HBR: "AI Won’t Replace Humans — But Humans With AI Will Replace Humans Without AI"

From the Harvard Business Review, August 4, 2023:

Summary.
Karim Lakhani is a professor at Harvard Business School who specializes in workplace technology and particularly AI. He’s done pioneering work in identifying how digital transformation has remade the world of business, and he’s the co-author of the 2020 book Competing in the Age of AI. Customers will expect AI-enhanced experiences with companies, he says, so business leaders must experiment, create sandboxes, run internal bootcamps, and develop AI use cases not just for technology workers, but for all employees. Change and change management are skills that are no longer optional for modern organizations.

Just as the internet has drastically lowered the cost of information transmission, AI will lower the cost of cognition. That’s according to Harvard Business School professor Karim Lakhani, who has been studying AI and machine learning in the workplace for years. As the public comes to expect companies that deliver seamless, AI-enhanced experiences and transactions, leaders need to embrace the technology, learn to harness its potential, and develop use cases for their businesses. “The places where you can apply it?” he says. “Well, where do you apply thinking?”

For this episode of our video series “The New World of Work”, HBR editor in chief Adi Ignatius sat down with Lakhani, author of Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World, to discuss:

• How executives and regular employees can (and must) develop a digital mindset
• Change management as a critical skill that must be in the DNA of any successful organization
• The shapes AI may take in the near and far future

“The New World of Work” explores how top-tier executives see the future and how their companies are trying to set themselves up for success. Each week, Ignatius talks to a top leader on LinkedIn Live — previous interviews included Microsoft CEO Satya Nadella and former PepsiCo CEO Indra Nooyi. He also shares an inside look at these conversations —and solicits questions for future discussions — in a newsletter just for HBR subscribers. If you’re a subscriber, you can sign up here.

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ADI IGNATIUS:
Karim, welcome to the show.

Karim Lakhani:
So glad to be here with you today, Adi.

ADI IGNATIUS:
You co-wrote a piece for us a few years ago, and it’s reflected in your book, where you say machine learning has basically changed the very rules of business. That’s a big statement. What do you mean by that?

Karim Lakhani:
The book really was a partnership between Marco Iansiti and Amy Bernstein, one of the editors at HBR. And what Marco and I noticed in about a decade’s worth of research and spending time with companies, both writing cases as advisors, as consultants, and so forth, was that the nature of the corporation (which really was established as the modern American corporation, which became the blueprint for the modern international corporation, established in the 1920s and 30s) was changing foundationally because of technologies like AI, like machine learning.

What we observed was that the entire business architecture in many of these AI-first companies at that time, in terms of business model, how you create value, how you capture value, and your operating model, how you deliver value, how you achieve scope, the number of customers you serve, the number of products you have, scale, the number of customers you serve, and learning these fundamental parts of a business architecture, were being rewired because of machine learning, AI, and digital technologies.

If you just reflect for a bit on your experience using Google, for example, much of your Google experience is fully automated, from the ads you see to the search you do to, if you’re using Gmail, how you interact with them. It’s not people that do those activities, it’s the algorithms that make that happen. Similarly with all the large e-commerce platforms like an Amazon or Alibaba or Netflix. But these companies work in a fundamentally different way than a company like General Electric, where I grew up right out of college in my first job.

These companies, the machines and the algorithms are at the center. The work is automated. The humans are actually designing the algorithms and testing them and checking them, making sure they’re working within bounds, but the actual transactions and activities are being mediated through the machines....

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If interested see yesterday's "Amazon to cough $75B on capex in 2024, more next year" (AMZN)" including: 

"Elon Musk says any company that isn’t spending $10 billion on AI this year like Tesla won’t be able to compete" (TSLA)
    This.
    This is such an important concept to grasp. It's the advantage flywheels, the rich get richer, winner-take-all reality of business in 2024.... 

Also Nov. 4:

Andreessen Partner On Where The AI Opportunities Are For Investors

....WSJ: What type of AI startups are interesting now, and not too expensive or too late?

MARTIN CASADO: It’s good to draw a comparison to the internet. Periodically in the history of the industry, we’ve seen the marginal cost of things go to zero. With compute, the marginal cost of computation went to zero. We had people calculating logarithm tables by hand, then we had a computer do it. That created the compute revolution. Then the internet, the marginal cost of distribution went to zero. When it comes to AI, it really feels like the marginal cost of language, reasoning and creation are going to zero. And if that’s the case, this is a supercycle. And if that’s the case, we’ve got decades. So there’s no “too late.” In that sense, we’re still very, very early....

I'm Going To Need A New Doctor

After being struck by an automobile in NYC during American Prohibition W.S.C. procured this Doctor's Note:

—Chartwell Trust via VinePair

If interested see Churchill's 1932 New York Times commissioned article, "My New York Misadventure". He was quite highly paid for his writing, in this case and elsewhere. From our introduction to 2013's "Why Aren’t Top Journalists Rich?":

It wasn't always thus.
In 1898 young Winston Churchill, after a couple other writing gigs (Daily Graphic, Telegraph) went off to war with a commission to write for The Morning Post. He produced thirteen articles between September 23 and October 8, 1898 for which he was paid fifteen pounds each. According to the ever handy BoE inflation calculator that is the equivalent of  £1651.03 per, or  £21463.39 for the lot, $33,053 in today's reserve currency for 15 days work. Not rich but not bad.

More on Churchill another time but here are a couple more factoids: He charged a half-crown (2 1/2 shillings, $11.38) per word in the 1930's, in 1936 his writing income was the equivalent of $800,000 now.
Again, not rich but able to afford his Pol Roger.
Then he went on to become the highest paid scribbler of his day and did some other stuff too....

Sheila Bair: "U.S. Debt Could Drive the Next Financial Crisis"

Sheila Bair was one of the heroes of the Great Financial Crisis and to this day her approach to straight talk is reminiscent of Harry Truman's comment when a supporter shouted "Give 'em [Republicans] Hell, Harry!" Truman replied, "I don't give them Hell. I just tell the truth about them, and they think it's Hell."

From Barron's, October 30

About the author: Sheila Bair is former chair of the Federal Deposit Insurance Corp. and founding chair of the CFA Institute Systemic Risk Council.

---

I have seen more than my fair share of financial crises during my time in the U.S. government. I was the assistant secretary of the U.S. Treasury for financial institutions during the 9/11 terrorist attacks and chair of the Federal Deposit Insurance Corp. during the 2007-2008 financial crisis. The U.S. government resorted to deficit-financed spending and tax relief to these crises, and to the pandemic. Those decisions were right.

Unfortunately, once the crises passed, we just kept spending as if nothing had changed. Now, the resulting overhang of federal debt could itself be the cause of a future crisis.

Our gross national debt exceeds $35 trillion. This puts the federal debt held by the public at a staggering 99% of U.S. gross domestic product, nearly as high as its peak at the end of World War II. After the war, our “greatest generation” of political leadership steadily restored our nation’s finances, bringing the debt down to about 31% of GDP by 1981.

Unfortunately, more recent political leadership has concluded that deficits do not matter. Both Republicans and Democrats have settled on deficits as the easiest way to pay for politically popular initiatives, be they lower taxes (Republicans) or higher spending (Democrats). Elected officials are wary of braving the political pain of deficit reduction, knowing their successors could easily squander those hard-fought battles with more deficit-financed spending and tax cuts.

Case in point is the current election. Both presidential candidates are proposing tax and spending giveaways to curry favor with voters. The nonpartisan Committee for a Responsible Federal Budget projects

that Vice President Kamala Harris’ proposals will increase the debt by $3.95 trillion over the next 10 years, which pales in comparison to Donald Trump’s plans, which will increase it by $7.75 trillion. Neither candidate is talking seriously about our unsustainable fiscal position, much less the related issue of projected funding shortfalls in two of our most important safety net programs, Social Security and Medicare. Based on current projections, the Social Security trust fund will run out by 2035, while Medicare’s Hospital Insurance fund will be depleted by 2036. Absent reforms to shore up these programs—and avoid automatic cuts—funding gaps will have to be filled with hundreds of billions in new deficit financing each year.

The dollar’s privileged status as the world’s reserve currency enables our fiscal indulgences. As the late Sen. Alan Simpson (R., Wyo.) once famously said, investors keep buying our debt because we are “the best-looking horse in the glue factory.” But as we continue to climb in the rankings of the world’s most indebted nations—we rank 4th among the other advanced economies in the Organization for Cooperation and Development—that perception could easily change.

There are hints that our privileged status is already eroding. Foreign ownership of U.S. Treasuries has fallen from 34% in 2012 to 28% in 2024. The dollar’s share of global reserves has fallen from more than 70% in 2000 to 58% today.

Make no mistake, if we continue on this path, investors will eventually lose confidence in our debt. The change could be gradual or sudden, but the consequences will be painful, no matter the pace. The federal government’s interest costs, already at $892 billion for 2024, will increase dramatically, as investors demand a higher risk premium. That will force painful tax hikes or spending cuts. Private sector borrowing costs tied to Treasury rates will also spike, damaging economic growth. Banks, managed funds, insurance companies, pensions, and other investors will be exposed to trillions of dollars in market losses as the Treasuries they hold lose value, precipitating widespread distress in our financial system...

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Using the word debt is a shorthand for explaining where the problem will first become impossible to avoid: The interest on the debt and the rate of interest required as a clearing price for that debt. Where it gets really interesting is if the Fed steps in to buy the paper the Treasury is floating to keep the interest rate from spiraling ever higher.

This Financial Repression will result in the Fed directly monetizing the deficit which results in liquidation of the debt by means of inflation. The only other choice is repudiation of the debt and there is no politician in the U.S., or anywhere in the world for that matter, brave enough to even mention that type of Jubilee, much less enact it.

Previously on/from Ms. Bair:

March 2023 - Former FDIC Head Sheila Bair Says The Feds Had Better Explain Exactly Why They Decided To Bail Out Uninsured Depositors At SVB and Signature
We are fans of Ms, Bair, she's a very clear thinker and not shy about sharing those thoughts.

"Fix income inequality with $10 million loans for everyone!"
File under: Things you don't expect from former regulators--humor, satire, pokes at former colleagues/bosses.
Sheila Bair is a former chairman of the Federal Deposit Insurance Corp.

"Dad Says Results Of Halloween Candy Inspection Could Be Delayed Up To 2 Weeks"

From the Babylonian Bee, November 1:

ATLANTA, GA — Local dad Brad O'Malley reportedly disappointed his young children this morning by informing them that the results of his inspection of their Halloween candy may be delayed for up to two weeks.

According to the O'Malley children, whose candy was confiscated last night immediately after their return from trick-or-treating, their dad let them know that "technical difficulties" had resulted in unavoidable delays in completing the annual candy inspection process.

"I'm really sorry, guys, but you'll just have to bear with me," O'Malley reportedly said. "We've got a lot of candy to go through here. With so many pieces, this isn't something that can be done overnight. We want to make sure every piece of candy is accounted for, including late-arriving candy from the more densely populated urban areas. We appreciate your patience in this matter."....

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Earlier -"Joint ODNI, FBI, and CISA Statement" 

"Joint ODNI, FBI, and CISA Statement"

From the Federal Bureau of Investigation, November 4:

Today, the Office of the Director of National Intelligence (ODNI), the Federal Bureau of Investigation (FBI), and the Cybersecurity and Infrastructure Security Agency (CISA) released the following statement: 

Since our statement on Friday, the IC has been observing foreign adversaries, particularly Russia, conducting additional influence operations intended to undermine public confidence in the integrity of U.S. elections and stoke divisions among Americans. The IC expects these activities will intensify through election day and in the coming weeks, and that foreign influence narratives will focus on swing states. 
 
Russia is the most active threat. Influence actors linked to Russia in particular are manufacturing videos and creating fake articles to undermine the legitimacy of the election, instill fear in voters regarding the election process, and suggest Americans are using violence against each other due to political preferences, judging from information available to the IC. These efforts risk inciting violence, including against election officials. We anticipate Russian actors will release additional manufactured content with these themes through election day and in the days and weeks after polls close.  

• The IC assesses that Russian influence actors recently posted and amplified an article falsely claiming that U.S. officials across swing states plan to orchestrate election fraud using a range of tactics, such as ballot stuffing and cyberattacks.
• Russian influence actors also manufactured and amplified a recent video that falsely depicted an interview with an individual claiming election fraud in Arizona, which involved creating fake overseas ballots and changing voter rolls to favor Vice President Kamala Harris. The Arizona Secretary of State has already refuted the video’s claim as false. 

 
Iran also remains a significant foreign influence threat to U.S. elections. As noted in a prior update, we have assessed that Iran has conducted malicious cyber activities to compromise former President Trump’s campaign. Iranian influence actors may also seek to create fake media content intended to suppress voting or stoke violence, as they have done in past election cycles. We previously reported that Iran also remains determined to seek revenge against select former US officials whom it views as culpable for the death of Islamic Revolutionary Guard Corps-Qods Force (IRGC-QF) Commander Soleimani in January 2020. It has repeatedly highlighted former President Donald Trump among its priority targets for retribution. 
 
In light of continued influence efforts by foreign adversaries and the increasing volume of inauthentic content online, CISA recommends voters seek out information from trusted, official sources, in particular, state and local election officials. 

The FBI and CISA encourage campaigns and election infrastructure stakeholders to report information concerning suspicious or criminal activity to their local Election Crime Coordinators via FBI field office (fbi.gov/fieldoffices), by calling 1-800-CALL-FBI (1-800-225-5324), or online at ic3.gov. Cyber incidents impacting election infrastructure can also be reported to CISA by calling 1-844-Say-CISA (1-844-729-2472), emailing report@cisa.dhs.gov, or reporting online at cisa.gov/report. Election infrastructure stakeholders and the public can find additional resources about how to protect against cyber and physical threats at CISA’s #PROTECT2024 (cisa.gov/protect2024). 

https://www.fbi.gov/news/press-releases/joint-odni-fbi-and-cisa-statement-110424

"Chinese companies use Biden’s climate law to expand their solar dominance"

Of course.

A deep dive from Politico, November 3:

The president tried to weaken China’s control over solar parts globally by funding U.S. manufacturing plants. But Chinese companies are tapping into the cash. 

A year ago, the Biden administration accused one of China’s largest solar manufacturers of evading American tariffs. Now the company is building a massive panel factory in Texas — and it could receive more than $1 billion in tax subsidies under President Joe Biden’s signature climate law.

The strategic move by Trina Solar marks an emerging dilemma for U.S. officials: Should America reward the companies of one of its biggest adversaries for creating domestic jobs and expanding clean energy?

Giving billions in taxpayer money to Chinese businesses could drive down the cost of solar energy, create jobs and cut greenhouse gas emissions. But it could also sideline American manufacturers that are struggling to compete with cheap Chinese-made imports and sink U.S. efforts to build clean energy technologies at home.

Trina’s factory is exactly what White House officials envisioned spurring when Biden signed the Inflation Reduction Act in 2022 — except that it is owned by a Chinese company. Even worse, to the company’s critics, the Biden administration itself has accused Trina of skirting U.S. tariffs on China by routing its shipments through Southeast Asia.

A White House official, speaking on the condition of anonymity, noted the climate law contains no provisions preventing Chinese solar companies from receiving tax credits under the IRA.

But leaders in Wilmer, where the facility is under construction, welcome Trina’s plans to employ 1,300 local people and offer an annual payroll of $80 million.

The city’s nonpartisan mayor, Sheila Petta, called the company’s arrival “a blessing.”

“The people with Trina have been marvelous,” she said. “I’ll be honest with you, I wish I had a few more companies like that.”

Not everyone agrees. The prospect of China benefiting from Biden’s climate law has triggered fierce debate on Capitol Hill, where there are mounting calls to bar Chinese companies from receiving IRA money. The issue has also fractured the U.S. solar industry, pitting manufacturers worried about cheap Asian imports against developers and installers that rely on inexpensive equipment from overseas....

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How Close Was [Chancellor] Merkel to the Communist System?

I don't think she could have done more damage to Germany's society and economy if she had been directly employed by the Soviets to do so.

From Der Spiegel, May 14, 2013:

A biography focusing on Chancellor Angela Merkel's time growing up in East Germany is making headlines because it suggests she was closer to the communist system than hitherto known. Her spokesman has denied she has covered anything up. 

A new biography covering Chancellor life in East Germany has caused a stir by suggesting she was closer to the communist apparatus and its ideology than previously thought.

Published this week and written by journalists Günther Lachmann and Ralf Georg Reuth, the book quotes Gunter Walther, a former colleague of hers at the Academy of Sciences in East Berlin, as saying she had been secretary for "Agitation and Propaganda" in the Freie Deutsche Jugend (FDJ) youth organization at the institute. Merkel, a trained physicist, worked at the academy from 1978 until 1989.

Excerpts from the book, "The First Life of Angela M.," were published in the newsmagazine Focus on Monday. The mass-circulation Bild newspaper has also given the book prominent coverage in recent days.

The book explores Merkel's life growing up in German Democratic Republic (GDR), where her father Horst Kasner was a Protestant pastor and a committed socialist. He moved to East Germany from West Germany in 1954.

Merkel has said in the past that her FDJ role at the academy was more that of a cultural secretary and that her duties included buying theater tickets and organizing book readings.

'Closeness to the System'

But former German Transport Minister Günther Krause -- an eastern German politician who worked with her in the final months of the GDR and as a fellow minister in the government ex-chancellor Helmut Kohl in the early 1990s -- contradicts her in the book and says she propagated Marxism-Leninism.

"With Agitation and Propaganda you're responsible for brainwashing in the sense of Marxism," he said. "That was her task and that wasn't cultural work. Agitation and Propaganda, that was the group that was meant to fill people's brains with everything you were supposed to believe in the GDR, with all the ideological tricks. And what annoys me about this woman is simply the fact that she doesn't admit to a closeness to the system in the GDR. From a scientific standpoint she wasn't indispensable at the Academy of Sciences. But she was useful as a pastor's daughter in terms of Marxism-Leninism. And she's denying that. But it's the truth." ....

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Intro and outro from February's "Germany’s Days as an Industrial Superpower Are Coming to an End"

What did they do to themselves? 

How much does a person or a political entity have to hate themselves to, to not just commit suicide, but to do it slowly?

***

...Mutti and her ministers have a lot to answer for and it is becoming more and more apparent, with each passing day. that she was the second worst Chancellor in Germany's history.

Related, October 2022 - "Germany’s Apokalypse Now"

Satellite-Inferred Global Temperature Down In October—With A Caveat

From one of the two keepers of the satellite temperature record, the University of Alabama - Huntsville's Dr. Roy Spencer, November 2:

UAH v6.1 Global Temperature Update for October, 2024: +0.73 deg. C After Truncation of the NOAA-19 Satellite Record

The Version 6.1 global average lower tropospheric temperature (LT) anomaly for October, 2024 was +0.73 deg. C departure from the 1991-2020 mean, down from the September, 2024 anomaly of +0.80 deg. C.

The new (Version 6.1) global area-averaged temperature trend (January 1979 through October 2024) is now +0.15 deg/ C/decade (+0.21 C/decade over land, +0.13 C/decade over oceans).

The previous (version 6.0) trends through September 2024 were +0.16 C/decade (global), +0.21 C/decade (land) and +0.14 C/decade (ocean).

The following provides background for the change leading to the new version (v6.1) of the UAH dataset.

NOTE: Snide comments which suggest someone has not read (and understood) that which follows will lead to comment privileges being revoked.

Key Points

• The older NOAA-19 satellite has now drifted too far through the diurnal cycle for our drift correction methodology to provide useful adjustments. Therefore, we have decided to truncate the NOAA-19 data processing starting in 2021. This leaves Metop-B as the only satellite in the UAH dataset since that date. This truncation is consistent with those made to previous satellites after orbital drift began to impact temperature measurements.

• This change reduces recent record global warmth only a little, bringing our calculated global temperatures more in line with the RSS and NOAA satellite datasets over the last 2-3 years.

• Despite the reduction in recent temperatures, the 1979-2024 trend is reduced by only 0.01 deg/ C/decade, from +0.16 C/decade to +0.15 C per decade. Recent warmth during 2023-2024 remains record-setting for the satellite era, with each month since October 2023 setting a record for that calendar month.

Background

Monitoring of global atmospheric deep-layer temperatures with satellite microwave radiometers (systems originally designed for daily global weather monitoring) has always required corrections and adjustments to the calibrated data to enable long-term trend detection. The most important of these corrections/adjustments are:

1. Satellite calibration biases, requiring intercalibration between successively launched satellites during overlaps in operational coverage. These adjustments are typically tenths of a degree C.
2. Drift of the orbits from their nominal sun-synchronous observation times, requiring empirical corrections from comparison of a drifting satellite to a non-drifting satellite (the UAH method), or from climate models (the Remote Sensing Systems [RSS] method, which I believe the NOAA dataset also uses). These corrections can reach 1 deg. C or more for the lower tropospheric (LT) temperature product, especially over land and during the summer.
3. Correction for instrument body temperature effects on the calibrated temperature (an issue with only the older MSU instruments, which produced spurious warming).
4. Orbital altitude decay adjustment for the multi-view angle version of the lower tropospheric (LT) product (no longer needed for the UAH dataset as of V6.0, which uses multiple channels instead of multiple angles from a single channel.)

The second of these adjustments (diurnal drift) is the subject of the change made going from from UAH v6.0 to v6.1. The following chart shows the equator crossing times (local solar time) for the various satellites making up the satellite temperature record. The drift of the satellites (except the non-drifting Aqua and MetOp satellites, which have fuel onboard to allow orbit maintenance) produces cooling for the afternoon satellites’ LT measurements as the afternoon observation transitions from early afternoon to evening. Drift of the morning satellites makes their LT temperatures warm as their evening observations transition to the late afternoon....

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Zuckerberg's Meta Permits U.S. Military Uses Of A.I. Models Favored By China (META; WTH?)

First up, from the New York Times, November 4:

Meta Permits Its A.I. Models to Be Used for U.S. Military Purposes
The shift in policy, covering government agencies and contractors working on national security, is intended to promote “responsible and ethical” innovations, the company said. 

Meta will allow U.S. government agencies and contractors working on national security to use its artificial intelligence models for military purposes, the company said on Monday, in a shift from its policy that prohibited the use of its technology for such efforts.

Meta said that it would make its A.I. models, called Llama, available to federal agencies and that it was working with defense contractors such as Lockheed Martin and Booz Allen as well as defense-focused tech companies including Palantir and Anduril. The Llama models are “open source,” which means the technology can be freely copied and distributed by other developers, companies and governments.

Meta’s move is an exception to its “acceptable use policy,” which forbade the use of the company’s A.I. software for “military, warfare, nuclear industries,” among other purposes.

In a blog post on Monday, Nick Clegg, Meta’s president of global affairs, said the company now backed “responsible and ethical uses” of the technology that supported the United States and “democratic values” in a global race for A.I. supremacy....

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Now is the time we juxtapose.

From The Jamestown Foundation's China Brief, October 31:

PRC Adapts Meta’s Llama for Military and Security AI Applications  

Executive Summary:

• Researchers in the People’s Republic of China (PRC) have optimized Meta’s Llama model for specialized military and security purposes.
• ChatBIT, an adapted Llama model, appears to be successful in demonstrations in which it was used in military contexts such as intelligence, situational analysis, and mission support, outperforming other comparable models.
• Open-source models like Llama are valuable for innovation, but their deployment to enhance the capabilities of foreign militaries raises concerns about dual-use applications. The customization of Llama by defense researchers in the PRC highlights gaps in enforcement for open-source usage restrictions, underscoring the need for stronger oversight to prevent strategic misuse.

---

In September, the former deputy director of the Academy of Military Sciences (AMS), Lieutenant General He Lei (何雷), called for the United Nations to establish restrictions on the application of artificial intelligence (AI) in warfare (Sina Finance, September 13). This would suggest that Beijing has an interest in mitigating the risks associated with military AI. Instead, the opposite is true. The People’s Republic of China (PRC) is currently leveraging AI to enhance its own military capabilities and strategic advantages and is using Western technology to do so.

The military and security sectors within the PRC are increasingly focused on integrating advanced AI technologies into operational capabilities. Meta’s open-source model Llama (Large Language Model Meta AI) has emerged as a preferred model on which to build out features tailored for military and security applications. In this way, US and US-derived technology is being deployed as a tool to enhance the PRC’s military modernization and domestic innovation efforts, with direct consequences for the United States and its allies and partners.

PLA Experts’ Vision for Military AI

The PRC’s 2019 National Defense White Paper, titled “China’s National Defense for the New Era (新时代的中国国防),” notes that modern warfare is shifting toward increasingly informationized (信息化) and intelligentized (智能化) domains, demanding advances in mechanization, informationization, and AI development (Xinhua, July 24, 2019).

AI development in the military has accelerated in direct response to the demands of intelligent warfare, which itself has been propelled by recent technological advances. Experts from AMS and the People’s Liberation Army (PLA) have highlighted several key capabilities that AI systems must achieve to meet the PLA’s evolving military needs. First, large AI models must enable rapid response and decision-making to enhance battlefield situational awareness and support command functions. This includes autonomous mission planning and assisting commanders in making informed decisions under complex conditions. Strengthening the fusion of information from multiple sources is also seen as crucial, using AI to integrate data from satellite feeds, cyber intelligence, and communication intercepts. This is then used to deepen intelligence analysis and support joint operations, as highlighted by the PLA Joint Operation Outline (中国人民解放军联合作战纲要), which entered its trial implementation phase in 2020 (MOD, November 26, 2020). [1]

Military AI is also being applied extensively to cognitive and psychological warfare (China Brief, September 6, 2019; September 8, 2023; June 21). Generative AI models can be deployed to produce media content to influence narratives, conduct strategic influence campaigns, and undermine an adversary’s morale, according to AMS experts. [2] Large Language Models (LLMs) like ChatGPT can also rapidly integrate diverse information sources to enhance military intelligence analysis. With strong language processing capabilities, they can simplify data extraction, support real-time translation, and transform complex data into actionable insights, aiding military personnel in decision-making on the modern battlefield.

Experts within the military apparatus, including top defense industry players like the China Electronics Technology Group (CETC; 中国电子科技集团), are currently working on AI to enhance cybersecurity and network threat detection. One paper authored by employees at CETC argues that AI models can play a pivotal role in identifying and countering cyber threats and establishing robust early-warning systems to fortify military communication networks. [3] Another area of focus is predictive maintenance and supply chain management. Here, AI can be used to anticipate equipment failures and streamline supply logistics. This optimization is critical for the PLA’s sustained operational readiness, especially during prolonged engagements.

PLA experts are prioritizing the development of smaller, more “lightweight” AI models for deployment in resource-constrained environments like frontline operations. These models must be robust and capable of performing effectively with limited computational power, making them suitable for edge devices—small computers or sensors that can process data and operate without relying on distant servers. The Aiwu Large Model (艾武大模型) is a good example of this. According to one research paper, Aiwu offers cross-platform compatibility on both manned and unmanned systems, and can execute diverse mission tasks under challenging conditions. [4]

PLA experts consider military AI to be a foundational asset that must be highly adaptable, capable of integrating multimodal data and supporting autonomous decision-making in a wide range of tactical and strategic contexts. This approach stems from the understanding that future warfare will demand intelligent systems capable of processing real-time data, making proactive decisions, and synthesizing information from diverse sources. [5]

PRC Researchers Adapt Llama to Meet Military Demands

The potential that PRC researchers see in Meta’s Llama model lies in the flexibility and efficiency of its foundational model. This makes it useful for adaptation to various military and security systems. [6] A recent iteration, Llama 3.1, was launched in July and was described as having “capabilities that rival the best closed source models” (Meta, July 23). (Llama 3.2 was released on September 25, and so has not yet been treated in relevant research.) As an open-source model, developers and researchers can modify and innovate on top of it. PRC security researchers have focused on adapting it for multilingual dialogue, high-quality code generation, and complex mathematical problem-solving. [7] They argue that the transformer model—an architecture for deep learning models that powers text-generating models like OpenAI’s ChatGPT, Meta’s Llama, and Google’s Gemini—enhances performance in tasks such as information summarization, threat analysis, and decision-making support that are crucial for defense and public safety (ACM, December 4, 2017). [8]....

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"Amazon to cough $75B on capex in 2024, more next year" (AMZN)

From The Register, November 1:

Despite extending server lifespans, AI's power demands drive more datacenter builds

Amazon expects to spend $75 billion on capital expenditure in 2024 and even more in 2025 – mostly on its cloud computing business – due to rising demand for generative AI and as more customers ditch their on-premises workloads.

The web services arm of Amazon (AWS) reported calendar Q3 net sales of $27.45 billion, up 19 percent year-on-year, and operating expenses of $17 billion, up from $16.08 billion. Operating profit jumped almost 50 percent to $10.45 billion.

In a contradiction to the message delivered to the UK's Competition and Markets Authority in its probe into the health of the local cloud market, AWS told investors last night that its business just keeps on expanding.

"We see more enterprises growing their footprint in the cloud, evidenced in part by recent customer deals with the ANZ Banking Group, Booking.com, Capital One, Fast Retailing, Itau Unibanco, National Australia Bank, Sony, T-Mobile, and Toyota," said Amazon CEO Andy Jassy, who previously ran AWS when Jeff Bezos headed Amazon....

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What our four years of blather regarding advantage flywheels is all about. 

In Nvidia's World, If You (and your company) Don't Have Money You Will Not Be Able To Compete (NVDA)

The advantage flywheels keep spinning and reinforcing each other to the point that the Pareto distribution of profits - 20% of companies reap 80% of the profits - is becoming Super-Pareto where 5% of the companies reap 95% of the profits and is approaching Hyper-Pareto at maybe 2% of companies reaping 98% of profits.

It all comes down to having the resources to keep up. 

I watched Mr. Huang give the keynote and it's all a bit much to digest before firing out comments that would make any sense at all so here are some of today's headlines to give a taste of what the intro paragraph is based on.

These are Nvidia's press releases via GlobeNewswire....

"Elon Musk says any company that isn’t spending $10 billion on AI this year like Tesla won’t be able to compete" (TSLA)

This.

This is such an important concept to grasp. It's the advantage flywheels, the rich get richer, winner-take-all reality of business in 2024....

The Hyper-Pareto Distribution Of Profits Is Happening Right Now (plus an anniversary)

It's not some cutesy management* fad or pop insight like "Business secrets of Genghis Khan."

To the rich go the profits and internalizing that fact makes the rest of this portfolio construction/fund management/investing stuff easier to conceptualize and execute.

And AI is accelerating the already extant dynamic....

*****

*Although people had been observing and discussing "rich get richer" and "winner-take-all" dynamics for over a century, one of our favorite pointers toward the current situation did come out of a business school. We've been hammering on this for so long that I start to bore myself. Here's a recapitulation from last year, linking to an article that was published seven years ago today:

HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

A prescient article from the Harvard Business Review, February 28, 2017:....

*****

Why Do the Biggest Companies Keep Getting Bigger? It’s How They Spend on Tech" 

...Much more important than the direct monetization of big data is the strategic advantage it can bestow over time.

In a winner-take-all economy, as in a horse race, small differences in superiority are rewarded all out of proportion to the actual advantage. A top thoroughbred may only be a couple fifths of a second faster than the field but those two lengths over the course of a season can mean triple the earnings for #1 vs. #2.

In commerce the results can be even more dramatic because rather than the 60%/20%/10% purse structure of the racetrack the winning vendor will often get 100% of a customer's business.....

Just to reiterate, every incremental advantage that a company can afford does not affect income production in isolation. They accrete in sometimes unforeseeable combinations:

How to Think About Companies: "Advantage Flywheels"

A very handy conceptual framework first posted after the start of the U.S. lockdowns, April 2020. Schools were closed so it seemed natural to link to a superb mini-MBA module.  

Eat your heat out HBR....

AI: Tesla Installing Second Dojo Supercomputer In New York Gigafactory (TSLA; NVDA)

AI: "Inside Tesla’s Innovative And Homegrown 'Dojo' AI Supercomputer" (TSLA)

It really is a big deal that a company can afford to spend over a billion dollars to build their own supercomputer and it really is a big deal that the same company has all the training data from the billions of miles of real-world driving and it really is a great example of the concept of advantage flywheels and hyper-pareto distribution of rewards, i.e. the rich get richer.

Whether it is going to open-up the $10 trillion addressable market and add the $500 billion of market cap that Morgan Stanley foresees is still an open question....

....As artificial intelligence comes more and more to the fore, the advantages accruing to those companies that can afford to make use of their data and custom train the machines will act as advantage flywheels that shift the distribution of profits from the normal Pareto: 80% of the loot goes to the top 20% of businesses to perhaps as much as 95% of all the profits going to the top 5% of businesses.

I didn't really mean the "eat your heart out HBR" line.

Here's the Harvard Business Review on this very point:
HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

And many more. If interested use the 'search blog' box, upper left.

Nukes: "US FERC rejects Amazon-Talen nuclear power agreement"

Good. The hyperscalers must pay their own way and produce/transmit a little extra for the public good.

From Global Data via Yahoo Finance, November 4:

The financial responsibility for necessary transmission and distribution upgrades remained unresolved. 

The US Federal Energy Regulatory Commission (FERC) has rejected an amended interconnection service agreement proposing to increase the load capacity of Amazon's data centre at the Susquehanna nuclear facility in Pennsylvania.

The amended agreement was executed between Talen Energy, PJM Interconnection and PPL Electric Utilities, and aimed to increase capacity at Susquehanna from 300MW to 480MW. 

FERC was concerned with the agreement's potential impact on the public, as increased capacity for the data centre could lead to higher power bills and affect the grid's reliability.

The regulatory body pointed out that diverting large amounts of power from the regional grid could result in a loss of supply, impacting electricity costs and grid stability....

....MUCH MORE

Quite a few of the names are down on the news including some of the old-line utilities such as Constellation Energy (down 10.8%).

Previously on Talen, March 6 - Amazon Just Bought A Nuclear Powered Data Center

Recently on the group, Oct. 27:

"Big Tech Is Betting on Nuclear Energy to Fuel A.I. Ambitions—But There’s One Problem"

Insightful reader (and most of ours are) may have noticed that amidst the hubbub surrounding small nuclear reactors powering artificial intelligence we haven't really pitched the companies, the Oklos and NuScales and Nano Nuclears and there's a reason for that: they aren't businesses yet. At best they are trading cards, lottery tickets, call options with unknown terms of exercise and expiration.

This view of the nascent group can look pretty darn fuddy-duddy in light of some of the moves in the stocks—60% to 120% in the last month and over 400% year-to-date but before they get to the point of having sales and earnings and cash flows there will be other opportunities to buy them, or their new competitors coming up. 

Once again it's Adam Smith and The Great Winfield and the Voodoo Beach Bunnies.*

And the headline story from Observer...

Andreessen Partner On Where The AI Opportunities Are For Investors

Keeping in mind that as recently as three years ago Marc Andreessen was quite enthusiastic about Web3 (never mind) and all that, it actually is good to know what Sand Hill Road is pitching. 

From the Wall Street Journal, October 27:

A Venture Capitalist on Where the AI Opportunities Are for Investors
Andreesen partner Martin Casado says there are three uses of artificial intelligence that are working for companies right now

Heaps of money have been invested in artificial intelligence. Valuations are soaring.

What does it mean for companies—and investors—looking to get a piece of it all? Where are the opportunities?

To get some answers, The Wall Street Journal’s global technology editor, Jason Dean, spoke with venture capitalist Martin Casado, a general partner at Andreessen Horowitz, at the annual WSJ Tech Live conference. Here are edited excerpts of their conversation.

The start of a supercycle

WSJ: What type of AI startups are interesting now, and not too expensive or too late?

MARTIN CASADO: It’s good to draw a comparison to the internet. Periodically in the history of the industry, we’ve seen the marginal cost of things go to zero. With compute, the marginal cost of computation went to zero. We had people calculating logarithm tables by hand, then we had a computer do it. That created the compute revolution. Then the internet, the marginal cost of distribution went to zero. When it comes to AI, it really feels like the marginal cost of language, reasoning and creation are going to zero. And if that’s the case, this is a supercycle. And if that’s the case, we’ve got decades. So there’s no “too late.” In that sense, we’re still very, very early.

Right now, these models that you hear about from Google and OpenAI and Anthropic, they’re backed by these massive companies that are not going to crash. Clearly this is strategic value to them, the beginning of something great.

There are these very large models that everybody’s heard about, like Gemini and OpenAI. But there are a bunch of smaller models that do things like speech or music or images. And if you look at that cohort of companies as an investor, they’re actually very successful.

WSJ:There are already huge valuations for some. The barrier to entry there seems like it might be getting more difficult. What is most interesting now?

CASADO: There are three use cases that are working right now, and maybe many more will work in the future.

Probably the use case working the most is creative composition. That thing could be an image, music. A number of companies in this space are growing as quickly as we’ve seen anything growing.

Imagine a AAA videogame. How much does it cost to create? Say $500 million to $1 billion. There’s not one aspect of that game that a model today could not create. You can create the 3-D meshes, the stories, the videos, the textures—and the actual compute inference cost to create all of that is like $10.

The No. 2 use case, it’s kind of a funny one. It’s companionship. We’ve never, as technologists, solved the emotion problem with computers. They’ve very clearly not been able to emote. But I’ll give you an example. My daughter is a Covid kid. She’s 14 years old right now and spends a lot of time on Character.AI. And not only does she spend time on Character.AI, when she talks to her friends she will bring her characters along. It has kind of entered the social fabric. We’re seeing great use of these kind of companionships.

The third space definitely working is code. For example, with Cursor, an AI code editor, you can program very sophisticated programmers, whether you’re an expert programmer or a novice programmer, using models, and they’re working very well....

....MUCH MORE

Capital Markets: "US Polls Spur Position Adjusting Ahead of Tomorrow's Election"

From Marc Chandler at Bannockburn Global Forex:

Overview: Weekend polls in the US made it seem that the Trump victory, which many large pools of capital, had discounted, was not so inevitable after all. The most dramatic market response was taking US yields and the dollar lower. The US 10-year yield is off about nine basis points to straddle 4.30% and the two-year yield down four basis points to around 4.16%. The greenback is also against all the G10 currencies. Most emerging market currencies are also firmer, led by central Europe and the Mexican peso.

Equities are mostly higher. Tokyo markets were closed for a national holiday but most of the large markets in Asia Pacific rose, with the exception of India. The MSCI Asia Pacific Index has fallen for the past five weeks. Europe's Stoxx 600 is trying to snap a two-week decline, and it is posting its first back-to-back gain in more than two weeks. US index futures also enjoy a firmer tone. European benchmark 10-year yields ae mostly 1-2 bp firmer, but Italian and Spanish bond have caught a bid, and yields are a little softer. On the other hand, Gilt yields are continuing to rise since the budget. The yield was near 4.20% before the budget and poked above 4.50%. It is now near 4.47%. Gold slipped closer to $2730 today (~$2736.70 settlement) before steadying. It is trading quietly near $2740 now. Iran's threat to strike back at Israel and OPEC+ decision to postpone production increases for the second time is lending support to December WTI. It is trading firmly near last week's high above $71. ...

....MUCH MORE

"Tesla's Oct. China-made EV sales fall 5.3% y/y" (TSLA)

From Reuters via Yahoo Finance, November 3:

BEIJING (Reuters) -US automaker Tesla (TSLA) sold 68,280 China-made electric vehicles in October, down 5.3% from a year earlier, data from the China Passenger Car Association (CPCA) showed on Monday.

Tesla stock was down over 1% in premarket trading on Monday.

Deliveries of China-made Model 3 and Model Y vehicles fell 22.7% from the previous month....

....MUCH MORE

The stock was recently changing hands at $244.52 down $4.46 (-1.79%). 

Indonesian Sovereign Wealth Fund INA and Singapore-Based Venture Capital Firm Granite Asia To J.V. $1.2 Billion Into Indonesian Tech

From Reuters via U.S. News and World Report, November 3:

SINGAPORE (Reuters) - Indonesian sovereign wealth fund INA and Singapore-based venture capital firm Granite Asia said on Monday they will jointly invest up to $1.2 billion in Indonesia's technology sector and in businesses with strong ties to the Southeast Asian nation.

The firms said in a joint statement that the investments will span both equity and hybrid capital. The statement did not say how much of the $1.2 billion will be shouldered by the two entities or over what period of time the investments will be made. It also did not name any intended beneficiaries....

....MORE

A smart Western VC would try to get some of this action before the Emirates or other GCC wealth funds tie it up. 

"Nvidia Reportedly Weighing Investment in Musk’s xAI" (NVDA; ELON)

Although the A.I. biz is not yet incestuous it does have a bit of an ouroboros vibe to it.

From PYMNTS.com, November 3:  

Nvidia is in discussions to invest in Elon Musk’s artificial intelligence (AI) startup, according to published reports.

Musk’s AI firm xAI is hoping to raise several billion dollars, valuing the company at around $40 billion, the New York Post reported Friday (Nov. 1).

A separate report by The Information says Musk had been in discussions with tech companies and venture firms such as Sequoia Capital, Andreessen Horowitz and Vy Capital.

Musk is expecting in January to hold a major funding round that could value xAI at as high as $75 billion, two sources told the Post.

And an analyst for Nvidia, speaking with the newspaper on the condition of anonymity, said that xAI’s rivals would still buy chips from Nvidia even if it invests in Musk’s company.

“If not, this transaction would never go forward,” the analyst said....

....MUCH MORE

Or maybe, as noted in October 12's "Materials Science: Using AI To Find New Chip-

And then, be still my heart, will the chips learn to train the next generation?  

Getting a bit of a double ouroboros vibe here:

Here at Ouroboros Group we believe a self-referential vortex of strange loops is the key to exceptional market depravity and thus dream demon returns at rates essentially double those of typical simple ouroboros techniques and paradigms.

—from 2018's Unicorns Backing Their Own VCs? Welcome to Peak Tech

More on cousin marriage in September 5's "ChatBots Are Not The Be-All And End-All Of Artificial Intelligence".

"The 20 greatest trading innovations"

 From The Trade, October 24:

In celebration of The TRADE’s twentieth birthday, editor Annabel Smith rounds up the 20 greatest trading innovations of the last few decades, exploring the solutions that have overhauled and reimagined the processes that traders depend on day in and day out to execute in the markets

1. Order and/or execution management systems (OEMS)

Kicking off this whistle-stop summary as the number one most impactful innovation in the industry is the order and/or execution management system (OEMS) – the beating heart of trading desks around the world. Brought to market in the early 2000s, the sometimes combined and sometimes separated systems were designed to enhance the previously manual processes associated with managing and executing orders. They offer a nifty alternative to the previous plethora of both written records and later, excel spreadsheets that traders were previously forced to grapple with each day to keep things in order.

These systems touch upon all elements of the trading lifecycle throughout the front-to-middle-to-back-office including execution, order, risk and portfolio management. Traders’ order blotters sit within these systems and trading teams use these systems to consolidate data sources and research in one place to increase efficiency and speed when going about day-to-day activities. They also use them to access the market, connecting directly to counterparties to access liquidity. An EMS overlays an OMS by enhancing connectivity, aggregating data and being more flexible as it solely pertains to execution needs.

2. Bloomberg Terminal

Up next and needing little introduction is the Bloomberg Terminal, Bloomberg’s data and proprietary trading platform. First brought to market in the early 80s the system has over the decades earned its title as the leading market data source and a must have for any financial institution looking to execute in the markets. This is reflected in its annual subscription now nearing $30,000. For this reason, the system is favoured by institutional investors as opposed to individual ones.

Its black background and computerised white text might seem a little out of date to individuals outside of the industry but its role in the financial markets has cemented this interface as a poster child for financial services. Home to Bloomberg’s central data services the interface offers users access to news, data, analytics, and multi-asset trading tools. Given its widespread adoption by institutions it’s also a people move source as users can see up to date contact details of peers. According to Bloomberg, it offers  sell-side and independent research from over 1,500 sources as well as proprietary research on various industries and markets.

3. CLS

Coming in at number three is the multi-currency settlement system, CLS. While perhaps not one of the most exciting aspects of the trade lifecycle, settlement is a central process that acts as a pillar for the capital markets. The settlement period relates to the space of time between the trade date and the settlement date when a trade is considered complete. Within this window both the buyer and seller must undertake any necessary actions to ensure the transaction can be completed.

Established in 2002, the CLS network is designed to minimise risk and offer operational efficiency to institutions within the settlement window by avoiding bilateral settlement that is more likely to fail.

The settlement window has found itself in the industry spotlight as of late thanks to the recent decision from regulators in the US to move North American markets to a T+1 settlement period, down from T+2.

4. Central limit order book (CLOB)

While it is easy to romanticise the sheer graft that went into trading a few decades ago, the introduction of central limit order books (CLOBs) and streamed pricing were much-needed innovations. The idea that in order to understand the changing price of an individual stock or security, one would have to study daily directories and newspapers is something that many of those starting out in the industry today will never understand. With no central directory of orders in the market, understanding pricing must have been a headache to say the least, leaving many individuals subject to arduous process of calling everyone in the phone book.

CLOBs allow for transparency of live orders that are prioritised by price and time. By seeing what is available on the order book, traders have an idea of how much volume can be executed at a specific price. Facilitated by exchanges, a CLOB allows buyers and sellers to submit their trading interests and then utilises a matching engine to match buy and sell orders based on specific requirements such as price time priority. Once a trade has been matched the buy and sell orders are removed from the order book and the bid and ask prices are updated accordingly to reflect the change.

CLOBs offer greater transparency and consolidated liquidity meaning participants have a greater chance of trading. They’re typically used in equities given that this asset class trades on exchange unlike fixed income and some foreign exchange assets. Thanks to huge leaps in technology, participants can hide their full amounts in what’s known as “iceberg orders” that replenish the order book once liquidity has been matched and removed from the book.

5. Algorithmic trading

Rounding out the top five of The TRADE’s rankings of the most influential innovations to come to trading are algorithms and the concept of executing algorithmically or automatically. Most common for low touch and ‘easy flow’ algorithms are often used for small orders in highly liquid markets. Algorithms are a computer programmed trading workflow that follows a defined set of parameters. These parameters could be anything from liquidity seeking to volume dependant or venue-specific such as dark seeking.

Algorithms often offer traders a quick and easy route to market. They remove the opportunity for human error by taking away any manual processes and offer a low latency solution that will often achieve best execution and avoid any unwanted price changes.

While this all sounds fantastic and you may be wondering why they aren’t used for all flow, there are some downsides. Unpredictable activity in the markets such as Black Swan events can render algorithms that rely on historical data useless and result in losses for firms. At the other end of the spectrum, a lack of human judgement and intervention can sometimes result in lesser results in nuanced situations that require human intuition.

Buy-side institutions will often use a broker’s algorithmic suite for execution, with many sell-side institutions vying for the interest of clients with the launch of new and innovative products with flashy names. Less common is the development of proprietary algorithms inhouse on the buy-side given the cost, time to implement, and the speed at which priorities evolve. For more information on algorithmic trading providers, check out The TRADE’s annual survey....

....MUCH MORE

I'd have to go with pockets. Or more broadly, storage in all its guises:

Following Up On "Commodity traders superior to chimpanzees": The Importance of Pockets

Storage: Very Important To Roman Emperors and Commodities Market Manipulators

*****

....How can you not love a book whose very Preface begins:

How do you know an empire when you see one? One classic answer to this
comparative conundrum is to look at storage facilities. Empires, it is assumed,
extract and centralize resources from across their territories, a brute imperialism
that finds expression in massive, central storage complexes and a continuing
concern with the circulation of stuff. The dazzling archaeological remains of
storerooms at Rome's ports of Ostia and Portus are testimony that the Roman
empire fits this rather restricted bill. But what can storage do beyond this
exercise of identification? Storage has more to offer the student of the Roman
world: as a topic that is at once at the core of survival and prone to envy, strife,
and competition; as a practice that is both grounded in the matter of economics
and inhabiting the social imagination, as an acute concern for farmers and 
rulers alike - storage opens up an inquiry into the very anatomy of Roman 
socio-economics....

If interested see also at Cornell Research:

The Emperor’s Closet—Power and Storage

Previously on the Storage Channel:

"The Effect of Futures Markets and Corners on Storage and Spot Price Variability".
To Create A "1%" In A Social Hierarchy You Don't Need An Economic Surplus, Just A Storable Form Of Wealth 
The Golden Age of Commodities Market Manipulation: Corners, Storage and Squeezes

These days however, to purloin that wealth, you don't even need to be dealing with storables:
How to Manipulate Non-storable Commodities Markets

Remember, the spectrum runs from storage to hoarding to market corners.
And corners in commodities refers to physical, you can't corner a commod by simply buying futures or forwards, you also have to take up the physical supply.
Conversely, squeezes are accomplished in the futures..

A couple decent papers on this aspect of the abundance theory are:
"Large Investors, Price Manipulation, and Limits to Arbitrage: An Anatomy of Market Corners" 

and
"Market Manipulation, Bubbles, Corners and Short Squeezes"
The only way to combat abundance is with artificial scarcity, i.e. manipulation....

 And back to pockets:

 London Property Will Always Be Affordable

"The money is always there, it's only the pockets that change"

-Gertrude Stein,

Also attributed to Coco Channel as:

"Money is money is money, it's only the pockets that change".

Possibly related:

What Have The Etruscans Ever Done For Us? (freeports and other storage facilities) 

"The Myth of scarcity and its threats to human society" [it all began with the Quaternary Megafauna Extinction and explanatory journalism]

"Malaysia expects its 'remarkable' IPO boom to continue in 2025"

 From Nikkei Asia, November 4:

CEO of local exchange eyes 50 listings, 20-year high on robust economy

While companies' initial public offering activities slowed in most Southeast Asian markets this year, one country is bucking the regional trend: Malaysia.

From a palm oil producer to a grocery chain, a number of new listings underscore what the local bourse calls a "remarkable" year for Malaysia's equity market, with its chief executive expecting that the IPO boom will continue in 2025....

....MUCH MORE

 

As noted a couple months ago:

"Singapore-Traded Grand Venture Technology Eyes Second Listing in Malaysia"

From Bloomberg, September 11:

• Components maker GVT could list shares in KL in 2025: sources
• Malaysia IPOs have raised far more than Singapore this year....

"Dollar slips ahead of US election and as Fed rate cut looms"

From Reuters, November 3:

Summary

• Dollar down early as dealers ponder election probabilities
• Fed and BoE priced to cut by 25 bps, Riksbank by 50 bps
• Eyes on possible China fiscal stimulus this week

SYDNEY, Nov 4 (Reuters) - The dollar slipped in Asia on Monday as investors braced for a potential pivot this week for the global economy as the United States chooses a new leader, and as it likely cuts interest rates again with major implications for bond yields.

 

The euro rose 0.4% to $1.0884 but faces resistance around $1.0905, while the dollar fell 0.7% on the yen to 151.81 yen . The dollar index eased 0.1% to 103.79.

 

Treasury futures rallied 10 ticks, recovering some of the losses suffered on Friday....

....MUCH MORE

We Are Missing Three+ Weeks Of Changes To The Internet

The headline at the Brownstone Institute seems a bit overwrought with "They..." but the story itself is huge:

October 30, 2024 

They Are Scrubbing the Internet Right Now 

Instances of censorship are growing to the point of normalization. Despite ongoing litigation and more public attention, mainstream social media has been more ferocious in recent months than ever before. Podcasters know for sure what will be instantly deleted and debate among themselves over content in gray areas. Some like Brownstone have given up on YouTube in favor of Rumble, sacrificing vast audiences if only to see their content survive to see the light of day. 

It’s not always about being censored or not. Today’s algorithms include a range of tools that affect searchability and findability. For example, the Joe Rogan interview with Donald Trump racked up an astonishing 34 million views before YouTube and Google tweaked their search engines to make it hard to discover, while even presiding over a technical malfunction that disabled viewing for many people. Faced with this, Rogan went to the platform X to post all three hours. 

Navigating this thicket of censorship and quasi-censorship has become part of the business model of alternative media. 

Those are just the headline cases. Beneath the headlines, there are technical events taking place that are fundamentally affecting the ability of any historian even to look back and tell what is happening. Incredibly, the service Archive.org which has been around since 1994 has stopped taking images of content on all platforms. For the first time in 30 years, we have gone a long swath of time – since October 8-10 – since this service has chronicled the life of the Internet in real time. 

As of this writing, we have no way to verify content that has been posted for three weeks of October leading to the days of the most contentious and consequential election of our lifetimes. Crucially, this is not about partisanship or ideological discrimination. No websites on the Internet are being archived in ways that are available to users. In effect, the whole memory of our main information system is just a big black hole right now. 

The trouble on Archive.org began on October 8, 2024, when the service was suddenly hit with a massive Denial of Service attack (DDOS) that not only took down the service but introduced a level of failure that nearly took it out completely. Working around the clock, Archive.org came back as a read-only service where it stands today. However, you can only read content that was posted before the attack. The service has yet to resume any public display of mirroring of any sites on the Internet. 

In other words, the only source on the entire World Wide Web that mirrors content in real time has been disabled. For the first time since the invention of the web browser itself, researchers have been robbed of the ability to compare past with future content, an action that is a staple of researchers looking into government and corporate actions. 

It was using this service, for example, that enabled Brownstone researchers to discover precisely what the CDC had said about Plexiglas, filtration systems, mail-in ballots, and rental moratoriums. That content was all later scrubbed off the live Internet, so accessing archive copies was the only way we could know and verify what was true. It was the same with the World Health Organization and its disparagement of natural immunity which was later changed. We were able to document the shifting definitions thanks only to this tool which is now disabled. 

What this means is the following: Any website can post anything today and take it down tomorrow and leave no record of what they posted unless some user somewhere happened to take a screenshot. Even then there is no way to verify its authenticity. The standard approach to know who said what and when is now gone. That is to say that the whole Internet is already being censored in real time so that during these crucial weeks, when vast swaths of the public fully expect foul play, anyone in the information industry can get away with anything and not get caught.....

....Disturbingly, this erasure of Internet memory is happening in more than one place. For many years,  Google offered a cached version of the link you were seeking just below the live version. They have plenty of server space to enable that now, but no: that service is now completely gone. In fact, the Google cache service officially ended just a week or two before the Archive.org crash, at the end of September 2024....

....MUCH MORE

On second thought, there might be a "They..."

Previously (Oct. 12) - After Breach and DDOS Attack The Internet Archive Is Still Down

Also the WEF post- "Psychologists say a good life doesn’t have to be happy, or even meaningful"

We'll be coming back to Debbie Lerman after the election. She was one of the very few researchers who....well, you'll see.