Automation Price Quotes

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Purchase Price $250,000 Down Payment $ 25,000 Mortgage Amount $225,000 At 7% Interest Rate 30 Years $1,349 $485,636 15 Years $1,899 $341,762 Difference $550 $143,874 Five hundred fifty dollars more per month, and you will save almost $150,000 and fifteen years of bondage. The really interesting thing I have observed is that fifteen-year mortgages always pay off in fifteen years. Again, part of a Total Money Makeover is putting in place systems that automate smart moves, which is what a fifteen-year mortgage is. Thirty-year mortgages are for people who enjoy slavery so much they want to extend it for fifteen more years and pay thousands of dollars more for the privilege. If you must take out a mortgage, pretend only fifteen-year mortgages exist. If you have a great interest rate, it is not necessary to refinance to pay a mortgage off in fifteen years or earlier. Simply make payments as if you have a fifteen-year mortgage, and your mortgage will pay off in fifteen years. If you want to pay any mortgage off in twelve years or any number you want, visit my website or get a calculator and calculate the proper payment at your interest rate on your balance for a twelve-year mortgage (or the number you want). Once you have that payment amount, add to your monthly mortgage payment the difference between the new principal and interest payment and your current principal and interest payment, and you will pay off your home in twelve years.

TELLING TIME Before she was old, she took canoe trips in the rain and buried her passions deep within nature poems. Ten years before she was old, her husband died and developers paid a mighty price for their dairy farm. She knew she was getting old, when rest stops in Iowa changed over to those crazy automated washrooms. When she was old, God helped with little things (growing tomatoes in her garden) but was missing on big ticket items (bringing her husband back). She knew she had lived too long when her grandson explained extinction to his stuffed polar bear.

His early research wasn’t especially original. Ax identified slight upward trends in a number of investments and tested if their average price over the previous ten, fifteen, twenty, or fifty days was predictive of future moves. It was similar to the work of other traders, often called trenders, who examine moving averages and jump on market trends, riding them until they peter out. Ax’s predictive models had potential, but they were quite crude. The trove of data Simons and others had collected proved of little use, mostly because it was riddled with errors and faulty prices. Also, Ax’s trading system wasn’t in any way automated—his trades were made by phone, twice a day, in the morning and at the end of the trading day.

Very briefly, this simple, practical measure would be for a portion of the machines of every company to become the property of everyone – with the percentage of profits corresponding to that portion flowing into a common fund to be shared equally by all. Consider what effect that would have on the course of human history. Currently, increasing automation reduces the portion of total income that goes to workers, diverting more and more money into the pockets of the rich who own the machines. But as we have seen, this ultimately diminishes demand for their products, as the majority have less and less money to spend. But if a portion of the profits were to go automatically into the bank accounts of the workers as well, then this downward pressure on demand, sales and prices would be alleviated, turning the whole of humanity into the beneficiary of the machines’ labour.

By now, though, it had been a steep learning curve, he was fairly well versed on the basics of how clearing worked: When a customer bought shares in a stock on Robinhood — say, GameStop — at a specific price, the order was first sent to Robinhood's in-house clearing brokerage, who in turn bundled the trade to a market maker for execution. The trade was then brought to a clearinghouse, who oversaw the trade all the way to the settlement. During this time period, the trade itself needed to be 'insured' against anything that might go wrong, such as some sort of systemic collapse or a default by either party — although in reality, in regulated markets, this seemed extremely unlikely. While the customer's money was temporarily put aside, essentially in an untouchable safe, for the two days it took for the clearing agency to verify that both parties were able to provide what they had agreed upon — the brokerage house, Robinhood — had to insure the deal with a deposit; money of its own, separate from the money that the customer had provided, that could be used to guarantee the value of the trade. In financial parlance, this 'collateral' was known as VAR — or value at risk. For a single trade of a simple asset, it would have been relatively easy to know how much the brokerage would need to deposit to insure the situation; the risk of something going wrong would be small, and the total value would be simple to calculate. If GME was trading at $400 a share and a customer wanted ten shares, there was $4000 at risk, plus or minus some nominal amount due to minute vagaries in market fluctuations during the two-day period before settlement. In such a simple situation, Robinhood might be asked to put up $4000 and change — in addition to the $4000 of the customer's buy order, which remained locked in the safe. The deposit requirement calculation grew more complicated as layers were added onto the trading situation. A single trade had low inherent risk; multiplied to millions of trades, the risk profile began to change. The more volatile the stock — in price and/or volume — the riskier a buy or sell became. Of course, the NSCC did not make these calculations by hand; they used sophisticated algorithms to digest the numerous inputs coming in from the trade — type of equity, volume, current volatility, where it fit into a brokerage's portfolio as a whole — and spit out a 'recommendation' of what sort of deposit would protect the trade. And this process was entirely automated; the brokerage house would continually run its trading activity through the federal clearing system and would receive its updated deposit requirements as often as every fifteen minutes while the market was open. Premarket during a trading week, that number would come in at 5:11 a.m. East Coast time, usually right as Jim, in Orlando, was finishing his morning coffee. Robinhood would then have until 10:00 a.m. to satisfy the deposit requirement for the upcoming day of trading — or risk being in default, which could lead to an immediate shutdown of all operations. Usually, the deposit requirement was tied closely to the actual dollars being 'spent' on the trades; a near equal number of buys and sells in a brokerage house's trading profile lowered its overall risk, and though volatility was common, especially in the past half-decade, even a two-day settlement period came with an acceptable level of confidence that nobody would fail to deliver on their trades.

In the past decade, the historically consistent division in the United States between the share of total national income going to labor and that going to physical capital seems to have changed significantly. As the economists Susan Fleck, John Glaser, and Shawn Sprague noted in the U.S. Bureau of Labor Statistics’ Monthly Labor Review in 2011, “Labor share averaged 64.3 percent from 1947 to 2000. Labor share has declined over the past decade, falling to its lowest point in the third quarter of 2010, 57.8 percent.” Recent moves to “re-shore” production from overseas, including Apple’s decision to produce its new Mac Pro computer in Texas, will do little to reverse this trend. For in order to be economically viable, these new domestic manufacturing facilities will need to be highly automated. Other countries are witnessing similar trends. The economists Loukas Karabarbounis and Brent Neiman have documented significant declines in labor’s share of GDP in 42 of the 59 countries they studied, including China, India, and Mexico. In describing their findings, Karabarbounis and Neiman are explicit that progress in digital technologies is an important driver of this phenomenon: “The decrease in the relative price of investment goods, often attributed to advances in information technology and the computer age, induced firms to shift away from labor and toward capital. The lower price of investment goods explains roughly half of the observed decline in the labor share.

Consider a New York Times story from April 22, 2014, that reported: Something strange is happening at farms in upstate New York. The cows are milking themselves. Desperate for reliable labor and buoyed by soaring prices, dairy operations across the state are charging into a brave new world of udder care: robotic milkers … Robots allow the cows to set their own hours, lining up for automated milking five or six times a day—turning the predawn and late-afternoon sessions around which dairy farmers long built their lives into a thing of the past. With transponders around their necks, the cows get individualized service. Lasers scan and map their underbellies, and a computer charts each animal’s “milking speed,” a critical factor in a 24-hour-a-day operation. The

There’s no better case study showing how connectivity and computing power will turn old products into digitized machines than Tesla, Elon Musk’s auto company. Tesla’s cult following and soaring stock price have attracted plenty of attention, but what’s less noticed is that Tesla is also a leading chip designer. The company hired star semiconductor designers like Jim Keller to build a chip specialized for its automated driving needs, which is fabricated using leading-edge technology. As early as 2014, some analysts were noting that Tesla cars “resemble a smartphone.” The company has been often compared to Apple, which also designs its own semiconductors. Like Apple’s products, Tesla’s finely tuned user experience and its seemingly effortless integration of advanced computing into a twentieth-century product—a car—are only possible because of custom-designed chips. Cars have incorporated simple chips since the 1970s. However, the spread of electric vehicles, which require specialized semiconductors to manage the power supply, coupled with increased demand for autonomous driving features foretells that the number and cost of chips in a typical car will increase substantially.

Simple Fast Funnels VS Hubspot There are 2 primary factors to consider when exploring Simple Fast Funnels VS Hubspot… Available Features. Price. Hubspot is a powerful platform, there’s no denying that, but they lack a few features that Simple Fast Funnels offers: 2 way SMS so you can send one way messages to your clients OR interactive messages. You can automate answers or have your customers reach you or customer service directly. Unified messaging. Housing all messages for particular customers in one place lets you simplify customer service. They can text, email, schedule calls or FB message you and you’ll see it all in one location. Simple Fast Funnels customer service has 24/7 chat support and guides you through any hiccups you may experience as you build your funnel. Simplified funnel building. No tech knowledge required. The biggest factor comparing these two platforms however is price: Hubspot charges a small fortune for their good features. Their price is over 10X the cost of Simple Fast Funnels. Simple Fast Funnels saves you thousands, or even tens of thousands yearly and you don’t get less features, you get MORE… We believe you should be able to run your business without paying rates like these. Call us old fashioned if you like. For Hubspot’s premium service, you’ll pay $3,600/month. That’s a lot of revenue to come up with each month just to pay for your operating platform. For Simple Fast Funnel’s premium service, you’ll get the same features and more for $297/month. If you haven’t tried Simple Fast Funnels out yet, we offer a 14 day free trial, that’s how sure we are you’re going to love this service.

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Automation has reached the point where most businesses need dramatically fewer employees. “Presumably, this should make companies more profitable and increase their willingness to invest in new products and services,” writes Larsson. “It does not. Instead, there is competition between more and more equal competitors, and all are forced to reduce prices to get their goods sold. The advantages of leading companies are getting smaller and smaller and it is becoming ever more difficult to find areas where unique advantages can be developed.”36 Regardless of the industry, “Most companies tend to use the same standard systems and more and more companies arrive at a situation where time and cost have been reduced to a minimum.

Algorithmic profits Algorithmic marketing is allowing companies to do things they couldn’t do before, and some early signs show it can deliver big value, especially in financial or information services. In North America, Amazon.com grew 30 to 40 percent, quarter after quarter, throughout the United States’ 2008-2012 recession, while other major retailers shrank or went out of business. From 2006 to 2010, Amazon spent 5.6 percent of its sales revenue on IT, while rivals Target and Best Buy spent 1.3% and 0.5%, respectively. That investment and focus has yielded increasingly sophisticated recommendation engines that deliver over 35 percent of all sales, an automated e-mail/customer service systems (90 percent are automated, versus 44 percent for the average retailer) that are a key component of its best-in-class customer satisfaction, and dynamic pricing systems that crawl the Web and react to competitor pricing and stock levels by altering prices on Amazon.com, in some cases every 15 seconds.

The reason for this pressure on the wages of all but the highest skill Western world workers is not an inability to generate additional income or profit to pay for labor. Rather, there is downward pressure on the price of labor. There are multiple sources for this pressure, but three in particular have been thoroughly documented: Automation, Globalization, and deunionization.

There is nothing in the manifestos of the Jana Sangh that has consistency or anything discernible as an economic ideology or any ideas about how Hindutva would influence the State. The manifestos are a collection of rambling and inchoate pronouncements. The Jana Sangh stood for mechanisation of agriculture and then immediately opposed it in 1954 (because the use of tractors would mean bullocks would get slaughtered). It wanted industry to calibrate its use of automation not based on efficiency but how many more individuals it could hire. It did not explain why a businessman should or would want to add cost rather than reduce it. In 1971 it said it wanted no automation in any industry except defence and aerospace. In 1954, and again in 1971, it sought to cap the monthly incomes of all Indians at Rs 2,000 and wanted the State to appropriate everything earned above that sum. It wanted residential bungalows to be limited to a size of 1,000 square yards.3 In 1957, it spoke of ‘revolutionary changes’ it would bring without saying what these were, and in the very next manifesto dropped the reference without explanation. All this is, of course, because they were responding to Congress manifestos of the time and had nothing real to offer of their own. Nor did they think they needed to: with a national voteshare that till 1989 was in the single digits, the party knew it would not be in power, would not need to implement a policy and, therefore, was free to say whatever came to mind. The Jana Sangh did not have any particular strategic view of the world and India’s place in it besides saying that India should be friends with all who were friendly and tough on those who were not. India should seek a place in the Security Council but there was no reference to why or what India’s role would be, or how its influence and strategic options would increase if it got this position. It offered no path for getting to the Security Council. Entitlement would apparently get India there.

At Doctor Essentials, our mission is to provide you with high quality medical essential equipment at affordable prices. We keep our costs and overheads down through careful product sourcing by expert buyers with years of experience, online-only sales and automated fulfillment, enabling us to offer you lower prices without compromising on quality and service standards. You care for your patients. We care for you. If you’re a busy doctor, nurse, paramedic or medical student, we’re your personal emergency service – providing the essential medical kit you need when you need it and at the right price.

The basic assumption of unionism was not the dignity but the drudgery of labor, and the strategy was, therefore, to do as little as possible for as much pay as possible. Thus, as automation eliminates drudgery, it eliminates the necessity for the unions, a truth that is already extending up to such "high-class" unions as the musicians'. The piper who hates to play is replaced by a tape, which does not object when the payer calls the tune. If, then, the unions are to have any further usefulness, they must use their political pressure, not for a greater share of profits (based on rising prices to pay for rising wages) but for total revision of the concept and function of money.

Even Baby Swings have gotten incredibly trendy and luxurious in this current day of automation. Buying a baby swing electric cradle will help to enhance household management and helps to reduce the parent’s work intensity. To know detail about Baby Swing Electric Cradle Price visit Baby Villa!

When it comes to choosing a customer relationship management (CRM) tool, businesses have plenty of options to choose from. Two of the most popular options are Go High Level and Active Campaign. While both tools offer similar features and benefits, there are some key differences that may make one a better fit for your business than the other. Go High Level: Overview and Features Go High Level is an all-in-one sales and marketing platform designed specifically for businesses that want to streamline their customer management processes. The platform offers a wide range of features, including: 1. Sales Automation: Go High Level offers a range of sales automation features, including lead capture forms, appointment scheduling, and automated follow-up emails. 2. Marketing Automation: The platform also offers a range of marketing automation tools, including email marketing campaigns, SMS marketing, and social media marketing. 3. CRM: Go High Level provides a comprehensive CRM solution, with features that include lead management, contact management, and deal tracking. 4. Analytics: The platform also offers detailed analytics and reporting tools, allowing businesses to track the success of their sales and marketing efforts. Active Campaign: Overview and Features Active Campaign is another popular CRM tool that offers a wide range of features and benefits. Some of the key features of Active Campaign include: 1. Email Marketing: Active Campaign is primarily known for its email marketing capabilities, offering a range of tools for creating and managing email campaigns. 2. Marketing Automation: The platform also offers marketing automation tools, including lead capture forms, automated emails, and CRM integration. 3. CRM: Active Campaign provides a comprehensive CRM solution, with features that include lead management, contact management, and deal tracking. 4. E-commerce: Active Campaign offers e-commerce integrations that allow businesses to track customer behavior and make personalized product recommendations. Go High Level vs. Active Campaign: Comparison While both Go High Level and Active Campaign offer similar features and benefits, there are some key differences between the two platforms that businesses should be aware of. 1. Sales and Marketing Automation: While both platforms offer sales and marketing automation features, Go High Level offers a more comprehensive set of tools. This includes appointment scheduling, SMS marketing, and social media marketing. Active Campaign is primarily focused on email marketing, although it does offer some automation features. 2. Ease of Use: Both Go High Level and Active Campaign are user-friendly platforms, but Go High Level is known for its simplicity and ease of use. This makes it a good choice for businesses that are new to CRM tools and want to get up and running quickly. 3. Pricing: Pricing is an important consideration when choosing a CRM tool, both Go High Level and Active Campaign offer competitive pricing. However, Go High Level offers more flexible pricing options, including a pay-as-you-go plan that allows businesses to only pay for the features they need. 4. E-commerce Integration: While both platforms offer e-commerce integrations, Active Campaign is known for its strong e-commerce capabilities. This includes features like abandoned cart tracking, product recommendations, and personalized product recommendations based on customer behavior. 5. Customization: Go High Level offers more customization options than Active Campaign. This includes the ability to create custom workflows and integrations with third-party apps. Which One to Choose? Choosing between Go High Level and Active If you're looking for a simple and easy-to-use platform with a comprehensive set of sales and marketing automation features, Go High Level may be the right choice for you.

When it comes to choosing a customer relationship management (CRM) tool, businesses have plenty of options to choose from. Two of the most popular options are Go High Level and Active Campaign. While both tools offer similar features and benefits, there are some key differences that may make one a better fit for your business than the other. Go High Level: Overview and Features Go High Level is an all-in-one sales and marketing platform designed specifically for businesses that want to streamline their customer management processes. The platform offers a wide range of features, including: 1. Sales Automation: Go High Level offers a range of sales automation features, including lead capture forms, appointment scheduling, and automated follow-up emails. 2. Marketing Automation: The platform also offers a range of marketing automation tools, including email marketing campaigns, SMS marketing, and social media marketing. 3. CRM: Go High Level provides a comprehensive CRM solution, with features that include lead management, contact management, and deal tracking. 4. Analytics: The platform also offers detailed analytics and reporting tools, allowing businesses to track the success of their sales and marketing efforts. Active Campaign: Overview and Features Active Campaign is another popular CRM tool that offers a wide range of features and benefits. Some of the key features of Active Campaign include: 1. Email Marketing: Active Campaign is primarily known for its email marketing capabilities, offering a range of tools for creating and managing email campaigns. 2. Marketing Automation: The platform also offers marketing automation tools, including lead capture forms, automated emails, and CRM integration. 3. CRM: Active Campaign provides a comprehensive CRM solution, with features that include lead management, contact management, and deal tracking. 4. E-commerce: Active Campaign offers e-commerce integrations that allow businesses to track customer behavior and make personalized product recommendations. Go High Level vs. Active Campaign: Comparison While both Go High Level and Active Campaign offer similar features and benefits, there are some key differences between the two platforms that businesses should be aware of. 1. Sales and Marketing Automation: While both platforms offer sales and marketing automation features, Go High Level offers a more comprehensive set of tools. This includes appointment scheduling, SMS marketing, and social media marketing. Active Campaign is primarily focused on email marketing, although it does offer some automation features. 2. Ease of Use: Both Go High Level and Active Campaign are user-friendly platforms, but Go High Level is known for its simplicity and ease of use. This makes it a good choice for businesses that are new to CRM tools and want to get up and running quickly. 3. Pricing: Pricing is an important consideration when choosing a CRM tool, both Go High Level and Active Campaign offer competitive pricing. However, Go High Level offers more flexible pricing options, including a pay-as-you-go plan that allows businesses to only pay for the features they need. 4. E-commerce Integration: While both platforms offer e-commerce integrations, Active Campaign is known for its strong e-commerce capabilities. This includes features like abandoned cart tracking, product recommendations, and personalized product recommendations based on customer behavior. 5. Customization: Go High Level offers more customization options than Active Campaign. This includes the ability to create custom workflows and integrations with third-party apps. Which One to Choose? Choosing between Go High Level and Active Campaign ultimately comes down to your business needs and preferences. If you're looking for a simple and easy-to-use platform with a comprehensive set of sales and marketing automation features, Go High Level may be the right choice for you.

Since The Great Recession, the global financial crash of 2008-09, the debt-fuelled post-recession recovery has been the weakest in the post-war era (since the end of World War Two). Whereas total outstanding credit in the US after the Wall Street Crash grew from 160% to 260% of GDP between 1929 and 1932, the figure rose from 365% in 2008 to 540% in 2010. (And this does not include derivatives, whose nominal outstanding value is at least four times GDP).[34] A long depression and rising right-wing populism have followed, including the stunning ascendency of property tycoon and TV celebrity demagogue Donald Trump as the President of the US in 2016.[35] The British public’s vote in June 2016 to leave the EU delivered another shock of global significance. A chronic drift towards trade wars and protectionism is accelerating and in January 2018, US Defence Secretary Jim Mattis said that “great power competition, not terrorism, is now the primary focus of US national security”, putting Russia, China and – yes – Europe in the crosshairs of the world’s long-time dominant economic and military power. Adding to this age of anxiety is the accelerating automation revolution. What should be an emancipatory and utopian development only generates insecurity at the prospect of unprecedented mass unemployment. It can be no coincidence that all these crises are converging at exactly the same time. They cannot be explained away by cynical and shallow generalisations about ‘human nature’. In the course of this investigation we will see that in fact all of these crises have a common root cause: the decaying nature of capitalism and its tendency towards breakdown. Indeed, average Gross Domestic Product (GDP) growth rates in the world’s richest countries have fallen in every decade since the 1960s and are clearly closing in on zero. Rates of profit, manufacturing costs and commodity prices are also trending towards zero. Drawing on Henryk Grossman’s vital clarification of Karl Marx’s methodology, we shall see that capitalism is heading inexorably towards a final, insurmountable breakdown that is destined to strike much earlier than a zero rate of profit. Indeed, we shall also see that the next, imminent economic crash will result in worldwide hyperinflation. We will also show that the economic crisis is intensifying competition between nation-states, forcing them into a situation which threatens the most destructive world war to date.

Human labour power is a unique commodity in that it produces surplus value – the amount of value that goes to the capitalist after the worker has been ‘paid’ for the part of the day that equates to the amount they and their family need to live on. The working day is split into two parts: necessary labour time and surplus labour time. Necessary labour time is the time it takes the worker (on average) to produce enough value to buy the commodities they need to reproduce themselves, ie to stay what is socially considered healthy enough to continue working. Surplus labour time is the time the worker works beyond necessary labour time. Since the going rate for labour power is necessary labour time, surplus labour time is surplus value that goes to the capitalist, realised through the sale of the commodities workers produce. For example: a worker in a toy factory is paid £10 a day to work 10 hours; she produces 10 toys a day, and a toy is worth £10 each. The capitalist is only paying the worker for her ability to work one hour each day to produce enough value to reproduce herself (one toy = one hour’s labour = £10). Her necessary labour time is one hour, and her surplus labour time that goes to the capitalist is nine hours. If the worker needs £10 a day to reproduce herself, then that £10 is the value of her labour power. If the capitalist cuts the daily wage below £10, he has pushed the wage below the value of labour power. (Indeed, struggles for better wages are usually struggles to push them back up to the proper value of labour power.) The price of labour power is determined like the price of any other commodity – on average, the cost of its production, ie necessary labour time. But if commodities are sold for the cost of their production then how does the capitalist make any profit? The capitalist purchases the worker’s human labour power  – the ability to work –  but, uniquely, always ends up with more than the amount it cost to purchase the commodity. The wage obscures the fact that the capitalist has only paid for necessary labour time. (Marx calls the social relations that are concealed by economic relations commodity fetishism.) Profit then is essentially unpaid labour. Wage labour is – especially for the poorest workers whose daily subsistence depends exclusively on the sale of their labour-power – wage-slavery. Marx’s investigations led him to realise that his analysis of capitalism must start with the commodity, since capitalism “presents itself as an immense accumulation of commodities”.[66] What all commodities have in common is that they are all exchangeable  –  they all possess exchange-value. And as they are all products of labour, what they all have in common which gives them this exchange-value is general human labour in the abstract. Therefore, the total value of all commodities is determined by total socially necessary labour time – how long they took to produce. (The socially necessary labour time of each finished product includes that of each component that goes into it.)

Branding adds spirit and a soul to what would otherwise be a robotic, automated, generic price-value proposition. If branding is ultimately about the creation of human meaning, it follows logically that it is the humans who must ultimately provide it.

By 2008, storm clouds were gathering over Microsoft. PC shipments, the financial lifeblood of Microsoft, had leveled off. Meanwhile sales of Apple and Google smartphones and tablets were on the rise, producing growing revenues from search and online advertising that Microsoft hadn’t matched. Meanwhile, Amazon had quietly launched Amazon Web Services (AWS), establishing itself for years to come as a leader in the lucrative, rapidly growing cloud services business. The logic behind the advent of the cloud was simple and compelling. The PC Revolution of the 1980s, led by Microsoft, Intel, Apple, and others, had made computing accessible to homes and offices around the world. The 1990s had ushered in the client/server era to meet the needs of millions of users who wanted to share data over networks rather than on floppy disks. But the cost of maintaining servers in an ever-growing sea of data—and the advent of businesses like Amazon, Office 365, Google, and Facebook—simply outpaced the ability for servers to keep up. The emergence of cloud services fundamentally shifted the economics of computing. It standardized and pooled computing resources and automated maintenance tasks once done manually. It allowed for elastic scaling up or down on a self-service, pay-as-you-go basis. Cloud providers invested in enormous data ​centers around the world and then rented them out at a lower cost per user. This was the Cloud Revolution. Amazon was one of the first to cash in with AWS. They figured out early on that the same cloud infrastructure they used to sell books, movies, and other retail items could be rented, like a time-share, to other businesses and startups at a much lower price than it would take for each company to build its own cloud. By June 2008, Amazon already had 180,000 developers building applications and services for their cloud platform. Microsoft did not yet have a commercially viable cloud platform. All of this spelled trouble for Microsoft. Even before the Great Recession of 2008, our stock had begun a downward slide. In a long-planned move, Bill Gates left the company that year to focus on the Bill & Melinda Gates Foundation. But others were leaving, too. Among them, Kevin Johnson, president of the Windows and online services business, announced he would leave to become CEO of Juniper Networks. In their letter to shareholders that year, Bill and Steve Ballmer noted that Ray Ozzie, creator of Lotus Notes, had been named the company’s new Chief Software Architect (Bill’s old title), reflecting the fact that a new generation of leaders was stepping up in areas like online advertising and search. There was no mention of the cloud in that year’s shareholder letter, but, to his credit, Steve had a game plan and a wider view of the playing field.

Energy costs also play a role and are illustrative of the challenge presented by the move to EVs. The widespread assumption is that energy costs are lower for EVs, but that is not true for many current EV owners. That is because many homeowners are subject to tiered electricity rates—the more you use, the higher the cost per kWh of electricity. The extra electricity for the car pushes many homeowners into a higher tier. They often end up paying more for electricity than they would have for gasoline. Electric utilities and their regulators originally embraced tiered rates in many states as a way of motivating energy-efficient behavior. When people pay higher rates for using more electricity, they buy more efficient refrigerators and turn off lights. But adding at-home charging is penalized by that pricing logic. The solution is for electric utilities to adopt new rate structures to accommodate and support the introduction of EVs. It is in their interest to do so because EV charging provides them a mechanism for managing their electricity loads more easily and cheaply. But it represents a radical departure for many utilities and their regulators, and thus it will happen only gradually.

First noted by the economist William Baumol in the 1960s, this phenomenon, now known as “Baumol’s cost disease,” basically says that prices in labor-intensive sectors such as healthcare and education increase faster than prices in sectors where most of the work can be more extensively automated.

Subsidy dependency has been coupled with the huge upturn in the so-called ‘financialisation’ of industry, whereby a company’s funds are increasingly dedicated to repurchasing their own shares in order to boost their stock price. In 2010, for example, the US American Energy Innovation Council (AEIC) asked the US government to triple state spending on clean energy to $16bn a year, at the end of a decade in which the companies comprising the council had spent $237bn on stock repurchases.477 From 2008 to 2017, 466 S&P 500 companies distributed $4 trillion to shareholders as buybacks, equal to 53% of profits, along with $3.1 trillion as dividends.This is explained away on the social democratic left as shareholder greed. But it is driven by the need to valorise capital. We did not cover it earlier, but Marx identified the increasing role of share capital as one of the main counter-tendencies.

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