Services revenue for the last four quarters reached $27.8B, figuratively placing Apple’s Services 98th on the Fortune 100 List. If Apple Services were a standalone company, its $27.8B in revenue would just squeak past Facebook’s $27.6B.
…It’s the consideration of Apple Services as a self-standing business. Remove “Apple” from “Apple Services”…would this stand-alone “Services” company enjoy the same success were it to service Android phones or Windows PCs?
With Services, Apple enjoys the benefits of a virtuous circle: Hardware sales create Services revenue opportunities; Services makes hardware more attractive and “stickier”. Like Apple Stores, Services are part of the ecosystem. Such is the satisfying simplicity and robustness of Apple’s business model.
Peer reviewed research suggests the cost of the battery pack is about 50% greater than the cost of the battery cells, however, we note the same article suggests that ratio will remain the same as battery prices drop. This is unlikely as there is no reason to believe the largely mechanical battery pack will decline proportionately any more than the cost of an engine or transmission will decline. Most likely, the battery pack assembly, excluding the cells, will decline only slightly.
For example, about 2 million new passenger cars are registered in France every year. If only half of those were EVs, subsidies would total $7.2B. Money for roads, infrastructure maintenance, policing, and so on have to come from somewhere, and if ICEV sales decline substantially, European governments’ huge gasoline tax revenues would also deteriorate; in such an environment, it is reasonable to assume that EV subsidies would eventually disappear and be replaced by taxes.
The transition from 4G to 5G will allow wireless technology to surpass three technical thresholds: 1) wireless internet speeds will surpass cable broadband and potentially also fiber optic cable; 2) the “internet of things” will have mass industrial applications for the first time; and 3) communication lag will fall to one millisecond—faster than the speed at which humans perceive touch response as instantaneous—giving rise to new, “tactile internet” applications such as remote surgery.
As a result of these barriers being broken, the 5G transition will likely have a larger and broader economic impact than shifts between previous wireless generations.
…many of America’s most popular apps aren’t in India’s top 100… Mr. Singh’s phone uses Google’s Android operating system, which nearly monopolizes India’s smartphone market… Apple Inc., in contrast, has a 3% smartphone market share in India, in part because its least expensive iPhone costs over $300; in India, more than 90% of smartphones cost less than that.
In the year through June, use of YouTube in India has more than doubled, while Gmail use fell 15%…Facebook says it has just over 200 million active users in India, the largest number outside the U.S…
UC Browser, from Alibaba Group Holding Ltd.’s UCWeb, is optimized to use less data for low-speed connections like those India’s poor use. UC Browser, with a less-than-1% market share in the U.S. and Europe, controls more than 40% of India’s mobile browser market…
Google has also benefited from the dominance of its Android operating system.
Paytm, the biggest mobile money app in India, now has more than 200 million users in India, vastly more the number of credit-card holders in India.
Some poor users say they are willing to pay for data even if it means forgoing consumption of things like cigarettes to afford prepaid cards. Sales of shampoo and some snacks foods have slipped for certain consumers as they put more rupees aside for their phones, say consumer-goods companies such as Nestlé SA.
Traditional machine learning models — not deep neural networks — are powering most AI applications. Engineers still use traditional software engineering tools for machine learning engineering, and they don’t work: The pipelines that take data to model to result end up built out of scattered, incompatible pieces.
Facebook’s FBLearner Flow and Uber’s Michelangelo are internal machine learning platforms that do just that. They allow engineers to construct training and validation data sets with an intuitive user interface, decreasing time spent on this stage from days to hours. Then, engineers can train models with (more or less) the click of a button. Finally, they can monitor and directly update production models with ease.
Services like Azure Machine Learning and Amazon Machine Learning are publicly available alternatives that provide similar end-to-end platform functionality but only integrate with other Amazon or Microsoft services for the data storage and deployment components of the pipeline.
Over the past month, small investors have pulled $17 billion out of U.S. stock mutual funds and exchange-traded funds and added $29 billion to bond funds. That’s the latest leg of a long-term trend: Since the internet-stock bubble burst in 2000, investors have withdrawn half a trillion dollars from U.S. stock mutual funds.
The math is simple: If you had a target of 50% in stocks and they go up 10%, you are suddenly off-target, with more than half your money there. Your financial adviser or target-date fund will automatically sell stock and buy bonds to get you back to 50%.
These automatic adjustments don’t mean stocks can’t crash or soar from here. But such sharp moves are at least somewhat less likely, and less likely to last, in a homeostatic market. So don’t believe anyone who tells you Dow 22000 is driven by euphoric “dumb money.” This is a market in which millions of small investors have been selling, not buying.
From a given “expensive” starting point, there was a 56% probability that the market had a 10% correction within 3 years, waiting for which would result in about a 10% return benefit versus having invested right away.
In the 44% of cases where the correction doesn’t happen, there’s an average opportunity cost of about 30% – much higher than the average benefit.
Putting these together, the mean expected cost of waiting for a correction was about 8% versus investing right away.
Now shifting focus from the historical record to looking forward, it’s true that the lower one’s expectation of the stock market return, the lower the expected cost of waiting for a correction. If you believe the stock market has a negative expected return to a particular horizon, then waiting for a correction to invest makes sense. However, at least as far as the historical record for the US stock market goes, higher market valuations are consistent with lower prospective long-term returns, but not negative expected returns.
In 2015, the American death rate—the age-adjusted share of Americans dying—rose slightly for the first time since 1999. And over the last two years, at least 12 large companies, from Verizon to General Motors, have said recent slips in mortality improvement have led them to reduce their estimates for how much they could owe retirees by upward of a combined $9.7 billion, according to a Bloomberg analysis of company filings. “Revised assumptions indicating a shortened longevity,” for instance, led Lockheed Martin to adjust its estimated retirement obligations downward by a total of about $1.6 billion for 2015 and 2016, it said in its most recent annual report.
The fact that people are dying slightly younger won’t cure corporate America’s pension woes—but the fact that companies are taking it into account shows just how serious the shift in America’s mortality trends is.
Changes to life expectancy in the U.K. could cut 310 billion pounds from British private-sector pension obligations, or 15 percent of the total liability, PwC estimated in May, although other actuaries have called that figure “relatively extreme.”
The question actuaries can’t yet answer is whether the slowdown is a short-term blip or a more permanent shift. If mortality improved by 1 percent a year for most of the past 70 years, might the U.S. revert to that soon? Or, Keener asks, “is this really a new reality that we’re living in?”
Like much of his generation, Yanoviak is desperate to get a piece of an increasingly scarce commodity: prime American real estate. Millennials are finding themselves out in the cold because building has slowed, and longer-living baby boomers are staying put, setting up a simmering conflict between the two biggest generations in U.S. history.
People 55 and older own 53 percent of U.S. owner-occupied houses, the biggest share since the government started collecting data in 1900, according to real estate website Trulia. That’s up from 43 percent a decade ago. Those ages 18 to 34 possess just 11 percent. When they were that age, baby boomers had homes at almost twice that level.