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.

Merry Monday: Venture Gets Antsy, Boom or Bust? Everyone goes Buggy over AI

Another Monday, another week of business excitement.

Venture investment firms are getting nervous as the projections for a slow IPO market in 2024 make fund exit profitability iffy as each fund matures. So what to do? Simple – roll the money into another fund that has no exit date and call it a day. And so, continuation funds, and their more desparate cousins, strip sales, are generating increased interest (subscription required, and I’m really sorry about that).

It’s hard to support a wealthy lifestyle before one is truly wealthy, but somehow VCs manage with their fees. But they want more. And they’re going to get it, by hook (clawback) or by crook (IPO).

It may be hard to believe, given most of these funds have ten year lifetimes, but even though we’ve gone through a lot of “booms” over the last decade, apparently they’ve chosen so poorly that they don’t have the exit they promised their Limiteds. In a more cynical moment, one might also wonder if the carry was so good they held off on distributions, hoping for more.

And then the pandemic hit. And then we had inflation grow. And now we are watching a world grow hotter in terms of climate and strife.

There are still optimists, however.

UBS Wealth Management just released a case study claiming that the 2020’s will look more like the 1990’s (without the early 1990’s recession) instead of some Roaring 20’s stock market insanity before folks jump off of buildings. For that alone, I must confess I’d rather consider a Clinton-style economic “Americans for a Bigger America” boom, as I don’t like heights.

In terms of technology investment, the 1990s was a good era for us personally.

We started off in 1991 (after two prior years of work with Berkeley with no real support) with the introduction of Porting Unix to the 386 in Dr. Dobbs Journal. Over the next two years, we painstakingly described our 386BSD port of Berkeley Unix from design to execution to distribution over the Internet.

  • 386BSD made manifest Stallman’s concept of “open source” as a means to encourage innovative software development.
  • 386BSD demonstrated that the Internet could be a viable mechanism for software distribution and updates instead of CDROMs and other hard media. 
  • 386BSD provided universities and research groups all over the world the economic means to finally conduct OS and software research using Berkeley Unix on inexpensive 386 PCs instead of minicomputers and mainframes. 
  • 386BSD spurred a plethera of new funded startups launched with a focus on open source online tools and support.

In sum, 386BSD broke the logjam on university research encumbered by proprietary agreements and spurred the growth of a new industry in Silicon Valley. 

Not bad for a research OS project that was disliked by Berkeley’s CS department and essentially moribund by 1989.

In 1997, we observed that Internet traffic wasn’t well-optimized. We launched and obtained funding for InterProphet, a low-latency TCP processor dataflow engine. In 1998 we went from concept to patents to prototype. We proved that dataflow architectures, a non-starter in the 1980s with floating point processing, was a viable means to effectively offloading TCP processing from the kernel to a dedicated processor, just as graphics was offloaded through use of dedicated graphics processors. We did this on a million-dollar handshake investment and a handful of creative engineers. Silicon Valley can be an amazing place.

Global strife and pain isn’t usually good for business. It was an age of “renovation, not innovation” the prior decade — hyper-focused on strip-mining extant technologies and vending rent-seeking fads — unequipped to deal with these unsettled times. 

But such times often spur interest in non-conventional problem-solving, opening a door to new technologies and risky solutions. Given the huge issues with climate change and what it spawns, we do need more “innovation, not renovation”. 

I guess I’m just an optimist.

Speaking of technology fads, as the smoke clears and the mirrors crack, will generative AI still be the savior Silicon Valley hopes it to be? As with all answers, it depends.

If one owns the datasets from which one mines the answers, likely “Yes”. Security and privacy issues are moot inside your datacenter, for the most part, assuming you actually invest in security. Cost reduction is a viable metric that businesses can use to determine the efficacy of AI independent of fads. Expect to see use cases that focus on support and customer effectiveness. We also should expect new solutions crafted out of analysis of highly complex areas, from drug development to climate modeling. 

However, generative AI has limits. The latest cut of a thousand critics, courtesy of Google, demonstrated that one could overload the AI generative variation responses to the point it begins to spew out actual training data using Internet data with a single word. Using an extraction technique that relied on an infinite request (do something “forever”), they achieved immediate results:

“After running similar queries again and again, the researchers had used just $200 to get more than 10,000 examples of ChatGPT spitting out memorized training data, they wrote. This included verbatim paragraphs from novels, the personal information of dozens of people, snippets of research papers and “NSFW content” from dating sites, according to the paper.”

I’m sure a new set of lawsuits based on infrigement are already in the works. Maybe even using ChapGPT to generate them. Who knows?

So let us send our thoughts and prayers to the poor VCs and happy lawyers. I haven’t seen this much eagerness for technology infringement lawsuits since the USL v UCB and Java v Everybody years. 

Merry Monday: MAVEN 10th Anniversary, Insatiable AI

We have passed the inevitable turkey day relatively unscathed — if anyone’s wondering, we had Tandoori game hens — and now it’s back to business.

The MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft launched from Cape Canaveral ten years ago, and to celebrate University of Colorado, Boulder published reminiscences of the launch from researchers at CU Boulder LASP (Laboratory for Atmosphere and Space Physics), University of California, Berkeley SSL (Space Sciences Laboratory), NASA Goddard Space Flight Center, and the University of Iowa.

I remember when my daughter Rebecca Jolitz went to the launch as an eager Cal physics and math undergrad working on simulations at Berkeley SSL. She had just returned from several months field work in Tahiti at the University of California GUMP research station as part of the Moorea student research group for that year, and was quite jet-lagged. After a day, she flew out with her father William to Cocoa Beach, his old stomping grounds when he worked long-ago for NASA-Ames. “When the Atlas V entered the clouds, he said this was a good launch and that this would be the first of many in my career.” Go MAVEN!

As AI companies whine about regulation stomping on innovation (where have I heard that before…), and OpenAI (a Microsoft(tm) company, as it owns 49% of the equity) turns into a soap opera version of “Day of our Lies”, Putin has decided he’s not getting enough attention throwing drones at Ukraine and has decided Russia needs to control AI. While he blathered on about Russian “culture” under attack, the real impetus for his concern is simple: AI-enhanced warfare will make Russia’s old-style top-down command structure too slow and cumbersome. Unfortunately for Putin, most everyone who could possibly do so and has the knowledge and skill fled for greener pastures to avoid conscription and likely death in Ukraine. How like a paper tiger Putin now looks to the rest of the world.

Speaking of OpenAI and Microsoft, another in the increasing number of infringement lawsuits by authors, artists, songwriters, and various other creators of intellectual property have filed suit, this time by nonfiction writers of works used in training OpenAI’s ChatGPT’s voracious appetite for novelty. Unlike the previous suits, Microsoft as well as OpenAI are facing the class-action lawsuit. As I noted above, Microsoft is the largest single equity holder of OpenAI, and curiously, pressured to reverse the termination-for-cause of its CEO, Sam Altman, and booted the rogue board members, adding their own selections without breaking a sweat. Microsoft is certainly the power behind the throne at OpenAI. They’re also the very deep pockets. Lawyers, get your lawsuits ready!

Sedate Sunday: Startups in the Age of Climate Change

As we sit by and watch the ever-increasing impact of climate change on our world, it stands to reason that startups must also be seeing an increase in interest, investment, and technology innovation to fight this. Yes, this would be reasonable.

The startup scene is never reasonable.

It’s not the 1980’s, kids. We don’t invest in technology or startups with the public good in mind anymore. Big global investments are entirely focused on making money fast — preferably by stealing it from you and me in fees and in turn selling our personal information to others who also want a piece of you and me. It’s rather disgusting, actually.

Want to change this? It’s pretty easy. 1) Require opt-in on personal information. 2) Disallow monopolies to bundle / require opt-in as a requirement for using their software. 3) Eliminate Section 230. Oh, and we might actually eliminate the tax carry loophole used by venture, forcing them to actually do some work.

None of these suggestions are going to happen, folks.

We all are watching what happened in Maui. Fire swept by 60mph winds consumed the entire town of Lahaina in a few hours, taking many in the town completely unaware. Cell service and power were down — obviously, there was inadequate or non-existent backup capability, and old-styles poles were knocked over like dominos — rendering notification impossible. No one thought to use the sirens. The counting of the dead has just begun, and already it has surpassed the death toll from the 2018 Camp Fire in California.

I suppose everyone is now asking “Why didn’t we see this coming?” Well, actually we did and we do. We just can’t get anyone to put money into startups to deal with this threat.

The 2020 CZU Lightning Complex Fires started with a hot wind and dry lightning. I know. I felt the pressure change and awoke. I walked to the screen door and almost fell over from the sudden blast of hot wind from a direction of the mountain wind shadow. William was by my side as we stepped out on our covered porch. William cautioned me to not step beyond the shelter of the porch. We watched the dry lightning start to hit different locations of the surrounding mountains as the wind gusted. And the fires began.

Unlike Maui, CalFire has much more extensive resources for fighting fires. Yet many communities burned to the ground. CalFire was hampered by the rills and gullies inaccessible to conventional firefighting equipment throughout the Santa Cruz mountains. Like Maui, we have been in the midst of long-term drought, so dead fuel was ubiquitous. The winds were strong, but not as strong as Maui.

While power was immediately knocked out for many locations (PG&E also relies on old-fashioned power poles in many mountainous regions), cellular and microwave links were maintained due to adequate battery backup. However, many locations in the mountains are “dead zones” with respect to cellular linkage. For those folks, they relied on house-to-house contact by local authorities and neighbors. Unlike the poor people of Lahaina, the mountain people had more time and more resources to get out, so loss of life was minimized. Loss of property, however, was considerable.

Also unlike the Maui fires, the strikes resulted in fires under the canopies of trees, so air flights dropping retardant and water from the local reservoirs failed to reach the actual fire points. This meant, simply, that small fires could not be staunched before they became big fires. This was a significant opportunity loss.

William and I were among the thousands under mandatory evacuation in the days after the lightning strikes. As we sat in a hotel near Stanford Hospital (William had cancer surgery scheduled that week), William looked up at me and said “You know, I’m tired of this. We could use existing technology to locate the fires. We could use drones to get under the canopy. We can carry retardant to drop on small fires before they become big fires.” And then, he began to put together a business plan to do exactly that.

It wasn’t easy for a man with terminal cancer to begin this process. But William and I were struck by the complete indifference by Silicon Valley companies and venture to the reality of climate change. Oh sure, they put money into charities to help folks after-the-fact. But that’s too-little, too late.

William is a legend in Silicon Valley. He’s the Father of Open Source Berkeley Unix. His work and its progeny are the engines of commerce. Yet he could not get sufficient interest beyond some meetings and happy talk. Apparently, wealthy folks can just relocate to safer locales. It is not a burning concern to these folks.

But with global climate change, is anywhere really safer?

There is actually some movement now on his vision to make a safer world 1-1/2 years after his death. So in this, I am hopeful.

To assist in spotting small fires before they become big fires, UC San Diego is working with CalFire to develop AI mechanisms to essentially sort through various feeds looking for anomalies that may indicate a fire starting.

This is the first item William outlined 3-1/2 years ago as we sat in our hotel room waiting out the fires.

As to drone development, at the time William was putting together his funding proposal and doing the research, drones were predominantly consumer-oriented, with the capability of handling a camera. They were user-operated over short distance. And they were completely unusable for carrying heavy loads like fire retardant.

But war is often the engine of change. And the war in Ukraine launched by Russia has resulted in a literal blitzkrieg of drone innovation and reduced cost of payload. This price to payload ratio is the key to affordable drone fire-fighting capability. After all, a cheap $2,000US drone targeting a small under-canopy fire is now much more cost-effective than a helicopter dropping fluids from above which may or may not work. As stated in the article, “A drone gives a lot of bang for the buck, as utterly new weapons often do.”

NATO has also announced a new $1B fund for defense and security startups. Expect to see startups focused on cyber-security, drone technology, and non-interceptible command and control hardware and software to take the lead here.

Translating weapons of war to consumer products is often challenging. However, drones have gone from consumer toys to weapons of war capable of carrying heavy payloads. So it is much more feasible to move them back to peaceful purposes like fire fighting.

It is as important to keep the peace as it is to make war. And climate change is not simply a war we can win or lose and walk away. We can only adapt. Or die.

Fun Friday: I Welcome our AI Overlords, Don’t You?

As the layoffs of the old continue here in Silicon Valley, the investment community and Big Tech ™ rush headlong into the wonderful world of AI. Every company and every startup now sees that brass ring ready to anoint the Overlords of AI ™ (pending I assume).

Elon Musk, annoyed with his not-good-enough OpenAI involvement, is simultaneously railing against the perils of AI and announcing a new AI company called xAI — which will apparently tell us how the real world works with an exploration of “the true nature of the universe”. Heh.

I guess the Earth and the Solar System aren’t enough anymore. Nor is the Milky way galaxy with everything within the Perseus and Scutum-Centaurus arms. Nope, now we’ve got to include the Hubble picture of all galaxies to get the maximum pitch potential. I guess the TAM is huge enough for even the most greedy investor. I think…

Meanwhile, ChatGPT application growth has finally started to slow down, as people rush to the new Threads app launched as a competitor to Twitter. Yes, folks, the dumbest site in all the Milky Way has been duped by Meta (the Facebook fellows) as an add-on to their Instagram app.

It is a truth universally acknowledged that a site in need of boosting must be in want of a cloned competitor. In other words, the quickest path to development is usually to rip and piggyback open source code onto something else and cross your fingers as you go live. It may not be ready, but it will be running, kinda.

Meanwhile, OpenAI is being investigated by the FTC for its propensity to unleash “hallucinating” AIs on the world, leading to rampant lies and misleading statements. They’re also annoyed that the AIs were trained on copyrighted works, but honestly I think that’s an afterthought as no one cared when source code attribution was deleted and content aggregators like Google News allowed one to find the article that didn’t require payment before. Why now? Maybe it just makes the filing more “human”.

The term hallucinating is a fascinating one for a piece of software, n’est-ce pas? It allows the company to elide responsibility for their software producing rotten results by implying the software is just some kind of person with a disability who should be treated with kindness and not legal threats. It also distances the company from this AI “person”, as person’s are only responsible for themselves and no one else.

This is, in sum, a very weird attempt to extend the ragged edges of Section 230 of the communications act to AIs where the AI software developer has no influence nor liability for what the AI actually says.

If you recall, the act states that “no provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider.”

The legal shield was passed to allow individuals to comment and post items on websites like Facebook and Twitter — and even blogs like mine if I so desire — with no liability to the provider of the service for the words said. People say dumb things, goes the thought, so why punish the website operator? This little sentence made the Internet providers rich beyond the dreams of avarice.

By acting like the AI itself is just providing information, and the developers and propagators of the information are just providers of an interactive computer service, they distance themselves from the liability of these acts.

So of course, everyone in Silicon Valley and beyond wants to extend it to AIs. Investors. Big Tech. Even Elon Musk.

That’s where the money is.

Sedate Sunday: Silicon Valley and Post-Cold War Innovation

I came across this essay on Silicon Valley’s ascendency. It’s a bit wordy in some places and only abstractly relates to Silicon Valley. But who can resist an article that merges IPR, Gramsci, Silicon Valley investment, and Bretton-Woods.

I was amused, no matter how romantized some of the the assumptions. Come on, we all know that communism was really just another form of kleptocracy in disguise, just like Prosperity Gospel, unbridled capitalism, and all the other scams. It’s the human condition writ large.

Scams work by promising people things they don’t merit nor deserve in return for becoming their trolls, fan-boys, minions, and various minor demons. At least Maxwell’s demons did some undeniably important work, but most of these lesser types from the Stygian Depths reject pile don’t want to work (hence the “merit” stuff I menioned), nor are they part of the in-group (hence the “deserve” part). They’re also non-too-bright as a rule. But they are useful in aiding the ascent to substantial power and wealth, primarily by flooding the airwaves and empty streets with bellowing monsters, which in turn is covered by a lazy press corp as a meaningful “event” which should be taken seriously by “those in charge”. 

Technology has certainly brought down the costs of this well-established mechanism. You don’t have to print pamphlets to get attention. You can even more cheaply motivate the mob using facebook ads targeted to any feeble-minded demographic, or pull off in-your-face twitter placement with a word from the Big Twit himself. 

Honestly, it makes me long for the good old days of board room shenagins when William and I pitched hard tech companies. And yes, they were just as misogynistic, narrow-minded, and assholish then as now. That hasn’t changed.

It’s just back then there were still rivals, rules, and relationships to manage in the SV investment side. So William and I had a fighting chance. And fight we did. Sometimes…sometimes we made a success — before anyone caught on. Those were amazing times.

Now writers view startups as some kind of historical media retcon — a rather odd combination of Highlander, Fawlty Towers, and The Big Bang Theory (no women allowed, folks, unlike real life). William, who handled acquisitions for Tandem at one point, also had a fondness for Barbarians at the Gate, but that’s East Coast, not West Coast. And despite what folks will tell you, all those hagiographic movies about SV are so ridiculous and boring  I just don’t bother.

But historical fiction about SV will continue to be popular, especially with a polisci or econ twist. So go ahead, and imbibe this one, especially the amusing views of open source development and startups:

“Within even the very early culture of Silicon Valley, a distinctive tension could be discerned between the “hacker ethic”—with its commitment to entirely free and open information, born as it was in a university laboratory—and the entrepreneurial drive to protect intellectual property. This was not a superficial short-term contradiction, but a defining productive tension that continues to animate the entire domain of networked and computer-driven social and economic relationships.”

Gilbert and Williams, How Silicon Valley Conquered the Post-Cold War Consensus

On to one of my personal pet peeves — there was no hacker ethic as described by the authors back when we were putting together various technologies for the Internet and Berkeley Unix prior to the early 2000s. The very concept of a hacker having any ethics is so laughable I wonder that any reputable journalist can type the words without gagging. We were in it for the fun, the money, and kicking over apple carts. Anything else someone tells you is a sales pitch.

Not to say there weren’t hackers back then. Of course there were. John Draper, aka Captain Crunch, was one such example. Back in the 1970s and 1980s, one could still get access to all the telecommunications and tech docs in public libraries and, with a bit of cleverness and elbow grease, hack pay phone, computers, and all sorts of primitive networks. Security was an afterthought in those days. Security is still an afterthought now. However, it wasn’t all fun and games. John was always followed around by men in suits and shiny black shoes at conferences, William noted.

Even 386BSD, which through Dr. Dobbs Journal articles and releases birthed the open source operating system (even Linux used the article’s 386 source code supplied with every issue), was based on a very different viewpoint from the present-day common viewpoint of everything “free”. Berkeley Unix had been licensed for over a decade, yet the vast majority of works which encompassed it were not proprietary. It was inevitable that eventually those code remnants would be removed and replaced.

Yes, the copyleft and RMS were talked about a lot back then with the long-awaited HERD OS expected to roll over everything in the universe and then Marxism would prevail! Gosh, I can barely type that while laughing. And yes, they really did believe they were some kind of Second Coming of the Open Source Proletariat before Bernie Sanders came along and stole their thunder.

This invested belief in the copyleft actually allowed Berkeley and us to work quietly. Frankly, no one expected Berkeley to finally get around to removing most of the old version 6 Unix detritus.

Even William’s and my prior company, Symmetric Computer Systems, contributed code on disk drive management.  And William and I contributed the source code for the 386 port, making Berkeley Unix actually usable.

During this time, I really enjoyed writing the Source Code Secrets: Virtual Memory book with William, based on the virtual memory system from CMU. The CMU Mach project provided the key in a new approach to a virtual memory system, permitting the jettisoning of the old industrious evaluation virtual memory system of a decade prior. It’s a nice piece of work that is much underappreciated.

And of course, when the unencumbered incomplete release was made public, we got creative and wrote entirely new modules to fill in the missing pieces for the releases.

But working on open source and working on proprietary intellectual property is not antagonistic as the author would state. One of my proudest moments was getting my patents granted for InterProphet’s low-latency protocol processing mechanism and term memory. 

The key is understanding what you owe to others and what you owe to yourself.

Berkeley Unix was a long-term project that collected the works of many people. Berkeley handled the release mechanics and integration. Sometimes they did new work, but not always. It was research, mostly paid for by the government. And that means you and me. 

William and I did the port to the 386, contributed code, wrote published articles, and devised new work as a research project. While we received no funding from Berkeley, we did have a lot of fun.

InterProphet, in contrast, was a 1997 startup focused on improvements in latency in networking using a dataflow architecture. Our innovations were funded, we had employees and an office, and we built the prototype and production boards. We developed the drivers and support software. We paid for really expensive proprietary chip design tools.

And we filed patents and held trade secrets. Intellectual property protection was a given in this work. (A bit of advice here: If your engineers decide to deal with bugs in their software by sending source code to the vendor, put a stop to it immediately. It causes no end of problems later.)

We had an obligation to the investors at InterProphet. And we kept our deals with that company. Just as William and I did with Symmetric Computer Systems back in the 1980s. Technology innovation was valued — at least enough so we could get another startup off the ground. It required due diligence and careful maintenance.

The mistake in many “historical” analysis of Silicon Valley innovation lies in conflating the technology innovation of the pre-2000 era with the non-innovative “free stuff” of the post-2000 period. Investment strategies were completely different. Business structures were different. Even financial structures pre and post IPO changed markedly. They’re not comparable. 

There is nothing “free” in using FaceBook, or Twitter, or Google News, or Apple Maps, or a plethora of other websites. And that is by design.

These websites and applications are intended to go “viral”. They must lure in an unsophisticated customer and make the site “sticky” so they can be tracked. Gosh darn, that’s all it was and is about. No innovation required. In fact, invention and innovation were derided. As John Doerr noted back then, it was “renovation, not innovation” that was king. 

And as the author notes, anything related to manufacturing was sent off to China. No more chip investments. No more hardware investments. No more of that “risky” tech innovation. It had all been done. 

I don’t usually call out specific VCs from that time, but John Doerr and Kleiner deserve it for singlehandedly killing an entire generation of technology with a cynical investment strategy. Special mention goes to Google, Apple, and Intel for corralling open source operating system innovation to maintain their profits.

So John and KPCB, and the tech monopolies as runner-ups — I salute you.

People went hunting for content to populate those websites. Youtube for example grabbed the few popular short videos circulating on the web and put them on the site just to appear like it was being used — until it was used through relentless press.

Customer acquisition dollars were high. A flip was six months.

Content was available in many ways. As the printed press conglomerates strove to grab eyeballs, they inadvertently gave their content away while cratering their traditional print advertising dollars. Aggregators glommed onto that content, manipulating the views towards paid ads and “curated” experiences. Video and music content was pirated as well, but entertainment media executives had been down this road many times before, and hit hard with copyright lawsuits. 

Databases of many kinds were publicly available as well, from geolocal map data to astronomy datasets. With that richness of information, the sky was the limit for people putting a front-end on the information. And so it is today.

I remember when Amazon was first funded as a bookstore. I bought a book — a Harry Harrison Stainless Steel Rat book I recall. One of the VCs back then gave me the dark side sell at an investment event: It was all about knowing what you look at, what you want, what you need. And putting that in front of you so you buy it. And Amazon takes a cut all the way to the bank. Privacy? Who cares. 

It took Amazon six years to a quarterly profit.

Think about that. Six years losing money. When a VC starts demanding quarterly profits, dig up Amazon’s pro formas.

Fun Friday: Back to the Old New Tech Lifestyle

As I sit in William’s and my office in Los Gatos, I’m struck with how empty everything feels. The aux offices nearby are now empty as the call of the wild beckons folks back to the non-performing real estate that leaves many CEOs fuming. People who once revelled in the glories of a non-commute day now struggle to drive the crowded freeways and fight to park near the lobby entrance, grab a quick drab coffee from the machine, and stagger to a shared table “desk”. Just like in the Before Time. 

As I always told the kids, “Traffic is the most important thing is Siicon Valley”.

 Does this upset me? Not really. I no longer have to hear the bellowing of the sales guy wafting through the walls. Nobody builds offices to be sound-proof. My relaxing music sounds so much nicer when I don’t have to crank it up to compensate, or put on noise-cancelling headphones.

But for those who worked at home, the demands of working in an office must be quite a struggle. Startup types do their “zero to one” juggling pitch act in any place that will suffice, whether it is a coffee shop, a conference room, a beach, or even, dare I say it, at home. Obtaining an office to work is actually a milestone funding achievement – not a given.

Hence, I am at our office today, surrounded by memorabilia, computer and software and writings, seeking inspiration!

Well, perhaps inspiration should step aside for the moment. Let’s take a bit to check the weak pulse of venture and startups.

As we move out of the “spend money for anything online” phase of a cloistered culture in the grips of the pandemic, major  companies responded by 1) laying off all of their excess employees hired to keep other major companies from hiring those same people they just laid off and 2) forcing everyone back to the office to listen to the CEO tell them how useless they were when they were stuck at home working. 

In like kind, investment in the wacko side dropped like an anvil. Crypto currency was shown to be a fraud (is anyone shocked?). Blockchain is too narrow for application. Gaming is hit and miss, usually miss. The gig economy is a bust. And whatever happened to Meta?

So now venture is hyping AI. Again. Yes. Again. 

In lockstep, startups are all adding their AI gambits to their existing offerings to look mod and rock their asses. Sigh. It’s a living.

So where do we stand. Easy. We have 1) M&A in the doldrums,  2) down rounds and the potential for clawbacks, and 3) VCs on the defensive. Let’s take these one at a time.

M&A:

As VCs closed their wallets, they hoped that continued hype would propel their less favored dead dogs into the eager arms of corporate strategy guys. (Note — William actually handled strategy and new ventures for Tandem in the old days, so I heard about this a lot, every day). Well, these guys aren’t quite as stupid as they thought. A bunch of desperate sounding VCs selling a high discount startup (hey, it’s 50% cheaper than last time!) wasn’t enough to move the acquisition forward. Frankly, these deals take time and are usually lined up well before one needs funding as their “Plan B”. 

At the same time, while venture was eager to deal, corporations looked at their bottom line and didn’t like what they saw. Stock prices are depressed, or at the very least not increasing dramatically. Integrating new companies into the fold is a costly investment in people and technology. And last and not least, the random pivots by VCs from one unicorn technology to a completely different unicorn technology has heads spinning and disrupt the acquisition process.

In an effort to preserve the appearance of astronomically priced unicorn startups, venture has grasped the tail of the AI GoogleBull while Microsoft NoPilot yaws and ChatGTFO hallucinates. It is a strange summer, even for Silicon Valley.

Already the tech journo crowd is side-eying all this sturm und drang. They’re starting to whisper that all this stuff is passe. After all, when you start to have ignorant Texas Aggie profs flunking students because he heard about AI taking over writing essays, you know the jig is up.

Down Rounds, Discounts and Clawbacks:

Let’s face it, startup valuations have always been, shall we say, invented? Created? Innovated? OK, yes we look at the upside potential. That’s because in zero-to-one that’s all you have — Potential. And potential can mean nothing — or it can mean everything.

But we also had to demonstrate a product, market, path to profitability, and an exit strategy. 

Guess what? This is where the tech innovators and the con-men (like poor little rich boy Sammy Bankrupt-Fried) and con-women (Orange is the New Black Liz Holmes) separate, if not actively scuttle away. 

Building a prototype and product is hard. Convincing customers to pay for it is extra hard. Making enough money to actually not need investment is super hard. And finding a means to transition beyond the startup mode, whether through acquisition, IPO or just plain good sales is excrutiatingly hard. So it’s no surprise that most unicorns skipped all that other stuff and got lots of money when money was basically free.

Now that things are hard, VCs are looking at all those other pesky hard things. And most startups funded in different conditions can’t step up and evolve. The end result is a lot of startups will not get further funding. They just aren’t worth it, valuation-wise.

While some of the fatter venture unicorns are pitched as promising M&A opportunities (see above), many others will shrivel and starve. The ones that pivot to some kind of revenue and profitability with real customers may survive, while those that restructure to some kind of “NewCo Tech Opp” (cough, AI, cough) may squeak by with fresh funding.

As venture partners and their Limiteds get increasingly disappointed in their portfolios, anticipate clawback. It’s never pretty, but it will happen.

VCs on the Defensive:

It’s only common sense that as returns nosedived, folks would start looking for someone to blame. And VCs are in the thick of it.

This lovely little article from Crunchbase is an excellent example of forensic analysis of successful investments. On this Fun Friday, I leave you with these thoughts from that article:

“What’s concerning with our sample of the largest IPOs of the past 10 years, however, is the absence of any real star performers among the big names. None are even above their first-day prices, let alone returning a multiple to their IPO investors.

It’s even more worrisome when one looks at how much capital has been going into startup investment. Over the past 10 years, investors have plowed more than $1.4 trillion (!) into seed through late-stage and pre-IPO financings.

At the peak, in 2021, a whopping $329.5 billion went into North American startup investments across all stages, per Crunchbase data. That — to put it in context — is more than the total recent valuation of all 20 of the biggest IPOs in our sample set.

To make good on that level of investment, startup backers will need not just hits but grand slams. Their recent batting averages indicate that’s unlikely to happen.“

Fun Friday: The Race for AI Creative Works Control

In April of 2020, William and I wrote in the Cutter Business Journal an article entitled Moving Forward in 2020: Technology Investment in ML, AI, and Big Data. We focused on three areas: surveillance (monetization), entertainment (stickiness), and whitespace opportunities (climate, energy, transportation). This statement bears emphasis:

Instead of moving from technology to key customers with an abstracted total addressable market (TAM), we must instead quantify artificial intelligence (AI) and machine learning (ML) benefits where they specifically fit within business strategies across segment industries. By using axiomatic impacts, the fuzziness of how to incorporate AI, ML, and big data into an industry can be used as a check on traditional investment assumptions.

[For additional information on this article, please see AI, ML, and Big Data: Functional Groups That Catch the Investor’s Eye (6 May 2020, Cutter Business Technology Advisor).]

But one might be puzzled as to where generative AI tools such as ChatGPT or Dall-E fit in the AI landscape and why we should care about AI art, AI news and press releases, AI homework and essays — even threatened AI music like what’s talked about in 1984 by Orwell.

The reality is these areas utilize easily crawled content available everywhere lying around in the Internet attic. It also takes tremendous computing power to conduct ML and process this data effectively into some kind of appearance of sensible output. Hence, these tools will remain in the corporate hands of the creators no matter what they claim about “open source” — it’s simply too difficult for anyone but a giant corporate entity to support the huge costs involved. So this is about monetization and stickiness. Large companies are willing and able to pay the cloud costs if the customer gets dependent on using their tools. Flashback to the tool-centric sell of the 1980s, Silicon Valley style. All we need is an AI version of Dr. Dobbs Journal and we’re all set.

Previous attempts at generative AI have usually focused on small ML datasets, leading to laughable and biased results. Now companies are looking at the shift at Google in particular from ads to AI, along with Microsoft and FaceBook. Everyone believes they are in a race and frantically trying to catch up before all that sweet sweet money is locked up by one of them.

But is there really any need to “catch up”? Is this a real trend, or just an illusion? Google made its fortune on categorizing every web page on the Internet. It had plenty of rivals back then. I was fond of Altavista myself. But there was also everything from Ask Jeeves to Yahoo. 

Now Google and Microsoft are analyzing the contents of these big pots of data with ML But it’s not just for analyzing. It’s for creating content. Music. Art. News. Opinion. And you need an awful lot of processing power to handle all that data. So it’s now a Big Guy Game.

One of the approaches to eliminating bias is to use ML to process more and more data. The bigger the data pot, the less the bias and error. Well, that’s the assumption, anyway. But it’s a dubious assumption given the pots analyzed are often variations on the theme. Most search categorization is based on recent pages and not deep page analysis. Google is no Linkpendium.

All this, oddly, reminds me a bit of the UK mad cow fiasco, where their agricultural industry essentially cultivated prions by feeding animals dead animals. Like Curie purified radium from pitchblend, the animals who died of this disease were then processed and fed to other animals. And since prions, like radium, persist after processing, the prions were concentrated and made it up the food chain into humans.

So in like kind the tools themselves are feeding back into the ML feedlot and being consumed again. It may take longer than a few days, but we will be back to the same problems in terms of bias and error.

However, the gimmick of having a “machine” write your essay or news blurb is very tempting. Heck, AIs are claimed to take medical exams or pass a law class or handle software programming better than people.

But being a doctor or attorney or a software engineer is much more than book learning, as anyone who’s done the job will tell you.

And of course, there is now backlash from various groups who value their creative works and are not interested in rapidly generated pale imitations polluting their space and pushing them out. They didn’t consent to have their works pulled into a training set and used by anyone. Imitation is neither sincere or flattering, and is even legally actionable if protected by copyright, trade secret, or patent. It’s not “fair use” when you suck it all in and paraphrase it slightly differently.

This isn’t new. William and I ran into this in the old days with our 386BSD code. We were happy to let people use it and modify it — what is code if not usable and modifiable? But we asked that provinance be maintained in the copyright itself by leaving the names of the authors. And we had entire modules of code that were written denovo in the days when kernel design meant new ideas. It was an amazing creative time for us.

So I remember how shocked I was when an engineer at Oracle asked me about tfork() and threading, since a Linux book he had talked about it but he could find nothing in the Linux source code. I pulled out our 386BSD Kernel book and showed him that it was novel work done for 386BSD and would not work in Linux. Upon discussion it turned out that book just “paraphrased” many of our chapters without even considering that Linux did not incorporate much of our work because it was a very different architectural design. It misled software designers — but I’m sure it sold a heck of a lot more books than we did by turning “386bsd” to “linux”. So it is today, but a heck of a lot easier for the talentless, the craven, and the criminal to steal.

Now many software designers are upset because their source code depositories are used as the models for automated coding, and they don’t like that one bit. And I don’t blame them.

We lived it. And it was a primary reason why the 386BSD project was terminated. Too many trolls and opportunists ready to take any new work and paraphrase it. So get ready to see this happen again in music, art, news, and yes, software. The age of mediocrity is upon us.

1984, here we come…

Fun Friday: Old Style SV and the Great DOD Financial Fallback

Silicon Valley tech has long run on DOD and related monies. From established companies like IBM and Raytheon to think-tanks like SRI and Xerox PARC to startups, it was understood that national security was a lucrative opportunity. War, whether hot or cold, is good for business, if you’re the right kind of business.

Symmetric Computer Systems, founded by William Jolitz in 1982, was one such company. Unix, TCP/IP and networking software, and processor technologies were all considered controlled technologies subject to export restrictions. Heck, when William and I took a 375 computer to Germany for a USENIX conference, we had to have the appropriate license to carry one with us — and I had to take special courses in how to apply for and maintain such licenses. I also had nice conversations with the various national laboratories and security agencies who loved our little systems. Easy to transport, hardy, and enough processing power to handle any immediate intelligence and scientific need. William understood his customer. And his primary customer was not conventional.

But things changed here in the Valley. Companies exported their technologies to cheaper shores. We stopped making semiconductors. We stopped building computers. By the time I had co-founded InterProphet, an inventor of low-latency TCP chip technology we pioneered, few VCs would consider a hardware or semiconductor investment at all. Everyone talked about their “China Strategy” and their Guangdong manufacturing as if that was the only key to success (it wasn’t). Even the US government was asking for RFPs for technologies which were expected to be built, not by US firms, but by Huawai. Technology was viewed as trivial, of no value except to pass on as a bribe to build inexpensive trinkets to bored Americans.

Silicon Valley transmuted from one that invented technology to one that concerned itself with “unicorns”, aka fantasy companies devoid of financial fundamentals. One of my investors in InterProphet, Dan Lynch of Cybercash and Interop fame, warned William and me of the folly of nailing down the technology too soon, before investment was secured. Once the market cap was determined, you were no longer a fantasy. Sometimes it was better to not build the product, but just talk about it. This was an accurate assessment of the situation over the last twenty years. Unfortunately, it was one concession William and I could never make. We loved to build products. We loved to make things. We loved to create.

So we retired from the game. It was sweet while it lasted.

This little meditation does have a point. And it has to do with the change in the world economy with 1) the pandemic and 2) the war in Ukraine. Bear with me.

The pandemic of 2020-2022 led to a sea change in the structure of work. In companies where people could work remotely, such as software development, there was little impact of the disease on the workforce. People could isolate, maintain their income stream, and produce. Technology companies were winners.

For the majority of businesses, people could not easily isolate. Schools were shut down and remote learning introduced (a boon to the Zooms of the world). But remote learning on such a scale had never been done, and its effectiveness was poor. Children isolated from their teachers, peers and supports did not do as well as college-educated professionals using Slack and cloud tools. Stores and entertainment venues such as movie theaters were closed down. Medical offices limited visits to reduce the threat of contagion. People died in isolation wards of the disease, separated from their families. It was a tragic and depressing time.

Given so many lost their jobs due to the pandemic through no fault of their own, extensive government funding was used to essentially pay people to stay home while a vaccine was developed. Remarkably, within one year after Covid struck our shores, a vaccine was made available. This will go down as one of the most amazing scientific achievements of our time.

But as the threat of contagion has eased, the ability to get tech workers back in the office has stalled. The frustration of the CEO and investment class towards these “entitled” workers has been venomous and extreme as they continue to look on their now empty business properties. And as government supports for the consumer class have ended, so too has the artificial consumer boom. And heck, if those tech workers won’t come to the office to bend the knee to management, well, let’s fire them.

Silicon Valley is a small place. One jumps off the cliff, all jump off the cliff.

The second impact (this is beginning to sound like Evangelion) was the war in Ukraine launched by Russia. This war had an immense unexpected effect on Silicon Valley investment for a simple reason — much of the funds channeled through crypto and currency schemes dried up when the EU, the UK and the US agreed to impose sanctions on Russia and its many collaborators. And while VCs and its unicorns did not advertise it, the underpinnings of many financial deals were based on money flows that have existed since the Cold War and were now interdicted. Whomp whomp, indeed.

It’s taken about a year for these investments to collapse. The collateral damage: job losses, startup failures, venture funds with negative outlook, and eventually clawbacks from angry customers, investors, and LLCs. We live in interesting times.

We are now embarking on a new Cold War, with Russia, China and the lesser lights (Iran, N. Korea, and so forth). There is no longer a demand for a China strategy or Russian oligarch monies. And this is a win for startups involved in technologies which have a basis in national security, just like Symmetric Computer Systems started with 40 years ago. What was old is new again.

So what should we be looking at in well-positioned investments?

Strategic investments in battery technologies, carbon capture, and energy storage are still strong contenders for long-term investment. AI technologies focused on separating the wheat from the chaff for meaningful intelligence, both business and governmental. Alternative satellite creation and maintenance, especially for low-latency non-interceptible communications — something I was solicited and wrote an RFP for about twenty years ago — will be a growing opportunity. And good old-fashioned secure software, hardware and networking is always a safe bet in bad times as a lucrative acquisition by a big guy.

Avoid broad consumer gimmicks like AI journalists, unless you’re a VC that can sustain the hype for at least six months. The lack of sustainable dark funds and non-protected IPR (AI can’t hold patents or copyright) given the current Cold War climate makes it problematic until everyone figures out how to get around the currency strictures. SPACs are nothing but trouble (hey, Palantir, how’s it going?). And the launch side of satellites is locked up for now.

Sedate Sunday: NIF Fusion Breakthrough, UC Strike Settled, Nuclear Investments Thrive

As a sum up to an eventful week, LLNL’s National Ignition Facility (NIF) announced that they had achieved fusion ignition. “LLNL’s experiment surpassed the fusion threshold by delivering 2.05 megajoules (MJ) of energy to the target, resulting in 3.15 MJ of fusion energy output, demonstrating for the first time a most fundamental science basis for inertial fusion energy (IFE).” The facility is impressive, using 192 lasers coordinated to burst on a tiny deuterium-tritium capsule.

The media was less impressed: “We are still a very long way from having nuclear fusion power the electric grid, experts caution. The US project, while groundbreaking, only produced enough energy to boil about 2.5 gallons of water, Tony Roulstone, a fusion expert from the engineering department at the University of Cambridge, told CNN.” 

Given all the years and planning and building and incredible cost, the NIF wasn’t just a cool way to try to bootstrap fusion ignition as a clean energy source. As physicist Bob Rosner, University of Chicago and former director of the Argonne National Laboratory, stated in an interview with John Mecklin at the Bulletin of the the Atomic Scientists, “The folks who succeeded so splendidly in attaining ignition and self-sustained fusion on December 5 were not part of DoE’s fusion energy program (which sits in the DoE Office of Science Office of Fusion Energy Sciences); they’re working instead for the National Nuclear Security Administration (NNSA), which manages our nation’s nuclear weapons stockpile.”

What’s all this got to do with nuclear weapons? Well, in the late 1980s there was a lot of pressure to ban underground nuclear testing, and it succeeded. So now, how do you certify that your nuke work as advertised? “NNSA decided to build new experimental facilities (one of which was the National Ignition Facility), efforts were made to construct new simulation codes to help certify the weapons, and investments were made in new generations of advanced computers that these codes required and could run on. And NIF was meant to, in part, validate the design code approaches used for the weapons.  Before NIF was even completed, they chose a target experiment that—in combination with simulation codes advances—could demonstrate that we knew what we were doing.”

When William and I ran Symmetric Computer Systems in the 1980s, we sold Symmetric 375 computers to LLNL precisely for this reason. As William had a unique security clearance due to his earlier work at NASA, he was asked to examine the simulations and correct any issues with the Fortran compiler supplied with the computers – which was done. Later, when they switched to Sun Microsystem computers, they continued to call us about “Fortran compiler issues” in our systems which didn’t exist. When we told them we found no errors, they admitted it wasn’t our 375 computers that were the problem. Instead, they tried to get us to fix Sun’s Fortran compiler because the Sun people “wouldn’t return our calls”. We told them, nicely, to either buy more 375 computers or take a flying leap. They chose the leap. I suspect the compiler errors delayed their simulation work for about 5 years. Such is the cost of cheapness.

In other news, the long strike of UC workers is over. Graduate students, postdocs and academic researchers are the backbone of the university, but as the cost of living has skyrocketed, pay has stagnated. I’m pleased to see UC is finally dealing with this issue fairly.

Given the NIF breakthrough, perhaps it’s only fair to review the $3.4B in nuclear investments this year. According to Crunchbase, one major player, Bill-Gates backed TerraPower, raised $750M in it’s most recent round. TerraPower uses molten salt reactor technology. Dr. Shu, Professor Emeritus at Berkeley, did a talk back in 2016 at Microsoft on his patented two-fluid molten salt breeder reactor (2F-MSBR) using thorium which I found quite interesting (yes, William and I were there). Dr. Shu felt that this was the only way to combat climate change and save the planet in his lifetime.

As to fusion, even though the NIF has had billions of investment over decades and has only now achieved scientific energy breakeven, there is still a lot of money involved in seeing it through: “The biggest single fusion investment came in December, when Cambridge, Massachusetts-based Commonwealth Fusion Systems raised a huge round of more than $1.8 billion led by Tiger Global and also included investments from Bill Gates, Marc Benioff’s Time Ventures and about two dozen others. Just before that, in early November, Everett, Washington-based Helion Energy closed a $500 million Series E led by Sam Altman—with an opportunity for an additional $1.7 billion tied to reaching performance milestones.”

Expect even more money thrown into conventional and fusion energy investments after NIF’s announcement.