Lynne – Lynne's Take on Tech

Thoughtful Thursday: Data Center Marauders and SV Villains

Today as our country spins further into self-induced insanity, I thought I’d talk a bit about (drumroll) data centers! This is ordinarily a rather dull topic to most, consisting of equipment and deployments and connectivity, hardware and software and systems, processors and networks, and of course, operating systems.

Since it is a dull but necessary topic that keeps things running, I could not resist writing about them back in the day. I even put together a book for Wiley entitled Inside the Internet Data Center in the early 2000s which predicted many Internet issues from the perspective of the data center administrator and how to deal with them. It was an enjoyable exercise. Unfortunately, the publisher decided it was an uninteresting field of study and canceled the book. I got to keep the advance and soon moved on to other projects. But data centers will always hold a fond place in my technology heart.

Now, everyone is talking about data centers. But not fondly. Not as an intellectual exercise. Nope, they are talking about them as technological marauders, stealing power and water and land from ordinary citizens in small towns. These entities are placed without any consultation or approval of the citizens in their communities. And the deals for taking the land and power and water are too often under nondisclosure, meaning nobody knows until it’s too late.

The big players in AI – Nvidia, Meta, Google, Amazon, OpenAI, and Microsoft – are now seen as the faces of villains. It’s a PR disaster for Silicon Valley. And yet, this is the endgame move. There are lots of pieces and players – and billions of dollars involved.

At the core, a data center is simply a processor receiving a request, accessing a database entry, and sending a result back. The devil is in the details. And there are a lot of devils, ranging from the actual hardware management and maintenance, to connectivity requirements, to database management, update and integrity — not to mention the software and operating systems that superintend these functions.

These operations require power. Lots of power. And they produce heat. Lots of heat. Hence the massive power and water requirements. And the increased demands of AI mean even more power and water for those AI chatterboxes telling folks that they can do no wrong, even though the actual interactivity to the end user is essentially meaningless.

According to McKinsey, almost $7 trillion will be invested in data center acquisition and development by 2030, $3 trillion in real estate and power infrastructure and $4 trillion in “computing hardware infrastructure” ($3.5T in servers and $.8T in storage). This is a mind-boggling number of processors.

Nvidia as the leading vendor of GPUs is beyond excited. At GTC this week, Nvida CEO Jensen Huang hailed these numbers, claiming he sees “at least $1 trillion” in revenue from Nvidia products through 2027. “I am certain computing demand will be much higher than that.” As Motley Fool noted, “This is startling — in a positive way — as it comes only five months after his earlier forecast, suggesting enormous momentum in orders in recent months. Also, Huang’s words imply that, from what he’s seen so far, he thinks revenue could surpass the level of $1 trillion.” If so, McKinsey’s predicted spend is underestimated.“

The real estate side of the equation is equally compelling. Data center REITs are all the rage. While partners in these ventures are often carefully shielded from local scrutiny, huge funds are usually involved in the acquisition of land and construction of essentially a bunch of big concrete shells. Rural locations are targeted. Land is cheaper in rural locations. Political resistance is diluted. And oftentimes water available for agriculture can be recaptured for equipment cooling. In addition, it is easy to buy a few local officials (and relatively cheap) and obtain through strong-arm tactics power easements to the datacenter.

When large corporations come into a community, they usually attempt to co-opt it by selling folks on jobs. However, once the datacenter shells are put together, there really isn’t much of a need for unskilled or semi-skilled labor. A large data center requires very few on-site personnel. Most software and systems administration is done remotely by engineers. Hardware failover means that a lot of CPUs and GPUs can burn out without having to swap out the damaged equipment.

The modern data center isn’t a factory with people working in shifts and products trucked to customers. It’s a factory for analyzing your most personal secrets, foibles, and thoughts, circumscribing every purchase you make and every comment you write, and monetizing it.

If fund managers believe that $4T in real estate is worthwhile, think of what value they place on your personal data. To get a 10-fold investment return, youre looking at the data value of literally hundreds of trillions of dollars estimated. These numbers rival the GDPs of major countries and blocks, with the US, China and the European Union in the $20 trillion economy group. That’s two countries and one economic block.

Now, these numbers are incredible, but also quite ephemeral. The same value of data of citizens incorporated implicitly in GDP as a complex factor is often claimed as a pure monetary value by AI enthusiasts. Nope, this isn’t the ROI. It’s about controlling the mindspace of investors and securing current investments.

What is real and tangible is the resistance of data center construction in communities throughout the US. And that antipathy has gone hand-in-hand with increased public fear of AI used for government surveillance. And most certainly some of the biggest advocates for its use have been companies like Palantir. People don’t like being reminded they’re being watched, even though that’s what the “free Internet” has been all about.

AI advocates have touted AI as the means for companies to find and fire people because they’re no longer needed. Lots of people. Huge numbers of people. This doesn’t make folks worried about their next paycheck feel real good about it. Especially when they open up their power bill and find it’s gone way up because a datacenter in their area has raised costs for everyone.

And finally, the debacles of AI misinformation from overeager AI advisors have become a joke, and a mean one at that. AI for the masses is not a trusted source.

This is how the standing of Silicon Valley companies has plummeted — not in terms of the stock market, but in terms of their trustworthiness.

William and I discussed the benefits of AI and data centers many years ago. Those benefits haven’t changed. But the mishandling, greed, and sheer contempt of major players in Silicon Valley and large investment funds have frittered away the goodwill and obscured the benefits.

It’s too bad. I really do like data center design. I like the software. I like the systems. I like the hardware. I like the benefits of AI.

But I don’t like the companies and pundits. Nobody does.

Sunday Reflection: Democracy is dying and Silicon Valley is Silent and Complicit

Alex Pretti, VA ICU RN, murdered 24 January 2026 by masked federal agents

The first thing I thought when I saw Alex Pretti was “He had a kind face”.

The second thing I thought was “He was shot down in the street for helping a woman as a medic”. (My father-in-law was a corpsman in WWII.)

The third thing I thought was “So many videos. Everyone can see it for what it is – a cold-blooded execution of a US citizen”.

The fourth thing I thought was “Silicon Valley is silent and complicit”.

Let me tell you how I got there.

William and I had a singular goal in launching open source Berkeley Unix in 1990 — to allow people to not only deploy servers under their control, but also to control the source code on which they ran.

This meant no company, no government, no billionaire, could sabotage, interdict, or otherwise censor the people or keep them from exercising their Constitutional rights.

When we released 386BSD 0.0 in 1992, I heard from people all over the world. Universities and colleges, NGOs, entrepreneurs. You name it. Most of these folks could never afford to host their own server, much less own one themselves. It was liberating and spawned universal access to the Internet.

But the tides of capitalism are brutal. Over time, monopolies grew to control great swathes of our global intellectual capital.

Let me be clear. A free society cannot exist when it is captive to the whims of a handful of billionaires and criminals. Nor can it endure the unfettered unhinged hate propaganda on social media secretly fomented by foreign enemies like Russia (yes, Russia is an avowed enemy I’m sorry to say) which we damn well can track and eliminate but won’t for a few cents more profit!

Who controls the press and social media? Silicon Valley billionaires.

Who controls the government? Silicon Valley billionaires.

Who is steadfastly feeding Americans a diet of lies and deceit? Silicon Valley billionaires.

These are very same people who made their success off Silicon Valley’s free exchange of ideas and technical works. But now for narrow and parochial reasons, the truth is blurred and waved away.

Tim Cook watches a ICU RN assisting an injured woman gunned down in the streets and then parties with Trump and Melania.

Elon Musk’s DOGE tech goons steal the social security data of US citizens and face no Republican censure.

Jeff Bezo’s Washington Post reporter Hannah Natanson’s home is raided in a ginned up fishing expedition and he shrugs it off.

Just to name a few. There’s plenty more right here in Silicon Valley.

There is this simple-minded belief that Silicon Valley is above all this. That we are a noble meritocracy. That we need not concern ourselves with the nation.

But we cannot be silent. We are complicit. Without us, these criminals would be knuckle-dragging in parochial ponds.

We provide the infrastructure for their hate.

We provide the support for their organization.

We provide the technical expertise for their exploitation.

And we are wrong. Silence and complaisance goes against everything Silicon Valley has stood for.

Silicon Valley is a success precisely because we do not suppress knowledge. We run by rule of law and not rule of brutality. We openly discuss and engage in new ideas. We thrive because of democracy. No other country holds our record for innovation and success. It is the core of our being.

Silicon Valley is the Golden Goose of America.

And now a handful of people who have made fortunes here in our community are intent on destroying that Golden Goose, for no particular reason I can discern other than that they’re bored. As the old saying goes, “Idle hands are the devil’s workshop”.

Renee Good, poet and mom, murdered 7 January 2026 by masked ICE agents

So do we stay silent and complicit while masked goons kill poets and nurses?

Do we turn away when the truth is strangled?

Do we turn off our minds as our freedoms are tossed away?

Or do we speak out and firmly remind our colleagues in Silicon Valley that they will be on the wrong side of history, morality, and ultimately, truth if they do not act in support of democracy, rule of law, and freedom of thought?

250 years. That’s how long we’ve lived in a democracy. 250 hard fought years.

I’d hate to see Silicon Valley destroy it. We’re far better than that.

Fun Friday: AIs are the Very Model of the Silicon Valley Elite

A lovely day is arising in the Santa Cruz Mountains, and another Fun Friday.

Rebecca Solnit commented on her Facebook feed today that “…AI has come for me too”, with lots of AI posts using her name and mimicking an article from 2008 entitled Men Explain Things to Me to snatch attention, hits, and money. Whether it works or not, I can’t really say. Facebook has a lot of cash sitting around to pay off bot farms, I assume, in lieu of the appearance of activity.

But what I found interesting is Solnit’s reposting of some selections from that article I had forgotten. As a well-heeled tech idiot held her and her friend captive with his “intellectual” rehash of “the very important Muybridge book that came out this year”, which was Solnit’s book by the way, so I’m sure she knew of it, she continues:

“He was already telling me about the very important book–with that smug look I know so well in a man holding forth, eyes fixed on the fuzzy far horizon of his own authority… So, Mr. Very Important was going on smugly about this book I should have known when Sallie interrupted him to say, “That’s her book.” Or tried to interrupt him anyway. But he just continued on his way. She had to say, “That’s her book” three or four times before he finally took it in. And then, as if in a nineteenth-century novel, he went ashen. That I was indeed the author of the very important book it turned out he hadn’t read, just read about in the New York Times Book Review a few months earlier, so confused the neat categories into which his world was sorted that he was stunned speechless–for a moment, before he began holding forth again. Being women, we were politely out of earshot before we started laughing, and we’ve never really stopped.”

I’ve worked in Silicon Valley for many years. I’ve had my writing on operating systems explained to me many times by eager men enthused by “that OS article”. I’ve had my technology explained to me by eager investors who “really got it” (Narrator: They didn’t really get it). I’ve even had lawyers suggest that my patents weren’t really my patents and should be assigned to someone else they like better and for no other reason than that it would make it more “salable”. Note in the last case they damn well knew my name was on them, and also that patent law frowns on this sort of thing, but oh well. Remember kids, don’t let your attorneys pretend they’re businessmen – they’ll come a cropper every time.

So this is normal operating procedure in Silicon Valley and always has been.

But what I found most amusing is you could describe the current AI nonsense in exactly the same words. AIs are the very model of the Silicon Valley elite with too much money and too little curiosity.

AIs don’t read the books they talk about.
They insist on your attention under false pretenses.
They drone on and on, precluding interruption.
They mash facts and fiction into an incoherent babble of words.

The only difference between the two is sometimes one can embarrass the elite. Sometimes.

Evolutionary essentialists often claim our only purpose is to reproduce ourselves. Looks like Silicon Valley has found a new modern means to do so. We are the Innovators!

I’m going to read a book and enjoy the day. You should too.

Fun Friday: Generative AI, Infected LLMs and Breaking Tulips

It’s a sunny and pleasant day here in Silicon Valley. A perfect day to chat about the imperfections of AI and the oddities of Breaking Tulips.

The extinct Semper Augustus Tulip (Norton Simon Museum)

Several weeks ago, so long now that everyone has likely forgotten, MIT put out a business survey of generative AI effectiveness, and found that hardly anyone is happy, except the consultants. “Just 5% of AI pilot programs from enterprises contributed “rapid revenue acceleration,” while the majority stalled and offered little financial impact”.

Of course, companies like Nvidia took a brief hit and then promptly went back up again, proof of the resiliancy of this latest Silicon Valley AI Bubble.

Given the wackiness of our current business climate and government, it is no surprise that people are clinging to generative AI as a beacon in the looming economic darkness. There are few opportunities for launching other technology startups as a few huge AI companies continue to suck in the majority of investment dollars and press hype.

New technologies are also a very hard sell in a risk-adverse market. Customers will only buy from extremely well-funded “startups” or well-established companies — if they purchase anything at all. And with the ever-present fears of economic upheaval, nobody wants to issue a PO, unless it’s for a sure thing.

And that sure thing is, of course, generative AI! Why? Because all the press and buzz says it is.

Behind the curtain there is great concern about results. That is why companies like IBM are actually doing a bit better. The assumption is there will be a need for high priced consultants to make generative AI a positive and lucrative business success. This confidence in the consultant pipeline and the belief that generative AI will eventually “get there” is what’s keeping the investment bubble going.

Oddly enough, contrarians are saying generative AI is just another “tulip bubble”. The actual Netherlands tulip bubble occurred from the early 1600s to the 1630’s. After a long period of fascination and investment in tulips by the aristocracy, the merchant class got into the action in a mass of speculation and eventual catastrophic collapse. It’s one of those “case studies” economics students love to pontificate about. So yeah, everything is a “tulip bubble” to some folks.

I’d like to say right now that our AI bubble is not a tulip bubble. If you want to go pick flowers, try crypto.

But there is one little piece of trivia about the tulip bubble that I do find applicable, particularly to broad-based LLMs. And that is the investor fascination with Broken Tulips.

Broken Tulips are a stunning flower. Induced by a virus, tulips will unpredictably turn from a humdrum bland solid color to an exciting streaked flaming riot of colors. These tulips were sought after by investors and caught the attention of the masses. Everybody wanted one. Artists painted them. Investors purchased them at huge sums. They were the height of tulip mania.

But a virus riddled plant is not a strong plant. And so it was with these tulips. They all died out very quickly — and so did the investment. According to the Amsterdam Tulip Museum, “Over time, the virus weakens the bulb and inhibits proper reproduction. With each new generation, the bulb grows weaker and weaker, until it has no strength left to flower and withers away.“ Not a good bet for seasonal returns. And since tulips are supposed to bloom every year, a dead plant is a dead loss.

Which brings us to another recent study, in the long line of studies, relating to generative AI LLMs and “hallucinations”, in this case by researchers at OpenAI. In Why Language Models Hallucinate, Kalai, et al. argue that language models are essentially encouraged to “guess” if they don’t know the answer, leading to absurd and false statements. They also state that this problem is persistent and pervasive due to the training and evaluation processes inherent in the process.

Current LLM models are akin to breaking tulips. They’re infected with incorrect assumptions that make them appear smart and decisive. Like a breaking tulip, this confidence inspires the customer to want more and more. In an age of complexity, nothing is more seductive than a decisive answer. And when a model seems to know more than you do, you can stop worrying and thinking and just defer to it. Even if it’s wrong.

Hallucinations popping up again and again are not a good basis for business decisions. Hence the MIT survey results.

Like that lovely infected tulip, the infection is persistent and insidious — to the point the LLM model may become too damaged to rely upon. Kalai, et al. offer no satisfactory cure for this infection. They state, “This ‘epidemic’ of penalizing uncertain responses can only be addressed through a socio-technical mitigation: modifying the scoring of existing benchmarks that are misaligned but dominate leaderboards, rather than introducing additional hallucination evaluations. This change may steer the field toward more trustworthy AI systems.”

In other words, businesses should go back to the drawing board and create their own LLM results based on binary true/false statements, carefully run, so as to mitigate the attempts to provide any non-verifiable answers. Which is how earlier models were typically done.

When a solution is sold as “simple”, telling the customer they now must do a lot of complicated work to make it trustworthy isn’t the best answer. But it’s the only path forward for these customers who are betting their future on generative AI.

Generative AI is not a tulip bubble. But some aspects of it are bubble-like. Given the promise it offers to business, I expect to see curated trustworthy business LLMs which are held proprietary.

However, for those heavily infected models used by the public, we can continue expect nonsense spewed out confidently and wrongly. I doubt most people will notice.

Sedate Sunday: AI Spending is Never Enough. Vine Revived?

It’s a pleasant morning here in the Santa Cruz mountains overlooking Silicon Valley and Monterey Bay. So what better time to think of AI and video?

According to the Guardian, our beloved tech overlords – Meta, Microsoft, Amazon and Google – have spent a whopping $155B on AI development this year alone. As the Guardian notes, this is “more than the US government has spent on education, training, employment and social services” the same period. Oddly enough, these are also the very areas where AI is expected to take over from all that expensive and pesky “skinware” (that’s people, in case you didn’t know). Such a coincidence.

Most of this money falls under the capital expenditures category, which is not an expense but an investment in infrastructure, R&D, semiconductors, and so forth, and hence runs under very different tax rules. Most of these investments I would say fall under the AI rubric only tangentially, but are categorized as “AI” to make investors happy. And happy they are. Big Tech (sans tariff goblins) have lots of money to spend on themselves.

From a Silicon Valley perspective, many of these investments are long-overdue, particularly in semiconductor design and datacenter platforms, along with requirements for low-latency low-loss networking. So this is actually a good thing for a broad swathe of hardware and software engineers and designers.

On a more amusing note, Musk announced yesterday that the Vine archive will be restored after seven years in cold storage after Twitter dumped it. I’d hate to be on the restore team. The bit rot coupled with mind rot would be formidable. But if you’re wishing you’d grabbed Aunt Martha’s six second blowing out the candles on her birthday cake over and over, now’s your chance, if it’s really still there. Industry and customers have long moved on to other video pastures, so this seems just another fair weather balloon soaring on bluster.

It’s still a beautiful day. Take a walk. Breathe the free air. Remember that nothing lasts forever. So take a chance today.

386BSD Release 0.1 Released on Bastille Day is Thirty-Three Years Old Today

I was thinking today about our creative work 386BSD Release 0.1 and the open source revolution William and I had the privilege to ignite on Bastille Day 1992, 33 years ago.

In March 1992, we released 386BSD 0.0, a fully open source operating system as documented over the prior two years in Dr. Dobbs Journal in our Porting Unix to the 386 series. 386BSD Release 0.0 was by design a very minimal release with novel code done by us filling the gaps. It had to be minimal, since there were concerns about proprietary code from old Unix releases of bygone years. By documenting and releasing this early OS as open source, we achieved a baseline release on which people could freely build.

And build they did! We received thousands of contributions, fixes and updates over the next three months. It was an immense challenge to inspect, vet, test, incorporate, and credit those responsible. But we did, with the support of the open source community, Berkeley Unix specialists, and Dr. Dobbs Journal editors. It was a remarkable time.

386BSD was the progenitor, platform, and inspiration of many open source projects. By porting it to the X86 processor, a proprietary academic testbed system only accessible to institutions and government became, in a moment, the means for any talented programmer to implement their ideas and expand their horizons.

A couple kids from Berkeley and a dream. That’s where it started.

As I sit and look at the current software ecosystem, I do wonder if what William and I achieved, with the further assistance of so many other wonderful people, would be possible today. I have my concerns and doubts.

But then I only need look at the tremendous value open source presents to the next generation of innovation to hope.

Keep the dream alive in your own life. It’s worth it.

A Tale of Two Universities

The wellspring of innovation in Silicon Valley is anchored by two major universities: the University of California at Berkeley (UCB) and Stanford University. UCB, ranked by US News in 2025 as the nation’s top public university and sixth worldwide, and Stanford University, a private university ranked as third worldwide, are both R1 research universities. R1 universities invest a substantial amount in research, award a significant number of research doctrates, and create the framework for advances in science.

These two universities are the powerhouses which drive Silicon Valley’s startup economy. One cannot understate their import in techology, medicine, aerospace, engineering, and science. Berkeley Unix, for example, was a major testbed for many operating systems and networking structures used today. 386BSD, which William and I spearheaded in the early 1990’s, pushed operating systems and networking into the mainstream and open source as the mechanism for new works.

This year UCB was rated second in space sciences by US News. However, the premiere MAVEN program based at UCB Space Sciences Laboratory and the University of Colorado Boulder Laboratory for Atmospheric Physics, like many other aerospace and science programs, was completely gutted in the most recent budget debacle, among other programs in aerospace. This is happening across every science, engineering, and technology program today in every R1 university!

MAVEN is a highly successful and well-published project which expands knowledge and technologies. But like so many other things we depend on, I suppose it’s not on TikTok enough to merit attention — hence its successes are ignored.

This reductive and unimaginative attitude is illustrative of how our current populist era sees the advances that Silicon Valley has created. We in the tech space have made the Internet possible. We have created the underlying hardware to transmit it. We create the economic incentives for startups. We are the information economy.

Yet we are treated terribly by a public and political system to which we have given so much. Perhaps too much. UCB, along with other R1 universities are facing catastrophic research cuts, layoff, and loss of top-tier scientists and researchers to international universities. Likely the next big advances will not be from the good old USA, but instead China and Europe. So much for America first.

To keep some critical research going and to keep commitments to their students, researchers and staff, UCB and Stanford may be forced to dip deeply into their endowments. UCB has an endowment overseen by the state of $22.6B. Stanford, in contrast, holds $37.6B in endowments.

The reason UCB has a substantially lower endowment despite its far greater research and teaching reach is due to the manner of how technology transfer is handled. UCB, as a public university, is torn between public responsibilities and the concerns of private technology locks held by companies and startups. This dichotomy has resulted in many different debacles, among them the Berkeley Unix lawsuits of the 1990’s and the CRISPR patent failures of the 2010’s. Simply put, UCB isn’t very good at monetizing their advances. Perhaps this is for the best.

Stanford, on the other hand, has no such public concern. Technology transfer is quite straightforward, and the easy movement of people between the lab and startups makes up much of the growth of their endowment. There are advantages to being private.

But despite the fact that Stanford (along with Harvard, Yale, and other private R1 universities) have also educated much of the current political, judicial, and financial ruling class today, these hefty private endowments have caught the populist eye and are ripe for plucking. A proposal to place a 21% tax on them has these universities quivering in fear. Stanford is already planning for budget cuts and layoffs.

The tech billionaires educated and nurtured by Stanford who are going to benefit the most from the latest federal budget do not appear to be concerned with the next generation of technology and innovation. Perhaps they are tired. Perhaps they are greedy. Perhaps they simply don’t want anyone to do better than they did, and they’re going to take it all to their grave — if they don’t find a way to live forever. It really doesn’t matter.

William and I gave back to UCB with our own sweat and blood and tears. 386BSD was a labor of love, and it changed the industry.

It’s a pity that Stanford, Harvard, and their ilk did not instill a similar sense of loyalty to Silicon Valley. Things might have been very different

Tariff Tuesday on Monday: TikTok, Instagram, and SV Misjudgment

It’s now Day Ten Million since the US went totally mad. Usually, that’s a typical day in Silicon Valley. I’ve found it enlightening how absurd the rest of the country looks when it mimics and distorts our little piece of heaven.

Which brings us to tariffs, or rather, the daily ever-changing threats of tariffs from our Fool-in-Chief. After briefly collapsing the stock market, the tariff levies were retracted, re-retracted, narrowed, cancelled, and suspended, for the most part. Of course, this changes daily, so take it for what it is — nonsense. Even China, stuck with 125% tariff at the moment, got exemptions for electronic products like smartphones, but that could change at any moment.

What is not nonsense is the impact on Silicon Valley. While huge companies like Apple can afford huge bribes to elected officials to keep their manufacturing humming and profitable, smaller businesses don’t have that luxury. Most smaller companies depend on reliable supplies of Chinese goods to integrate into their products, from chemicals to pharmaceuticals to medical devices to electronics. Most of the world relies on manufacturing in China, from washers to cars, because China has spent decades building up the expertise and equipment. Just cancelling it like a TV show and telling businesses to switch the channel won’t make it any more easier to repair a smartphone or a refrigerator or build laptops without Chinese components. Hollywood ain’t real life.

Which brings us to TikTok, the oft-maligned video snippet entity from China that American narcissists embrace.

Rumors here and there suggest that much of China’s tariff problems stem from a reluctance by ByteDance to part cheaply with TikTok to a favored US-based bidder. In 2024, ByteDance was deemed a national security issue due to accessing sensitive user data (as if US companies’ manufacturing and purchasing all our goods from them wasn’t sensitive but teenager’s babblevid is, heh). ByteDance was told to sell TikTok to someone we like or we’d ban them. The ban has never taken effect, because it gets extension after extension as bidders come and go. Add in the extra wrinkle that China would have to approve the deal, and it gets complicated. China can wait them out, endure a ban, or even subvert it if it so chooses.

A deal with a multitude of big pockets was supposedly coming together last month. Then, wack, China gets tariffed on everything. Well, almost everything. Well, maybe not things we like. Well, maybe everything. This is what most idiots think is “negotiation”. So the sale if it even existed got pulled, again.

Why is this company such a big deal when American companies couldn’t be bothered to to care about video?

It all comes back to Silicon Valley’s “misjudgment”.

Back around 2010, I was pitching a server-based video processing company that did not require any video editing skill or software. We just took clips from smartphones, added music and titles, cleaned up the artifacts and noise, put it in the required format, and placed it in a webpage automatically. A minute of video could be processed and look professional online in a minute. It was called CoolClip.

Why wasn’t CoolClip everywhere? Well, as one noted Sequoia Capital VC who will remain nameless but hails from South Africa as does Dear Leader Musk said (paraphrased), why do any production at all? YouTube doesn’t need it. Nobody needs it.

And another VC, a fellow Berkeley alum who was at that time at Mayfield, added the point that all production should be done in China. Why put it on a server and have a computer handle it when we can get *people* to do the production by hand, frame by frame. Isn’t that better?

And there were lots of lesser lights with equally inane opinions, like the wanna-be Gen-X tech journo player who basically said “Well, your stuff works, but no one wants it” with no investigation, wasting all our time. Sigh

Look, these people weren’t stupid (well maybe the tech journo), unlike the current administration. So what was really going on here?

The fact is, Silicon Valley investment did not see any value in short video. They weren’t up on formats, the complexities of editing software, and the rapid evolution of smartphones with cameras. They were blind to the Internet video disruption.

And now everyone is trying to grab for a piece of TikTok for $100B+. Crazy, right?

Which brings us to Instagram. Meta’s hopes for a market grab from TikTok has been on a roller coaster, with the looming FTC antitrust trial casting a dark shadow over its hopes. Filed in 2020 (nope, this isn’t a Biden decision), even Zuck’s recent payoffs to the president (paltry as they are) may not save Meta from forced divestment of Instagram and Whatsapp.

The trial starts today. Grab the popcorn and enjoy.

Meditations on the Abyss

It’s Monday. The stock market is in free-fall as businesses finally move out of denial and into panic over tariffs against our neighbors and threat of recession.

Congress is even more ineffectual and foolish than usual. It no longer has the cover of being divided by separate parties, as one single party owns the executive and legislative branch. Now they are exposed and frightened.

And our Supreme Court, the last recourse of the downtrodden, is a farce, beholden to extreme interests and no longer concerned with trivialities like “rule of law” and “precedent”.

All in all, just another day in the fractured US of A.

So what are the elder American people who voted for all this concerned about? Not their children losing their govenment jobs. Not the price of eggs, housing, medicine, and other needs for life. They claim to worry about their social security checks and medicare and the VA (for the many veterans), but can’t wrap their heads around anything actually happening to them.

The young tiktok “influencers” – the ones who didn’t lose their jobs yet – are ghost dancing their way along Spring Break (Who the hell ever had time for this during college? Nobody I knew ever did…) and SXSW. Aww, they’re so cute. Look at their little tiktoks. They think they’re “creative” and “tech-savvy”. Bless their little hearts.

All these folks seriously think they’re above all this. So they keep with the cheering. That’s what’s great about addiction cults. They’ll starve to death whilst destruction rains down on them.

And so it goes.

In Silicon Valley, as we head into the long-predicted recession, what are the prospects for startups and technology? As with anything else, it’s complicated, but there are opportunities if one is very very careful.

The first rule of these times is: Only work with people who you know will keep their deals. Money isn’t easy, so the con artists get desperate. They offer amazing deals. Don’t bother.

The second but just as important rule: Keep your cards close. It’s impressive the number of lying “me-too” assholes that crowd a deal when you’re getting traction.

Recessions can actually work out for startups – hard technology startups, that is. William and I got several technology startups funded during recessions. This is because flim-flam deals don’t have the same upside as during the times when money is cheap.

Technology is inherently a counter-strategy to risk-adverse investments. Recessions bring very low yields when low-risk. So look for reputable investors, appropriate referrals, and work your term sheet pragmatically.

As to all those “influencers” at SXSW who think tiktok is technology? Don’t hire them. Hire those young scientists and engineers and project managers laid off from the government because they were on “probation” for the sin of, get this, getting promoted for doing a good job. You won’t regret it.

AI Trends for 2024: What’s Old is New Again

There’s a lot of shock and awe in the AI space these days. And lots of money on the table. But through the sturm und drang, some trends are emerging. To level-set, I went back and reread our last published article together, Moving Forward in 2020: Technology Investment in ML, AI, and Big Data (William F Jolitz & Lynne G Jolitz, Cutter Business Journal, 7 April 2020).

Four years ago, AI was at a crossroads. When we looked a traditional value propositions in technology, where one went from a specific technology to a target customer in a high value sector to a broadened sector and use, AI was doing miserably. 70% of companies said their AI projects provided little to no benefit to their company. Only 40% of companies said they had made a significant investment in AI. The frustration lay with “products sold with ill-defined benefits” which led to “unsustainable revenue that plummets when customers become disillusioned from a tactical lack of sales focus”. We stated the key problem was “the startup’s sales focus no longer aligns with the customer’s strategic focus”. In tech speak, they couldn’t figure out what to do with it and got disappointed.

We suggested what we called an “axiomatic” approach: “Instead of moving from technology to key customers with an abstracted TAM (Total Available Market), we must instead quantify AI and ML benefits where they specifically fit within business strategies across segment industries”. We then highlighted three areas to watch: surveillance, entertainment, and whitespace, while also discussing the issues with ad hoc architectures which potentially disrupt the cloud services costs and security. In terms of architectures, there is now more focus on data ownership and control, as well as reducing costs in the cloud. But it’s still very much the same as four years ago for most customers.

But the key prediction where we were literally “on the money” was our analysis of chaotic disruption of the market forwarded and funded by “super angels”. This was how companies like OpenAI spawned and spurred tremendous disruption in a very short timeframe:

“Venture capital (VC) investments in ML/AI fixate on a startup’s ability to obtain go-to-market sales by disintermediating other vendors and to lock-up highly profitable (yet elusive) opportunities. The VC’s intent is startup validation and gauging threats to other vendors’ uncompetitive businesses that will drive the startup’s ability to gain partnerships and revenue shares. However, sometimes, the result is not what VCs would wholly desire but rather more like paralysis with no clear “win” — because the startup only partially engages the customers and does not succeed in displacing other vendors. To force the win, tactical deconstructing/reconstructing of AI/ML solutions around existing layers of edge and cloud platforms as an investment category is akin to desperately reshuffling poker chips on the poker table. This is best avoided. Industry disruption is inherently unstable. Like an ouroboros, it can abruptly turn from obvious low-hanging fruit targets to feeding off earlier successful targets undergoing a state of change.
The potential for radically greater opportunities is more interesting than patiently maintaining course or re-navigating the rough waters to see existing ventures through to a reasonable conclusion. This potential is the realm of super angels, self-funders, and leading edge “winners.” These individuals and groups see no disadvantage to riding a chaotic wave because they’ve gotten accustomed to being so out in front of theirthe self-competition within their newly chosen, ever-shifting “whitespace path.”
However, the traditional VC process is disadvantaged by these groups because venture capitalists’ gut instincts based on the feel of the deal get whipsawed by the loss of bragging rights to ROI, limiting them from getting too far out beyond their headlights. Thus, chaotic disruption is a no-go zone for most. For those who decide to enter these perilous waters, the tendency to share risk across many partners leads to a kind of groupthink at odds with the fast moves and flexibility required of the super angels.

As open source investments demonstrated, it’s a risky business consuming your own potential customers. In the AI chaotic disruption, all potential customers are considered targets: media, artists, writers, businesses.

In consuming the “long tail” of literature, art, whitepapers, business databases, and personal information and opinion on the Internet and then regurgitating it as facsimiles stripped of authorship and authority, companies like OpenAI and Google whipsawed established players. As we have seen, the rush of businesses and consumers to magnify this effect was phenomenal — and dangerous.

The intent was to rapidly drive paniced companies to sign exclusive agreements and become the dominant company in AI for the next half century. If it sound unbelievable, note we now have only a few companies which dominate search, content, and connection due to brand recognition and addictive use. It takes a lot of money to maintain an addition, or establish a new one.

As the investment space is still suppressed due to poor conditions despite all the dry powder, there are a few bright spots. Battery investments continue to spark interest. Climate change companies surge and storm. Crypto was actually legalized by the SEC, because you can’t play with GameStop forever — so it’s time to jump into the big scams, kids. Space investments are, well, vast. AI plays a role in all of these.

But because of the chaotic disruption strategy that our billionaires strategized in Silicon Valley, AI now has the attention of everyone, from governments and military and NGOs to plain ordinary users. It doesn’t matter if AI is “lazy”. Even the IMF is jumping in.

Will AI benefit humanity? That’s out of my paygrade. William and I saw it had unique potential in many areas in 2020. That’s still true in 2024. I hope the chaotic disruption doesn’t prevent us from seeing some real benefits for the better.