Ready for the Holidays, Facebookers and Googlers?
December 22, 2022
Despite an ongoing worker shortage, this economic downturn is proving to be bad for some folks’ job security. Business Insider: India reports, “Meta, Google Put Employees on ‘Notice Periods’ to Find New Role or Leave.” The write-up tells us:
“Facebook’s parent company Meta and Google are reducing staff to cut costs amid the economic downturn, apparently putting some of them on traditional 30 to 60 days ‘lists’ to find a new role within the company or leave. Meta plans to cut costs by at least 10 per cent in the coming months and has put out more and more workers whose jobs are being eliminated on its traditional ’30-day list,’ reports Wall Street Journal. On the other hand, Google’s parent Alphabet has reportedly deployed a similar approach, typically giving workers 60 days in which to apply for a new role if their jobs are set to be cut. ‘Facebook parent is looking to reduce costs by at least 10 per cent, people familiar with the plans said, while Google has required some employees to apply for new jobs,’ the report mentioned. …Last month, Google fired more than 50 workers at its incubator Area 120 and gave them extra 30 days to find another job at the company.”
A Google spokesperson assures us most of those folks were able to shift into another position. It is no coincidence the company has also suspended new hires while warning that any employee whose work is not up to snuff may find themselves out of a job. We also learn:
“In a company message viewed by Insider, Google Cloud sales leadership has threatened employees with an ‘overall examination of sales productivity and productivity in general’ and that if next quarter results ‘don’t look up, there will be blood on the streets’.”
Yikes. So much for Google being the most nurturing workplace around. As for the Meta-book, Zuckerberg has said the company plans to steadily reduce its payroll over the next year. But never fear. Whatever the fate of other workers, we suspect both Meta and Alphabet will protect their top executives’ lucrative positions. Which company is next? Salesforce perchance?
Cynthia Murrell, December 22, 2022
A Cheerful Look at Year End 2022 and Most of 2023
December 9, 2022
Year end and the New Year approach. It is time for reflection and prediction. I noted this Silicon Valley-esque real news write up titled “Tech Kept Talent Happy Doling Out Stock During the Boom. It’s Screwing Investors in the Bust.”
I circled this interesting chunk of prose:
In a period where investors are focused on profitability over growth, such retention and hiring efforts begin to look costly. Shareholders are still paying for the existing stock grants and now they’re going to pay for new grants…
Ah, ha. Presumably none of the high tech sector watchers noticed this?
Maybe in the midst of the 1998 downturn? What about 2008? And now stock based compensation is news.
What does this mean for 2022? Maybe a bit of gloom? And what about 2023? My thought is that MBAs and accountants will be beavering away in the grips of spreadsheet fever to make life better for themselves. I wonder if these folks keep their business school ethics lecture notes close at hand?
Stephen E Arnold, December 9, 2022
Alphabet, an Investor Is Grousing. Will That Person Be Assuaged?
December 7, 2022
Google’s parent company Alphabet is a multi-billion dollar corporation. Like any large corporation, it probably carries way too much fat, i.e. the books do not balance and it is because of the human ego. Google is a hot mess when it comes to human relations, but an activist investor believes Alphabet is a financial fiasco as well: “Investor Tells Google: Cut Costs Now And Stop Paying Staff So Much.”
TCI Fund Management is an activist investing firm and they suggested that Alphabet cut costs at the search engine giant. During the pandemic, Google had a hiring spree and TCI says the company now has too many employees and they are all too expensive. Google pays its employees 67% more than Microsoft people and 152% more than the top twenty US technology companies.
Alphabet’s profits are down to $13.91 billion compared to $18.936 billion in 2021. Alphabet is reviewing all its other companies. Some are doing well, while others like the Best Bets division are not. TCI Fund Management said Alphabet is not serving the shareholders:
“Alphabet’s ability to pursue M&A is limited due to ‘regulatory scrutiny’ so it should follow Apple’s capital allocation strategy and become “cash neutral over time through increased share repurchases.’ The group’s stock price is down 34 percent in the year to date, the share price is ‘cheap’ and buybacks could take advantage of this, TCI said.
It concluded: ‘In the era of slower revenue growth, aggressive cost management is essential. We look forward to your announcement in a clear action plan as a matter of urgency.’”
Google is not too big to fail, because tech geeks have huge egos and could run the company into the ground if they are not careful. Alphabet will probably ignore TCI’s suggestions, unless a former Google came up with them.
Whitney Grace, December 7, 2022
Cheap Training for Machine Learning Is Not Hyped Enough. Believe It or Not
December 6, 2022
I read an interesting article titled “Counting the Cost of Training Large Language Models.” The write up contains a statement which provides insight into the type of blind spots that plague whiz bang smart software companies. Here’s the statement which struck me as amusing and revelatory:
It has been becoming increasingly clear – anecdotally at least – just how expensive it is to train large language models and recommender systems…
Two points. Anyone who took the time to ask about the cost of retraining a Bayesian and neurolinguistic system from the late 1990s would have learned: [a] Smart software, even relatively simple implementations, require refined and curated training data before a system is deployed. This work is tedious and requires subject matter specialists. Then there is testing and fiddling knobs and dials before the software becomes operational. [b] The smart software requires retraining with updated data sets, calibration, and testing on a heartbeat. For some Autonomy plc type systems, the retraining could be necessary every 180 days or when “drift” became evident. Users complain, and that’s how one knows the system is lost in the tiny nooks and crannies of lots of infinitesimals adding up to a dust pile in a dark corner of a complex system.
After three decades of information available about the costs of human centric involvement in making smart software less stupid, one would think that the whiz kids would have done some homework. Oh, right. If the information is not in the first 15 items in a Google search result, there are no data. Very modern.
The write up identifies a number of companies with ways to chop down training costs. To be clear, the driving idea for Snorkel from the Stanford AI Lab is reducing the costs of building training sets. The goal is to be “close enough for horseshoes” or “good enough.” Cut the costs and deal with issues with some software wrappers. Package up the good enough training data and one has a way to corner the market for certain ML applications. But it’s not just the Google. Amazon AWS is in the hunt for this off-the-shelf approach to machine learning. I think of it as the 7-11 approach to getting a meal: Cheap, quick, and followed by a Big Gulp.
The write up has a number of charts. These are okay, but I am not sure about the provenance of the data presented. But that’s just my skepticism for content marketing type write ups. There are even “cost per one million parameters” data. Interesting but who compiled the data, what methods were used to generate the numbers, and who vetted the project itself? Annoying questions? Sure. Important? Not to true believers.
But I know the well educated, well informed funding sources and procurement officials will love this conclusion:
some people will rent to train, and then as they need to train more and also train larger models, the economics will compel them to buy.
Yep, but what about the issue of “close enough for horseshoes”? Yep, here’s another annoying question: Is this article the kick off for another hype campaign? My initial reaction is, “Yes.”
Stephen E Arnold, December 2022
Apple Factoid or Why a US Company Shows Affection for Pandas (Digital and Furry)
December 6, 2022
I spotted an article with a killer title: “Apple Reaches Highest Ever Monthly Market Share in China.” What’s the factoid? The write up provides what may be a semi credible factoid:
One in every four devices sold in China during October 2022 was an iPhone.
Here’s a passage from the write up I found intriguing:
Apple has been reaching new heights in terms of market share in China during the last two years. It reached a record monthly market share in November and December 2020, and in October, November and December 2021. Notably, 2020 was also the year when US sanctions were imposed on Huawei.
The article provides no information about why a US company is thriving in an environment of restrictions on certain Chinese-US interactions. Perhaps there is information to be found, but it is not in reports of what appear to be significant sales by a US firm in the Middle Kingdom.
Stephen E Arnold, December 6, 2022
FTX: What Does B Stand For?
December 2, 2022
I am not a krypto kiddie. After the mysterious Nakamoto white paper became available, I made an informed judgment: Bad actors will love this crypto thing. My hunch was correct. The meltdown of a crypto wizard and his merry band of tea totaling worker bees have demonstrated that cyber fraud can be entertaining.
I read “Does B Stand for Bankman-Fried or Bankruptcy?” The write up asks a simple question. I noted this passage from the “real” Silicon Valley write up:
SBF said FTX failed on risk management and he didn’t “knowingly co-mingle funds.”
There you go.
Now what does B stand for? Here are my suggestions:
bamboozle – to rip off, fool, or deceive
bane – a source or ruin, harm, or evil
baseborn – a nice way to question one’s family position in society
bebotherer – one who brings trouble
besotted – drunk and incoherent
bonkers — a few cans short of a six pack
brock—a nasty, little, furred creature
I am leaning toward bamboozle but I think brock has a certain charm. Perhaps a combo; to wit:
The brock bamboozled himself and others.
Close enough for horseshoes as the “we’re not talking” analytics folks like to say among friends at lunch.
Stephen E Arnold, December 2, 2022
Why Did Smart People Fall For The FTX Scam? Uh, Maybe Greed?
November 29, 2022
When we hear how people fall for scams, we tell ourselves that we are too smart and will never become a victim of one. Despite our intelligence, we all become scam victims at some point in our lives. Hopefully, the aftermath is no more devastating than broken pride and a well-learned lesson. Unfortunately, investors in the FTX crypto currency have lost everything like people in the 1930s Depression. The Guardian expresses why FTX lured so many people: “Why Were So Many Smart People So Dumb About FTX? Did They Seriously Just Like Sam Bankman-Fried’s Vibe?”
Area Mahdawi wrote the editorial about crypto currencies and she immediately rips into Sam Bankman-Fried’s unprofessionalism. The FTX inventor played videogames during business meetings. That does not inspire confidence. Large investors threw money at him and he was described as the “next Warren Buffett” and it was believed he could become the world’s first trillionaire.
Behind the proverbial curtain, Bankman-Fried was pulling a typical scam: shifting funds from FTX to his other company, Alameda Research. He then made risky risky trades and lost billions! His net worth fell from $16.2 billion to $3. Bankman-Fried lived a luxurious life a lá Anna Delvey in the Bahamas with his nine employees and they all had various romantic relationships with each other.
Mahdawi thinks people fell for Bankman-Fried for two reasons:
- They didn’t understand what he was selling, so that meant he was a genius.
- They liked his charisma.
Some investors were impressed that Bankman-Fried played videogames during meetings. Why? Maybe he conveyed an autistic savant vibe that appeared he could crunch the numbers and do magic tricks. Mahdawi said this would not have happened to other people, especially women:
“I don’t know about you, but I’m having one of those want-to-tear-my-hair-out-with-frustration moments right now. Can you imagine a woman playing video games in a meeting and being handed billions by investors? That would never happen. Last year, female founders secured only 2% of venture capital in the US and I’ll bet you everything I have that those founders were as buttoned-up as you can get. I’ll bet you they didn’t get a billion dollars because people “just liked their vibe”.”
She’s right, but also wrong. It depends on the person handing out the loans and the office politics. As to why the people invested their money with the scam artist, they wanted to make more money. Chalk it up to simple greed. Greed is good too.
Whitey Grace, November 30, 2022
The Collision of Nation State Bias and High School Science Club Management
November 28, 2022
CNN offered some interesting pictures of the labor management misunderstanding in Zhengzhou, China. Even though I have been to China several times, I was not sure what made Zengzhou different from other “informed” cities struggling with what may be an ill-advised approach to Covid. In fact, the images of law enforcement and disgruntled individuals are not particularly unique. These images are more interesting when a blurry background of Apple and a Taiwanese company add a touch of chiaroscuro to the scenes.
What is interesting is that “Apple Has a Huge Problem with an iPhone Factory in China” mentions the “Taiwan contract manufacturing firm Foxconn.” CNN, however, does not offer any information about the involvement of individuals who want to create issues for Foxconn. China and Taiwan sort of coexist, but I am not certain that the Chinese provincial government either in Henan or the national government in Beijing are particularly concerned about what happens to either Apple of Foxconn.
The fact that workers suddenly became upset suggests that I have to exercise a willing suspension of disbelief and assume the dust up was spontaneous. Sorry, a “Hey, this just happened because of pay” or some similar dismissive comment won’t make me feel warm and fuzzy.
The write up asserts:
The Zhengzhou campus has been grappling with a Covid outbreak since mid-October that caused panic among its workers. Videos of people leaving Zhengzhou on foot went viral on Chinese social media in early November, forcing Foxconn to step up measures to get its staff back…. But on Tuesday [November 22, 2022] night, hundreds of workers, mostly new hires, began to protest against the terms of the payment packages offered to them and also about their living conditions. Scenes turned increasingly violent into the next day as workers clashed with a large number of security forces. By Wednesday [November 23] evening, the crowds had quieted, with protesters returning to their dormitories on the Foxconn campus after the company offered to pay the newly recruited workers 10,000 yuan ($1,400), or roughly two months of wages, to quit and leave the site altogether.
Seems straightforward. A confluence of issues culminated in a protest.
Now let’s think about the issue this way. These are my working hypotheses.
First, Foxconn may not perceive the complaints of its employees as important. Sure, the factory workers have to do their job, but these are Chinese factory workers. Foxconn has a Taiwan spin. This may translate into Chinese government passivity. Let the Taiwan managers deal with the problems.
Second, Apple is a US outfit and it embraces some of the tenets of the high school science club management method. The kernel of the HSSCMM is that science club members know best. Others do not; therefore, if something is not on the radar of the science club, that “something” is irrelevant, silly, or just plain annoying.
Third, the workers have some awareness of the financial resources of Foxconn and Apple. Thus, like workers from an Apple store to the quiet halls of the Apple core spaceship, money talks.
Fourth, Covid. Yep, not going away it seems.
What happens when China is not too interested in Foxconn, Foxconn is not too interested in Chinese workers, and Apple is busy inventing ways to prevent people from upgrading the Mac computers?
That’s what CNN understands. Protests, clashes, and violence. Toss in some Covid fear and one has the exciting story for consumers of CNN “real” news.
Is there are fix? For China and its attitude to Taiwanese businesses which allegedly exploit Chinese workers, sure. I won’t explore that solution. For Foxconn, sure, but it will take time for Foxconn to de-China its production operations. For Apple, not really. The company will follow the logic of the science club: Find some people who will work for less.
Net net: Apple and its HSSCMM will probably not find too many fans in the Middle Kingdom. And Foxconn? Do China and Apple care? Apple cares about money. China cares about the Middle Kingdom. Foxconn cares about what? Building plants in the US… soon?
Stephen E Arnold, November 28, 2022
Snorkel: Now Humans Are a Benefit?
November 23, 2022
Snorkel emerged from Stanford University’s AI lab. Some at the Google are ga-ga over Snorkel’s approach to reducing the cost of creating training sets for machine learning. If you are not paying attention to the expense of training models the old-fashioned way, when humans do the work, months or years of effort are required. Then — surprise — after operating in the real world for six months (plus or minus depending on the use case), the model has to be retrained.
Snorkel wants to get subject matter experts to build a training set one time. Then the numerical recipes will harvest additional information and automatically update the training set. Imagine better, faster, cheaper. Well, that’s the theory. Thus the entire AI industry push for finding short cuts to deal with the need for building training sets for initial model training and the work needed to make sure the model does not drift off into craziness. (I won’t mention the name of any search vendors, but a number of these outfits have performed oblation for their VC gods. Why? The results of the user’s query returned garbage. Confusing the information in a PowerPoint pitch with returning relevant and precise results for a user’s query is a bit like resolving the conflicts between Newtonian and quantum physics.)
I read “AI Startup Snorkel Preps a New Kind of Expert for Enterprise AI.” My immediate reaction was a question, “Why didn’t Google buy the company?” Hmmm. Now Snorkel is going to push to be a commercial success, perhaps like DeepDyve, an outfit which used or uses Snorkel technology.
The write up says:
Snorkel’s Data-centric Foundation Model Development, as the offering is called, is an enhancement to the startup’s flagship Snorkel Flow program. The new features let companies write functions that automatically create labeled training data by using what are called foundation models, the largest neural nets that exist, such as OpenAI’s GPT-3. The new functions in Snorkel Flow let a person who is a domain expert but not a programmer create a workflow that will then automatically generate labeled data sets that can be used to train the foundation programs for specific tasks.
The base technology emerged from projects guided in part by Christopher Ré. The work goes back more than a decade. Snorkel itself has been a start up for several years.
Smart software is getting a lot of tire kicking action by large companies. My hunch is that Snorkel wants to sell its methods to the firms just now having a bean counter come to a meeting and saying, “Have you taken a look at how much money our AI teams need to retrain our models?”
Then a whiz kid — possibly a graduate of Stanford — says, “Get Snorkel!”
Well, that’s my hunch. Will the models avoid the horrible fate of self immolating smart software which just gets stuff wrong? Probably not. But the PowerPoints and Zoom presentations will explain that Snorkel does not go “under water.” Snorkel lets an apoplectic accountant breathe somewhat more easily until the next quarterly analysis of smart software expenses.
Stephen E Arnold, November 23, 2022
Academic Publisher eLife Shifting to Peer Review Model
November 17, 2022
The racket, er, field of academic journalism has needed a shakeup for quite some time. Will this be the move that does it? Science reports, “Journal Seeks to Upend Scientific Publishing by Only Reviewing—Not Accepting—Manuscripts.” The non-profit, online-only eLife hopes the change will offer readers more nuance than the traditional accept-or-reject dichotomy. The free-to-read journal used to charge writers $3000 if it accepted and published their paper. Writer Jeffrey Brainard relates:
“Under the new approach, eLife will charge authors $2000 if they accept the publisher’s offer to have a submitted manuscript undergo peer review. Regardless of whether the critiques are positive or negative, the manuscript and its associated, unsigned peer-review statements will be posted online and be free to read. If the author revises the paper to address the comments, eLife will post the new version.
Since eLife was founded in 2012, it has tried other innovations. In 2020, for example, it started to require all submitted manuscripts be published as preprints. Abandoning the ‘accept’ stamp is a logical next step, says eLife’s editor-in-chief, biologist Michael Eisen of the University of California, Berkeley.
Eisen, who co-founded the open-access Public Library of Science journals in 2003, says the detailed critiques written by reviewers that eLife recruits are its main contribution to the scientific process. The reviews, he says, are ‘more nuanced, more informative, and more useful to the community than our thumbs-up or thumbs down publishing decision.’ He also argues that the new model will speed up a peer-review process that at other journals is often opaque and slow because it can involve multiple rounds.”
The plan is similar to a practice already put into place by open-research platform F1000Research, which allows readers to review manuscripts posted by researchers. Eisen, however, expects to offer higher quality critiques on his site. Some details are still being ironed out, including how to decide which papers to invite for review. The new policy is to be implemented in January 2023. Researchers funded by the NIH will be glad to know they can declare a reviewed manuscript the final version of record, allowing it to be indexed by the PubMed search engine (a funding requirement). Ultimately, says Eisen, the new approach will push the publisher to the background and researchers’ work to the fore. We wonder how other academic journals feel about that philosophy.
Cynthia Murrell, November 17, 2022
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