"Chinese EV company launches automated factory where humanoid robots build humanoid robots"

From Mumbai's FirstPost, September 8:

Chinese electric vehicle maker XPeng says it has commissioned an automated production line designed to manufacture advanced general-purpose humanoid robots, in what the company describes as a first for the industry.

The announcement came from XPeng CEO He Xiaopeng, who shared images of the facility and a humanoid robot on X. According to He, the production system is designed to use robots to manufacture robots, reducing the extent of manual involvement in the assembly process.

Today, we launched the world’s first automated production line for advanced general‑purpose humanoid robots, using robots to mass‑produce robots, autonomously. This was uncharted territory, and we solved it from scratch. The commissioning of our production line means humanoid robots are now ready to scale up and step into the real world. What touched my heartstrings most was watching our very first advanced general‑purpose humanoid robot complete assembly and walk off the line on its own. To me, this is not just about a smarter tool or a commodity. I hope it gains true generalization ability to take on dangerous, repetitive, or undesirable tasks, and ultimately make life better. Perhaps one day, robots may become our companions, friends, or part of family. Grateful to every colleague on this momumental mission. And a warm welcome to IRON!

— Xiaopeng He (@xiaopenghexpeng) September 8, 2026

Continues:

...The commissioning of our production line means humanoid robots are now ready to scale up and step into the real world.

What touched my heartstrings most was watching our very first advanced general‑purpose humanoid robot complete assembly and walk off the line on its own. To me, this is not just about a smarter tool or a commodity. I hope it gains true generalization ability to take on dangerous, repetitive, or undesirable tasks, and ultimately make life better. Perhaps one day, robots may become our companions, friends, or part of family.

Grateful to every colleague on this momumental mission. And a warm welcome to IRON! 

....MUCH MORE

And In Other Elon Musk News....

We haven't had any Elon posts recently but that headline is evergreen, on any given day someone somewhere is publishing something on Mr. Musk.

Our most recent mention of the man was the outro from September 9's "Meanwhile, In Shanghai: Investors Demand Brain - Computer Interface Companies":

....Also quite a few posts on Elon Musk and Neuralink and on Dr. Miguel Nicolelis.

Which led me to ask the GoogleBox about Neuralink which led to Business Insider, July 21:

Investors are valuing Elon Musk's Neuralink at $42 billion on secondary markets

Demand for a piece of anything related to Elon Musk is booming.

The near-trillionaire's brain chip startup, Neuralink, is being valued as high as $42 billion in recent secondary market transactions, according to correspondence seen by Business Insider and a person familiar with the matter.

That's an almost five-time increase from Neuralink's last funding round last year, when the startup raised at a $9 billion valuation, Semafor reported at the time.

According to private markets research provider Caplight, transactions in recent months have ranged from $29 billion to $42 billion, with some current bidders even attempting to buy shares at an almost $60 billion valuation....

....MUCH MORE 

Flashback: What I'm Reading: Gambler's Fallacy and the Hot Hand

Most of our visitors know this stuff but here we have such a good exposition it may be worth a gander for even the time-constrained reader
Bold emphases mine.
From Frontiers in Psychology, Feb. 5, 2015:
Small samples and evolution: did the law of small numbers arise as an adaptation to environmental challenges?

Gorka Navarrete^1*, Carlos Santamaría² and Dan Froimovitch³

• ¹Laboratory of Cognitive and Social Neuroscience, Psychology Department, Universidad Diego Portales, UDP-INECO Foundation Core on Neuroscience, Santiago, Chile
• ²Cognitive Psychology Department, University of La Laguna, Tenerife, Spain
• ³Department of Physiology, University of Toronto, Toronto, ON, Canada

In the context of casino gambling, only a minority (~15%) of players presented with a streak of at least length 6 in roulette disregard recent events in deciding their next move, which is the normatively optimal approach to such a decision (Croson and Sundali, 2005). The majority of people would instead subscribe to a belief in a recency effect. This intriguing pattern of reasoning is categorized as either the gambler's fallacy, when the subject perceives negative recency (GF; Laplace, 1951; Tune, 1964; Tversky and Kahneman, 1971), or as the hot hand fallacy, when positive recency is perceived (HH; Gilovich et al., 1985). Such tendencies demonstrate, among a variety of things, that magical thinking is not exclusive to astrologists and tarot fanatics. Both the GF and HH refer to instances of the subject projecting a relationship between prior and present events, albeit in opposing directions. 

For example, subsequent to observing a run of 6 “heads,” a subject committing the GF would expect “tails” on the next coin toss. Alternatively, a subject committing the HH, following a similar streak of, say, successful basketball throws, would expect another “hit” on the next throw. Both fallacies have been posited as consequences of our immanent adherence to the law of small numbers—a distorted conception of chance, according to which short random sequences are considered highly representative of their underlying generating process (Tversky and Kahneman, 1971; Gilovich et al., 1985); But, counterintuitively, when dealing with sequences governed by chance, the short sub-sequences that we mistake as essentially representative of the overall generating process, actually deviate systematically from sequential properties on the global level; such small sub-sequences, on the basis of which we draw predictive inferences, are rather misrepresentative, containing excessive alternations and lacking sufficient long runs (Gilovich et al., 1985).

When predicting the next outcome in a random bivariate sequence of events, after having observed a local streak in either direction, we tend to fall into one of two behavioral categories, depending on how random the underlying process is perceived to be (Burns and Corpus, 2004). In accordance with the law of small numbers, when the conception of a random generating process is committed to, we expect the next event following a streak of a particular signal to switch to the alternate signal. Alternatively, when the generating process is believed to be nonrandom, we tend to expect the next signal to be consistent with that of the preceding streak. In very simple terms, given a streak in one direction (e.g., three heads in a row):

(a) When a causal mechanism explaining the streak does not easily come to mind, we tend to commit the GF (e.g., after a few heads, we believe the next throw is more likely to land tails). This occurs most often when the sequential probability is perceived to be fixed (Navarrete and Santamaría, 2012).

(b) When a causal mechanism is easily accessible (e.g., tampered coin, hot hand, etc.), and the sequence appears to be non-representative of our typified notion of a random sequence, we tend to commit the HH (e.g., after a few successful shots, the player is more likely to succeed again).

In general, we hold—or are inclined to feel as though we hold—a certain degree of control over the events of our immediate environment (Harris and Osman, 2012). We tend to think that the probability of experiencing a car accident is related to our performance behind the wheel; and while this is oftentimes the case, it is definitely not the case as frequently as we would like. The difficulties humans encounter in dealing with phenomena of fixed probabilities are likely related to the fact that, amidst our proximal surroundings, things rarely appear to occur by pure chance. 

Ordinary events around us are sourced in recognizable causes and elicit appreciable consequences. 

Moreover, we are innately specialized in discerning patterns (Lopes, 1982) and cause-effect relationships between successive events—especially those in temporal proximity to one another. From an ecological standpoint it is rare for one to observe sequential events that are completely independent of each other (Ayton and Fischer, 2004). Thus, it is of little surprise that we exhibit a distinctive ineptitude when it comes to handling random sequences.

Situations in which past events bear no influence on those of future ones, and, in particular, in which the probability of sequential outcomes is fixed, are primarily confined to games of chance, psychology laboratories, and sample spaces that tend toward infinity (Navarrete and Santamaría, 2012). Games of chance are known to be commonly addictive—a feature perhaps attributable to an illusory sense of control linked to an incapability to understand how they operate.

One could argue that games of chance were created with the intent of deceiving humans (Pinker, 1997). Moreover ecological circumstances in which the sample-size accessible to the subject exceeds a few dozen events are virtually absent from a rural or hunter gatherer setting (and likely from any other). Throughout our evolutionary history, it is likely that humans confronted minimally-sized samples exclusively, for which our current limited-capacity numerical cognition served us adequately (as a cautionary side note, see (Navarrete and Santamaría, 2011) for a comment on why such evolutionary arguments should be treated with special care). The numerical representations we seem hardwired to invoke are ill-suited for the processing of large samples....MUCH MORE 

Also at Frontiers in Psychology:
Nepotistic patterns of violent psychopathy: evidence for adaptation?

Previously in Gambler's Fallacy and the Hot Hand:
"How to Make a Bad Decision"
How Gamblers Get Hot (the 'hot hand' is real)

Recognizing and then managing a trader's hot streak is one of the more challenging things you can do in finance especially when the trader can't articulate what's going on, whether in credit derivatives or octopods who pick World Cup winners....

Baseball and Investing: "The ‘hot hand’ might be real after all"
"Luck vs. skill: What Bill Gross and Bill Miller have in common"
Taxonomy of Logical Fallacies (or How to open your mouth without removing all doubt*)

Speaking of fallacies (post immediately below)....a repost from August, 2009. You'll find the Gambler's Fallacy under the Probabilistic fallacies:... 

A Glossary of Luck

The language of luck, from “gris-gris” to “Irish lottery.”
apophenia: The tendency to perceive connections or meaningful patterns in random data; often used in ref. to divination, as in reading of tea leaves, or Roman practice of finding meaning in entrails. (See also gambler’s fallacy.) 
depressive realism: A psychological hypothesis that claims depressed people judge their control of events more accurately than do nondepressed people.  

Predicting the Improbable
"The ‘Hot Hand’ Debate Gets Flipped on Its Head"
Baseball and Investing: "The ‘hot hand’ might be real after all"
Luck vs. skill: What Bill Gross and Bill Miller have in common
More on The Top Earning Hedge Fund Managers and The Metaphysics of Moolah
"Can Investors Profit Using Academic Research?"
Investing Tips From the Dalai Lama
Remember When the Unluckiest Man in the World Won the Lottery?

Originally posted December 19, 2016 

For the Victims of 9/11

 Rest in Peace

Inflation: UP 0.4% For The Month Of August; Up 3.4% Over The Last Twelve Months

 From the Bureau of Labor Statistics, September 11:

CONSUMER PRICE INDEX - AUGUST 2026

The Consumer Price Index for All Urban Consumers (CPI-U) increased 0.4 percent on a seasonally adjusted basis in August after rising 0.1 percent in July, the U.S. Bureau of Labor Statistics reported today. Over the last 12 months, the all items index increased 3.4 percent before seasonal adjustment.

The index for gasoline rose 3.9 percent in August, accounting for over one third of the monthly all items increase. The index for energy increased 2.1 percent over the month. The shelter index rose 0.3 percent in August after rising 0.1 percent in July. The index for food increased 0.1 percent over the month, as the index for food away from home increased 0.3 percent. 

The index for all items less food and energy rose 0.3 percent after increasing 0.2 percent in July. Indexes that increased over the month include communication, lodging away from home, airline fares, education, and used cars and trucks. Conversely, the index for medical care and the index for motor vehicle insurance were among the major indexes that decreased in August.

The all items index rose 3.4 percent for the 12 months ending August as it did for the 12 months ending July. The all items less food and energy index rose 2.4 percent over the year, following a 2.5-percent increase over the 12 months ending July. The energy index increased 16.3 percent for the 12 months ending August. The food index increased 2.7 percent over the last year....

....MUCH MORE 

Over the last twelve months the price of gasoline is up 27.4% and the price of fuel oil is up 52.0%.

—Table A. Percent changes in CPI for All Urban Consumers (CPI-U): U.S. city average 

If interested see also: 

Table 2. Consumer Price Index for All Urban Consumers (CPI-U): U. S. city average, by detailed expenditure category  

"Diesel Crunch Set To Worsen As Refining Capacity Falls Short, Industry Warns"

From ZeroHedge, September 10:

The global diesel market - already trading at record prices - is set to further tighten in the coming months and keep fuel prices high, raising the prices of all goods and threatening the inflation targets of the central banks.

Industry officials, who gathered at the APPEC petroleum conference in Singapore this week, warned that the market has not seen the worst of the diesel crisis yet. Analysts say the real stress in oil markets is in the diesel market right now, OilPrice reported.

Global fuel markets are very tight and inflexible, despite the higher crude oil flows out of the Persian Gulf in recent weeks, Russell Hardy, chief executive of the world's biggest independent oil trader, Vitol Group, said on Tuesday.

“We're still not running enough refining capacity to prevent those draws, and we keep eating into the surplus that exists around the world,” Hardy said at the event, as carried by Bloomberg.

Despite the uptick in flows from the Strait of Hormuz, only 1 million barrels per day (bpd) out of an estimated 10 million bpd outbound flows are refined products, the rest is crude.

Refinery capacity is constrained in the Middle East, due to Iranian strikes on refineries and the trickle of fuel flows through Hormuz.

Moreover, refinery capacity in Russia is also severely restricted by nearly-daily Ukrainian drone strikes at Russian refineries, while Russia has banned diesel exports until at least the end of September.

Refineries in the United States and elsewhere have been running at maximum capacity this summer, having delayed maintenance. But they are unlikely to continue operating at these elevated utilization rates for much longer....

....MORE 

And at Bloomberg, September 11: 

US Diesel Prices Rise Past $6 a Gallon for First Time Ever 

"'Clean' Energy And Tech Spending Slides 17%. New Report Blames China, But Doesn't Tell The Whole Story."

From Investor's Business Daily, September 10:

Global spending on "clean" energy and clean tech plunged 17% in the first half of 2026, according to Rhodium. The research firm's new report peels back global spending trends across solar energy, electric vehicles, sustainable aviation fuel, and manufacturing.

Investments in the first quarter in particular fell so much than even a Q2 bump couldn't make up the difference. Q1 spending on cleaner energy plus related tech and manufacturing fell by $151.1 billion, or 28%, returning to 2024 levels, per Rhodium.

Its Clean Investment Monitor report pins 88% of the global decline on China in Q1, as it cut tax incentives for electric cars and transitioned solar and wind generation "toward market-based pricing." The latter, the report said, "drove a rush of installations ahead of the (June 2025) deadline, followed by an uneven pullback."

Electric car sales in the U.S. followed a similar trend in the first half of 2026. EV sales took off last summer after the Trump administration moved to slash tax incentives, triggering a subsequent pullback that makes year-over-year comparisons look grim, per earlier Benchmark reports.

Unsteady investments also show up in solar and battery manufacturing investment, which both declined globally, slipping 13% sequentially in Q1 and falling another 6% in Q2, per Rhodium. The sector's wobbly year to date also shows up in clean energy and technology stocks such as Tesla and First Solar.

Bright Spots In Other Clean Energy Reports....

....MUCH MORE 

"The Value Gap: Europe Cannot Scale"

I'm still smarting over the cat pee story. 

A working paper from the National Bureau of Economic Research, August 2026:

ABSTRACT
In 2008, the aggregate market value of U.S.-listed firms was roughly one-third higher than that of European-listed firms. By 2023, it was more than 300% higher, a difference of $34 trillion. The valuation gap is broad-based, rather than concentrated among a few superstar firms, and is driven by differences in firm values, not in the number of listed firms. Across sectors, the gap is larger in R&D-intensive industries and in industries with high returns to scale. European firms’ size is strongly correlated with home-country GDP, whereas U.S. firms’ size is unrelated to home-state GDP. Smaller European firms also face a particularly large cost-of-capital gap and do not appear able to substitute debt for limited access to equity financing, including venture capital. Taken together, these facts suggest that financial and product-market frictions constrain European firms’ ability to scale. 

I. INTRODUCTION

In 2008, the aggregate value (market capitalization) of U.S. publicly listed firms exceeded that of European firms by a third. By 2023, the U.S. stock market value exceeded Europe’s by more than 300%. The gap has risen from 3 trillion to 34 trillion USD, more than the value of U.S. GDP. This divergence is not a matter of exchange rate movements or the current size of the economy: scaled by GDP, U.S. market capitalization rose from 78% to 177% between 2008 and 2023, while Europe’s rose from 43% to just 63%. It is not a reflection of migration by European firms: cross-listing explains little of the gap. Instead, the main driver is the addition of several generations of younger firms with immense growth potential (and, in several cases, the realization of that potential), and with very high valuations. This simply has not happened in Europe.

What explains the lower valuation of European firms? Differences in the number of
listed do not explain the value gap, which is entirely driven by an increase in the average value of U.S. firms relative to European firms, i.e. this is a valuation gap. The valuation gap does not reflect sectoral composition—the average within-sector (where sectors are defined using the 4-digit SIC taxonomy) U.S.-Europe gap is 50%, while the unconditional gap is 62%. It is not driven by a handful of superstar firms. Therefore, broad-based valuations differences drive behind the gap. When we examine how firms are valued, we find that the gap in value is largest among younger, and more R&D-intensive firms, and within industries where scale economies are important.1 The U.S.-Europe gap, in otherwords, is driven by growth opportunities: in the number, size, and quality of high-growth
firms.

Our results are consistent with a technological change that has raised the returns to scale. Recent technologies—information technology, software, and intangible capital—disproportionately reward firms that can grow large (Bloom et al., 2012; Schivardi and Schmitz, 2020; Lashkari et al., 2024; De Ridder, 2024). Firms in the United States have adopted and exploited these technologies faster than European firms. A shift of this kind raises the value of exactly the firms where we find the largest differences: younger, smaller, R&D-intensive firms, and in industries where the winners can scale up quickly....

....MUCH MORE 

"Cat Pee Was the Billion-Dollar Business Nobody Saw Coming"

I'm obviously doing something wrong with this energy and high-tech approach.

From Inc., September 10:

Founder Daniel Rotman raised little money, hired cautiously, and built around a practical product instead of growth-at-all-costs. The result was a $1.4 billion acquisition by Mars.... 

....VIDEO 

Inc. had the story back in June:

Cat Fancy: How Daniel Rotman’s PrettyLitter Turned $1 Million in Capital Into a $1.4 Billion Exit 

The innovative cat litter business may have been unsexy, but it was wildly lucrative when it sold to Mars. Now Rotman and his investors are ready to tell the whole scoop.  

During the 2010s, buzzy direct-to-consumer brands were snatching up tens of millions in venture capital, but first-time founder Daniel Rotman raised barely any for his cat litter brand, PrettyLitter. Even as the company’s sales surpassed $100 million, he hired just a dozen full-time employees. In 2021, the scrappy team scaled the company to what would ultimately be a $1.4 billion acquisition by Mars. Five years after exiting, Rotman has left his formal role as an adviser at the multinational manufacturer and is returning to his first career: politics. 

Now, he is sharing the playbook that got him to a nine-figure exit. His first piece of advice? “Go unsexy. Go for those categories that are ripe for disruption that really need someone smart representing the needs of the consumer,” says Rotman. “While everyone’s looking at dog…No one was looking at cat, so the whole time I was eating everybody’s lunch.” Suddenly, he says, all of the incumbents and investors had the same reaction: “Where the hell did these people come from?”...

Inflation: Producer Price Index UP 0.4% In August, UP 5.4% Year-over-Year

From the Bureau of Labor Statistics, September 10: 

The Producer Price Index for final demand moved up 0.4 percent in August, seasonally adjusted, the U.S. Bureau of Labor Statistics reported today. Final demand prices rose 0.1 percent in July and decreased 0.1 percent in June. (See table A.) On an unadjusted basis, the index for final demand increased 5.4 percent for the 12 months ended in August.

In August, the index for final demand goods advanced 1.1 percent, and prices for final demand services increased 0.1 percent.

The index for final demand less foods, energy, and trade services rose 0.3 percent in August after moving up 0.4 percent in July. For the 12 months ended in August, prices for final demand less foods, energy, and trade services advanced 4.7 percent.

Final Demand
Final demand goods: The index for final demand goods advanced 1.1 percent in August following two consecutive decreases. Over three-fourths of the broad-based rise can be attributed to prices for final demand energy, which moved up 4.2 percent. The indexes for final demand goods less foods and energy and for final demand foods increased 0.4 percent and 0.1 percent, respectively.

Product detail: Over a third of the August increase in the index for final demand goods can be traced to prices for diesel fuel, which jumped 24.1 percent. The indexes for gasoline, jet fuel, home heating oil, candy and nuts, and tobacco products also advanced. In contrast, prices for residential electric power fell 0.5 percent. The indexes for fresh sausage and for aluminum mill shapes also decreased. 
(See table 2.)

Final demand services: The index for final demand services edged up 0.1 percent in August, the third consecutive increase. The August advance can be attributed to a 2.3-percent rise in prices for final demand transportation and warehousing services. Conversely, the index for final demand trade services moved down 0.2 percent, while prices for final demand services less trade, transportation, and warehousing were unchanged....

....MUCH MORE including the always interesting Table 2.

"Asia’s ultra-rich are moving their money. Here’s where it’s going"

From CNBC, September 8/9:

• Ultra-high-net-worth people are “always looking at both financial instruments as well as physical assets in real estate and in precious metal,” said Alvin Lee, Maybank Singapore CEO.
• “Singapore will continue to be very strong in appealing to offshore wealth, so with the Middle East conflict, a lot of money that left Singapore for Dubai is returning,” Lee said.
• Many Chinese people are looking to invest or live in Malaysia, Lee said. 

Asia’s ultra-rich are increasingly willing to tap into new asset classes, gold is leaving Dubai for Singapore and wealthy Chinese are flocking to Malaysia, the Singapore CEO of Malayan Bank Bhd said.

Ultra-high-net-worth people are “always looking at both financial instruments as well as physical assets in real estate and in precious metal,” Alvin Lee said in an interview. “Gold’s rise in price is testament to the fact that it’s a good store of value. It continues to be very appealing,” he said.

While gold is off its record highs from early this year, its price of around $4,400 per ounce is still well elevated versus history, with Goldman Sachs forecasting the yellow metal to reach $4,900 by year-end on the back of central bank buying.

As Asia’s richest people buy into precious metals, among the oldest investments in history, they’re also willing to try much newer and more innovative concepts. That’s coming as they “are very focused” on the transfer of wealth from older to younger generations, Lee said.

“Increasingly, we do see the wealthy being very open to new asset classes, whether it’s digital assets or cryptocurrencies,” Lee said, adding that the interest is coming primarily from the younger people. 

Singapore’s appeal
“Singapore will continue to be very strong in appealing to offshore wealth, so with the Middle East conflict, a lot of money that left Singapore for Dubai is returning,” Lee said. Physical gold is being shipped to Singapore from Dubai in historically outsized quantities, he added. 

Singapore tends to benefit “directly or indirectly,” when there is a regional or global crisis, Lee said. “Given our safe haven status, given the fact that we have strong IP, a very stable government, and very attractive tax jurisdiction.”

Rich Chinese eying Malaysia
Lee said that increasingly Chinese people are becoming quite open to investing in Malaysia. In terms of places to move business or even their families, “they are very open to Malaysia because in terms of valuation, it looks very attractive relative to Singapore.”....

....MUCH MORE 

"US says deal aims to stabilize Venezuela power grid in 6-12 months" (GEV)

From Reuters, September 3:

U.S. Energy Secretary Chris Wright said a deal between Venezuela and U.S. energy equipment and services company ​GE Vernova aims to help stabilize Venezuela's beleaguered power ‌grid in six months to a year and boost it in coming years.

 

"The plan is immediately ... in six to 12 months (to) focus on getting ​existing assets on the ground back in working order, back ​in condition, stabilize the grid, expand the hours of ⁠service," Wright told reporters late on Wednesday before flying back ​to Washington.

 

GE Vernova was one of several companies that committed to ​expanding energy projects in Venezuela during a ceremony in Caracas on Wednesday overseen by interim President Delcy Rodriguez and Wright....

  , opens new tabwas one of several companies that committed to ​expanding energy projects in Venezuela during a ceremony in Caracas on Wednesday overseen by interim President Delcy Rodriguez and Wright. 

....MUCH MORE 

The stock is down today, $950.19 last, off $21.12 (−2.17%). It's been a tough month for the big dog, down 5.3% since August 10:

 

TradingView 

On the other hand GEV is up over 700% since it was spun out of GE in March 2024, making the recent ructions easier to bear. 

As King Louis XVI (Mel Brooks) said in History of the World Part 1:

"It's good to be the King"

Liquid Metal: Lars Ulrich Sells Three Bay Area Properties For $84 Million

From the San Francisco Standard, September 4:

Metallica drummer Lars Ulrich sells prime SF, Marin properties for $84 million 
In addition to a $68 million compound in San Francisco, the artist sold a 161-acre plot in Marin County, which will become public open space. 

Metallica drummer Lars Ulrich has been offloading major Bay Area real estate in recent weeks: San Francisco’s biggest combined home sale of 2026 and a Marin County property that is one of the largest private landholdings within 20 miles of the city limits.

The 62-year-old heavy metal star is the owner behind two trusts on adjoining Presidio Heights mansions that were sold on the same day last week for almost $68 million, a source confirmed to The Standard. Though the price is for two separate homes, if treated as one transaction it would be the second-highest sale in city history, after Laurene Powell Jobs’ $71 million purchase on Billionaire’s Row in 2024.

Ulrich purchased the homes from longtime friend and Salesforce CEO Marc Benioff in two separate transactions nearly a decade ago.

The larger of the two, a 16,000-square-foot property at 3277 Pacific Ave., was purchased for $30 million in May 2017 through a trust connected to family office firm WG & S, as first reported by The Real Deal (opens in new tab). 

WG & S’ cofounder and former managing partner Eric Wasserman is a board member of Metallica’s All Within My Hands Foundation and a partner at Black Squirrel Partners, the band’s family office....

....MUCH MORE 

In other celebrity real estate news, BBC, September 9:

Nicolas Cage's driveway collapses as sinkhole opens up at his Malibu home 

"Burnout Nation: Why Neijuan (Involution) Feels Pervasive in China"

Two from International Banker. First up, August 24:

On Chinese social media, the word neijuan—involution—has become shorthand for the grinding sense that everyone is racing harder but getting nowhere. State media officially refers to it as “rat race-style irrational competition”. The symptoms are everywhere: Parents scramble to buy tutoring hours for preschoolers, young professionals log “996” workweeks (9 AM to 9 PM, six days a week) to show commitment, and startups pour money into user-acquisition contests in which winners are decided by who can lose the most. The result, in public conversation and private life, is pervasive exhaustion: more effort, smaller returns.

Neijuan isn’t just a mood; it is the visible product of structural forces that push people and firms into escalating, largely zero-sum competition. Four dynamics in particular combine to make involution unusually widespread in contemporary China: a vast pool of entrepreneurial aspiration, a “copy-and-scale” business culture, state-enabled production and subsidies, and a credential-driven labor market.

Too many founders chasing too few distinct opportunities

China is an entrepreneurial country. Whether driven by necessity, opportunity or cultural prestige, an unusually large absolute number of people want to start businesses or be their own bosses. Entrepreneurship rates in China—particularly early-stage activity among young people—are elevated compared with many advanced economies. Data from the Global Entrepreneurship Monitor shows that up to 2019, entrepreneurial intention—defined as the percentage of the 18-64 population who are latent entrepreneurs and intend to start a business within three years—was in the double digits (see Figure 1). Multiply even modestly higher entrepreneurial intention by a population of roughly 1.4 billion, and the result is an enormous number of would-be founders. By the early 2020s, cumulative registrations of market entities in China exceeded 100 million, with millions of new firms registering every year.

 

This high level of aspiration is reflected in data from the World Values Survey (WVS), which reveals a distinct Wealth Value Gap (Figure 2). While populations in the United Kingdom and France largely reject “being rich” as a core personal value, the Chinese show a much broader acceptance of wealth as a primary goal. This is paired with a significantly more positive outlook on market rivalry. Echoing President Xi Jinping’s repeated assertions that “China is not afraid of competition”, the data also shows that the Chinese lean heavily toward viewing competition as a beneficial force, whereas their Western and Japanese cohorts remain far more skeptical....

....Copy, iterate, scale: when imitation becomes a race to the bottom...

....MUCH MORE    

And August 10:

China’s Banking Problem of Unwanted Credit 

At the end of June, rediscount rates on Chinese commercial bills—short-term payment instruments that banks can buy as credit assets—fell to 0.01 percent as lenders rushed to meet quarter-end targets. Regulators subsequently imposed a 0.5-percent floor and, on July 22, extended it to both bid and ask quotes from all market participants. The episode showed how aggressively banks were competing for assets while demand for ordinary loans remained weak. 

That imbalance is concentrated rather than economy-wide. Strategic industries, state-linked borrowers and some exporters continue to absorb substantial credit, while households and many domestically exposed private firms remain cautious. Pressuring banks to increase lending volumes can therefore weaken underwriting standards and create future bad loans without producing much additional consumption or private investment.

Chinese banks extended 1.61 trillion yuan in new loans in June, up from 520 billion yuan in May but below the 1.95-trillion yuan expected by economists surveyed by the Wall Street Journal. June normally produces a firm quarter-end increase as banks strive to meet lending targets, making the shortfall particularly revealing.

Such weakness reflects the wider slowdown in China’s economy. Gross domestic product (GDP) grew by 4.3 percent year-on-year in the second quarter, down from 5 percent in the previous quarter and the slowest pace since late 2022. Industrial production expanded by 5.3 percent in June, supported by exports and high-technology manufacturing, while retail sales rose by only 1 percent. Fixed-asset investment excluding rural households fell by 5.7 percent during the first half, including an 18-percent decline in real-estate development investment. Private fixed-asset investment fell by 8.5 percent, or 4.9 percent after excluding real estate.

This divergence helps explain uneven credit demand. Exporters and technology firms benefit from external demand, industrial policy and several financing channels. Households and companies dependent on the domestic economy face a far weaker environment. Dan Wang, China director at Eurasia Group, described export performance as “quite stellar”, but added that it “doesn’t really trickle down to any of the domestic demand”. Much of that strength comes from capital-intensive, highly automated manufacturing, limiting the benefits to household incomes and employment....

....MUCH MORE 

There was a time when China's credit impulse was the most important number on the monthly data calendar. Now, not so much:

 

Via Dark Side of the Boom, September 8

Still going down. 

If interested here is an older (2024) Bloomberg article: 

China’s Once-Mighty Credit Cycle Is a Fading Force on World Markets 

"Americans Without College Degrees Are Having One of the Best Job Markets in Years"

From the Wall Street Journal, September 6:

Unemployment among younger workers who didn’t go to college has rarely been lower in recent decades. It is the opposite story for college grads

For most U.S. workers—those without college degrees, that is—it is one of the best job markets in decades.

In fact, the unemployment rate for workers ages 22 to 34 who never graduated from college has rarely been lower in the past two decades, according to a new analysis by labor-market think tank Burning Glass Institute. 

***

What is just as remarkable is how different that is from the experience of job seekers who did graduate from college, says Gad Levanon, Burning Glass’s chief economist. For most of the past two decades, the two groups largely tracked each other, in good economic times and bad.

Now, though, just as job hunters without degrees are having one of their best runs, those with college educations are having one of their worst. And those with advanced degrees or in fields such as science and technology are having an even harder time than usual.

That divergence of fortunes is a departure from what the U.S. economy has seen for years, and much of it boils down to supply and demand: There aren’t enough skilled tradespeople to go around, for example, as older generations retire and immigration drops.

Meanwhile, more Americans have college degrees than ever, just as artificial intelligence is doing more of the entry-level work companies typically hire young graduates for.

“There’s a rapidly growing supply of people with a bachelor’s degree, and you have a rapid decline of people who don’t,” Levanon says. “I don’t think it’s a temporary thing.”

 ***

A wrinkle: On an absolute scale, it is still easier to find a job with a college degree. The unemployment rate for degree-holders in their prime working years—ages 25 to 54—averaged 2.7% for the 12 months ending in July. That is well below the 3.6% rate for workers with just some college education, and 4.7% for people with a high-school diploma only.

So, to gauge how the job market has shifted for each cohort, Levanon compared current unemployment rates for the different groups with their own range of unemployment rates since 2003. The analysis included data through July.

By that measure, the job market looks much better, historically speaking, for blue-collar workers, including those in construction and on manufacturing lines, and manual-service workers—think security guards, nurses and many restaurant and retail employees.

***

The more physical and in-person the work is, the lower the unemployment tends to be by that occupation’s own historical standards. Friday’s booming jobs report reinforced the trend: Food services and drinking places added 59,000 jobs in August, more than a third of all 162,000 jobs added to the U.S. economy last month.

By contrast, college-educated workers ages 22 to 34 years old have only seen worse unemployment in the past two decades during the pandemic and the economy’s slow rebound from the 2007-09 recession....

....MUCH MORE 

Arctic Sea Ice Volume Is Finally Running Ahead Of The Prior Two Years

It has been a rough few years for the Arctic Ice.

May 2024 - Arctic: Well, The Ice Has Begun Retreating Fom Its Winter Maximum....

....And it was not a good year.

As long-time readers know we focus on sea ice thickness and volume rather than extent. This is because of the way ice melts. Just as the ice in your glass will last longer in block form than as thin shavings, the Arctic ice better resists melting the thicker it is.

We might have a winter where the polar vortex stays nice and tight around the Arctic Circle, keeping the colder  air over one (large) spot and have less, sometimes far less ice extent than in winters where the circumpolar winds break down allowing the cold air to head south, forming a thin skin of ice over a greater area.

The problem is, that thin skin begins to melt as soon as the sun returns to the Northland. The thicker ice melts slower and has a better chance of becoming second-year or multi-year ice which is the stuff that has the best chance of resisting the warm air of summer....

March 2025 - Arctic Sea Ice Sets Lowest Winter Maximum Extent In The 47-Year Satellite Record

October 2025 - Good News/Bad News On The Arctic Ice Cap

First, the bad news. The ice is in terrible shape.

As always, our interest, because of the way ice melts, is in thickness rather than extent....

October 2025 - "Chinese Freighter Halves EU Delivery Time on Maiden Arctic Voyage to UK"

Because of the way ice freezes (and melts) we would expect the graph to show faster growth in extent than in the last few years. Unfortunately that is because more water is exposed and come next spring it won't be very thick compared to the multi-year ice you really want to see.  

May 2026 - "NASA and JAXA data show another record-low Arctic winter sea-ice season" 

*** 

And from the Danish Meteorological Institute, retrieved Wednesday AM Copenhagen time:

 

The volume of ice up north passed that of the 2025 and 2024 seasons in July 2026. We were not sure if the trend would continue but now that the ice is approaching the seasonal low point it looks as though the bottom is in.

Capital Markets: "Oil Higher, Yen Consolidates, US to Reveal Bond Buyback Plans"

From Marc Chandler at Bannockburn Global Forex:

There are two main developments today. The first is the escalation of the Middle East war has lifted oil prices. October WTI rose 9.7% last week, and with today’s gains, is a little more than 4% this week. This has helped lift bond yields.  The second is the short squeeze of the Japanese yen. Since the middle of last week, the yen has surged about 4.7%.  Although US Treasury Secretary Bessent appears to take credit for it, recall that initially after the intervention drove the dollar to JPY155, it had recovered to almost JPY160.40 last Wednesday.  Many observers are concerned that the short yen positions funded the purchase of higher yielding or more volatile assets.  However, it appears that some have shifted from yen funding to dollar funding, and we note that the Swiss franc may also replace the yen on the margins.  The franc is near the year’s low against the euro. 

Separately, the US trade conflict with Canada continues.  The US has moved to block imports of some goods and has threatened to impose more tariffs on others.  President Trump has threatened to bar Canadian companies from selling to US contractors. The import banks on some dairy products and alcohol will take effect in three weeks, while new tariffs will be in place in a week and these new tariffs will be stacked on top of the industry-specific levies that have already been implemented. Canada and the EU are expected to soon announce a comprehensive agreement. Canada appears prepared to do everything but join the EU itself. Next week Canada’s PM Carney will meet with EC President von de Leyen....

....MUCH MORE   

Meanwhile, In Shanghai: Investors Demand Brain - Computer Interface Companies

From the South China Morning Post, September 8:

Eager capital prompts IPO plans for more Chinese makers of brain-computer interfaces
Arfysica and Neuracle aim for Star Market listings amid what a Morgan Stanley analyst calls the ‘early stage of a multi-year IPO upcycle’ 

A handful of home-grown Chinese companies involved in brain computer interfaces (BCIs) are moving towards initial public offerings (IPOs) on onshore markets, taking advantage of the sector’s status as a new darling of private capital.

The trend fits into a broad pattern of hi-tech firms flocking to list on the Shanghai Stock Exchange’s Nasdaq-style Star Market.

Among the BCI hopefuls, Shanghai-based Arfysica Innovation is the latest to register for IPO coaching for a Star Market listing, according to a filing with the China Securities Regulatory Commission (CSRC). The company, which develops products for central nervous system injuries and disorders of cognition, hired Huatai United Securities as its sponsor.

BCIs aim to allow brain signals to control external devices, such as computers or robotic limbs. Elon Musk’s Neuralink is a prominent company developing the technology.

Founded in 2015 with registered capital of 100 million yuan (US$15 million), Arfysica is controlled by founder Wang Wei, who holds a combined 51 per cent stake and serves as the company’s legal representative, according to the CSRC website. Wang earned a bachelor’s degree from Tianjin University before completing a PhD in biomedical engineering at the University of Southampton in the UK in 2006, and later worked at Siemens Healthcare, according to her LinkedIn profile.

The company raised an undisclosed amount of capital in its latest financing round in February. Its earlier round in January raised 160 million yuan from investors including the state-owned National SME Development Fund, according to company database Crunchbase.

Another IPO candidate, Shanghai-based Neuracle Medical Technology, signed an IPO coaching agreement with Citic Securities on February 4, according to a filing with the CSRC. The company won China’s first-ever regulatory approval for an implantable BCI system designed to help patients with spinal cord injuries regain hand movement.

It has raised 72 million yuan across five rounds of investment, counting HSG, Tsinghua Holdings Capital and Baidu Ventures among its investors, according to Crunchbase. Its legal representative, Xu Honglai, graduated from Tsinghua University in biomedical engineering, according to the university’s website.

At least two other Chinese BCI companies are pursuing onshore IPOs, according to local media reports....

....MUCH MORE 

If interested see May 2024's "China's brain-computer interface technology is catching up to the US. But it envisions a very different use case: cognitive enhancement.".

August 2016 - Oh Great, Now Our Brains Can Get Hacked
I knew this was going to happen. Knew it. Afraid to say it, sound like crazy person, but knew it. Links below. 

Also quite a few posts on Elon Musk and Neuralink and on Dr. Miguel Nicolelis.

Google's TPU Chips Will Deliver Up To 50% Better Perfomance Per Dollar On Some Inference Chores Vs. Nvidia (GOOG; NVDA)

Took ya long enough.*

From SemiAnalysis, September 7:

• TPU Inference Externalization Full Steam Ahead - InferenceX
• InferenceX, Up to 50% Better Performance per Dollar, Rapid Externalization of TPU stack, Growing Customer Base, Ironwood, TPUv8i, Reducing CUDA Moat 

For more than a decade, the industry has watched Google build an empire on its own silicon. Search, Ads, YouTube, and every generation of Gemini run on TPUs. Few accelerators have attracted as much architectural scrutiny or as much debate about what their performance and economics would look like outside the company that designed them. Anthropic being the biggest user of TPUs, surpassing Deepmind’s own use by 2029.

Google’s internal success was never the question. The question was how much of that advantage the rest of the industry could actually get. Could you take an open-weight model, serve it through a familiar inference engine, and beat NVIDIA on the economics that matter to your business?

Today, we are publishing the first third-party inference results for TPUv7 Ironwood on InferenceX Official Preview. In our apples-to-apples comparisons against B200/B300, Ironwood delivers up to 50% better performance per dollar. Its advantage extends across much of the Pareto curve, and we examine the economics from both sides: Google’s internal total cost of ownership and the external TCO an actual customer pays.

Ironwood (TPUv7) is the first generation in which Google is competing for others’ inference workloads with chips that can be purchased outright or rented through its own cloud. In November 2025, we already said that Anthropic loves TPUs and committed to over one million of them (around 400k+ in direct purchases and 600k+ rented through GCP), used mainly for training but also for inference. Our Accelerator Model has the latest figures for Anthropic’s TPU shipments and Google’s overall TPU shipments by quarter, plus estimates for TPUv8i, v8t, and various v9 / v10, and more

We are excited by how quickly the new TorchTPU stack is developing, the external stack for TPUs. Later in the article, we will discuss the upcoming work needed for TPU software externalization, including optimizing speculative decoding, disaggregated prefill, KV-cache offloading, multi-turn agentic workloads, and more. Even so, we at SemiAnalysis strongly believe that TPU externalization is heading in the right direction and moving full steam ahead. Furthermore, unlike AMD, which is still learning how to build a test-first software culture, Google has decades of software engineering experience and an extremely well established quality-driven culture, so we expect external TPU software to mature rapidly.

In this article, we will cover all the optimizations that went into TPU kernels and the serving stack for open-weight models, including DP attention optimization, MoE routing and kernel optimization, and reducing padding in GDN kernels. We will also take a deep dive into the TPU system and discuss the next steps the amazing TPU performance engineers are pursuing to make the stack widely available.

Google has spent more than a decade demonstrating what it can build with TPUs. Now we get to measure what the rest of the industry can do with them.

Shoutout to the Google (Chris Chan, Jahangir Hasan, Wangyuan Zhang, Anne Stern, Puneith Kaul, Ruizi Dong, Sangam Jindal, Qi Zhou, Madhan Jaganathan, Gang Ji, Jun Wan, Devanshu Jain, Jiaxin Cao, Srinath Mandalapu, Haowen Ning) and Inferact teams and RedHat Teams (Michael Goin) for this amazing TPU foundation and performance! Furthermore, shoutout to the RadixArk team that is also working on TorchTPU SGLang.

InferenceX Official Preview: TPUv7 Ironwood vs. Blackwell and Blackwell Ultra 

We are already seeing strong results from the upcoming native TorchTPU vLLM stack in apples-to-apples comparisons against Nvidia GPUs. Google is using Qwen3.5 397B in FP8 as the initial bring-up model. Later sections take a deep dive into why the new TorchTPU approach is a marked improvement over the previous TorchAX path for external TPU vLLM/SGLang serving.

Once that foundation is in place, Google plans to extend support to other open-weight models, including Kimi K3 and GLM5.3. Once a handful of models are well optimized, we believe adding optimized support for a wide range of popular open models near day 0 becomes far easier. Today, vLLM and SGLang concentrate their day-0 support on Nvidia, with passable day-0 coverage for AMD. We expect TorchTPU to be stable enough in the near future that vLLM and SGLang maintainers may add TPUs to that day-0 list. The stack is expected to leave private beta & be open sourced around October. 

In apples-to-apples comparisons of aggregated serving with FP8 and single-token prediction, we are seeing up to 50% better performance per dollar from TPU than from B200 and B300 running FP8 in aggregated serving. When serving models using FP4 on NVIDIA GPUs, there is quality loss verus FP8. TPUv7 does not have native FP4 computation thus on FP4, NVIDIA GPUs still maintains the lead. This will change with TPUv8i which has native FP4 support thus we strongly believe TPUv8i Boardfly will be competitive to Rubin NVL72.... 

....MUCH MORE
*April 2017 - Watch Out NVIDIA: "Google Details Tensor Chip Powers" (GOOG; NVDA)
We've said NVIDIA probably has a couple year head start but this bears watching, so to speak....

And many, many more, including November 2025 "CHIPS: Google's Tensor Processing Unit (Finally) A Viable Competitor For Nvidia (GOOG; NVDA)" 

"Samsung Leads 4.7 Trillion Won Investment in French AI Firm Mistral… to Develop AI Specialized for Semiconductors"

This was the most in-depth article on the chip venture that we saw. We'll go to Bloomberg for the large-by-large financing.

From Korea's Edaily, September 9:

• Strategic Partnership Signed Suddenly to Coincide with South Korea-France Summit
• DS Data and Mistral Raji Join Forces… to Build Enhanced Security
• "Setting a New Standard for Semiconductor Innovation… Contributing to the Global Value System"

Samsung Electronics Chairman Jay Y. Lee and Arthur Ménch, CEO of Mistral AI, pose for 

a commemorative photo on the 8th (local time) at the Élysée Palace in Paris, France, after 

exchanging an investment agreement in the presence of President Lee Jae-myung and French 

President Emmanuel Macron. From left: Samsung Electronics Executive Vice President Lee 

Jong-myung, Samsung Electronics Chairman Jay Y. Lee, President Lee, President Macron, 

and Arthur Ménch, CEO of Mistral AI. (Photo: Yonhap News)

[Edaily Reporter Han Kwangbeom ] SamsungElectronics(005930)Samsung Electronics has led a 3 billion euro (approximately 4.7 trillion won) Series D funding round for the French artificial intelligence (AI) company Mistral AI and signed a long-term technology partnership. Through this, the company has significantly expanded its influence in the global AI ecosystem.

SamsungElectronics announced on the 9th that it has entered into a strategic partnership with Mistral AI and agreed to jointly develop “semiconductor-specific AI” that combines the technology and manufacturing data from its DS (Semiconductor) Division with Mistral AI’s high-efficiency AI model technology to enhance productivity and precision across the entire semiconductor operations. SamsungElectronics plans to use this partnership as an opportunity to accelerate the AI transformation across all business divisions, including semiconductors, and strengthen its competitiveness in the global AI semiconductor market.

The signing of this partnership was timed to coincide with the South Korea-France summit. Previously, Mistral AI had officially announced a 3 billion euro investment round led by SamsungElectronics, with EQT’s Scale-Up Europe Fund and PSG Equity serving as co-leads. New investors in this round included BlackRock, Advent, and the Grand Duchy of Luxembourg, while major existing shareholders—such as NVIDIA, ASML, Andreessen Horowitz (a16z), and Salesforce Ventures—also participated in significant reinvestments.

SamsungElectronics’ investment marks the largest equity investment in the history of European tech companies, and Mistral AI has achieved a valuation of over 21 billion euros (approximately 33 trillion won) just three years after its founding. Mistral AI stated, “This investment is a significant milestone achieved under SamsungElectronics’ leadership,” adding, “The funds raised will be used to strengthen our infrastructure and product capabilities and accelerate large-scale deployment; above all, they will serve as a driving force to continue and expand our frontier research and AI model development.”

◇Mistral: Europe’s Leader in “Sovereign AI”… Unparalleled Influence in Technological Sovereignty and the Ecosystem

Mistral AI, a leading player in the European AI ecosystem, was founded by AI researchers from Google DeepMind and Meta, led by CEO Arthur Mensch. Mistral AI possesses unparalleled technical capabilities to build customized AI models in on-premises environments for industries requiring a high level of data security, such as finance, manufacturing, and energy....

....MUCH MORE 

And from Bloomberg, September 7: 

Mistral AI Boosts Valuation to €21 Billion in Samsung-Led Round 

Mistral AI has raised €3 billion ($3.5 billion) at a valuation of more than €21 billion from investors led by Samsung Electronics Co. to fund the development of artificial intelligence models and build computing infrastructure.

The EU’s Scaleup Europe Fund and PSG Equity co-led the round, the company said in a statement on Tuesday. The Paris-based startup has nearly doubled its €11.7 billion valuation from its last fundraising round a year ago.

The funding will give Mistral the ammunition to advance in industrial AI, which involves rolling out the tech for manufacturing processes and is emerging as one of the company’s key differentiators, Chief Executive Officer Arthur Mensch said in an interview. While Mistral is a fraction of the size of generative AI behemoths such as OpenAI and Anthropic PBC, the company has been selling itself as a sovereign alternative for Europe. It’s struck deals with large European industrial companies including Airbus SE, BMW AG and Dutch chip-machine maker ASML Holding NV, which led Mistral’s previous round.

“This fundraising is also a way for us to further expand in the US, in Asia and of course to double down on what we’ve been doing in Europe,” Mensch said. “This is a technology that requires significant infrastructure.”

That involves owning “significant assets” such as data centers, he added. Earlier this year, Mistral raised $830 million in debt for a data center project outside Paris that would use Nvidia Corp. chips. The company committed a further €1.2 billion to a data center buildout in Sweden, its first data center investment outside France.

Similar to the ASML partnership, the agreement with Samsung “opens the door for further collaboration,” Mensch said. ASML, which participated in this most recent funding round, invested €1.3 billion for an 11% stake last year. ASML CEO Christophe Fouquet said at the time he planned to “flood the entire organization” with AI.

Mistral was founded in 2023 by Mensch, an alumnus of Google’s DeepMind, and ex-Meta Platforms Inc. researchers Timothée Lacroix and Guillaume Lample. It develops open-source large language models, in contrast to the “closed” models developed by its larger American counterparts. Mensch has touted open source as more cost efficient and easier to integrate into large, complex corporate systems.

Mensch is counting on gaining traction with European governments, fearful of relying too heavily on artificial intelligence products owned by American and Chinese companies. US President Donald Trump’s administration compounded these fears this summer, when it ordered Anthropic to disable access to its most advanced AI models for all foreign nationals, citing national security concerns....

....MUCH MORE

Most recently on Mistral: 

July 21 - "Microsoft Deepens Ties With Mistral, Targeting Europe and Enterprise AI"
When your company (Mistral) is not just the national standard-bearer but the flagship for the whole continent it's amazing how many companies come knocking on your door.... 

***

....It's also another sign of how MSFT is distancing itself from OpenAI. Another couple years and Mr. Nadella will be saying "Sam who?" 

If interested, quite a few of our Mistral links are in July 17's "Airbus migrating 70 critical apps from AWS to France's Scaleway amid digital sovereignty push".

And a couple I forgot to include:

"Why Paris may be the most important AI city outside Silicon Valley"
Though this is an infomercial for one of TechCrunch's products it also happens to be true, though Shenzhen could probably make a claim to that moniker as well....

FrenchTech: "Mistral launches Industrial Engineering AI with Airbus, BMW and EDF as headline customers" (plus rebutting the Pope)

And a couple more from the hazy depths of time gone by (2024):

FrenchTech: "Mistral AI, Europe’s OpenAI rival, adds top LLM to Amazon Bedrock"

FrenchTech: Mistral AI Is Cutting Deals Right and Left
Some adroit, some gauche....

I am so sorry. 

July 22 - "Samsung is in talks to take an equity stake in Mistral AI as the French startup seeks €3 billion at a €20 billion valuation"

And many, many more, going back to:

June 2023 - French Tech: "Mistral AI secures €105M in Europe’s largest-ever seed round"

Although we've been pitching French startups as a potential engine of growth to supplant German dominance, and although we've made Artificial Intelligence one of the foci of the blog since 2013 - "Why Is Machine Learning (CS 229) The Most Popular Course At Stanford" - and although we began juxtaposing the two strands five years ago, I'm still impressed with this sort of money going into a company that was formed in the last five weeks....

Navier-Stokes Equations Solutions: OpenAI Denies All Allegations

Following on the post immediately below, "Turbulence: OpenAI Says It Has A Solution For The Navier–Stokes Millennium Prize Problem". 

From Scientific American, September 8:

Prior to the announcement, rumors were circulating online among mathematicians over the proof’s origins—OpenAI has denied all allegations 

For the second time ever, someone has solved one of the seven Millennium Prize Problems—math’s biggest targets, each worth a $1-million prize. But unlike the first time, that someone is an artificial intelligence start-up.

Today OpenAI announced that its internal model has proved that the Navier-Stokes equations, which mathematicians use to study how fluids move, are fatally flawed. The reveal comes after mathematician Tristan Buckmaster alleged that OpenAI had tackled the proof after the company became aware that Buckmaster and his colleague Levent Alpöge had been using a specific method to break a related problem. OpenAI has denied the allegations.

OpenAI’s proof shows that, on rare occasion, the Navier-Stokes equations “blow up,” meaning they dictate that a fluid’s speed becomes infinite at some points, something that is impossible in nature. The company says the proof has been certified using the programming language Lean, which all but guarantees its correctness.

“We’re a little bit in shock,” says Diego Córdoba. He and Luis Martínez-Zoroa originally developed the approach the AI used to solve the problem, which is called “forcing.” “If it’s done, that will be a big surprise for us,” Córdoba says.

The night before OpenAI announced the proof, Buckmaster posted on social media that he and Alpöge, who is a mathematician and an employee of Anthropic, had blown up the Euler equations, widely seen by the field as a step toward solving the Navier-Stokes problem. In a statement released on Monday, Buckmaster alleged that OpenAI had found out about the pair’s progress in the last week and had adopted the same method as Buckmaster and Alpöge had been using to solve the full problem.

In a press briefing on Tuesday, OpenAI mathematician Sébastien Bubeck denied the rumors about the proof’s origins. Bubeck said OpenAI’s internal model had independently solved the Euler problem by totally different means than those employed by Buckmaster and Alpöge. OpenAI’s solution to the full Navier-Stokes problem, however, did follow a similar method as that used by the two mathematicians. And the proof was developed over the weekend, according to Bubeck—that is, after the time that Buckmaster claims the news of his and Alpöge’s result had reached OpenAI. Bubeck emphatically denied that the two mathematicians’ work had influenced OpenAI. “We did not use their prompt or proofs to prompt our models,” he said....

....MORE 

 And at Reddit's r/codex, September 8:

Blown up: OpenAI allegedly stole mathematicians' private research from their Codex chats!

TLDR: Two mathematicians spent a year cracking one of the hardest problems in math and fed every draft of their works into Codex and Claude. Days before they could publish, OpenAI suddenly showed up with the same solutions. When asked if their model (Sol and Astra) was trained on the pair's private chats, OpenAI did not answer the question till this day.

For a full year, two mathematicians , Tristan Buckmaster (NYU mathematician) and Levent Alpoge, worked in silence on a problem that had stumped some of the best minds alive. The kind of problem where, if you solve it, your name goes in the history books.

And every single day, they testing their ideas, their drafts, their half-finished proofs into LLM such as Codex and Claude, which they paid for it out of their own pocket.

Then came the breakthrough. They finally cracked it. They were days away from telling the world.

That's when OpenAI suddenly said to them:

"Our model solved it too."....

....MUCH MORE