Musko naujasis dirbtinio intelekto (AI) startuolis kelia klausimų apie „Teslos“ planus

„Save paskelbęs „Technokaralius“ mato dirbtinio intelekto ateitį ir turi atskiras įmones, kurios siekia šios vizijos.

 

     Bet kas laimi, kai jo įmonių technologijos vis labiau persidengia?

 

     Praėjusią savaitę Elonas Muskas ir jo karalystės čiuptuvai buvo rodomi daugiausiai dėmesio, todėl kilo klausimų, ar Tesla investuotojams padeda ar trukdo naujausias milijardieriaus startuolis xAI. Ši įmonė naudojasi entuziazmo antplūdžiu, kurdama į žmogų panašią dirbtinio intelekto technologiją.

 

     Tuo tarpu daugelis investuotojų jau seniai džiaugiasi Tesla darbu ir planais diegti dirbtinį intelektą su automobiliais be vairuotojo ir humanoidiniais robotais.

 

     Šie investuotojai teigia, kad „Tesla“ nėra automobilių įmonė. Tai technologijų jėgainė, galinti iš tikrųjų pritaikyti šį neaiškią dalyką, vadinamą AI, realiame pasaulyje – atliekant sunkias, prasmingas užduotis. Dėl to Muskas netgi pasiūlė, kad „Tesla“ kada nors būtų verta būti vertingiausia kompanija pasaulyje, daugiau, nei „Apple“ ir „Aramco“ kartu paėmus.

 

     „Investuotojams, manantiems, kad „Tesla“ dirbtinio intelekto funkcijos ir produktai gali būti labai vertingi, gali būti susirūpinę, kai imamasi kitų pastangų, kuriose pagrindinis dėmesys skiriamas AI“, – „Truist“ analitikas Williamas Steinas. Securities, sakė Muskas trečiadienį per automobilių gamintojo konferencinį pokalbį.

 

     Muskas teigė, kad bendrovės yra viena kitą papildančios. "Manau, kad tai iš tikrųjų padidins Teslos vertę", - sakė jis.

 

     Daugelį metų jo įmonės galėjo padėti viena kitai, tačiau jų eismo juostos buvo gana aiškios: Tesla, vienintelė viešai prekiaujama, buvo skirta automobiliams; SpaceX, skirta Marsui. Boring Co buvo skirta tuneliams; Neuralink, smegenų kompiuteriams. Starlink, SpaceX produktas, buvo skirta planetiniam internetui; ir „Twitter“ - tarpasmeniniam bendravimui.

 

     Iš pirmo žvilgsnio skirtumas tarp Tesla ir xAI iki šiol priklauso nuo problemų, kurias jos nori išspręsti, sudėtingumo. Bandydama įdiegti visiškai be vairuotojų automobilius, „Tesla“ dirbo su dirbtiniu intelektu, tradiciškai taikomu siaurai konkrečiai užduočiai: vairavimui.

 

     Anksčiau šį mėnesį oficialiai išleisdamas xAI, Muskas nurodė, kad jo startuolis siekia ištirti daug didesnių problemų – idėjų, kurios glumina žmoniją ištisas kartas, pavyzdžiui, galbūt, gravitacijos prigimtis.

 

     Norėdami tai padaryti, jis nori sukurti pažangų AI, vadinamą dirbtiniu bendruoju intelektu, tikėdamasis pasiekti tai, kas skamba, kaip antžmogiškas intelektas.

 

     Arba, kaip sakė Muskas, bendrovės misija yra sukurti pažangų AI, galintį atsakyti: "Kas iš tikrųjų čia vyksta?"

 

     Tai gali lemti smulkmenos, tokios, kaip xAI verslo planas. Muskas pagailėjo šių ypatybių, o tik sakė, kad xAI konkuruos su OpenAI ir „Google“ Bard. „OpenAI“ generatyvaus AI pokalbių roboto, žinomo kaip „ChatGPT“, sėkmė Silicio slėnyje atnaujino jaudulį, kad pažangesnis AGI įmanomas po daugelio metų teorijų kūrimo.

 

     Vis dėlto Muskas nubrėžė, kad „Tesla“ vaidina svarbų vaidmenį AGI ateityje, ypač dėl to, kad ji kuria humanoidinį robotą, vadinamą Optimus, kuris yra jos darbo prie be vairuotojo automobilio atšaka.

 

     „Manau, kad „Tesla“ vaidins svarbų vaidmenį AI ir AGI, ir manau, kad turiu tai prižiūrėti, kad įsitikinčiau, ar viskas gerai“, – gegužę „Tesla“ akcininkams sakė Muskas. „Paprastai žmonės neįvertina – arba labai mažai žmonių, net iš AI bendruomenės – neįvertina, kiek daug galimybių turi Tesla dirbtinio intelekto srityje. Tai iki šiol pažangiausias realaus pasaulio AI. Nėra nė vieno žmogaus, kuris būtų net arti to."

 

     2021 m. įmonė surengė AI dieną, kurios metu buvo išsamiai aprašyta, kaip sukurti Optimus ir dirbtiniam intelektui skirtą skaičiavimo galią, įskaitant superkompiuterį, pavadintą Dojo, padedantį plėtoti be vairuotojo automobilio technologiją.

 

     Trečiadienį Muskas atskleidė, kad „Tesla“ iki kitų metų pabaigos planuoja išleisti daugiau nei 1 mlrd. dolerių Dojo kūrimui.

 

     „Dojo“ buvo sukurtas, siekiant apdoroti didelius vaizdo įrašų kiekius, naudojamus, kuriant be vairuotojo automobilio sistemą, o dabartinė versija nėra skirta didelių kalbų modeliams, naudojamiems, kuriant į „OpenAI“ panašius pokalbių robotus. Anksčiau šį mėnesį Muskas sakė, kad naujos kartos Dojo dirbs su taip vadinamaisiais dideliais kalbos modeliais." [1]

1. Musk's New AI Startup Raises Questions About Tesla Plans. Higgins, Tim. 
Wall Street Journal, Eastern edition; New York, N.Y. [New York, N.Y]. 24 July 2023: B.4.

Musk's New AI Startup Raises Questions About Tesla Plans.

"The self-proclaimed Technoking sees an AI future and has separate companies pursuing that vision.

But who wins as the technologies of his companies increasingly overlap?

Elon Musk and his kingdom's tentacles were on prime display this past week, raising questions about whether Tesla investors are helped or hindered by the billionaire's latest startup, xAI. The venture is taking advantage of the rush of enthusiasm to develop a humanlike artificial-intelligence technology.

Meanwhile, many investors have long been excited about Tesla's work and plans for deploying AI with driverless cars and humanoid robots.

Tesla isn't a car company, these investors argue. It is a tech powerhouse that can truly deploy this fuzzy thing called AI into the real world -- doing hard, meaningful tasks. Because of that, Musk has even suggested, Tesla is worthy of someday being the world's most valuable company, more than Apple and Aramco combined.

"For investors that think that there might be quite a bit of value in the AI features and products of Tesla, it might be concerning to see you pursuing another endeavor where AI is the focus," William Stein, an analyst focused on AI from Truist Securities, told Musk Wednesday during the automaker's conference call.

Musk said the companies are complementary. "I think it will actually enhance the value of Tesla," he said.

For years, his array of companies might have helped each other out, but their lanes were pretty clear: Tesla, the only one publicly traded, was for cars; SpaceX, for Mars. Boring Co. was for tunnels; Neuralink, for brain computers. Starlink, a product at SpaceX, was for planetary internet; and Twitter, for interpersonal communications.

On the surface, the difference between Tesla and xAI so far comes down to the complexity of the problems they want to address. In trying to deploy fully driverless cars, Tesla has been working on a kind of AI traditionally applied narrowly to a specific task: driving.

In officially rolling out xAI earlier this month, Musk cast his startup as seeking to explore much bigger issues -- the sorts of ideas that have puzzled humanity for generations, like, perhaps, the nature of gravity.

To do that, he wants to develop an advanced AI -- known as artificial general intelligence -- with the hope of achieving what sounds like superhuman intelligence.

Or, as Musk put it, the company's mission statement is about creating an advanced AI that can answer: "What the hell is really going on?"

The rub might come down to details, such as xAI's business plan. Musk was light on those specifics, beyond saying xAI would compete with OpenAI and Google's Bard. The success of OpenAI's generative AI chatbot known as ChatGPT renewed excitement in Silicon Valley that the more advanced AGI is possible after years of theorizing.

Still, Musk has painted Tesla as playing an important role in the AGI future, especially as it works to develop a humanoid robot called Optimus, an offshoot of its driverless-car work.

"I think Tesla's gonna play an important role in AI and AGI, and I think I need to oversee that to make sure it's good," Musk told Tesla shareholders in May. "Generally, people do not -- or very few people, even in the AI community -- do not appreciate just how much capability Tesla has in AI. It's by far the most advanced real-world AI. There's no one even close."

In 2021, the company held an AI Day, which included details of work to develop Optimus and computing power designed for AI, including a supercomputer dubbed Dojo to help development of its driverless-car technology.

On Wednesday, Musk revealed that Tesla is planning to spend more than $1 billion through the end of next year on Dojo, which he said gives the company advantages over rivals looking to train their driver systems with expensive computing power that is in great demand.

Dojo was developed to deal with large amounts of video used in making a driverless-car system, and the current version isn't meant to handle large language models used to create OpenAI-like chatbots. Earlier this month, Musk said the next generation of Dojo will work with such so-called LLMs." [1]

1. Musk's New AI Startup Raises Questions About Tesla Plans. Higgins, Tim. 
Wall Street Journal, Eastern edition; New York, N.Y. [New York, N.Y]. 24 July 2023: B.4.

The Research Scandal at Stanford Is More Common Than You Think

"There are many rabbit holes on the internet not worth going down. But a comment on an online science forum called PubPeer convinced me something might be at the bottom of this one. “This highly cited Science paper is riddled with problematic blot images,” it said. That anonymous 2015 observation helped spark a chain of events that led Stanford’s president, Marc Tessier-Lavigne, to announce his resignation this month.

Dr. Tessier-Lavigne made the announcement after a university investigation found that as a neuroscientist and biotechnology executive, he had fostered an environment that led to “unusual frequency of manipulation of research data and/or substandard scientific practices” across labs at multiple institutions. Stanford opened the investigation in response to reporting I published last autumn in The Stanford Daily, taking a closer look at scientific papers he published from 1999 to 2012.

The review focused on five major papers for which he was listed as a principal author, finding evidence of manipulation of research data in four of them and a lack of scientific rigor in the fifth, a famous study that he said would “turn our current understanding of Alzheimer’s on its head.” The investigation’s conclusions did not line up with my reporting on some key points, which may, in part, reflect the fact that several people with knowledge of the case would not participate in the university’s investigation because it declined to guarantee them anonymity. It did confirm issues in every one of the papers I reported on. (My team of editors, advisers and lawyers at The Stanford Daily stand by our work.)

In retrospect, much of the data manipulation is obvious. Although the report concluded that Dr. Tessier-Lavigne was unaware at the time of the manipulation that occurred in his labs, in papers on which he served as a principal author, images had been improperly copied and pasted or spliced; results had been duplicated and passed off as separate experiments; and in some instances — in which the report found an intention to hide the manipulation — panels had been stretched, flipped and doctored in ways that altered the published experimental data. All of this happened before he became Stanford’s president. Why, then, didn’t it come out sooner?

The answer is that people weren’t looking.

This year, a panel of scientists began reviewing the allegations against Marc Tessier-Lavigne, focusing on five papers for which he was a principal author.

In the earliest paper reviewed, a 1999 study about neural development, the panel found that an image from one experiment had been flipped, stretched and then presented as the result of a different experiment.

A 2004 paper contained similar manipulations, including an image that was reused to represent different experiments.

“Basic biostatistical computational errors” and “image anomalies” were found in a 2009 paper about Alzheimer’s that has been cited over 800 times, including the reuse of a control image with improper labeling.

At least four of the five papers appear to have manipulated data. Dr. Tessier-Lavigne has stated that he intends to retract three of the papers and correct the other two.

The report and its consequences are an unhappy outcome for a powerful, influential, wealthy scientist described by a colleague in a 2004 Nature Medicine profile as essentially “being perfect.” The first in his family to go to college, Dr. Tessier-Lavigne earned a Rhodes scholarship before establishing a lab at the University of California, San Francisco, in the 1990s and discovering netrins, the proteins responsible for guiding axon growth. “He’s one of those people for whom things always seemed to go just right,” an acquaintance recalled in the Nature Medicine article.

Anonymous sleuths had raised concerns of alteration in some of the papers on PubPeer, a web forum for discussing published scientific research, since at least 2015. These public questions remained hidden in plain sight even as Dr. Tessier-Lavigne was being vetted for the presidency of Stanford, an institution with a budget of $8.9 billion for next year — larger than that of the entire state of Iowa. Reporters did not pick up on the allegations, and journals did not correct the scientific record. Questions that should have been asked, weren’t.

Peer review, a process designed to ensure the quality of studies before publication, is based on a foundation of honesty between author and reviewer; that process has often failed to catch brazen image manipulation. And when concerns are raised after the fact, as they were in this case, they often fail to gain public attention or prompt correction of the scientific record.

This is a major issue, one that extends well beyond one man and his career. Absent public scrutiny, journals have been consistently slow to act on allegations of research falsification. In a field dependent on good faith cooperation, in which each contribution necessarily builds on the science that came before it, the consequences can compound for years.

When we first went to Dr. Tessier-Lavigne with questions in the fall, a Stanford spokeswoman responded instead, claiming the concerns raised about three of his publications “do not affect the data, results or interpretation of the papers.” But as the Stanford-sponsored investigation found and he eventually came to agree, that was not true.

Dr. Tessier-Lavigne’s plan to retract or issue robust corrections for at least five papers for which he was a principal author is a rare act for a scientist of his stature. It seems unlikely this would have happened without the public pressure of the past eight months; in fact, the report concluded that “at various times when concerns with Dr. Tessier-Lavigne’s papers emerged — in 2001, the early 2010s, 2015-16 and March 2021 — Dr. Tessier-Lavigne failed to decisively and forthrightly correct mistakes in the scientific record.”

The Stanford investigation did not find that Dr. Tessier-Lavigne personally altered data or pasted pieces of experimental images together. Instead, it found that he had presided over a lab culture that “tended to reward the ‘winners’ (that is, postdocs who could generate favorable results) and marginalize or diminish the ‘losers’ (that is, postdocs who were unable or struggled to generate such data).” In a statement, Dr. Tessier-Lavigne said, “I can state categorically that I did not desire this dynamic. I have always treated all the scientists in my lab with the utmost respect, and I have endeavored to ensure that all members flourish as successful scientists.”

Winner-takes-all stakes are, unfortunately, an all-too-common occurrence in academic science, with postdoctoral researchers often subject to the intense pressure of the need to publish or perish. Having a paper with your name on it in Nature, Science or Cell, the high-profile journals in which many of the papers reviewed by the Stanford investigation appeared, can make or break young careers. Postdocs are underpaid; Stanford recently purchased housing that was intended to be affordable for them, then reportedly set minimum salary requirements for living there higher than their wages. They are also jockeying to stand out in a field with limited lab positions and professorship openings. And senior researchers sometimes take credit for their postdocs’ work and ideas but brush off responsibility should errors or mistakes arise.

What isn’t common, of course, is the “frequency of manipulation of research data and/or substandard scientific practices” in the labs Dr. Tessier-Lavigne ran, the Stanford report concluded. Falsification, the technical term for much of this conduct, involves “violating fundamental research standards and basic societal values,” according to the National Academy of Sciences. In his statement, Dr. Tessier-Lavigne said that he has “always sought to model the highest values of the profession, both in terms of rigor and of integrity, and I have worked diligently to promote a positive culture in my lab.” Despite the report’s characterization of what went on in his labs as rare and irregular, lessons from this case apply across the field, especially regarding the importance of correcting the scientific record.

A 2016 study by a handful of prominent research misconduct investigators — including the well-known image analyst and microbiologist Elisabeth Bik, who helped identify a number of the manipulations in the work coming out of Dr. Tessier-Lavigne’s labs — showed that around 3.8 percent of published studies include “problematic figures,” with at least half of those showing signs of “deliberate manipulation.” But only approximately 0.04 percent of published studies are retracted. That gap, which shows a lack of accountability among both individual researchers and the scientific journals, is a profoundly unfortunate sign of a culture in which admitting failures has been stigmatized, rather than encouraged.

“My lab management style has been centered on trust in my trainees,” Dr. Tessier-Lavigne said in his statement. “I have always looked at their science very critically, for example to ensure that experiments are properly controlled and conclusions are properly drawn. But I also have trusted that the data they present to me are real and accurate,” he wrote.

Science is a team sport, but as the report concluded, Dr. Tessier-Lavigne, a principal author with final authority over the data, was responsible for addressing the issues in his research when they were brought to his attention. In the judgment of the Stanford investigation, he “could not provide an adequate explanation” for why he had not done so.

To his credit, he began the correction process for a few of these examples of data manipulation in 2015, when the first allegations were made publicly. But when Science failed to publish the corrections for two of those papers, the report found that after “a final inquiry on June 22, 2016, Dr. Tessier-Lavigne ceased to follow up.” He was made aware of the allegations once more when public discussion resumed in 2021. The report found that he drafted an email inquiring about the unpublished corrections but did not send it. He will now retract both those papers.

In another case — in which there was no public pressure to act — he was made aware “within weeks” of an error in a 2001 paper, according to the Stanford report. Although he wrote to a colleague that he would correct the scientific record, “he did not contact the journal, and he did not attempt to issue an erratum, which is inadequate,” the report concluded.

In the past few years, the field has made great strides to combat image manipulation, including the use of resources like PubPeer, better software detection tools and the prevalence of preprints that allow research to be discussed before it is published. Sites like Retraction Watch have also furthered awareness of the problem of research misconduct. But clearly, there is still progress to be made.

The shake-up at Stanford has already prompted conversations across the scientific community about its ramifications. Holden Thorp, the editor in chief of Science, concluded that the “Tessier-Lavigne matter shows why running a lab is a full-time job,” questioning the ability of researchers to ensure a rigorous research environment while taking on increasing outside responsibilities. An article in Nature examined “what the Stanford president’s resignation can teach lab leaders,” concluding that the case was “reinvigorating conversations about lab culture and the responsibilities of senior investigators.”

This self-reflection in the scientific research community is important. To address research misconduct, it must first be brought into the light and examined in the open. The underlying reasons scientists might feel tempted to cheat must be thoroughly understood. Journals, scientists, academic institutions and the reporters who write about them have been too slow to open these difficult conversations.

Seeking the truth is a shared obligation. It is incumbent on all those involved in the scientific method to focus more vigorously on challenging and reproducing findings and ensuring that substantiated allegations of data manipulation are not ignored or forgotten — whether you’re a part-time research assistant or the president of an elite university. In a cultural moment when science needs all the credibility it can muster, ensuring scientific integrity and earning public trust should be the highest priority.

Theo Baker is a rising sophomore at Stanford University. He is the son of Peter Baker, the chief White House correspondent for The Times."

The Ruble: A Political History

"The Ruble: A Political History

By Ekaterina Pravilova

(Oxford, 543 pages, $39.95)

When reading Ekaterina Pravilova's original, fascinating and meticulously researched "The Ruble" it is a good idea to keep in mind its subtitle: "A Political History." For Ms. Pravilova's multi-layered account of the evolution of the paper ruble from its inception in the mid-18th century until the post-revolutionary reforms in the early 1920s goes beyond the merely monetary. "The biography of the ruble," explains Ms. Pravilova, "is a history of the Russian state, written in the language of money." Regardless of the type of political system in place, she writes, "money does not simply reflect an existing (or imagined) social and political order but creates it; it is not a consequence or an attribute but an integral and constitutive part of any regime." Ms. Pravilova, a professor of history at Princeton, shows that the ruble has been, above all, a symbol and an instrument of centralized, autocratic and imperial power.

The story begins in 1769 with the launch, under Catherine the Great, of assignats, Russia's first paper currency. This was, Ms. Pravilova maintains, a risky move. Historically, money had been "a token of legitimacy," an indication of the "pureness and integrity of monarchical power." But even in Catherine's time, the figurative, if not the literal, flimsiness of paper money posed both economic and political dangers to the absolutist state.

Assignats, which bore a promise of convertibility into coinage, were quick to catch on. They were much easier to carry across a vast empire than coins, and they were fully backed by copper and silver coins lodged in two Assignat Banks. They also came with a temptation -- to which, inevitably, the empress succumbed. In the absence of adequate credit mechanisms, it wasn't long before the printing presses sped up to help pay for her wars and the expansion of empire. Russia had shifted to a monetary system in which the state's currency and the state's debt were, to a degree, the same thing. Assignats were backed by an undersized metallic hoard; property pledged by aristocrats; and Catherine's promises. Unsurprisingly, this was not enough to prop up their value.

The reign of Alexander I (1801-25) saw the emergence of two sharply divergent views on the future of Russia's money, each wrapped up in sharply divergent views of the Russian state. To oversimplify, liberals believed in a state where the ruler was accountable to the people and the currency to the discipline of the market -- in this case, a silver standard. For their part, the ideologues of autocracy argued for nominalism, a doctrine, relates Ms. Pravilova, that "reserved for the state the right to determine the value of money." Insisting that a currency's value should be supported by some guarantee (such as reserves) to boost its credibility in the marketplace risked encroaching on the czar's ability to do what was necessary to fund the discharge of his "sacred duties": The ruler's word should be reassurance enough.

The nominalists eventually prevailed. But defending their victory required the establishment of monetary and financial arrangements so convoluted that, despite Ms. Pravilova's best efforts, their descriptions may demand several re-readings before they can be grasped. The stratagems also included siphoning off funds (to the state) that could have otherwise been invested in commerce and industry, with results made more damaging by the extent to which Russia was kept at a counterproductive distance from the international capital that could have accelerated its modernization.

Some relief arrived with the turn to what Ms. Pravilova dubs "autocratic capitalism" in the wake of disaster in the Crimean War. A new, more liberal czar, Alexander II (1855-81), opened the Russian market to foreign traders and investors, adopted free trade and allowed "credit rubles" to move in and out of the country. This turned rubles into a commodity with its own price, an exchange rate watched keenly by the increasing number of Russians who could travel abroad. "Tangible valuables," writes Ms. Pravilova, "started yielding their place to intangible resources of every many kinds (securities, bonds, shares), while the role of the ruble became more abstract -- the measure of value rather than a value itself."

But the reformers did not go far enough: "They spoke the languages of capitalism and autocracy, not seeing the mismatch between the two," Ms. Pravilova notes. It was a preview, in some way, of the internal contradictions that doomed Mikhail Gorbachev's attempts to transform the Soviet system from within. In due course, some of the reforms that marked the earlier years of Alexander's reign were reversed (thus tariffs were reimposed on industrial goods), partly prompted by fears of what they could mean for autocratic rule. Nevertheless, in 1897, after a period of experimentation, Russia went onto a version of the gold standard, which, in practice, "strengthened the state's role in finance and the economy" even as it allowed "Russia to play on the international monetary market." In some respects, time had moved on. And then came 1914.

Because control of money was of both practical and symbolic value to the autocracy, it is perhaps fitting that soaring inflation played no small part in the regime's collapse three years later. It's no less appropriate that the chaos of the immediate post-revolutionary years and the fragility of the new regime were mirrored by a period of monetary confusion. "The ruble," writes Ms. Pravilova, "turned into a very vague category that included dozens of various types of currencies" -- including bank notes issued by the czars, by the provisional government that immediately succeeded them, and (valued at a rather lower level) by the ultimately, if at first precariously, victorious Bolsheviks.

In the end, however, as the Communist Party's grip on power tightened, so did its control over the currency, as it implemented its own variety of nominalism. The ruble was worth, domestically anyway, what the party said it was. The Soviet currency, writes Ms. Pravilova, was turned into a "subsidiary tool" of the command economy, and for citizens, a "sort of generalized ration-card." It was an arrangement that lasted longer than it should have.

---

Mr. Stuttaford is the editor of National Review's Capital Matters." [1]

1. Imperial Tender. Stuttaford, Andrew. 
Wall Street Journal, Eastern edition; New York, N.Y. [New York, N.Y]. 27 July 2023: A.15.

 

Rublis: politinė istorija

Rublis: politinė istorija

Jekaterina Pravilova

 (Oksfordas, 543 puslapiai, 39,95 doleriai)

 

     Skaitant originalų, žavų ir kruopščiai ištirtą Jekaterinos Pravilovos „Rublį“, verta nepamiršti jo paantraštės: „Politinė istorija“. Daugiasluoksnis M. Pravilovos pasakojimas apie popierinio rublio evoliuciją nuo jo atsiradimo XVIII amžiaus viduryje iki porevoliucinių reformų XX a. 2 dešimtmečio pradžioje neapsiriboja vien tik pinigais. „Rublio biografija, – aiškina ponia Pravilova, – tai Rusijos valstybės istorija, parašyta pinigų kalba. Nepriklausomai nuo esamos politinės sistemos tipo, rašo ji, „pinigai ne tik atspindi esamą (ar įsivaizduojamą) socialinę ir politinę tvarką, bet ir ją sukuria; jie nėra pasekmė ar atributas, bet neatsiejama ir sudedamoji bet kokio režimo dalis. “.

 

 Prinstono istorijos profesorė M. Pravilova rodo, kad rublis visų pirma buvo centralizuotos, autokratinės ir imperinės valdžios simbolis ir įrankis.

 

     Istorija prasideda 1769 m., kai, vadovaujant Jekaterinai Didžiajai, buvo išleista assignatai – pirmoji popierinė valiuta Rusijoje. Tai buvo rizikingas žingsnis, teigia M. Pravilova. Istoriškai pinigai buvo „teisėtumo ženklas“, rodantis „monarchinės valdžios grynumą ir vientisumą“. Tačiau net ir Jekaterinos laikais perkeltinis, jei ne tiesioginis, popierinių pinigų trapumas kėlė ir ekonominį, ir politinį pavojų absoliučiai valdžiai.

 

     Assignatai, kurie žadėjo konvertuoti į monetas, greitai patiko. Juos buvo daug lengviau nešti per didžiulę imperiją, nei monetas, be to, jie buvo visiškai paremtos varinėmis ir sidabrinėmis monetomis, patalpintomis dviejuose Assignatų bankuose. Jie taip pat atėjo su pagunda, kuriai imperatorienė neišvengiamai pasidavė. Nesant tinkamų kredito mechanizmų, neilgai trukus spaustuvės paspartėjo, kad padėtų sumokėti už jos karus ir imperijos plėtrą. Rusija perėjo prie pinigų sistemos, kurioje valstybės valiuta ir valstybės skola tam tikru mastu buvo tas pats. Assignatas buvo paremtas per mažo dydžio metaliniu lobynu; aristokratų įkeistu turtu; ir Jekaterinos pažadais. Nenuostabu, kad to nepakako, kad sustiprintų jų vertę.

 

     Valdant Aleksandrui I (1801–25), susiformavo dvi labai skirtingos nuomonės apie Rusijos pinigų ateitį, kurių kiekviena buvo apipinta smarkiai skirtingais požiūriais į Rusijos valstybę. Supaprastinus, liberalai tikėjo valstybe, kurioje valdovas buvo atskaitingas žmonėms, o valiuta – rinkos drausmei – šiuo atveju sidabro standartas. Savo ruožtu autokratijos ideologai pasisakė už nominalizmą – doktriną, pasakoja M. Pravilova, kuri „pasilieka valstybei teisę nustatyti pinigų vertę“. Reikalaudamas, kad valiutos vertė turėtų būti paremta tam tikra garantija (pvz., atsargomis), siekiant padidinti jos patikimumą rinkoje, kilo pavojus, kad caras gali daryti tai, kas būtina, kad būtų finansuojamas jo „šventų pareigų“ vykdymas: Valdovo žodis turėtų būti pakankamai patikinimo.

 

     Galiausiai nugalėjo nominalistai. Tačiau, norint apginti jų pergalę, reikėjo sukurti tokius sudėtingus piniginius ir finansinius susitarimus, kad, nepaisant didžiausių M. Pravilovos pastangų, jų aprašymus gali prireikti keletą kartų perskaityti, kol juos pavyks suvokti. Į gudrybes taip pat buvo įtrauktas lėšų (valstybei), kurias kitu atveju būtų buvę galima investuoti į prekybą ir pramonę, nukreipimas, o rezultatus dar labiau pablogino tai, kad Rusija buvo laikoma neproduktyviu atstumu nuo tarptautinio kapitalo, kuris galėjo paspartinti jos modernizavimą.

 

     Šiek tiek palengvėjo, kai po Krymo karo nelaimės atėjo tai, ką ponia Pravilova praminė panašiu į „autokratinį kapitalizmą“. Naujas, liberalesnis caras Aleksandras II (1855-81), atvėrė Rusijos rinką užsienio prekybininkams ir investuotojams, priėmė laisvą prekybą ir leido „kredito rubliams“ judėti į šalį ir iš jos. Tai pavertė rublius preke, turinčia savo kainą – valiutos kursą, kurį atidžiai stebėjo vis daugėjantys rusai, galintys keliauti į užsienį. „Materialios vertybės, – rašo ponia Pravilova, – pradėjo užleisti savo vietą įvairių rūšių nematerialiems ištekliams (vertybiniams popieriams, obligacijoms, akcijoms), o rublio vaidmuo tapo abstraktesnis – vertės matas, o ne pati vertė. “

 

     Tačiau reformatoriai nenuėjo pakankamai toli: „Jie kalbėjo kapitalizmo ir autokratijos kalbomis, neįžvelgdami šių dviejų neatitikimo“, – pastebi M. Pravilova. Tai tam tikra prasme buvo vidinių prieštaravimų, pasmerkusių Michailo Gorbačiovo bandymus pertvarkyti sovietinę sistemą iš vidaus, apžvalga. Atėjus laikui, kai kurios reformos, žymėjusios ankstesnius Aleksandro valdymo metus, buvo atšauktos (todėl pramoninėms prekėms buvo vėl įvesti tarifai), iš dalies paskatintas baimės, ką jos gali reikšti autokratiniam valdymui. Nepaisant to, 1897 m., po laiko, praleisto eksperimentuojant, Rusija pasirinko aukso standarto versiją, kuri praktiškai „sustiprino valstybės vaidmenį finansuose ir ekonomikoje“, net ir leido „Rusijai žaisti tarptautinėje pinigų rinkoje“. Kai kuriais atžvilgiais laikas pajudėjo.

 

Ir tada atėjo 1914 m.

 

     Kadangi pinigų kontrolė autokratijai turėjo ir praktinę, ir simbolinę vertę, galbūt, dera, kad sparčiai didėjanti infliacija turėjo nemenką įtaką režimo žlugimui po trejų metų. Ne mažiau tinka ir tai, kad chaosas, kilęs iškart po revoliucijos, ir naujojo režimo trapumas atsispindėjo pinigų sumaišties laikotarpiu. „Rublis, – rašo ponia Pravilova, – pavirto į labai miglotą kategoriją, apimančią dešimtis įvairių rūšių valiutų“, įskaitant banknotus, išleistus carų, Laikinosios vyriausybės, kuri tuoj pat juos pakeitė, ir (vertinama gana žemesnio lygio) galiausiai, nors iš pradžių nesaugiai, pergalingi bolševikai.

 

     Tačiau galiausiai, stiprėjant komunistų partijos galiai, sustiprėjo ir valiutos kontrolė, nes ji įgyvendino savo nominalizmo įvairovę. Rublis buvo vertas šalies viduje tiek, kiek partija sakė. Sovietinė valiuta, rašo M. Pravilova, buvo paversta komandinės ekonomikos „pagalba“, o piliečiams – „tam tikra apibendrinta raciono kortele“. Tai buvo susitarimas, kuris truko ilgiau, nei turėjo.

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     P. Stuttafordas yra „National Review's Capital Matters“ redaktorius.“ [1]

 

1. Imperial Tender. Stuttaford, Andrew. 
Wall Street Journal, Eastern edition; New York, N.Y. [New York, N.Y]. 27 July 2023: A.15.