections of society.
The second part consists of description of Priyavrat vansh, description of Dweeps, Varsh, Swarg, Narak, description of various planet movements, Bharat charitra, Muktimarg and dialogue between Nidhag and Ribhu.
Next is the description of Manvantars, avtaar of Vedvyas,
and ways to get freedom from Narak. Then we find a dialogue between Sagar & Aurva rishi, structure of Dharma, Shradh Kalp,Varnashram dharma, good behavior and story of Maya & Moha.
In the 4th part we find the description of Chandra vansh along with the description of its rulers.
Next are the questions regarding Krishnavtar, Gokul, the slaying of Putna, atrocities of demon Aghasur, Killing of Kansa, leela in Mathura, demons slayed by Krishna in order to ease the load of Prithvi, Krisha's marriages and sermon by Ashtavakra.
Story 16- it is about how Bhagwan Shiva explained the meaning of Vedas to the Rishis.
வேதத்துக்குப் பொருள் அருளிச் செய்த படலம்
Once there was a great deluge,everything in the world was destroyed.All lifeforms that existed got perished.Afterwards ,due to Bhagwan Shiva creation started.Then from Bhagwan Shiv ji's mouth-birth of 🕉 OM- Pranavam happened.From Pranavam,4 vedas appeared. Rishis learned them.
Many Rishis in Naimisharanya learned Vedas&recited them but they didn't understand the meaning&essence of Vedas. They were worried as they couldn't find any guru who can teach them the meaning of Vedas.That time,Rishi Arabhatar visited them.Rishis told him about need their worry.
Rishi Arabhatar told them that Bhagwan Shiva has given Vedas &he would be grateful enough to teach the meaning as well.But for that rishis have to rigorous penance at a sacred place.Also told them to go to Sundareswarar temple in Madurai to do tapas in front of Dakshinamurthy.
Assured them that Dakshinamurthy himself will come & teach them.Rishis proceeded to Madurai & started their tapas in front of Dakshinamurthy sannidhi for almost a year starting from Karthigai month pournami to next year Karthigai month pournami following all rituals..annadan