Infoman

Member since 2017-07-15T03:50:57Z. Last seen 2025-04-09T16:00:01Z.

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  Infoman

  Cooling on China

  Economist (UK) 22/7/2023

  BRITAIN IS “ROBUST” and “ahead of many of our partners” in responding to a rising China, Rishi Sunak, the prime minister, said on July 13th. The House of Commons Intelligence and Security Committee (ISC) disagreed. Its report on China, published the same day, slammed the government for putting economic concerns ahead of national-security ones and human rights. In doing so, it said, the government had jeopardised even the business benefits. It laid out a “nightmare scenario” in which Chinese entities steal blueprints, win influence and exert “political and economic influence at every step”.

  One problem is that Conservative policy on China has zigzagged for a decade, veering from David Cameron’s relationship-chilling meeting with the Dalai Lama in 2012 to a “golden era” when President Xi Jinping clinked glasses with the Queen at Buckingham Palace in 2015. The government largely stood by (though it later let in many refugees) as freedoms were muzzled in Hong Kong. The pandemic sharpened awareness of Britain’s reliance on China, hardening attitudes.

  A “rainforest of initiatives” has followed more recently, says Kevan Jones, an MP and member of the ISC. A new National Security Law came into effect on July 11th, updating counter-espionage laws to tackle the theft of trade secrets. This was partly aimed at subversion by Chinese state entities. Scrutiny of investments has increased. A regime introduced in 2021 screens for risks when firms conduct acquisitions or mergers. Over half the interventions in the first full year involved Chinese ones. The role of Chinese firms in infrastructure is also being re-examined. Huawei telecommunications equipment from China will be phased out by 2027. Chinese investment in Britain’s nuclear programme has been limited but not halted. The government is to set up a national security unit for procurement.

  China matters—it ranks fourth as a trading partner, accounting for nearly 7% of trade—but Britain lacks a co-ordinated policy on how to conduct relations, notes Mr Jones. A British prime minister last visited China in 2018. That’s partly because the Tories are so divided on how to handle the relationship, reckons Yu Jie of Chatham House, a think-tank. In contrast Germany, which is even more reliant on China, published its first China strategy this month (see the China section), pledging to reduce dependence on it.

  Might policy become clearer under Labour, if it were to win the next election? Labour is more openly critical of China. In 2021 the party endorsed a House of Commons motion accusing China of genocide. That would probably remain the party’s position in government. Sir Keir Starmer, its leader, who accuses the Conservatives of “cosying up” to the Chinese Communist Party (CCP), says he wants a “full audit” of relations with the country.

  That chimes with Labour’s wish to demonstrate strong Atlanticist credentials. Rachel Reeves, the shadow chancellor, is inspired by President Joe Biden’s industrial policy, which aims to reduce American reliance on Chinese supply chains. Ms Reeves says Labour would develop “national economic security”. Sir Keir also wants to show a clean break from the leadership of Jeremy Corbyn. It emerged last year that Barry Gardiner, Mr Corbyn’s shadow trade secretary, now nicknamed “Beijing Barry”, had taken donations from Christine Lee, a solicitor whom Britain’s security services declared was “involved in political interference activities” on behalf of China’s Communist Party.

  Yet in practice Labour will struggle to be much tougher. Its China strategy—”compete, challenge and... co-operate” — is as wishy washy as “protect, align and engage”, the Conservative one. Sir Keir frequently says that economic growth is “the absolute foundational stone for everything”, and disengaging from China would be hard to reconcile with that.

  Labour would face the same barriers to countering foreign threats. An effort launched in 2020, for example, to work out how deeply Britain’s supply chains are entwined into China’s economy, has shown that it would be extremely hard to disentangle them.

  Sir Richard Moore, head of MI6, Britain’s spy agency, said on July 19th that his service now devotes more resources to China than to any other country. Yet the security agencies are preoccupied by covert challenges whereas much of China’s state activity in Britain is overt. The government has let Chinese investments flow in and thus sensitive data to go freely to China, says the security report. This has happened in various ways: through academic funding or collaboration on research; allowing access to intellectual property via manufacturing agreements; the sale of Huawei equipment for use in 5G networks; and by welcoming Chinese money in new nuclear facilities. Individual Whitehall departments are supposed to scrutinise all of this, but they lack expertise and resources. Often they are not even looking, the security committee says.

  No single agency considers the overall impact of Chinese state actions, and it is unlikely a Labour government would convene one. Even in America, which has stricter restrictions on engagement with China, government agencies tussle over which one drives China strategy. Britain’s advantage may be that it lacks a large Chinese diaspora, which means that its elections are less susceptible to Communist Party meddling, reckons Charles Parton of the Council of Geostrategy, a think-tank. That’s reassuring, but only marginally.

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  2023/08/17
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  Infoman

  Alarm as voices on climate crisis quit Twitter after Musk takeoverDamian Car­ring­ton En­vi­ron­ment edi­tor

  The Guardian 16/8/2023

  Half of people regularly tweeting about the climate and nature crises abandoned Twitter after it was taken over by Elon Musk, researchers say.

  Twitter, now renamed X, had previously been the leading social media platform for environmental discussion, the researchers said, describing the decline as “troubling”. The “exodus of environmental users on Twitter” was an “existential threat” to a main way of informing people wanting to take climate action.

  Musk, who has called himself a “free speech absolutist”, radically cut Twitter’s content moderation staff after the takeover, which ran from April to October 2022. Reports have found rising dis- and misinformation about climate change on the platform and a sharp increase in hate speech. Scientists said in December there had been a surge in debunked climate change denialist posts on Twitter since the Musk takeover.

  The researchers studied 380,000 users who tweeted regularly about global heating and biodiversity and found 47.5% had become inactive six months after the final takeover. Only 21% of a control group of 458,000 who tweeted about US politics became inactive in the same period.

  “The incredible power of Twitter was that it was this open forum where people could share ideas and opinions and influence other people,” said Prof Charlotte Chang, of Pomona College in California, who led the research. “We have this immense challenge of empowering stakeholders across all sectors of society to take action to halt the loss of biodiversity and to combat catastrophic climate change. We were pretty disheartened to find that after the sale, our environmental Twitter community has really declined.”

  The analysis is published in the journal Trends in Ecology & Evolution. It analysed Twitter use of the groups in 15-day intervals from July 2019 to April 2023.

  X’s media office did not respond to a Guardian request for comment.

  The climate scientist Prof Mark Maslin, of University College London, said in May: “There’s been a massive change [on Twitter]. I get so much abuse and rude comments now.”

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  2023/08/16
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  Infoman

  Hello Mr Arthur! How are you 😊 Can you please share this link with the school as it has my demo teaching classes.

  Thank you!

  https://drive.google.com/drive/folders/1gWUfi9jN6bpJRe5_Wz9FbWih60xKQUmb

  2023/08/16
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  Infoman

  Expensive stocks

  Economist (UK) 12/8/2023

  TRY A LITTLE, and it is never too hard to argue that the stockmarket looks risky and a crash must be coming. But in the long run such arguments are usually best ignored. Since 1900 American shares have posted an average real return of 6.4% a year. Over three decades, that would transform the purchasing power of $1,000 into $6,400. Bonds, the main alternative, do not come close. With an average historical return of 1.7% a year, they would generate a measly $1,700. Cash would do worse still.

  The lesson for today’s investors, many of whom were caught out by this year’s bull market, might seem obvious. Forget about a downturn that may or may not materialise. Just buy and hold stocks, and wait for returns that will erase any number of brief dips. Unfortunately, there is a catch. What matters today is not historical returns but prospective ones. And on that measure, shares now look more expensive—and thus lower-yielding—when compared with bonds than they have in decades.

  Start with why stocks tend to outperform bonds. A share is a claim on a firm’s earnings stretching into the future, which makes returns inherently uncertain. A bond, meanwhile, is a vow to pay a fixed stream of interest payments and then return the principal. The borrower might go bust; changes to interest rates or inflation might alter the value of the cash flows. But the share is the riskier prospect, meaning it needs to offer a higher return. The gap between the two is the “equity risk premium”—the 4.7 percentage points a year that stocks have historically earned over bonds.

  What of the next few years? Estimating the return on a bond is easy: it is just its yield to maturity. Gauging stock returns is trickier, but a quick proxy is given by the “earnings yield” (or expected earnings for the coming year, divided by share price). Combine the two for ten-year Treasury bonds and the s&p 500, and you have a crude measure of the equity risk premium that looks forward rather than back. Over the past year, it has plummeted (see chart).

  Now consider the equity risk premium’s moving parts: earnings, Treasury yields and share prices. Both expected earnings and Treasury yields are roughly where they were in October, when share prices hit a trough. But since then shares have risen a lot, shrinking their earnings yield and bringing it closer to the “safe” Treasury yield. This might mean three things. Investors might believe earnings are about to start growing fast, perhaps because of an ai-fuelled productivity boom. They might think earnings have become less likely to disappoint, justifying a lower risk premium. Or they might fear that Treasuries—the benchmark against which stocks are measured—are now more risky.

  Sustained earnings growth is the dream scenario. The second option, though, is less rosy: that investors have let their revived animal spirits get ahead of them. Ed Cole of Man Group, an asset manager, argues the squeezed equity risk premium is a bet on a “soft landing”, in which central bankers quash inflation without a recession. This has become easier to envisage as price rises have cooled and most countries have so far avoided downturns. Yet surveys of manufacturers still point to recession in that sector, and the full dampening effect of rate rises may not yet have been felt.

  The third possibility is that, rather than cooing over stocks, investors are shunning the alternative. Last year was the worst for bonds in both America (where they lost 31% in real terms) and across developed markets (a 34% loss) in over a century.

  After that, says Sharon Bell of Goldman Sachs, a bank, it is unsurprising if some investors are wary of bonds and inclined to splurge on shares, especially if they believe inflation has moved structurally higher— something shares, as claims on nominal earnings, protect against, whereas bonds, deriving value from fixed coupons, do not. At the same time, governments are set to issue ever more debt to cover ageing populations, defence spending and cutting carbon emissions, while central banks have disappeared as buyers. Higher bond yields, and a mechanically lower equity risk premium, will be the result. This would imply a regime change, to one where the equity risk premium has shifted lower for the long term (rather than temporarily, to be corrected by a fall in share prices).

  Whatever the reason for the squeeze, investors have now placed their bets on rising profits. In a recent analysis, Duncan Lamont of Schroders, an investment firm, compared returns on the s&p 500 going back to 1871 with the yield gap against tenyear Treasuries. He found the relationship “has not been helpful in giving a steer on short-term market movements”. Over the longer term, though, there is a clear link. For stocks starting with a low yield gap to do well over ten years, “a near-condition has been real earnings growth”. Animal spirits can only take you so far before earnings must deliver. They would not have to slip far for even a long-term investor to conclude today’s market is too pricey.

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  2023/08/14
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  Infoman

  Uber lyft Ride-hailing profits

  Economist (UK) 12/8/2023

  IT HAS BEEN a bumpy journey for investors in Uber, the world’s biggest ridehailing company, since it was listed in 2019. In its first six months as a public company Uber’s share price plunged by a quarter as doubts swirled over whether the perennial lossmaker would ever turn a profit. Thereafter it has seesawed, soaring amid the pandemic-era craze for tech stocks, then diving back down as rising interest rates spoiled investors’ appetite for businesses reliant on cheap funding.

  Since its nadir in July last year signs of greater financial discipline have pushed the price of Uber’s shares back to where they first traded in 2019. Costs have come down; fares are up. This month the company reported an operating profit of $326m for the second quarter of the year, its first time in the black. Uber’s glee was heightened on August 8th when Lyft, its domestic arch-rival, reported yet another operating loss, of $159m. Lyft’s market value remains in the doldrums, down by 85% from the level at which its shares began trading publicly in 2019, six weeks before Uber’s.

  Still, for Uber, breaking even is a low bar for success. Even adding in the latest profit, the company has clocked up $31bn of net losses since its first available results in 2014. Investors now have $21bn of invested capital tied up in the company. Annualising its most recent quarterly operating profit implies a return on that capital of roughly 5% after tax. That is less than half the company’s current cost of capital, sug

  gesting that investors’ money could be more fruitfully deployed elsewhere.

  The hope, of course, is that Uber’s profits, having broken above ground, will now soar into the stratosphere. Hold your horses. In the past five years over 60% of the firm’s revenue growth has come from businesses other than ride-hailing. Most important has been food delivery, which surged during the pandemic. Uber’s profit margin—before interest, tax, depreciation and amortisation—when ferrying meals is less than half that when ferrying people.

  Uber promises that the business will continue becoming more lucrative as it matures. Yet margins for DoorDash, which generates nearly three times Uber’s fooddelivery sales in America, are barely better. In freight, Uber’s third line of business, the company is losing money as it fights for space in a crowded industry in the throes of a downturn (see earlier article).

  A further concern is Uber’s focus on expansion beyond America, where it is now scarcely growing. Although it does not split out profits by geography, its margins are probably best in America, where it captures nearly three-quarters of sales in the ride-hailing market. Elsewhere, it faces stiff competition from local rivals: Bolt and FREENOW in Europe, Gojek and Grab in South-East Asia, and Ola in India. That will keep a tight lid on margins.

  Investors’ bet on Uber was predicated on the idea that ride-hailing is a winnertakes-all business. That justified torching billions of dollars in a race for market share, which Uber is, seeing Lyft’s woes, indeed winning—at least at home. Whether taking it all turns Uber into the colossal cash machine investors once hoped for is another question.

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  2023/08/14
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  Infoman

  Rosé’s summer reign

  Economist (UK) 12/8/2023

  WHEN TEMPERATURES reach 26°C (78.8°F) in Britain, a few things happen. People strip off their clothes and flock to parks and swimming pools. And they buy rosé. According to Majestic, Britain’s largest wine retailer, 26°C is the exact point at which sales of the pink stuff outpace those of red and white. During a heatwave last year, the company sold one bottle every 12 seconds.

  Rosé is the ultimate summer tipple. Like a strong, zesty margarita, a chilled glass of pale rosé makes a perfect aperitif. (Unlike a margarita, you can probably enjoy more than two without disgracing yourself.) People have been drinking versions of rosé wine for millennia, starting with the ancient Greeks. More than 2,000 years ago the ancient Romans started cultivating vineyards in Provence, in southeastern France.

  Provence remains rosé’s heartland. With 35% of the output, France is the world’s leading producer of rosé. It is also its leading consumer: a third of the bottles of wine drunk there are pink in colour. In the past 15 years, exports of Provençal rosé have increased by around 500%. Château d’Esclans sells an eye- and mouth-watering 10m bottles every year. LVMH, a luxury group that owns a number of revered champagne houses and wineries, has in recent years bought Château Galoupet and acquired stakes in Château d’Esclans and Château Minuty, rosé juggernauts. In America, Whispering Angel, a pink wine produced by Château d’Esclans, sells the most bottles of any French wine of any hue.

  Travel and social media help explain the wine’s global spread. Before the pandemic, France was the world’s leading tourist destination. The pale wine came to be seen as sophisticated thanks to glitzy events such as the Cannes Film Festival. Social-media tributes like #roséallday (a celebration of day drinking) and #brosé (a hashtag used by men who enjoy the wine) have brought attention to the drink. Consumers have also realised the wine’s versatility, agreeing with Julia Child, a popular television cook, that “rosé can be served with anything.” Dry rosés, pleasantly acidic and refreshing (unlike the cloying notes rosé is infamous for, which are common in cheaper varieties), can accompany many cuisines well.

  Rosé still remains a target of derision among oenophiles. It has earned the offensive moniker “bitch diesel” (so named because it is pink and has been marketed to women). According to Sacha Lichine, the president of Château d’Esclans, when he first approached potential distributors he would get the door slammed in his face: traditional folk “think that it’s not a real wine. They think that it’s a Coca-Cola wine,” he explains.

  Barbara Drew, a master of wine at Berry Bros & Rudd, Britain’s oldest wine merchant, suggests that the dismissal of rosé as “not a serious wine” is partly because it generally does not age as well as red, so is not of interest to some collectors and investors. But such squabbles over value ignore rosé’s central role in summer culture. Enjoying it is nothing to blush at.

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  2023/08/14
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  Infoman

  Free exchange Twitternomics

  Economist (UK) 12/8/2023

  ELON MUSK is no fan of the Federal Reserve. At least a dozen times over the past year the owner of X (a firm until recently known as Twitter) has savaged America’s central bank for raising interest rates. Last December, for instance, he tweeted that its hikes might go down as the “most damaging ever”. But Mr Musk’s disdain for the Fed is not mirrored by the Fed’s attitude towards X. On the contrary, the central bank’s researchers rather like the site, treating it as a compelling barometer of the economy.

  This puts X in a peculiar position. Its value as a business remains dubious, which is why Mr Musk has been scrambling to remake it, with changes including (but not limited to) the company’s name. Yet its value to the economy is a different story altogether. The firm can serve as a timely indicator of both fundamental trends and market sentiment.

  There is a large, growing literature on how to decode economic signals from social-media sites, ranging from Facebook to Reddit. But even in the sea of online information and commentary, Mr Musk’s site stands out. Others simply cannot match its volume and frequency. By 2013 Twitter users were already producing more than 5,700 posts a second. By 2016 Instagram’s larger user base was producing only 1,000. Three papers recently published by the Fed explore the platform’s economic contributions.

  The first is as a predictor of markets. Sentiment gleaned from tweets seems to be rather good at presaging short-term movements in both share prices and bond yields. In one paper a group of economists including Francisco Vazquez-Grande sifted 4.4m finance-related tweets posted between 2007 and April 2023 to create a Twitter Financial Sentiment Index. They used a machine-learning model to measure each tweet’s sentiments: a message about stocks going to the Moon would be positive; Mr Musk’s quips about the Fed would presumably count as negative.

  The index, they find, correlates tightly with corporate-bond spreads (the difference between yields on corporate and government bonds, which usually widens as investors turn pessimistic). More than merely shadowing financial movements, posts can even foreshadow them. The overnight index before the stockmarket’s open dovetails with the coming day’s equity returns. A separate paper by Clara Vega and colleagues finds that the site’s sentiment also closely tracks Treasury yields. Indeed, the correlation is stronger with tweets than with sentiment measures gleaned from the Fed’s own official communications.

  A second use of tweets is as a gauge of economic conditions. Posts about job losses in particular seem to offer timely information about the labour market. Tomaz Cajner and co-authors construct a separate machine-learning model to digest posts with keywords such as “lost job” or “pink slip”. Their measure of job losses mirrors official data on employment levels from 2015 to 2023. This correlation is potentially powerful because most government statistics appear with a lag, whereas the tweets are available immediately. Twitter, for example, would have provided a ten-day advantage in detecting the collapse in employment at the height of the covid-19 pandemic in 2020.

  The Fed papers also see a third use for tweets: as a bellwether of sorts for monetary policy. Ms Vega and colleagues find that the social-media site fares better than changes in bond yields in predicting monetary-policy decisions on the day of their announcement. The Twitter sentiment index, meanwhile, is good at anticipating shocks from tighter policy such as rate increases. Tweets tend to turn sour just ahead of these moves. (That the site wastes little time in turning bitter will come as scant surprise to regular users.)

  No one is about to ascribe powers of causation to X. The socialmedia posts instead reflect broader feelings that are already coursing through financial markets. Still, the cornucopia of tweets does provide an additional way of measuring such sentiment, which, if proved valid over time, would be highly valuable.

  Beyond the Fed, some analysts are also finding other potential applications. Agustín Indaco of Carnegie Mellon University in Qatar calculates that the volume of tweeting alone can account for about three-quarters of cross-country variation in GDP. Rather like satellite images of night lights, tweets may therefore be a way of observing economic health without relying so heavily on tardy official statistics. This metric may work best in poorer countries, where heavy posting on social media would be a proxy for the state of telecommunications and use of smartphones.

  Marking the spot

  If X is so economically useful, why is it not more lucrative? The various papers do not venture so far as to examine the gulf between Twitter’s struggle for profitability and its evident utility—not just as an economic tool but as a platform for sharing information, opinions, jokes and more. Mr Musk was onto something when he described the firm as a “common digital town square”. The problem in economic terms is that a town square falls into the category of public goods such as parks and clean water. Although public goods can be privately owned, it is notoriously hard to extract profits from them given that, by definition, it is difficult to charge people for all the benefits they confer.

  Mr Musk is doing his darnedest to shift the economic equation at X by giving additional privileges to users who pay $8 a month for the site’s blue-check verification. Tweets by users who cough up now receive extra promotion, among other benefits, appearing more often in the feeds of other people on the site. That, however, poses a trade-off. Paid-for tweets may start crowding out betterinformed posts from users who would rather not subscribe to the site. Over time, a social-media site that prioritises payment over credibility will function less well as a town square and, by extension, as an economic indicator. The gain to X’s finances would be a loss to the Fed’s economists.

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  2023/08/14
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  Infoman

  Orwell mania

  Economist (UK) 12/8/2023

  Wifedom: Mrs Orwell’s Invisible Life.

  By Anna Funder. Knopf; 464 pages; $32. Viking; £20

  Julia. By Sandra Newman. Mariner Books; 400 pages; $30. Granta; £18.99

  FEW WRITERS have achieved the cult status of George Orwell. He is so much a part of the collective imagination that John Rodden, an Orwell scholar, goes so far as to call him “the most important writer who ever lived”. He was not the best writer of his time, explains Mr Rodden, author of several books on the writer’s “afterlife”, but his universal recognition, continuous publication and repeated spikes in popularity are “an unprecedented phenomenon rivalled only by Shakespeare himself”.

  Orwell’s most celebrated novel, “1984”, tells the story of Winston Smith, an everyman who embarks on a love affair in defiance of the surveillance state led by Big Brother, the supreme leader, whom some believe Orwell modelled after Josef Stalin. With “telescreens” that snoop on citizens, “thought police” enforcers and a system called “doublethink” in which both everything and the opposite are equally true, Orwell’s fiction has been prescient, invoked to describe the ills of nearly every age. “1984” has repeatedly topped Englishlanguage bestseller lists, including in 1954 (the year the BBC did a television adaptation), 1984 and 2003 (the centenary of Orwell’s birth). Political events bring Orwell new readers, including Donald Trump’s inauguration in 2017 and fomenting of the riot at America’s Capitol in 2021. After Russia’s invasion of Ukraine, “1984” became the most-downloaded electronic fiction book in Russia last year.

  Angst over totalitarianism, the manipulation of truth and the spread of surveillance technologies has hardly abated. Today’s world is increasingly Orwellian, argues Jean Seaton, director of the Orwell Foundation: consider social-media pileons, analogous to the “Two Minutes Hate” the novel’s characters spew at enemies of the state. The dangers Orwell flagged are as easily used by the left to bludgeon autocrats as by the right to denounce the left’s punishment of “wrongthink”.

  It is thus no surprise that in 2023, with fears of autocracy and culture wars at fever pitch, the man who wrote so deftly about dark subjects is back in the spotlight. Films in production include a new documentary on Orwell’s life and an animated “Animal Farm”; a Russian-language “1984” was recently released. At least three Orwell books have been published in the past year, grappling with subjects including Orwell’s relationship with Russia.

  Two more books are forthcoming, which look more closely at the women in Orwell’s life and work. For all his prescience and scrutiny of tyranny, Orwell was blind to another sort of repression: towards women. Along with a new biography by D.J. Taylor, a British historian, the books draw on letters discovered in the past 20 years between the writer and various paramours, as well as some written by Orwell’s first wife, Eileen, to her best friend. The picture that emerges is disheartening—but hardly unusual for a man of Orwell’s time.

  Eileen O’Shaughnessy was married to

  Orwell from 1936 until her death in 1945. One of the first women to attend Oxford University, she was brilliant and witty but abandoned a master’s degree in psychology to wed Orwell. Their life was one of hardship. Eileen struggled to make a remote, unheated cottage a home, nursing the tubercular Orwell back to health while typing up and advising him on his work. She was often the main breadwinner.

  Anna Funder’s “Wifedom” offers bleak details, including the day Eileen cleaned a blocked toilet, standing knee-deep in excrement, when Orwell appeared at a window to ask, “Teatime, don’t you think?” His wife dedicated her life to helping Orwell “fulfil his destiny”, one friend wrote, to the point of fatally ignoring her own health. Meanwhile Orwell was conducting numerous affairs. Before and after they married, her husband was a “sexual opportunist” who pounced on women who came his way, Mr Taylor writes.

  This philandering had long been known to scholars, less so to the public. In the wake of #MeToo and numerous feminist reassessments of badly behaved male artists, he is “due for a bit of reappraisal from that perspective”, says Stefan Collini, an emeritus professor at the University of Cambridge who recently edited a collection of Orwell’s essays. “Wifedom” depicts a man who relied extensively on women while erasing them from his own writings. How could it be, Ms Funder asks, that she read “Homage to Catalonia” twice and never realised that Eileen was also in Barcelona, working for a socialist group against Franco’s fascists?

  Invisible woman

  As the author of “Stasiland”, a prizewinning book on the East German security state, Ms Funder is well-versed in totalitarianism. Her aim is not to “cancel” a thinker she deeply admires. Her inquiry is instead a reaction to realising that she too has vanished into the invisible role of wife, doing the lion’s share of parenting and household management to the detriment of her career. Elegantly and imaginatively resurrecting Eileen, Ms Funder comes to see patriarchy as another form of “doublethink”, which Orwell defined as “a vast system of mental cheating”. Men “imagine themselves innocent in a system that benefits them, at others’ cost”, Ms Funder writes.

  Yet some women take part in their own erasure, a point Ms Funder does not probe deeply enough. Orwell and early biographers wrote Eileen out of history; she colluded by minimising her own suffering. Severely anaemic on the eve of an expensive—and fatal—operation, she wrote to Orwell that “What worries me is that I really don’t think I’m worth the money.” All this makes it doubly refreshing to see Julia, the heroine of “1984”, emerge with full agency in Sandra Newman’s eponymous novel. Such feminist retellings are a booming genre today, with the women of Troy, Shakespeare’s wife and mythological goddesses narrating their lives as the protagonists in new books.

  For decades feminists have called out the sexism of Orwell’s depiction of Winston Smith’s lover, Julia, who is presented as a nymphomaniac and honeypot trap, leading to their crushing by the state. “With Julia, everything came back to her own sexuality,” Orwell wrote. Whether the writer was himself a misogynist or simply satirising a group of sexist men, the author’s estate had long felt there was something missing in the story. They sought a writer who might give a new dimension to the tale, writing a spin-off of “1984” for the 21st century. “The only way to approach it was from a feminist perspective, because the whole regime was so horrifyingly misogynist,” says Bill Hamilton, Orwell’s literary executor.

  Ms Newman’s “Julia” offers a female character with a rich inner life. Her Julia is a survivor, more subversive than Winston, adroit at evading control, finding a kind of liberty in “sexcrime”. “She imagined freedom as exuberance, a clumsy romping,” Ms Newman writes. If Julia entraps Winston, it is because she too has been coerced and victimised. A twisty ending in keeping with the original makes this an enjoyable read even to those unfamiliar with “1984”.

  Neither Orwell’s “troubling” behaviour towards women nor the #MeToo movement inspired the estate’s decision to give the new novel its full backing, says Mr Hamilton. Yet this “Julia” cannot help but balance out his blind spots and bring his opus up to date. After all, he is the perennial man of the hour—not only yesterday but today, and almost certainly tomorrow.

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  2023/08/14
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  Infoman

  Programmable factories

  Economist (UK) 12/8/2023

  IN A FACTORY on the Carolinas’ border, Stanley Black & Decker is assembling cordless electric drills. As part-finished drills travel in boxes along a conveyor belt, a robotic arm photographs and scans them for defects. Another robot nestles electric motors into the drills’ casings. A third one places and tightens screws. A single piece of software oversees the entire production line, which is capable of pumping out 130 cordless power tools every hour under the supervision of just seven humans. The assembly line it replaced in China needed up to 40 workers and rarely produced more than 100 an hour.

  “Thirty years from now we will laugh at our generation of humans, putting products together by hand,” predicts Lior Susan, the boss of Bright Machines, a San Francisco-based company that installed the plant’s software. It is not that the design of the electric drills or the various steps involved in making them have changed. Rather, it is the way the automated machines doing the work are being driven by instructions that have been encoded into software having been in effect copied from the brains of Chinese factory workers, who mostly did the job manually.

  Making things this way resembles a model used by the semiconductor industry, where chips are designed using software that directly links to the automated hardware which fabricates them. For the Fort Mill plant, and other firms starting to employ such software-defined manufacturing systems, it promises to transform the factory of the future by allowing moresophisticated products to be designed and put into production more quickly. All of which promises big cost savings.

  Make this please

  To understand why, consider a simplified version of how a new power tool is made. A team of designers come up with a fresh feature, say a longer-lasting battery. They map out every element of the new product, from the battery compartment to the circuitry, that needs to be changed as a result. It is complex work, not least because a small change to one component can have a big impact on another, and so on.

  The design is then “thrown over the wall” to the people responsible for making it. Sometimes that is a third-party factory, often in China. Engineers, designers and production staff exchange information and meet up, constantly tweaking the design in response to the various successes or failures involved in making a series of prototypes. Little things, such as a screw than cannot be tightened correctly because it is hard to reach with an electric screwdriver, might result in a return to the drawing board—which nowadays is mostly a computer-aided-design (CAD) program.

  Eventually, all the kinks are ironed out (hopefully) and the new product is ready for production. The finer details of how all this was achieved, however, are likely to remain locked up in the minds of the workers assembling the prototypes. Humans are, after all, incredibly flexible and often come up with workarounds.

  This process has been employed for decades, yet is inherently uncertain and messy. Designers cannot predict with any confidence what things the factory can or cannot easily accommodate. As a consequence, the design team may purposely leave some features a bit vague, and be put off innovative ideas for fear of being told it cannot be made or is impossibly costly.

  When the hardware is controlled by

  software, rather than by humans, all this changes. Designers can dream up new products with a far greater certainty that they are manufacturable. This is because the constraints of the production line—even fiddly details like the positioning of screws—are encoded in their CAD programs. Those programs, in turn, are directly connected to the software which controls the machines in the factory. So, if a design works in a digital simulation, there is a good chance it will also “run” on the production line.

  This tight integration of manufacturing hardware and CAD software has been a boon in semiconductor manufacturing, where vast machines etch circuits into silicon just a few nanometres (billionths of a metre) wide. Chip designers with firms such as Apple, Nvidia or Qualcomm use specialised programs, largely produced by two companies, Cadence and Synopsys, to sketch out circuits. The design files are then sent directly to silicon foundries, such as TSMC, in Taiwan, for production.

  “Until the advent of those tools, people were laying out integrated circuits by hand,” says Willy Shih of Harvard Business School. Mr Shih imagines the impossibility of attempting to do that today with, for instance, Apple’s M1 chip, which contains 114bn transistors. Producing such complexity is only possible in a system where software allows humans to ignore the detail and focus on function.

  Stanley Black & Decker has not yet turned its CAD tools loose on Bright Machines’ system to design new products. But the idea is that they soon will. “What Cadence and Synopsys did to semiconductors is what we will do to product design,” says Bright Machines’ Mr Susan.

  Layer by layer

  Some companies have already started designing products this way. VulcanForms is a foundry, but one that makes metal components rather than chips. It operates out of a former aircraft hangar in northern Massachusetts, where its vast computercontrolled machines focus 100,000 watts of invisible laser light onto a bed of powdered metal. The powder melts and fuses into intricate patterns, layer by layer, until a component with dimensions specified to within a hundredth of a centimetre emerges. It could be part of the engine in a military drone, or a perfectly formed hip-replacement joint. This is a type of additive manufacturing, more popularly known as 3D-printing. VulcanForms’ machines are driven by CAD software and can produce any metal component with a diameter up to about half a metre.

  “When I became familiar with what VulcanForms was doing, I could see predictable patterns that mirrored some of the learning with semiconductors,” says Ray Stata, the founder of Analog Devices, an American chipmaker, and a member of the foundry’s board. In chipmaking, he says, the software linking designer and manufacturer has produced huge gains in efficiency and economies of scale.

  VulcanForms uses software made by nTopology. This lets people without the skills required to operate lasers, to design objects for production by the foundry. It can result in components with previously unmatched levels of performance, because they can be produced as complex geometric structures which are impossible to manufacture any other way, says John Hart, chief technology officer of VulcanForms. Objects can be created at high volumes, such as forging 1,000 spinal implants from a single powder bed. With additive manufacturing, products can also be produced in one go, as single components, rather than being assembled from individual parts. This reduces the amount of material required as the parts tend to be lighter. It also cuts down on assembly costs.

  Software-defined manufacturing has an impact on some of the big trade and political challenges faced by companies. For firms that are increasingly uncomfortable with relying on Chinese manufacturers, it can make reshoring production a more viable option. Mr Susan puts it in martial terms: “Manufacturing is a weapon. When we give design files to China, we give the source code of that weapon to our enemy.”

  There will be implications for manufacturing jobs. Although automation usually means a reduction in the number of people assembling things on the shop floor, it also creates some jobs. Technicians are required to program and maintain production systems, and in offices successful companies are likely to boost the numbers working in design, marketing and sales. These jobs, though, require different skills so retraining will be necessary.

  Mr Shih also notes that factories themselves, not just the machine tools and processes within them, are coming under the thrall of software. He cites Tecnomatix, a subsidiary of Siemens, a German industrial giant, whose software lets designers lay out an entire factory so that the making of new products can be simulated in a virtual environment, known as a digital twin, before manufacture begins in its physical counterpart.

  If the future of manufacturing is following semiconductors, then there is still some way to go. Producing mechanical objects is not the same as etching elaborate circuits that have no moving parts. For a start, things are far less standardised, with components having all sorts of end uses. “We’re just at the beginning with mechanical structures,” says Mr Stata. “The whole process of putting materials together in an additive method is in its very early stages. The flexibility and possibility that opens up is mind-boggling.”

  Yet some of the implications are becoming apparent. Products could reach a level of performance and precision which is simply unachievable when their production is limited by human hands. Laying out a factory floor in two dimensions to accommodate human workers will become a thing of the past. Factories designed by software will be denser, much more complex three-dimensional places, full of clusters of highly productive, highly automated machinery.

  These factories of the future may be almost deserted places, attended to by a handful of technicians. But with software also taking care of the intricacies of production, they will be easier to use by people developing and designing new products. That should free their imaginations to soar to new levels.

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  2023/08/14
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  Infoman

  Betting on life sciences

  Economist (UK) 12/8/2023

  Official efforts to boost the life-sciences sector are welcome, but only a start

  MANY CITIES hope that success in one industry may beget success in another. Take Aberdeen, which grew rich from oil exploitation in the North Sea. By a decade ago, the Granite City laid claim to more multimillionaires per head of population than anywhere else in Britain. Now a local tycoon, Sir Ian Wood, hopes to foster growth in a different sector. In May, with government funding, his development agency, Opportunity North East, opened a university-backed research facility to help startups in the city expand their commercial initiatives.

  His bet is on life sciences, a term encompassing high-tech efforts in making pharmaceuticals, biotechnology or medical devices. The city already has a decent record here. Professor David Blackbourn of the University of Aberdeen says ten companies have been spun out from his institution. One, TauRx, based in a former bus depot, is trying to develop a treatment for Alzheimer’s and has raised over $800m since its founding in 2002. Its innovation, tested in human trials, targets tau tangles (abnormal clumps of protein that stick to neurons in the brain). Regulators will soon determine if that treatment is sufficiently effective. Its chief operating officer, Glenn Corr, calls it a “life and death” moment for the company.

  For life sciences in general much is also on the line. Since coming to office last year, Rishi Sunak has set great store by developing high-skilled sectors, such as artificial intelligence and the life sciences, arguing that they will bring long-term gains to the economy. Life sciences gained prominence during covid-19. The world’s first randomised trial for covid treatment was conducted by the University of Oxford and then an effective vaccine for covid was developed by AstraZeneca, a British-Swedish company. It saved millions of lives.

  Already some 300,000 people are employed in the sector and the government talks of that number surging. To that end, Mr Sunak’s administration has set out several ways that Britain aims to make matters easier for life-sciences startups. Will Quince, a health minister, says the “ecosystem” in which small firms operate puts too many obstacles in the way of those eager to grow. Both politicians talk of sweeping them away.

  How much is really changing? Britain undoubtedly has advantages in advanced research. It is home to world-beating universities in life sciences in Cambridge, London and Oxford (see table on next page), and in spots like Aberdeen. British universities publish some of the most-cited academic publications in life sciences, though the country falls a bit short in getting patents filed. It would help if academics were spurred harder to apply for them.

  But academic excellence needs nurturing. Many had expected that, by now, Britain would have rejoined Horizon Europe, the EU’s fund (and the world’s largest) for research and innovation, worth some £85bn ($108bn). Boris Johnson, when prime minister, said this would happen after Brexit. Mr Sunak had seemed poised to unveil a deal to do so in July. He did not, apparently because of worries about paying in necessary funds. A decision may be taken soon. An alternative British-only scheme, called Pioneer, is widely seen as a second-best option.

  Beyond the universities, a second series of hurdles block Britain’s startups. Here, again, the country enjoys distinct advantages, so should be able to prosper. Around

  a third of all life-sciences-focused startups in Europe are reckoned to be there, more than in any country on the continent. That is partly because of abundant talent, an entrepreneurial culture and sufficient funding for early-stage growth.

  But the startups face at least three more big challenges: painfully slow processes for getting trials for drugs or other products under way; the high cost of property (with knock-on effects on labour costs); and difficulty in securing access to largescale capital to allow promising firms to grow. On each of these, the government has taken some welcome steps.

  Excessive delays in firms being able to conduct clinical trials are beginning to improve. The problems were created in part because the underfunded medicines regulator, the MHRA, took longer than most counterparts in other countries to let firms administer the first dose of a medication in a trial. Waiting for most of a year to get a trial started is “a really long time when your patent clock is ticking”, laments Lisa Patel of Istesso, a firm developing drugs to treat auto-immune diseases. (As 90% of products under trial end up failing, the faster the process is done, the sooner researchers can move on.)

  As a backlog at the MHRA caused by the covid pandemic eases, trial efficiency is improving. Another measure for the regulator is whether companies can recruit trial participants quickly enough. By May, according to official data, 73% of trials signed up their target number of patients on time, up from just 23% in May last year. The government also promises to tackle a shortage of staff at the MHRA, which had held it back.

  The main reason for optimism, meanwhile, is an independent review that reported in May, by Lord O’Shaughnessy, which offered 27 recommendations including several to accelerate the regulatory process. The government sounds eager to implement many. These include creating networks to help speed up clinical trials, giving NHS staff incentives to sign up their patients, and finding ways for new technologies to be rolled out sooner in the NHS.

  Government efforts to tackle the high cost of property are more limited. Many startups want to be in the “golden triangle” near Cambridge, London and Oxford, where finding space for labs, or for staff to live, is painfully pricey. Officials have announced plans to develop new lab space in Cambridge, and to build more homes there. Campuses are expanding in Oxford; private developers in London are building labs and offices for the sector, notably in Kings Cross and Canary Wharf. Such increased activity by private actors is an encouraging sign.

  The third problem of raising largerscale capital is the biggest challenge. Whereas venture funds for startups remain plentiful, investment for those moving to later stages has long been too hard to obtain. Last year only 22 life-sciences companies in Britain raised £30m or more in funding rounds. In America nearly 400 did so. Worryingly, life-sciences firms collectively were able to raise only £3.3bn in equity finance last year, down from £7.2bn the year before.

  The government has tried to make up some of the shortfall. Since 2021 British Patient Capital, a subsidiary of the government-funded British Business Bank, has co-invested in eight later-stage biotechs. It also provides investment to specialist venture-capital funds. “But we really need to try to attract in much more private-sector capital to make a dent in what are quite significant funding gaps,” says Catherine Lewis La Torre, its outgoing chief.

  In this, the biggest gain would be if more long-term capital from pension funds found its way to the firms. The government wants those who run definedcontribution pension schemes to invest in unlisted outfits, including life-science companies. In July the chancellor, Jeremy Hunt, said nine large investment funds had agreed to allocate at least 5% of their pension savings in such unlisted firms by 2030, up from 1%. If that came to pass, it would potentially add billions of pounds in funding for such firms.

  Steve Bates, chief executive of the BioIndustry Association, calls that a gamechanger. He argues that the combined benefits of hurdles coming down at home and others going up elsewhere (such as draft legislation in the EU that could limit the patent life of pharmaceuticals) make Britain look increasingly attractive to those trying to expand in the sector.

  Maybe so, but other big challenges will prove much harder to overcome. England remains a small market for pharma companies, accounting for only 2% of global pharmaceutical sales, whereas America makes up nearly 50%. Pharma firms complain about an NHS drug-pricing policy, now being renegotiated, which obliges them, in effect, to accept a discount that is currently worth 26.5% on the value of sales of most branded medicines. Those that produce new tech also grumble that the NHS has been far too slow in adopting their innovations, and changing habits here will not be quick.

  The London Stock Exchange looks increasingly moribund. Brexit has not made it easier to manufacture in Britain, whereas exporting to the EU has become more complicated. Britain is a diminishing actor in export markets: its firms account for 4.3% of global pharma exports, with both production volumes and export values dropping over the past decade. Nor has Britain been able to draw hefty levels of foreign direct investment into its life-sciences firms: in 2022 these shrank by nearly half, to £1bn. By contrast Ireland’s more than doubled, to £3.7bn.

  In one area, British firms do reasonably well: startups find that bigger firms are often keen to buy them. Of the ten British companies with the largest venture rounds in 2018, one has since been bought by an American pharma company, Pfizer, and another by a Swiss one, Roche. Such exits are a boon to founders, some staff and potentially to future patients. They should encourage more new firms to be founded. British buyers may themselves also grow by taking over minnows. But it’s not what Mr Sunak has in mind when he talks of creating a superpower in the life-sciences. One measure of success, in future, will be how many businesses can grow up without being forced to sell out.

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  2023/08/14
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  Infoman

  The AI Nanny In Your Baby’s FutureThe Wall Street Journal

  12/8/2023

  Imagine being the parent of an infant or toddler a decade from now. Most aspects of child rearing won’t have changed, but others may well be transformed by the use of artificial intelligence. AI devices are likely to become electronic babysitters, just as previous generations of parents adopted television and video games as tools for lightening their caregiving duties.

  AI teddy bears could respond in personalized ways to baby coos and toddler questions. Computer-assisted “nannies” who never tire of reading the same book over and over would make bedtime a breeze. Advanced nursery versions of Alexa could sing and teach favorite songs on demand, play games and even deduce

  why a baby is crying.

  Like innovations of the past generation, these tools will leverage technology to engage children and save parents time and stress. Unlike previous tools, however, there is reason to worry that, because of their sophistication in mimicking human behavior, AI childcare devices may alter the way that infants and toddlers process their experience of the world.

  This is because of the remarkable way in which our brains develop during the first years of life. Human infants arrive in the world a bit underdone. A likely evolutionary reason is that if a typical fetus spent any longer developing in utero, its head would simply be too large to deliver safely. So nature had to compromise: Babies are born after 40 weeks, but the 40-weekold baby brain still has a lot of growing left to do. Most of that growth occurs at a breathtaking pace during the first two years of life; about one million new neural connections form every second. The brain grows to about 80% of its adult size by a child’s third birthday.

  This provides a short window of time in which to set up a child for success in life by nurturing their foundational brain development. It is at the heart of why humans are the most intelligent, creative and productive of all species.

  What babies need most to optimize this early period of rapid advance is rich conversation, what developmental psychologists call “serve and return” interactions. This comes naturally to parents interacting with their children and is known to fuel children’s growth in cognitive and emotional skills.

  Before now, this necessary ingredient could only be provided by a caring adult. Despite what marketers might have you believe, classical music, educational TV and Baby Einstein videos cannot create meaningful new neural connections in a baby’s brain. They are not contingently responsive—there’s no back and forth.

  Emerging AI tools change all that. They have been built in our image, much the way human brains are built. They consist of neural networks of complex connections, forged from massive data inputs. ChatGPT receives that necessary input in the form of large language models, while children receive it in the form of loving interaction with adults. That line will be blurred when we supplement brain-building human interaction with automated alternatives.

  It’s not hard to understand why parents would want to leverage technological innovation to ease their family burdens. Child rearing, particularly in the early years, is an all-consuming task. AI assistance could be transformational for overwhelmed parents, just as washing machines and other appliances revolutionized caretaking in the middle of the last century, freeing women to enter the workforce in droves.

  Why not use AI nannies to engage human babies in the kind of back-and-forth conversation that builds brains? It could have profoundly positive developmental impacts, increasing the frequency and consistency of brainbuilding moments during the period when children’s brains are most “plastic”—that is, most capable of rewiring themselves based on what they encounter. The technology could be a boon to children who otherwise might experience developmental delays. It could help to unlock cognitive potential and close achievement gaps.

  But we must proceed with caution. New technologies can shape the architecture of our brains. When early humans began to use tools to make markings and patterns, new neurons were activated that ultimately enabled the brain to use the visual cortex in an entirely new way—to read and write. In our own day, a January report in JAMA Pediatrics showed that habitual social media use is producing changes in how adolescent brains respond to social rewards.

  There is much that we still don’t know about foundational brain development. Introducing young brains to responsive AI may alter them in fundamental ways we can’t anticipate. If we provide the wrong sort of input or interaction, we may distort cognitive development in farreaching ways.

  Consider one recent revelation in neuroscience. Researchers have long understood that more conversations between adults and children leads to advances in children’s language and vocabulary development. But studies in the last decade have unveiled a crucial mechanism underlying this relationship: The brain waves of children and their human caregivers literally sync up when they are trying to communicate or play together. This has also been observed in adults doing collaborative activities like singing or dancing in groups and communicating face to face. They experience similar brain activity in the same brain regions, and the more their brain waves match, the more productive the outcome.

  In children and their caregivers, that phenomenon happens particularly in the prefrontal cortex, where learning takes place, as a team of Princeton researchers reported in 2020. Further research with young children has shown that this “neural synchrony” boosts vocabulary acquisition as well as social learning and problem-solving skills. Artificial intelligence, though able to engage in back-and-forth exchanges, lacks the physical human brain necessary for neural synchrony. We simply do not yet know what it means for the developing human brain to experience one without the other.

  Resiliency—which is just as important as cognition when it comes to lifelong achievement— is another skill that is almost entirely dependent on early, foundational brain development. When a child encounters a variety of experiences early in life and is guided through those experiences by a loving adult, they learn how to respond adaptively.

  Research also shows that adults with positive memories of receiving lots of care from their parents display higher levels of “grit” and ambition. But what does it mean for a child to grow attached to an automaton, if parents cede some fundamental responsibilities? “There is a danger that this could have a serious effect on their social and emotional development,” wrote Noel Sharkey and Amanda Sharkey, researchers at the University of Sheffield, in a paper in the journal Ethics and Information Technology in 2021.

  We cannot put the AI genie back in its bottle, nor should we. But without better understanding, we risk squandering the capacity for development that resides in the first few years of life —and risk disrupting our own evolutionary fabric.

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  2023/08/12
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  Infoman

  Britain isn’t in ‘managed’ decline. The country is about to fall off a cliffsher­elle Jac­obs

  The Daily Telegraph Nobody seems to know how to save the UK from its cur­rent trap, but I have a revolu­tion­ary sug­ges­tion

  As with the Man­hat­tan Project, Bri­tain must gather a team of bril­liant, unortho­dox free-thinkers to unlock the riddle of the ‘Brit­ish dis­ease’

  The received wis­dom is that Bri­tain is in the gentle throes of man­aged decline. That after the reck­less ecstas­ies of Brexit and the abort­ive Truss exper­i­ment, it must now soberly face up to its unre­mark­able post-imper­ial des­tiny. Many see something quint­es­sen­tially Brit­ish in the coun­try’s ongo­ing slide – an unsen­sa­tional story of dis­gruntle­ment, dys­func­tion and decay. Nobody seems to care that the rul­ing class has given up on free­ing the coun­try from a doom loop of high taxes, low growth and crum­bling pub­lic ser­vices. Few bat an eye­lid as the US eco­nomy heads for an “immac­cu­late soft land­ing”, while Bri­tain’s still reels from infla­tion and pub­lic sec­tor strikes.

  But the UK’S fate is not merely to become stead­ily poorer, crankier and rougher round the edges – a place where, year by year, you become slightly more likely to spend your life rent­ing, be accos­ted by men­tally unstable beg­gars on the street or die of cur­able can­cer. The risk however is that such a scen­ario – one of slow-burn­ing misery rather than a full-blown emer­gency – may in fact be too optim­istic. The coun­try is not so much slump­ing along a down­ward slope as hurt­ling towards a cliff edge.

  Bri­tain is fast approach­ing a state of emer­gency. By most people’s defin­i­tion, the coun­try is almost broke. Even with taxes at a peace­time high, the state is bor­row­ing bil­lions to pay for unsus­tain­able spend­ing. After the author­it­ies bungled how they issued pub­lic debt, debt ser­vi­cing costs are now the fast­est rising in the G7.

  As the pro­por­tion of over-65s soars, the coun­try is sit­ting on a pub­lic sec­tor pen­sion time­bomb. Health spend­ing is now so gar­gan­tuan that the Brit­ish state will soon look like a mere sub­si­di­ary of an unre­form­able NHS. This is aside from the dire state of the eco­nomy, which has effect­ively been in a veget­at­ive state for the past 15 years.

  All this wouldn’t be quite so ter­ri­fy­ing if Bri­tain could spend its way out of crisis, emu­lat­ing Japan’s escape from its lost dec­ade. But as the Liz Truss exper­i­ment showed, Bri­tain may not be in a pos­i­tion to take on any more debt, whether for a tax-cut­ting bon­anza or a Biden-style stim­u­lus pack­age.

  And yet there is wide­spread com­pla­cency among the elite about the pos­sib­il­ity that Bri­tain could be head­ing for a genu­ine crisis – one that the fiscal and mon­et­ary author­it­ies’ old levers may be incap­able of con­tain­ing. Eco­nomic experts still sneer at the pos­sib­il­ity that a coun­try like the UK could ever run out of money, arguing that sov­er­eign defaults are the pre­serve of the devel­op­ing world and coun­tries without inde­pend­ent cent­ral banks. Are they really cer­tain that fin­an­cial mar­kets will forever look at Bri­tain and think the coun­try is a going con­cern?

  Unless Bri­tain changes course, it is not unthink­able that it is now a con­tender to become the first wealthy West­ern coun­try to col­lapse from the pres­sures of demo­graphic trends and fin­an­cing its wel­fare state. Or that it will have to incur the humi­li­ation of fall­ing out of the G7, rub­bing shoulders in world rank­ings with Argen­tina and Poland rather than the US and Ger­many.

  The ques­tion is how on earth we get out of this trap. Some might be temp­ted to ima­gine that what the coun­try needs is another leader in the Thatcher mould – someone imbued with the right mix­ture of pat­ri­ot­ism and stub­born­ness to force-feed the coun­try tough medi­cine. But this makes one very hasty assump­tion: that any­one actu­ally knows in detail what needs to be done.

  Brit­ish decline is a genu­ine mys­tery wrapped in an enigma. Not a single eco­nom­ist has been able to con­vin­cingly explain the coun­try’s “pro­ductiv­ity puzzle”, for example. Des­pite pur­su­ing end­less strategies to tackle regional inequal­ity, the chick­en­and-egg conun­drum, whereby com­pan­ies base them­selves in Lon­don to recruit the best tal­ent, and work­ers, in turn, flock to Lon­don for the best jobs, remains frus­trat­ingly unre­solved.

  In polit­ical and media circles, the story arc of Brit­ish decline is his­tri­onic and garbled. Brexit is the most pop­u­lar cul­prit, even though stag­na­tion pred­ates it. “Evil bankers” are also blamed, even though flat pro­ductiv­ity since 2008 sug­gests the euphoric bank­ing boom obscured, rather than gave birth to, a deeper mal­aise. Another lazy argu­ment is that Bri­tain’s decline is post-imper­ial karma. The post-second World War Ger­man eco­nomic mir­acle ought to put such super­sti­tious self-fla­gel­la­tion into per­spect­ive.

  Nor is it entirely clear how to defuse the booby traps embed­ded in the Brit­ish eco­nomy. Cut the wrong wire – by try­ing to aggress­ively reduce taxes (as Truss attemp­ted) – or push through a Roosevel­tian Green New Deal (as Keir Starmer dreams of doing) – and you risk speed­ing up the det­on­a­tion timer. Slash the wel­fare state and you risk a repeat of the aus­ter­ity stag­na­tion fiasco. Try to crush infla­tion through rate hikes and you court a full-blown mort­gage crash.

  But Bri­tain is not entirely lack­ing in genius. Instead of search­ing for a mes­si­anic hero of the moment (a fig­ure who almost cer­tainly does not exist within the ranks of either major party any­way), maybe what is needed is no less than a national effort akin to the Man­hat­tan Project or the crack­ing of the Enigma code at Bletch­ley Park. Per­haps what the UK must do is to gather a team of bril­liant, unortho­dox, eccent­ric free-thinkers – eco­nom­ists, entre­pren­eurs, tech­no­lo­gists, his­tor­i­ans – to unlock the sphinxian riddle, not of nuc­lear phys­ics or crypto­logy, but of the “Brit­ish dis­ease”.

  The Man­hat­tan Project remains the model of what can be achieved against the odds, away from the polit­ical snip­ing, petty bur­eau­cracy and self-indul­gent pess­im­ism of the centre. The father of the atomic bomb J Robert Oppen­heimer delib­er­ately chose to base his work in the New Mex­ican hills because he under­stood that the fron­tier embod­ied the Amer­ican char­ac­ter: its stub­born indi­vidu­al­ism coupled with a remorse­less com­mit­ment to civil­ising pro­gress. Bri­tain’s best minds might be invited to set up shop in our own answer to the fron­tier on one of our windswept Scot­tish islands, where the para­dox­ical bril­liance of the Brit­ish char­ac­ter – a com­bin­a­tion of self­pos­ses­sion and open­ness – might be free to bloom.

  This could well be just an airy dream. Maybe our politi­cians are too cow­ardly and second-rate to fol­low through with build­ing a demo­cratic man­date to push through a com­plex, multi-stage and pain­ful rem­edy any­way. But as Bri­tain dangles on a cliff edge, we have little choice but to think dif­fer­ently and try something drastic.

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  2023/08/08
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  Infoman

  BOE raises key interest rate to 5.25%

  The Wall Street Journal 04 Aug 2023

  LONDON—The Bank of England on Thursday raised its key interest rate for the 14th time in a row and said it might do so again as it tries to cool the fastest rise in consumer prices in the Group of Seven advanced democracies.

  The U.K.’s central bank increased its bank rate to 5.25% from 5%, lifting it to its highest level since February 2008 and matching recent moves by both the Federal Reserve and the European Central Bank.

  Like the U.S., the U.K.’s economy has proved surprisingly resilient during the past year, defying expectations that it would slip into recession following the surge in food and energy prices that followed Russia’s invasion of Ukraine. However, economists warn that rising borrowing costs could push it into contraction.

  The BOE began to raise its key interest rate before the Fed and the ECB, but the U.K.’s inflation rate has fallen less rapidly than that of either the U.S. or the eurozone. In June, U.K. consumer prices were 7.9% higher than a year earlier, compared with 5.5% in the eurozone and 3% in the U.S.

  With further to go before it can be sure that inflation will fall to its 2% target, the BOE said it would raise its key interest rate again if there are signs that big wage increases are set to lead to additional price rises, particularly in the dominant services sector.

  “I don’t think it is time to declare it’s all over, and we’re sticking where we are,” said BOE Gov. Andrew Bailey. “If we get more evidence of more persistent inflation, then we will have to react to that.”

  The BOE signaled that it be in the final stages of its long series of rate rises.

  The central bank forecast that inflation would be below its 2% target from mid-2025 if it were to raise its key rate to 6%, which financial markets viewed as the likely peak before Thursday’s announcement.

  The BOE also described its policy stance as “restrictive,” meaning it is weakening activity and cooling inflation.

  Previous falls in the inflation rate largely have been because of energy prices, which aren’t affected by BOE policy. That is a further indication that policy makers aren’t convinced they need to push rates much higher to get inflation under control.

  “They are suggesting that they are coming to the end of the rate-hiking cycle,” said Mohit Kumar, chief European economist at Jefferies. “It could mean maybe one or two more rate increases, but they are not going to do a lot more.”

  The British pound and government bond yields fell after the decision but reversed course later alongside a rise in U.S. Treasury yields.

  “I think the market has a bit of a quandary here,” said Ben Nicholl, a portfolio manager at Royal London Asset Management. “The bank talked about a few different paths.”

  Investors pared bets on how high they expect the BOE to ultimately lift borrowing costs after the decision.

  Markets are pricing in a peak policy rate of about 5.75% by early next year, sug gesting two more quarterpoint increases. Expectations have fallen sharply since early July, when investors had anticipated rates to peak around 6.5%, according to interestrate swaps markets.

  Markets’ attention is now shifting to what comes next after central banks end their most aggressive tightening cycles in decades. Investors believe the Fed is done raising rates after its 11th increase last month, while the ECB could deliver one more in September, according to swaps markets. All three central banks likely will keep rates on hold for nine to 12 months before moving to interest-rate cuts in 2024, Kumar said.

  However, the BOE has underestimated the scale and persistence of the U.K.’s inflation problem since consumer prices began to rise rapidly in mid-2021. The BOE last week tapped former Fed Chair Ben Bernanke to conduct a review of its forecasting process, with the results expected to be published in spring 2024.

  The economy has yet to feel the full force of the BOE’s in terest-rate increases. As Americans have done, Britons locked in ultralow rates on debt such as mortgages and auto loans in the decade-plus that followed the 2008 financial crisis. Though rates on some loans such as credit cards are rising along with interest rates, a chunk of consumer debt is still tied to the low rates of past years.

  But unlike in the U.S., where interest rates on mortgages are fixed for between 15 and 30 years,

  British mortgages typically carry a fixed rate for between two and five years before being renegotiated, so a rising number of homeowners have been seeing their mortgage move to sharply higher interest rates.

  Oxford Economics’ Michael Saunders, who was a BOE rate setter until last year, estimates that the average interest rate on a U.K. mortgage loan rose by 0.9 of a percentage point through June from late 2021, compared with a likely total increase of 2.5 percentage points by the end of 2026.

  “The BoE are likely to be aware that even if the policy rate and interest rates on new loans stop rising, the economy will face a powerful delayed monetary tightening through the refinancing of expiring fixed rate mortgages over the next few years,” Saunders wrote in a note to clients.

  Roughly three million households are expected to see their monthly mortgage payments rise by the end of the year, according to BOE data.

  One of the BOE’s nine rate setters voted against the increase, arguing that the lagged impact of previous moves would be enough to bring inflation down to the central bank’s 2% target. Two rate setters voted for a larger, half-percentage-point rise, given that the central bank had underestimated inflation in the past.

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  2023/08/05
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  Infoman

  What are the Top 5 Jobs in AI?

  Artificial Intelligence What are the top 5 jobs in AI? From travel developments in the form of autonomous vehicles to changes in education such as teaching via virtual tutors; Artificial Intelligence (AI) is all around us and is rapidly changing our everyday lives. As such, there is a growing demand for skills to create the tools required in implementing AI in a variety of industries, impacting the increase of jobs available too.

  As a result of artificial intelligence developments, which will enable organisations and industries to grow, the World Economic Forum predict 97 million new jobs to be created by 2025. This drastic increase and reliance on AI are predicted to provide a wealth of opportunities in a range of careers and sectors both now and in the future.

  In this blog, we’ve ranked what we think are the top 5 jobs in AI and assess what skills and traits are required to succeed in each of these roles. 1. AI Researchers

  The role of an AI Researcher is to identify new methods of using artificial intelligence to overcome problems and limitations that organisations are facing. Typically, they will specialise in understanding large data sets and converting its learnings into ideas and plans to develop new AI technologies that can be bought-to-life by Data Scientists.

  To become an effective AI Researcher, soft skills such as critical thinking are crucial as the role will involve frequent brainstorming to find new methods and approaches. Alongside this, some of the more specialist skills required include mathematics to utilise statistics and predict how AI programs will run, and the ability to analyse data with experience in tools such as RapidMiner or SketchEngine. 2. Data Scientists

  Whilst an AI Researcher is responsible for finding new methods for AI to problem-solve, their findings will typically be passed onto a team of Data Scientists whose role it is to apply these methods in real-life situations. As such, their roles are crucial to interpreting data effectively and executing tactics to develop AI models and practices.

  The key skills required to succeed as a Data Scientist includes fluency in programming language such as Python and R, and a knowledge of algorithms and their frameworks to build AI models. Good communication skills are also essential as Data Scientists typically work together in teams and require a good understanding of the analysis conducted by AI Researchers.

  One notable example of how AI Researchers and Data Scientists work together is overcoming how facial recognition technology is more likely to misidentify a person with darker skin. Whilst a team of AI researchers identified that three commonly used facial analysis algorithms worked better on light-skinned people, a team of Data Scientists are working to use this information and fix the bug to make the technology effective regardless of skin colour. 3. Machine Learning Engineers

  Whilst data scientists work on information based on ‘data’ and human learning collated by AI Researchers, Machine Learning generates powerful predictive models from a technology-based interpretation without being particularly programmed but understanding the surrounding regularities in data. Read our blog to find out more about the differences between Data Science and Machine Learning.

  This method generates important alternative results which can speed up the process in identifying new solutions, or spot gaps that can’t be easily identified by the human eye. As a result, Machine Learning Engineers have the job of designing self-running AI systems to automate these predictive models and enhance their effectiveness.

  They will typically work alongside AI researchers to understand the data that Machine Learning will be programmed to solve, and communicate with data scientists, IT, and software teams. The key skills required to succeed in this role include strong analytical skills and experience in the use of machine learning packages such as TensorFlow and SciPy. 4. Deep Learning Engineers

  Deep Learning is a subdivision of machine learning where artificial intelligence is programmed with ‘brain like’ structures called neuro networks, designed to mimic the thought process of humans. Although a more time-consuming process compared to machine learning, the results can be more effective, leading to an increasing demand from businesses for Deep Learning Engineers.

  Deep Learning Engineers are responsible for programming AI systems to ensure they create transferable solutions. They will typically train their systems to better understand unstructured data in a variety of forms such as text and PDF’s, meaning some of the typical pre-processing of data can be removed to configure more detailed results.

  Similarly, in most jobs within artificial intelligence, the ability to code is a must for Deep Learning Engineers with expertise in software such as Python. Successful employees in this area are typically focused individuals who are patient, curious and have a good data intuition. 5. Robotics Scientists

  Whereas Data Scientists typically programme technologies to find solutions, Robotics Scientists design and build mechanical devices to perform tasks that can work in conjunction with humans and support their activities.

  Robotics scientists are required to understand how ‘robots’ can tackle an issue in the way that humans can’t do on their own, and the expertise can be applied across a range of industries. In healthcare for example, robotic technology has been created to deliver colonoscopy and surgery, with AI robots programmed to detect possible cancer polyps.

  Robotics scientists are responsible for designing this software and training artificial intelligence on how to perform. As a result, they must be able to think innovatively, possess a good knowledge of mathematics and computer science, and own high-level programming skills. What are the top 'less technical' jobs in AI?

  Expertise in artificial intelligence also opens up a host of ‘less technical’ career opportunities such as roles in cyber security, data analytics and user experience design. These jobs typically require the support of AI such as machine learning to detect suspicious activity in cyber threats. However, these roles are better suited to those who would like to specialise in broader technology roles but can still apply their knowledge of artificial intelligence.

  If you want to learn skills that employers are actively seeking within technology and the AI development sector, you should consider studying our specialised online Masters in Artificial Intelligence. At the University of Leeds, our course modules range from Data Science and Algorithms to optional modules in Machine Learning and Robotics to equip you with the expertise required for a successful career in AI. Disclaimer: This article is not based on data but on the author’s personal perceptions of the AI industry.

  2023/07/28
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  Infoman

  1. 會唔會到倫敦買退休屋？
  2. 退休屋缺點：買盤選擇少，難放盤，唔可以出租，鄰居老人家，年輕人唔可以入住
  3. 優點：以便宜價錢買到比較優質單位，老人家作鄰居會比較安全？

  2023/07/25