Is Silicon Valley Over? Not by a Long Shot

Having lived in Silicon Valley all my life, I’ve seen it transform from an agrarian area dotted by fruit orchards into a technology powerhouse.

When I started my career as a tech industry analyst in 1981, Silicon Valley encompassed San Jose up the peninsula to Palo Alto and Menlo Park; an area known as the Santa Clara Valley. Now it represents cities as far north as San Francisco and as far east as Oakland and Fremont. All told, Silicon Valley hosts over 5,000 tech-related companies, and income from tech companies in San Jose, Santa Clara, and Sunnyvale alone account for $235 billion, according to the American Enterprise Institute.

Until 1995, when the internet kicked off the tech revolution, most people were unfamiliar with Silicon Valley. Until about 2010, when I traveled to much of the Midwest and East Coast, people had no idea where this “Silicon Valley” was in California.

Fast forward to today and Silicon Valley is a household name. For the most part, it’s equated with technology that transforms people’s lives for the better, like PCs, the web, smartphones, and tablets. But thanks to massive data breaches, most recently with Facebook and Cambridge Analytica, Silicon Valley’s image is tarnished in ways none of us could have imagined even three years ago. Not to mention sexual harassment issues, a lack of diversity, and pay inequality.

For decades, Silicon Valley execs could fly under the radar of most regulatory bodies. But it is looking more likely now that companies like Facebook, Twitter, Google, and others that deal directly with people’s personal data are about to face serious regulation. The region is rattled.

I’m frequently asked if Silicon Valley can survive the scrutiny and remain the world’s center for tech innovation? As one who has seen Silicon Valley’s many ups and downs over the last 35 years or so, I have no doubt that it will weather even this storm. There’s a lot of brain power in the region, and it’s still at the center of much of the major advancements, from semiconductors to PCs, and is helping drive 5G. Automakers, meanwhile, have beaten a path to the Valley to prep for the autonomous vehicle revolution.

Despite the setbacks, Silicon Valley is doing some of its best work in a decade in areas like AI, machine learning, and robotics. And augmented and virtual reality is at the heart of many of the big Valley-based tech companies’ research today.

Is there anything that should have Silicon Valley worried? China’s tech advancements are clearly a threat, and the cost of living in Silicon Valley makes it difficult for those not earning six figures to live here. But while I think Silicon Valley’s current struggles are far from over, I expect it to continue to be at the center tech advancement that will power every aspect of our future.

Tesla’s Tussle With Feds Over Model X Accident Is a Fool’s Errand

Silicon Valley trailblazers have reshaped our lives with their innovations. But the same irrepressible attitude and disregard for traditional rules that drive idiosyncratic individuals and iconic company founders like Facebook’s Mark Zuckerberg, Uber’s Travis Kalanick, Tesla’s Elon Musk, and Apple’s Steve Jobs also often leads to clashes with lawmakers.

Zuckerberg’s testimony last week on Capitol Hill, where he was grilled over user privacy, is evidence of the “beg for forgiveness, not permission” approach. But at least Zuck issued a mea culpa before Congress and took accountability for the Cambridge Analytica fiasco.

Contrast that with Tesla’s tit for tat with the National Transportation Safety Board (NTSB). The agency is investigating a fatal Model X crash in California involving Tesla’s semi-autonomous Autopilot feature, with which it has played fast and loose compared to more conservative automakers. The Model X accident was within days of another death involving an Uber self-driving vehicle.

It’s just the latest example of Silicon Valley’s disdain for following the rules of the road. When Google first revealed in late 2010 that its self-driving cars had logged more than 100,000 miles in California, there were no laws against testing autonomous cars on public roads in the company’s home state. But Google was aware it was pushing the legal limits.

“Keeping the project quiet enabled Google to test under the radar of public opinion and lawmakers,” recalls Seval Oz, who at the time headed business development for the company’s self-driving car project. “We just didn’t want the program to slow down for any reason.”

Silicon Valley has since become the epicenter of self-driving technology, and the area’s “move fast and break things” ethos has extended to autonomous vehicle testing. A large part of Uber’s strategy, first with its ride-sharing business and later with its autonomous technology, involved skirting rules.

War of Words

The war of words between Tesla and the NTSB started after a March 23 crash that killed Walter Huang, who struck the center divider on a Northern California highway while behind the wheel of a Model X.

A week after the accident, Tesla revealed that the vehicle’s Autopilot semi-autonomous feature was turned on, that Huang didn’t have his hands on the steering wheel for six seconds prior to the crash, and he failed to take evasive action.

The release of this information—and blaming the driver before the investigation was complete, which can take months—violates an agreement to keep accident data confidential until the NTSB is ready to release it. On Wednesday, Tesla withdrew from the investigation “because it requires that we not release information about Autopilot to the public, a requirement which we believe fundamentally affects public safety negatively.”

But following what Bloomberg described as a tense phone call late Wednesday between NTSB Chairman Robert Sumwalt and Elon Musk, the agency took the unusual step of removing Tesla from the investigation.

In a statement on Thursday, the agency said that “releases of incomplete information often lead to speculation and incorrect assumptions about the probable cause of a crash.” Sumwalt added that “it is unfortunate that Tesla, by its actions, did not abide by the party agreement.”

Later the same day, Tesla insisted it severed ties on the investigation with the NTSB, not the other way around. And took a jab at the agency: “It’s been clear in our conversations with the NTSB that they’re more concerned with press headlines than actually promoting safety,” Tesla said in a statement.

As of press time, the tiff between Tesla and NTSB is still playing out. Tesla will reportedly still provide data to the agency, which investigates accidents and makes safety recommendations but does not set policy, but will not be a formal party to the probe.

Coming on the heels of the Uber autonomous car fatality, the Tesla accident—and the company’s combative approach to the investigation—likely won’t inspire cooperation or help instill confidence in public officials who are growing more circumspect about self-driving technology. It also smacks of Silicon arrogance on Tesla’s part and could not only cost progress on self-driving policy but also lives.

New Trade War Targets China, ZTE But US Firms Caught in Crossfire

The message coming from the US and UK governments and trade organizations today? Fear China.

They’re trying to drum up a 5G trade war, but US companies are getting hit by friendly fire.

First, the US Commerce Department today banned US companies from selling components to ZTE for seven years, according to Phone Scoop, though it didn’t ban ZTE from selling phones in the US.

Meanwhile, in the UK, the government told telecom companies not to buy ZTE infrastructure. Huawei infrastructure is fine across the pond, which is funny because the US government swore off Huawei infrastructure.

But three of ZTE’s US-based optical component suppliers are already getting battered in the stock market. ZTE phones also use processors and modems from San Diego-based Qualcomm, apps from Mountain View-based Google, and Gorilla Glass from New York-based Corning.

At least on the surface, our government is angry because ZTE didn’t sufficiently punish employees who sold gadgets from China to Iran, because those gadgets involved some US-made components.

Zoom out and you see the real reason why both of these things are happening now. It’s similar to why our government prevented Broadcom from dismantling Qualcomm. The UK government’s rationale isn’t about any specific threat Huawei or ZTE poses right now: it’s about not letting “China,” or anything Chinese, have too large a market share or too much influence in the tech industry.

Ironically for a company that government action just saved, Qualcomm, which now earns more than half of its revenues in China, is going to suffer from the sanctions against ZTE. Unlike Huawei, ZTE doesn’t make its own processors and modems, so it relies heavily on Qualcomm for chipsets. So ZTE is likely to shift more of its business to Taiwan-based Mediatek, already its No. 2 supplier, dealing a blow to Qualcomm.

China could also retaliate further against Qualcomm; its takeover of Dutch semiconductor firm NXP is being held up by Chinese regulators, which an analyst likened to a “hostage” situation in an interview with Reuters.

Google could also get hit. Various commentators are pointing out that the ban may prevent ZTE from using Google’s apps, leading the smartphone maker to turn to other alternatives from China or Europe.

But that’s what happens in a trade war. As borders close, you start taking damage from your own side’s actions. Qualcomm seems caught off guard by all of this; it declined to comment, while ZTE has not yet responded to a request for comment.

What’s Good for the Goose …

I don’t like this trade war, but it’s not like we aren’t doing anything the Chinese government hasn’t been doing for years. For a decade now, China’s censors have been slowing or blocking US-based internet companies so as to nurture and protect local Chinese competitors.

China’s Tencent and Sina Weibo benefited hugely from their government blocking Facebook and Twitter, and slowing a lot of Google services to a halt. Facebook’s WhatsApp is banned outright. Local app stores have flourished because Google Play was rendered unreliable.

The Chinese government has strict controls on which Hollywood movies can play in its theaters. It cracks down whenever users on a social network look like they might be forming groups that are too vibrant and aren’t controlled by the government. It’s far from a free-trade regime; it’s far from a free-anything regime.

Until now, the struggle between Chinese and Western technology companies for market share has also been a struggle of philosophies. China’s software, content, media, and social-networking giants have had real trouble extending themselves out of China because they’re so tightly adapted to the peculiar restrictions and culture of their own market. Its industrial and hardware firms have done better globally.

Perhaps that trend informs some of the Trump administration’s policies; it’s been passionate about saying it will protect old industries like coal, oil, steel, and automobiles. The airy-fairy world of Google’s software dominance, created by open minds and free trade, may not strike as viscerally in the Oval Office as the sight of Huawei’s cell towers going up on poles throughout Africa.

Cold War Innovation

Maybe it takes a cold war to get a stuck government to move. After all, it took fear of the Russians to send us to the moon.

The CTIA, our national wireless trade organization, released a report today about the “race to 5G” that’s also full of China fearmongering—in this case, to spur our government to auction more spectrum off for 5G.

The report, by Analysys Mason and Recon Analytics, strokes legislators’ egos while admonishing them that if they don’t release more “mid-band” spectrum soon, China will “win” the “race to 5G.” Looking at Analysys Mason’s chart halfway through the report, it looks like the US, South Korea, and China are all about equally aggressive when it comes to innovating on 5G deployment. But our wireless industry wants more spectrum and the ability to overrule local restrictions on small cell siting. A cold war looks like a good way to push legislators to get those things.

For what it’s worth, the CTIA is getting its money’s worth from the report. I’m watching headlines roll in from Axios and CNET saying that “China is winning the 5G race”—China as a singular, threatening entity, not as a place where many different companies, run by many different people, compete with each other.

The report’s recommendations, broadly, are right. America can create more jobs, more growth and more innovation by flipping more spectrum from old, inefficent uses like UHF television and older forms of radar, into new 5G technologies. I’d add that we also need more unlicensed spectrum bands like the 2.4GHz and 5GHz Wi-Fi bands, because those create the kind of ferment of startup innovation in which the US specializes.

But driving us there through a cold-war fear that cuts off potential sales markets and damages the open-mindedness that has led to America’s software leadership is one step forward, one step back.

Calm Down About Facebook

Facebook has been in the news alot over the last few weeks. All because a researcher used the Facebook API to scrape data from Facebook users and their friends and then sold that info to an analytics firm that worked with political campaigns.

Somehow this has morphed in a privacy debate because developers with access to the Facebook API cannot take what they want from Facebook and sell it to anyone they want.

So, as I watch Congressional hearings, I have to laugh. This is not about privacy; it’s about the money.

With 2 billion users who gladly tell Facebook their favorite TV shows, movies, clothing brands, how they spend their time, who their friends are, who they voted for, what political movements they support, the color of their eyes, whether they wear glasses and on and on, Facebook has every bit of information needed to figure out what you might want to buy or do.

The fact that Facebook has not fully exploited this (to my knowledge) is somewhat mysterious.

It’s uniquely qualified to, for example, identify the 100 people in Northern Arkansas who want a pack of oversized silver balloons. With this type of information arsenal, Facebook should theoretically be able to obliterate the TV networks and the major newspapers and steal their advertising dollars.

There are ways it can go after Google and Bing, too. Growth for Facebook does not mean getting more users—it has enough. Growth mean finding new ways to target advertising and develop paid services.

So…why all the complaining about privacy? This notion is a mainstream media creation developed as a means to kill the monster. Facebook executives are then in a bind and have to apologize. Otherwise they’d seem uncaring and cavalier about privacy. We have Mark Zuckerberg and COO Sheryl Sandberg saying they are sorry and it won’t happen again, unable to explain why it happened in the first place.

Now Congress is raking Facebook over the coals. Zuckerberg, the visionary of the whole scheme, hemmed and hawed and apologize as best he could on Tuesday before the Senate. He’ll appear before the House today for another opportunity to say something stupid that will dominate the news for a couple of weeks.

There is absolutely zero reason Facebook should be saying anything to Congress. I’ve never heard a good reason to show up. I’d love to hear testimony like this:

REPRESENTATIVE: So Mr. Zuckerberg, do you have any way that people can protect their privacy when using Facebook?

ZUCKERBERG: Protect it? They are the ones putting private information on the site. They are voluntarily doing it. We do not force them. We do not trick them.

REPRESENTATIVE: Yes, but do they know this information can be captured and exploited by a third party?

ZUCKERBERG: Hey, do you think we want a third party taking the data of all these people and exploiting it so they can make money without cutting us in? Hell, no. We already put a stop to that. We established this system for our benefit not theirs.

REPRESENTATIVE: So then it is okay for you to violate users’ privacy?

ZUCKERBERG: Yes, it is. They said so when they signed up. They post the fact that they are five foot two and we tell them that they might want to shop at Macy’s in the petite section. So what? This is why they use the site in the first place – to connect with friends and find useful information. It’s not as if we are planting bugs in their homes, like Amazon.

REPRESENTATIVE: So why do you think we are having this hearing?

ZUCKERBERG: Because the Washington Post and other skittish media companies kept pushing you to. So you might greenlight some stupid legislation to prevent our users from using the site the way they want. The obvious goal is to keep us from making any money. To make yourselves seem like you are helping the consumer. It’s all a load of bull.

This would be an honest exchange that can only be imagined since it will never occur. Big media is indeed behind a lot of the complaining and the reasons are clear, at least to me. Facebook is a threat to their bottom lines.

Alexa, Teach Me How to Talk to You

When Apple introduced its first personal digital assistant (PDA), the Newton, in 1992, it was clear from the start that it was not long for this world.

As a concept, the Newton was a head-turner, but its design and functions were weak, to say the least.

Its biggest problem was the deeply flawed handwriting-recognition technology. The mobile processors available at the time were incapable of handling this task with any level of accuracy or precision, while the software was poorly executed.

I remember flying to Chicago for the launch of the Newton at the request of then-Apple CEO John Sculley, who drove this project from the beginning. But during the onstage demo, the handwriting recognition failed repeatedly. We were told it was an early version of the software, but I had a strong sense that Apple was overpromising.

During the early years of the Newton, Palm Computing founder Jeff Hawkins began working on his own version of a PDA. While that device was still in development, Hawkins invited me to his office to see a mockup, which was a wooden block sculpted to look like what would eventually became the PalmPilot.

I asked Hawkins why he thought the Newton had failed. He pointed to his time at Grid Systems, which introduced the first real pen computing laptop in 1989 called the GridPad. It too had a low-level CPU and was not able to handle true character recognition. But it taught Hawkins that when it came to pen input and character recognition, one needed to follow an exact formula and write the characters as stated in the manual.

That is why the PalmPilot included the Graffiti writing system, which taught a user how to write a number, letter of the alphabet or specific characters (like #, $) in ways the PalmPilot could understand. I was one of the first to test a PalmPilot and found Graffiti to be very intuitive. One could call this a form of reverse programming since the machine was teaching me how to use it in the language it understood.

Fast forward to today, and I believe we have a similar thing going on with digital assistants.

One big difference this time around is that the processing power, along with AI and machine learning, makes these digital assistants much smarter, but not always accurate.

In what I think of as a Graffiti-like move, Amazon sends me weekly emails that include over a dozen new questions Alexa can answer. This too is sort of a reverse programming, as it teaches me to ask Alexa the proper questions.

From a recent email, here are some of the new things Alexa can respond to:

• “Alexa, what’s on your mind?”
• “Alexa, what’s another word for ‘happy?'”
• “Alexa, what can I make with chicken and spinach?”
• “Alexa, call Mom.”
• “Alexa, test my spelling skills.”
• “Alexa, wake me up in the morning.”
• “Alexa, how long is the movie Black Panther?”
• “Alexa, speak in iambic pentameter.”
• “Alexa, how many days until Memorial Day?”

These weekly prompts allow me and other Echo owners to understand the proper way to ask Alexa a question, and builds up our confidence in interacting with the platform.

I have no doubt that as faster processors, machine learning, and AI are applied to digital assistants they will get smarter. But I suspect that more and more companies that create digital assistants will also start using Amazon’s model of teaching people how to ask questions that are more in line with how their digital assistants want a query to be stated.

Electric Vehicles Are Coming for Your Snacks

Most major automakers have committed to converting their entire future fleets to some form of electric power, and if you look at autonomous vehicle developers like Waymo, it’s clear that electric vehicles (EVs) will go hand in hand with self-driving technology.

Unlike traditional internal combustion engines, EVs don’t require oil changes, have fewer moving parts to wear out, and rarely break down, which should worry the more than 160,000 independent auto repair shops in the US. In an EV-dominated future, gas stations will eventually be hit hard.

But this is not just a concern for mechanics; fewer gas station visits mean a big drop in beverages sales, according to a Morgan Stanley report released last week.

Even if you pay at the pump with a credit or debit card, chances are some of your fuel stops include a trip inside a gas station or convenience store to buy a drink or snack. In fact, Jeff Lenard of the National Association of Convenience Stores told The Washington Post that fuel sales comprise just 40 percent of gas station profits. The rest of revenue is rung up inside the store, and beverages are the bulk of sales.

For example, 63 percent of US sales for Monster Beverages comes from gas stations and convenience stores, the Morgan Stanley report revealed. Other convenience store purchases, such as alcoholic beverages and tobacco products, may not see the same declines since when people fuel up they tend to buy beverages impulsively and consume them right away.

“Beverages drive sales, and beverages drive profits at convenience stores,” Lenard added. “So any competition that could reduce those sales and those profits is a concern.”

The Morgan Stanley report acknowledged that EVs currently comprise only a small fraction of the total vehicles currently on US roads. From December 2010 to February 2018 the combined market share of all EVs in proportion to traditional internal combustion engine new vehicle sales was just 0.7 percent, according to InsideEVs. Convenience store industry analysts believe that any significant damage to their bottom line—and beverage sales—due to electric cars is still decades away.

But given automakers’ commitment to EVs, rapid market growth is expected. So convenience stores might want to consider catering to EV owners, much like the Mid-Atlantic gas station chain Sheetz (where customers can order food items such as drinks and sandwiches via touch screen while filling up) has partnered with Tesla to install Supercharger stations.

And while the Journal estimates that 80 percent of EV owners charge at home and a full battery can get them where they want to go and back in a day, road-tripping EV owners may spend more time—and more money—at convenience stores like Sheetz since it takes much longer to top off at a public charging station than it does to fill a gas tank.

“I think [convenience] stores will do what they always do,” Lenard added. “They’ll find a better way to compete.” And there will always be a convenient place to stop in for a beverage or snack even if you just need fuel for your body.

4 Reasons Not to Fear Deep Learning (Yet)

In 2012, a group of scientists from the University of Toronto made an image-classification breakthrough.

At ImageNet, an annual artificial intelligence (AI) competition in which contestants vie to create the most accurate image-classification algorithm, the Toronto team debuted AlexNet, “which beat the field by a whopping 10.8 percentage point margin… 41 percent better than the next best,” according to Quartz.

Deep learning, the method used by the team, was a radical improvement over previous approaches to AI and ushered in a new era of innovation. It has since found its way into education, healthcare, cybersecurity, board games, and translation, and has picked up billions of dollars in Silicon Valley investments.

Many have praised deep learning and its superset, machine learning, as the general-purpose technology of our era and more profound than electricity and fire. Others, though, warn that deep learning will eventually best humans at every task and become the ultimate job killer. And the explosion of applications and services powered by deep learning has reignited fears of an AI apocalypse, in which super-intelligent computers conquer the planet and drive humans into slavery or extinction.

But despite the hype, deep learning has some flaws that may prevent it from realizing some of its promise—both positive and negative.

Deep Learning Relies Too Much on Data

Deep learning and deep neural networks, which comprise its underlying structure, are often compared to the human brain. But our minds can learn concepts and make decisions with very little data; deep learning requires tons of samples to perform the simplest task.

At its core, deep learning is a complex technique that maps inputs to outputs by finding common patterns in labeled data and using the knowledge to categorize other data samples. For instance, give a deep-learning application enough pictures of cats, and it will be able to detect whether a photo contains a cat. Likewise, when a deep-learning algorithm ingests enough sound samples of different words and phrases, it can recognize and transcribe speech.

But this approach is effective only when you have a lot of quality data to feed your algorithms. Otherwise, deep-learning algorithms can make wild mistakes (like mistaking a rifle for a helicopter). When their data is not inclusive and diverse, deep-learning algorithms have even displayed racist and sexist behavior.

Reliance on data also causes a centralization problem. Because they have access to vast amounts of data, companies such as Google and Amazon are in a better position to develop highly efficient deep-learning applications than startups with fewer resources. The centralization of AI in a few companies could hamper innovation and give those companies too much sway over their users.

Deep Learning Isn’t Flexible

Humans can learn abstract concepts and apply them to a variety of situations. We do this all the time. For instance, when you’re playing a computer game such as Mario Bros. for the first time, you can immediately use real-world knowledge—such as the need to jump over pits or dodge fiery balls. You can subsequently apply your knowledge of the game to other versions of Mario, like Super Mario Odyssey, or other games with similar mechanics, such as Donkey Kong Country and Crash Bandicoot.

AI applications, however, must learn everything from scratch. A look at how a deep-learning algorithm learns to play Mario shows how different an AI’s learning process is from that of humans. It essentially starts knowing nothing about its environment and gradually learns to interact with the different elements. But the knowledge it obtains from playing Mario serves only the narrow domain of that single game and isn’t transferable to other games, even other Mario games.

This lack of conceptual and abstract understanding keeps deep-learning applications focused on limited tasks and prevents the development of general artificial intelligence, the kind of AI that can make intellectual decisions like humans do. That is not necessarily a weakness; some experts argue that creating general AI is a pointless goal. But it certainly is a limitation when compared with the human brain.

Deep Learning Is Opaque

Unlike traditional software, for which programmers define the rules, deep-learning applications create their own rules by processing and analyzing test data. Consequently, no one really knows how they reach conclusions and decisions. Even the developers of deep-learning algorithms often find themselves perplexed by the results of their creations.

This lack of transparency could be a major hurdle for AI and deep learning, as the technology tries to find its place in sensitive domains such as patient treatment, law enforcement, and self-driving cars. Deep-learning algorithms might be less prone to making errors than humans, but when they do make mistakes, the reasons behind those mistakes should be explainable. If we can’t understand how our AI applications work, we won’t be able to trust them with critical tasks.

Deep Learning Could Get Overhyped

Deep learning has already proven its worth in many fields and will continue to transform the way we do things. Despite its flaws and limitations, deep learning hasn’t failed us. But we have to adjust our expectations.

As AI scholar Gary Marcus warns, overhyping the technology might lead to another “AI winter“—a period when overly high expectations and underperformance leads to general disappointment and lack of interest.

Marcus suggests that deep learning is not “a universal solvent but one tool among many,” which means that while we continue to explore the possibilities that deep learning provides, we should also look at other, fundamentally different approaches to creating AI applications.

Even Professor Geoffrey Hinton, who pioneered the work that led to the deep-learning revolution, believes that entirely new methods will probably have to be invented. “The future depends on some graduate student who is deeply suspicious of everything I have said,” he told Axios.

Tech CEOs Need Keep the April Fools’ Jokes to Themselves

Unlike the amusing gags of the past, this year’s April Fools’ Day was an incredible dud. Elon Musk, for example, “joked” that Tesla was broke.

The gag wasn’t too big of a stretch, though, and Tesla stock took a dive on Monday. Oops. (No worries. It rebounded on Tuesday.)

Musk missed the point here; it was along the lines of telling your spouse that you have cancer, then saying “April Fools!” These jokes should be simple, obvious when deconstructed, and have hints within that they are, indeed, jokes. Above all the joke is not on you, but on someone else.

I imagine there were more than a few associates who knew this was a bad idea, especially given speculation about Tesla’s future and continuing problems with Autopilot.

It’s likely that Musk thinks that as a CEO of a public company he can tweet whenever he wants to. After all, Trump does it and he’s the president of the country. So what possibly could go wrong?

Let’s assume that Musk is monitored by corporate media folks. They have to worry about SEC rules and public perceptions. Did they tell Musk the tweet was not acceptable? Since Musk is perceived as a business genius, I can see him laughing off the concerns and convincing them that it was a classic April Fools’ joke and a great promotion for the company because it ridicules the Tesla skeptics.

Oh. Okay, boss.

Sadly, the internet has made April Fools’ gags useless and outdated. Every day is April Fools on the web. Hoaxes abound.

Another problem I have is institutionalizing jokes. A kid in the sixth grade teasing a classmate is one thing, but a billion-dollar corporation making fake announcements is a new level of tomfoolery.

Since April 1 is not recognized by any government authority, I believe a corporation should be fined by regulatory agencies for false statements. If the stock price dips and you are day trading, you may have been defrauded.

Bring action against one of these corporations, and they will all suddenly realize that they are not comedians. Start with Tesla.

Why Waymo and Jaguar Are a Perfect Self-Driving Car Match

As Uber pulls back on public autonomous car testing following a recent fatal accident in one of its self-driving vehicles, Waymo is moving full steam ahead with on-the-road assessments of the technology.

On the eve of the New York Auto Show, for example, Waymo announced that it would buy, outfit, and deploy 20,000 Jaguar I-Pace fully electric SUVs for autonomous ride-sharing purposes by the end of 2018.

“Not 2019, not 2020, but by the end of this year,” Waymo CEO John Krafcik announced at a press conference in New York. Krafcik also said Waymo plans to eventually provide 1 million robo-taxi rides per day.

The self-driving Jaguar I-Paces will join the fleet of fully autonomous Chrysler Pacifica minivans Waymo has been testing in the Phoenix area with passengers onboard since last April, as part of its “early rider program.” While the program started out with safety drivers behind the wheel of the minivans, Waymo shifted in Novebmer to not having humans at the helm.

“When people use Waymo’s [ride-sharing] service, they’ll have access to a broad selection of vehicles tailored for their trip,” Krafcik added last week. “They can choose a minivan if they’re traveling to soccer practice with their family. If two people are running a quick errand, why not take a self-driving Jaguar?”

I-Pace a Perfect Match for Waymo

Waymo probably had its pick of automakers to work with, and any car company would, of course, welcome selling 20,000 vehicles in one fell swoop. But the partnership came about because Waymo was looking for a specific type of vehicle and Jaguar was able to deliver it before competitors.

“The way this partnership came about is we contacted Waymo to learn about their technology,” Jaguar Land Rover (JLR) North America president and CEO Joe Eberhardt told me in an interview at the New York Auto Show last week. “They contacted us almost in parallel because they were looking for a certain type of car for their fleet and had specifications that we just happen to meet almost perfectly with the I-Pace.”

“We surveyed the world and found that the I-Pace was the best next vehicle for Waymo,” Krafcik said. “Its size makes it perfect for city driving. Its modern electrical architecture means it’s well suited to our technologies. And it’s big, fast-charging battery means it can drive all day, which is perfect for our self-driving service.”

“We fulfilled all of that and we were ready to go to market,” Eberhardt added. “If you look at battery electric vehicles, the I-Pace is the very first SUV from an established player. Yes, Tesla was there before us, but amongst the others we’re the first. And for Waymo it was really a perfect match.”

While Waymo gets a luxury battery electric vehicle with the specs and range it needs, JLR gets to partner with one of the premier self-driving players. “With this partnership, Waymo will help us gain access to technology and learn from it and allow us to get to the forefront,” Eberhardt said.

This is significant since, as a niche automaker compared to larger luxury competitors, the partnership with Waymo gives JLR an edge on self-driving innovation, without the massive RD expenditure others in the space are making. “Now we’re right there with the best,” Eberhardt said.

JLR will also continue its own self-driving RD and testing in the UK “with all the universities and scientific institutions and research centers we’re working with,” Eberhardt added. “But this will also be influenced and informed by whatever we learn from the partnership and vice-versa. And I think it can only get stronger as a result.”

JLR will also get plenty of exposure for the new I-Pace, which goes on sale in the US later this year. Eberhardt pointed out that the 20,000 vehicles will be purchased over the six years of the partnership but added that “the sales will probably happen towards the front end” of the period.

“Just to get the exposure for the brand and the product is phenomenal,” Eberhardt said. “That was a big aspect for us to do the deal. That’s marketing you can’t buy.”

And I’m guessing that, given the option, more people will probably want to ride in a self-driving Jaguar I-Pace rather than a Chrysler Pacifica. “The vehicle itself is graceful in the long tradition of Jaguar,” Waymo’s Krafcik said. “Combined with our self-driving technology, it will provide a safe, delightful experience for our passengers.”

Apple Needs to Get Serious in the Battle Against Netflix, Amazon

One of the most important growth businesses for Apple has been its services division. It brings in about $7.5 billion a quarter now, and it could be a Fortune 100 business if it was ever spun off on its own.

In thinking about Apple’s services business over the last few weeks, two conversations I had with Sony co-founder Akio Morita and Steve Jobs many years ago came to mind.

Not long after Sony purchased a movie studio, I had the privilege of interviewing Mr. Morita on one of my trips to Japan. At the time, Sony was known primarily as a hardware company that made TVs, portable music players, and stereo equipment. So why a movie studio? Mr. Morita told me that he saw movies as just “digital bits,” which represented important content that could be shown or used on his devices.

Keep in mind this was over a decade before the idea of content tied to devices was really in focus and showed the incredible foresight Mr. Morita had as Sony’s CEO. Unfortunately, once he retired, Sony lost its portable music lead to Apple and the iPod, not to mention laptops, smartphones, and tablets. Today, Sony faces competition from smart TVs and PC gaming and challenges due to constant restructuring, cost cutting, and a senior leadership that does not seem to see future consumer trends.

Steve Jobs was a real fan of Mr. Morita and had a similar view of digital content, especially music. When I spoke with Jobs, he made it very clear that Apple is a software-first company. Its goal is to use software, hardware, and services to tie people to its overall ecosystem.

So it’s been surprising how far behind Apple is when it comes to investing in content beyond music. The chart below shows Apple investing about $1 billion on non-sports video programming in 2017 compared to Netflix, which spent $6.3 billion, and Amazon at $4.5 billion. This year, Netflix could spend up to $8 billion.

That said, perhaps Apple has its eye on some bigger prize in the content space. Yes, it could create more original content and go after existing shows, but it might make sense for Apple to take a page from Sony’s playbook and buy a major movie studio, or at the very least, acquire some dedicated production companies that already have proven content and the ability to create more shows quickly.

As Apple SVP Eddy Cue said at SXSW recently, “we know how to create apps, we know how to do distribution, we know how to market. But we don’t really know how to create shows.”

While that may be true, it could it could use its hefty bank account to acquire that kind of knowledge and capability. Buying a movie studio may not make sense, but purchasing a proven TV production company could help it compete with Netflix, Amazon, and beyond.