PCs, proteins, pitching, and profits

To Dad… folks told me that they liked the roundup format. As a panderer, I'm going to try to make this the Sunday norm. Per the headline, today’s roundup is about PCs, proteins, pitching, and profits.

You weren’t following it, because why would you? But, if you’re curious, the Rumble in the Judiciary is over. The DOJ won. Google lost. Congrats, the price of your next Asus just went up.

Just after Google lost, Lee-Anne Mulholland — Google’s VP of regulatory affairs, wrote this, “We’ve invested billions of dollars in Chrome and Android. Breaking them off would change their business models, raise the cost of devices.”

Are you having flashbacks of the Abe Simpson shaking-fist meme? Yeah, me too.

As someone who’s happy to not use Google, I searched Amazon :-).

A brand-spanking new Asus Chromebook is $68.99. The cheapest new Asus Windows Laptop is $224.99. And, you’d have to pay another hundred bucks for Office.

I posted a version of this to LinkedIn. Where, minutes later, a person who hates Google far more than I do replied with full-on snark, “Maybe that’s because Microsoft doesn’t offset computers by showing people ads.”

That got me thinking. Am I happier to spend less than $70 on a Chromebook because Google subsidizes it because they show me ads OR am I more happy spending three times more for Microsoft’s machine?

Before I answered myself, I noticed that Microsoft made $49B in ad revenue in the last twelve months. And, unlike Google, who I don’t like, MS didn’t subsidize my Windows PC. For that matter, Apple didn’t offset my iPhone and they made $10B on ads last year.

In their own monopolistic way, Google behaves like an old school filler-up-station. Say, Exxon Mobil, a child of another broken monopolist home (Standard Oil). You fill up there and pay with their card, they give you a few cents back per gallon. Or, maybe, if you’re lucky, a Flintstones Pebbles drinking glass. For all the hate dumped on Google, at least they have a loyalty program.

Do you prefer to pay for your PC with cash or with your ad attention? Yeah, me too.

Trust is at an all-time low and dropping faster than a bowling ball in vacuum because the people we are told to believe without question can (and, sadly far too often do) lie to us.

“Breathtaking.” That’s what neuroscientist Christian Haass said when he heard about Dr. Eliezer Masliah’s peer-reviewed papers on Alzheimer’s and Parkinson’s research. “People will, of course, be shocked, as I was … I was falling from a chair, basically.”

Unlike Leonard McCoy, I’m an ad guy, not a doctor. I have this friend. Augustine. He’s a doctor. Of ad fraud. He made some software that tests how many real people visit a website. But he won’t run it and give you a Good Housekeeping sticker if you pass. Because, he says, once you have the sticker you can lie with impunity. Money would be lost. Time would be wasted. Blather. Doctors, pfft.

Dr. Masliah has bona fides up the freaking wazoo. He’s been the senior leader of the National Institute of Aging since 2016. He has published 777 peer reviewed papers.

Lies.  

Science, a leading peer review journal found “scores” of papers are “riddled” with falsified images of proteins and brain tissue. Some of them, the investigation shows, have been reused across papers published years apart to document entirely different experiments. The NIH dumped Masliah.

For thirty to forty years, despite extensive research, Alzheimer’s Disease (AD) has remained refractory -- that’s doc-speak for hard to treat. An anonymous Professor of Biochemistry and Associate Dean says that, “The central dogma of Alzheimer’s Disease, ACH, was constructed more than a hundred years ago. It has been an intuitive cul de sac that has yielded nothing to slow or stop the course of the disease.”

Decades of damage have been done that can’t be undone. You have to wonder how much time was lost. How much money was wasted. How many people’s lives have been impacted. And, this may not be an outlier.

At the end of the piece, scientists at Science, worried about how this apparent catastrophe could give, “Science a further black eye, just as the public’s confidence in science is sinking to new depths.” 

Everyone seems to be talking about margins of error these days. As usual, the smartest takes come from the mouths of babes. In this case, your genius grandson, Ethan.

This pitch is clearly outside the strike zone. The ump called it a strike. OK, “human error.” I get that a ball going ninety plus miles per hour and breaking several feet can look like a ball when it’s actually a strike. I get that a superimposed two-dimensional box is a poor stand-in for three-dimensional life. But come on. This seems to happen a lot. And, a lot of the time, the bad calls go against your team. The team you cheer for or bet on.

Ethan found this site that calls balls and strikes on the people who call balls and strikes. It adjudicates the adjudicators. It umps the umps.

Umps were under 90% right about 5% of the time. Ok. Sure. Some wrong calls. No one is perfect. Plus, you’d think things would even out in the wash. The more wrong calls umps make the more even the wrongsidedness would be. Let’s ignore the video tape and go to the data. Seven times this year, the Red Sox played the White Sox. At worst, you might lose a sock in the dryer. In all seven games, the umps got more than 90% of the pitches right. Even then, in three of the seven games, the umps few bad calls gave one team at least half an extra run.

The few, most talented people who adjudicate games got so much stuff wrong that they changed the outcome of 9% of MLB games this year.

This is outside margin of error. Let’s see if we get things more right the stakes are higher. The playoffs.

The crews that call playoffs games get more balls and strikes right than their more massive regular-season brethren. They still managed to change the winner of two out of 27 playoff games. If you’d like to know which games, drop me a note in the comment section.

“Outside the margin of error” is a phrase we read or hear a lot these days. A lot of the time, it has a lot more to do with things more important than baseball scores.

In 1980 I was a child, I talked like a child, I wondered how GM could sell lots of cars and lose lots of money. As a man I'm gob smacked how big companies lose big money. Corinthian MBAs 13:11.

Despite the godawful body of the “It works” Chevy Citation, the crushed burgundy velour that a 2000-era mall-walker wouldn’t don as a track suit that overcovered the optional front bench seats of the Olds 88 like the excess skin on an aging shar-pei, and John DeLorean’s Edsel-level bad Chevy Vega, GM sold $58B worth of cars in 1980. In this final year as CEO, Thomas Aquinas Murphy yep – his real name – said, “General Motors is not in the business of making cars. It is in the business of making money.” Um. Then-newbie CEO Roger Smith audaciously blamed the$763M loss on shifting consumer demand and inflation. The word you’re looking for is chutzpah. With extra spittle. Smith was GM’s first MBA-trained CEO. Yep, the truck and bus guy.

We’ve come a long way.
Executives don’t need to blame things when they lose gobs of money.

Check it. Sam Altman runs OpenAI. One hundred million people use the company’s ChatGPT product every week. This year, OpenAI will sell $5B of their smart service. They’ll lose $4B. No remorse. No excuses. No explanation. No chutzpah. Just loses. Ironically, he is converting the money-losing not-for-profit into a for-profit that will lose money for the foreseeable future.

But, OpenAI isn’t Amazon. Famously, Amazon lost gobs of money on every sale for its first couple of decades of operation. And, pretty much, they still do. But, they got so big, they sell the services that keep them running to other companies that lose money. Like investing $4B of in-kind services to OpenAI competitor, Anthropic. File this under “S” for “Stuff you can’t make up.”

This year, OpenAI will spend $3B to train its AI, $2B on computers to run its models, $400M to host the computers, and $500M on data. Smartly, they’ll spend $1B to research how to lower those costs. Somehow that research doesn’t include $700M on employee salaries or the $600M to pay executives and their presumably lavish perqs.

Maybe Sam doesn’t know he’ll run out of money before he changes humanity. Or, maybe, he’s banking his company’s future bank on Moore’s Law that compute costs will go down. And, that he won’t need to buy content. Maybe our demand for his AI services will shift to simpler fare so ChatGPT can serve up high-margin AI leftovers to inflate their profits. FWIW, Sam doesn’t have an MBA. Or, maybe, his child-like thinking is just what big companies need.

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