Crypto isn’t the only clown show: Rest of the world has $65 TRILLION in US dollar liabilities — far more than previously estimated

i only have 6 fingers but i’m just a regular guy nothing to see here

Report comes from the BIS, which is like the Central banks’ Central bank. It also releases the best research, but Powell gets 100x more msm coverage, because Amurica.

Hidden leverage…liquidity issues…10x more debt than capital…reminds me of something 🤔. Only we’re talking TRILLIONS here, not a measly bankman fraud scam of just billions.

Full report here (it’s brief): https://www.bis.org/publ/qtrpdf/r_qt2212h.htm

Verbatim excerpts below:

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The missing dollar debt from FX swaps/forwards and currency swaps is huge, adding to the vulnerabilities created by on-balance sheet dollar debts of non-US borrowers. It has reached $26 trillion for non-banks outside the United States, double their on-balance sheet debt. Moreover, it has grown smartly since 2016, despite the often significant premium demanded on dollar swap funding. For banks headquartered outside the United States, dollar debt from these instruments is estimated at $39 trillion, more than double their on-balance sheet dollar debt and more than 10 times their capital.

Dollar dominance is striking in this FX market segment, greater than in any other aspect of dollar use. As a vehicle currency, the US dollar is on one side of 88% of outstanding positions – or $85 trillion. An investor or bank wanting to do an FX swap from, say, Swiss francs into Polish zloty would swap francs for dollars and then dollars for zloty.

Off-balance sheet dollar debt may remain out of sight and out of mind, but only until the next time dollar funding liquidity is squeezed. Then, the hidden leverage and maturity mismatch in pension funds’ and insurance companies’ portfolios – generally supposed to be long-only – could pose a policy challenge. And policies to restore the flow of dollars would still be set in a fog.

SBF (FTX) interviewed by Andrew Ross Sorkin – my meandering and annoyed takes

Worth watching in full. I’ve heard Stephanopoulos’s interview was harder hitting but haven’t watched it yet.

I downloaded an MP3 version of it, so the reactions below are based on his voice and replies alone and not body language, though I’m notably handicapped when it comes to eq:

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Repeatedly distanced himself from Alameda, made clear he ran FTX but claimed not to know what was going on in detail at Alameda — beggars belief considering he owned 90% of Alameda and every prior Alameda CEO was Sam’s close personal friend or *perhaps cough cough* more

Tries to blame the collapse on leverage, which I assume is a hot button issue with regulators and easier to understand by the general public, but annoying that Sorkin doesn’t dig deeper into the obviously fraudulent evidence (like systemic co-mingling and improper usage of customer funds; Alameda front-running / VIP status on FTX exchange; taking out multiple BILLIONS in personal loans, where did those funds go?; the role of close senior execs including Nishad and Gary)

Within FTX structure, shifts blame to regulators (repeatedly claims FTX US and FTX Japan, etc, were ok and solvent because there were stringent regulations). It’s sorta like saying I stole my classmate’s lunch money because the teacher wasn’t in the room

With two Stanford law professors as parents, he clearly understands the importance and practice of “plausible deniability”

His public track record proves beyond a doubt that he is a very effective and disciplined communicator. Just read his many tweet threads. So why would we suddenly assume he’s NOT being disciplined and purposeful in conducting these interviews, despite his *claims* that his lawyers don’t want him to do this?

Hilarious bit at the end where he complains about hypocritical “do-gooderism”, when his publicly stated life’s work was to promote an over-intellectualized neo-facade of do-gooderism known as ineffective altruism. Merriam Webster literally defines a “do gooder” as “an earnest often naive humanitarian or reformer” gtfo of here

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I hope he ends up in jail. I hope it takes many years before he steps foot in a cell, so he has to spend time and brain cells and stress and money defending himself in court and outside it.

But knowing how the American penal system works he’ll probably receive a light sentence served in a cushy minimum security getaway with plenty of utilitarian philosophy books and vegan couscous or whatever the f he pretends to eat

Incredible articulation of why big tech platforms don’t seem to care about their users

“Mark Zuckerberg in Warhammer Total War portrait smirk” c/o Lexica

It feels like one of those timeless patterns of history where a ruler in any domain — whether an Emperor, a Founder CEO, or even a teacher in a classroom — initially serves his people, but when that ruler acquires too much power over a long period of time, he starts to believe the people serve him. I’m sure there’s a wise Confucius proverb describing precisely this…

Highly recommend: https://tedgioia.substack.com/p/how-web-platforms-collapse-the-facebook

Direct quotes:

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Why do I need to log in to Reddit to read comments? Why can’t I fix a spelling error on Twitter? Why can’t I find the names of the band members on Spotify? Why is the whole first page of Google search results sometimes filled with paid advertising? Why does TikTok send all my private data to China?

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It’s obvious that these companies didn’t do focus groups or market research before making these decisions. Or if they did, they must have ignored what they learned.

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I’ve focused here on Facebook, but there’s a larger lesson here. Web platforms don’t fail because of the competition. They don’t self-destruct because they are weak. The collapse comes because they are strong. They lose the thread because of their dominance and power, which gives their leaders the mindset of authoritarian rulers.

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The solution is simple: *Serve the users, instead of manipulating them*

Interesting snippets from State of AI Report 2022

output from Playground AI

Full report here: https://www.stateof.ai/

I’m far from an AI expert, just an interested student who gets the tingly feels every time I use Stable Diffusion or see output from ChatGPT.

Snippets (copied verbatim):

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The chasm between academia and industry in large scale AI work is potentially beyond repair: almost 0% of work is done in academia.

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Finding faster matrix multiplication algorithms, a seemingly simple and well-studied problem, has been stale for decades. DeepMind’s approach not only helps speed up research in the field, but also boosts matrix multiplication based technology, that is AI, imaging, and essentially everything happening on our phones.

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The authors argue that the ensuing reproducibility failures in ML-based science are systemic: they study 20 reviews across 17 science fields examining errors in ML-based science and find that data leakage errors happened in every one of the 329 papers the reviews span

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many LLM capabilities emerge unpredictably when models reach a critical size. These acquired capabilities are exciting, but the emergence phenomenon makes evaluating model safety more difficult.

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Alternatively, deploying LLMs on real-world tasks at larger scales is more uncertain as unsafe and undesirable abilities can emerge. Alongside the brittle nature of ML models, this is another feature practitioners will need to account for.

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Landmark models from OpenAI and DeepMind have been implemented/cloned/improved by the open source community much faster than we’d have expected.

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Compared to US AI research, Chinese papers focus more on surveillance related-tasks. These include autonomy, object detection, tracking, scene understanding, action and speaker recognition.

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NVIDIA’s chips are the most popular in AI research papers…and by a massive margin

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“We think the most benefits will go to whoever has the biggest computer” – Greg Brockman, OpenAI CTO

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As such, the AI could reliably remove 36.4% of normal chest X-rays from a primary health care population data set with a minimal number of false negatives, leading to effectively no compromise on patient safety and a potential significant reduction of workload.

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The US leads by the number of AI unicorns, followed by China & the UK; The US has created 292 AI unicorns, with the combined enterprise value of $4.6T.

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The compute requirements for large-scale AI experiments has increased >300,000x in the last decade. Over the same period, the % of these projects run by academics has plummeted from ～60% to almost 0%. If the AI community is to continue scaling models, this chasm of “have” and “have nots” creates significant challenges for AI safety, pursuing diverse ideas, talent concentration, and more.

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Decentralized research projects are gaining members, funding and momentum. They are succeeding at ambitious large-scale model and data projects that were previously thought to be only possible in large centralised technology companies – most visibly demonstrated by the public release of Stable Diffusion.

Matt Ridley on evidence for the lab leak hypothesis (Jordan Peterson podcast)

Great overall podcast, because Peterson is a world class explainer and to explain well he needs to understand well and to understand well he really digs and pokes thoroughly. Not saying I believe all of it, because China number one and all that.

Reasons why it *could* be a lab leak (but definitely not saying it is, y’know), my paraphrased notes:

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-there was a lab near the outbreak researching exactly this kind of virus

-the virus was atypical in its ability to spread between humans (transmissibility)

-they identified a “furin cleavage site” (an added bit of DNA code) in the virus DNA

-there’s still a lack of finding the animal transmission vector / specimen(s)

-the multiple attempts to cover up early findings (in both China and the US) that even hinted at a potential lab leak / man-made virus

-there was a red herring of an identified pangolin virus whose DNA sequence was later found to be too different, and was not found near the same area

-those scientists and administrators in charge in both the US and China had grant proposals and research projects on precisely this (furin cleavage, bat viruses, gain of function)

-there were prior bio safety incidents at that very lab, on which the top Chinese leadership were consulted

-this new virus differs greatly from others like it, which were bat viruses, but not particularly lethal, and mostly intestinal

-in the case of SARS, the transmission chain very clear, and the animal vector and index cases were eventually found; none of that’s happened here

-although there was a heavy concentration of cases near the suspected origination wet market, it’s a bit of drawing the bullseye after taking the shot; only those who self-identified as being near that market were diagnosed with it — if you weren’t near the market, even if you had the same symptoms, you were diagnosed with something else (like the flu?)