Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

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In today’s post: plug-and-play solar panels could speed adoption; a breakthrough in wireless EV charging; drones, hydrogen-powered planes, and fancy robot vacuums; bringing transparency to US healthcare; a blockchain milestone for the California DMV and the prospects of a US bitcoin reserve; a blood test for memory loss due to Alzheimer's; the blameless consumer; the paradox of digital monopolies and why we should want Google to win; checking in on the weather forecast for the AI bubble. Welcome back to SITALWeek!

Stuff about Innovation and Technology
DIY Solar
The NYT reports on the rise of small-scale solar installations in Europe that can instantly provide power to a home simply by plugging the panels into a wall outlet. The plug-and-play solar panels can hang from a balcony and eliminate the costly, time consuming installation required to tie traditional solar power into circuit breaker panels and register with utilities. 
 
Remarkable Resonance
Oak Ridge National Laboratory has a prototype 270kW wireless charger, which they demoed using a Porsche Taycan. The wireless charger can take an EV from 10% to 80% in 20 minutes, rivaling the fastest DC superchargers on the market. This wireless breakthrough could potentially overcome many common issues with corded fast chargers, including broken plugs and maintaining liquid cooling systems. “The Oak Ridge system pairs a magnetic resonance transmitter pad with a receiver mounted to the underside of the car. The system’s secret sauce is its polyphase windings—lightweight electromagnetic coils arranged over a coil to generate a rotating magnetic field that eliminates current ripples and field cancellation.” And, if you’re wondering (like I was), yes, the 19 µT electromagnetic field is safe (it’s well below the 5 Gauss [500 µT] safety threshold that’s used in laboratory/medical settings; for reference, Earth’s surface magnetic field readings range from 25 to 65 μT). Wireless chargers require close proximity to the vehicle-mounted receivers (due to rapid decay in charging strength with distance). In other wireless power news, theories abound for using microwaves to beam power from space. A one square kilometer solar array in space could beam down 1GW of power, roughly enough for 875k homes. 
 
UTM for BVLOS
The FAA has given multiple commercial drone delivery operators permission to fly autonomously in the same airspace at the same time. Previously, only one drone company could occupy an airspace. Drones from Google’s Wing and Zipline can simultaneously operate in Dallas, Texas using the UAS Traffic Management (UTM) technology for Beyond Visual Line of Sight (BVLOS), which enables drone-to-drone communication. This video from Zipline shows how UTM works.
 
Hydrogen Heli
The EVTOL maker Joby conducted a 523-mile flight using their emission-free H2FLY hydrogen-electric technology. Joby’s CEO JoeBen Bevirt commented: “Imagine being able to fly from San Francisco to San Diego, Boston to Baltimore, or Nashville to New Orleans without the need to go to an airport and with no emissions except water. That world is closer than ever, and the progress we’ve made towards certifying the battery-electric version of our aircraft gives us a great head start as we look ahead to making hydrogen-electric flight a reality.” Here is a short video of the record-breaking flight.
 
Rosier Roomba
iRobot’s new $1400 Roomba Combo 10 Max floor cleaner not only vacuums and mops floors, but can automatically clean and dry its mop head, as well as replace its cleaning fluid and empty its dust container. It’s the closest effort yet to a fully autonomous floor cleaning machine (here is a video demo). Perhaps next they could add a robotic arm to first clear the floor of socks and dog toys. I recently read a good post from iRobot cofounder Rodney Brooks on real-world robot deployments and also re-read his 2008 essay “I...Am a Robot”. Whether it's autonomous delivery drones, autonomous EVTOLs, complex robotic floor cleaners, or robot dogs that vacuum up cigarette butts on beaches, it’s encouraging to see so many robotic milestones for a multitude of form factors finally come to fruition.
 
DMV Digitizing
The California DMV plans to put over 40 million car titles on a blockchain to streamline transfer of vehicle ownership. If successful, this would be a milestone for creating blockchain-based records of real-world objects at scale. California’s DMV already has an app for storing your driver’s license on your phone (and digital ID access will soon be available natively with Google Wallet). The promise of holding legal possession of items on a blockchain appears to be moving closer to reality. In other crypto news, the US government’s notion of building a bitcoin reserve is logical and thought provoking. After going through the classic hype cycle and trough of disillusionment, blockchain technologies and currencies could emerge from their cocoon in the next decade with a new wave of innovation and adoption. 
 
Cost Plus Transparency
Mark Cuban’s success driving down prices for consumers and alleviating drug shortages with Cost Plus Drugs continues to inspire. And, his crusade against PBMs will hopefully prove successful. While the Internet has pulled the curtain back on many complex industries that price discriminate (while simultaneously increasing the ability for others to collude against consumers, e.g., witness the recent FTC probe into surveillance pricing), digitalization has been slow to impact healthcare to date. Cuban’s tactic to enable a healthcare cost revolution is deceptively simple: transparency. 

Miscellaneous Stuff
Circulating Brain Biomarkers
A new blood test can accurately attribute memory loss to Alzheimer’s in 90% of cases, a success rate that far exceeds the diagnostic success of either neurologists (73%) or primary care physicians (60%) – and is a far more accessible option than brain scans and spinal taps. The peptide p-tau217 test is indicative of amyloid plaques in the brain, but it could be a while before it’s approved for routine use. If a blood test for Alzheimer’s is commercialized, it could greatly reduce the time between symptom onset and diagnosis, allowing for earlier interventions. 
 
Sugary Resurrection
Leaf Brands is an independent candy company that acquires trademarks for dead candy brands that still have nostalgic hold over people’s sweet tooth. Examples include Astro Pops, Tart N’ Tinys, Hydrox, and Wacky Wafers. Niche brands have frequently been mismanaged and/or neglected in the hands of large candy conglomerates, leading to an early demise. Leaf revives such brands, recreating the candies through careful flavor testing and manufacturing outsourcing. Leaf has also created at least one novel candy of their own: 
Farts Candy, a chewy Nerd-like product. Now, most of the industry is controlled by four major candy companies, and because of their size, they are afraid to take any chances, [Leaf founder] Kassoff said. “Can you imagine an executive at Hershey in a meeting saying, ‘I have a great idea for a new product, it’s called Farts.’ They would probably be fired. We have a major problem in our industry and that is the lack of creativity and fun.” 
Farts are available in both Fruiti Farts and Sour Farts flavors.

Stuff About Demographics, the Economy, and Investing
Consumer Scapegoating
Back when I covered the teen retail/fashion industry (many, many decades ago) I got used to CEOs blaming anything and everything for weak clothing sales: weather, supply chain, the economy, elections, inflation, etc. In every instance, weak sales were actually a result of a fashion cycle misstep, changing consumer preferences, or, on longer time horizons, demographic shifts in their customer base. When sales were ahead of expectations, the companies, of course, took all the credit. I never once heard the CEO of Oakley say that the company beat the quarter because it was unexpectedly sunny outside. I’m reminded of this experience as I read many stories over the last couple of months of CEOs blaming consumer weakness for light sales. In every instance that I dug into, there was no evidence of consumer weakness. Indeed, despite the reflexive headline circus in business media right now that suggests we are imminently headed for (or already in) a recession, there’s scant legitimate evidence of struggling consumers. There are some signs that consumers are becoming pickier and returning to the borrowing/spending patterns that predominated before COVID induced economic chaos (a time period through early 2020 when the consumer and economy plugged along at a healthy pace). Looking beyond the scapegoating, I found that the underlying reasons for poor sales grouped into a few different categories: GLP-1 impact on consumer demand for a variety of products, ranging from grocery-store to luxury items; demographics (aging customers); changing preference/tastes (particularly as Millennials and Gen Z enter peak consumption years); and, perhaps the most common, companies that used the COVID disruption as an excuse to take advantage of customers are being displaced by innovators with a better value proposition. I am not suggesting CEOs are intentionally lying about their businesses, but I am saying that management teams are often the last to know the truth about their own products/services, and they are quick to assign blame to outside factors. And, CEOs are as highly vulnerable to the same algorithmic influences as everyone else, i.e., if they hear other leaders blame the consumer in the news, they too will adopt that point of view. In January 2023, 98% of CEOs queried by Ernst & Young predicted an imminent recession. Over eighteen months later that recession hasn’t happened, and it may still not come to pass anytime soon. So, next time you hear a company reflexively blame the consumer (or blame anything for that matter), your skepticism meter should be pinned at its limit. 
 
Search Win-Win
Last week, a federal judge ruled that Google was guilty of building an illegal online search and advertising monopoly. This ruling marks yet another example of US and EU regulators continuing to overlook the value of natural monopolies in digital platforms. In many cases, it makes sense to have a winner-takes-all product due to the network effects that accrue for all sides of the marketplace. In the case of Google, Pareto efficient auctions for advertisers assure maximum ROI and provide revenues for Google to invest in maintaining the best user experience. Competitive products are a click away, and it’s hard to argue that Google’s competitors weren’t deep pocketed enough to compete. According to the judge’s musings, Microsoft even offered to hand over Bing to Apple for free, but Apple understood the product quality mattered and that Bing wasn’t even close to being in the same league as Google. It’s possible the same winner-takes-all scenario will play out as our interaction with everything shifts to a conversational AI interface; however, LLMs currently appear to be more of a (very expensive) commodity than search engines ever were (which could change). While I suspect it’s likely this ruling against Google will be overturned on appeal, it’s worth thinking about the consequences if it were to stand, as the exercise illuminates some of the strengths and weaknesses amongst the various big tech platforms. As long as Google maintains a superior product, they would likely come out ahead financially if they were barred from paying a TAC (traffic acquisition cost) to Apple for search queries, an amount today that’s in excess of $20B a year. Further, Google’s AI model Gemini is well positioned to cement Google’s position as one of the gatekeepers of the digital world. Apple would likely be prevented from striking a new exclusive deal with another search or AI product, thus harming their cash flow. It would be difficult for Microsoft/OpenAI to build enough traffic in the consumer search market to create a network effect large enough to catch Google’s twenty-year lead (although Microsoft could still build enough traffic in the business world). Meta is in a unique position, given their current dominance in digital conversations, to build powerful AI+search products, but they have yet to prove such a concept would gain use on their social apps. Meta has recently amped up its war with Apple by attacking the iOS iMessage monopoly, taking WhatsApp to 100M users in the US. This move demonstrates Meta’s ability to flex its dominance in social distribution to drive product adoption. As for Apple, there are two schools of thought: One framework is that Apple could free ride the hundreds of billions of dollars in AI investments by Microsoft, Meta, and Google by ensuring the best product is available on Apple devices. Yet, it seems entirely plausible that Apple could be cut out of the AI platform transition and become solely a commodity hardware provider, or worse: a new AI-based operating system could crown a new hardware winner in smartphones or augmented reality devices, leaving Apple to become a very large footnote in the history of technology companies. If I were Apple, I would be hedging my bets by investing much more aggressively in homegrown AI technology. While we can’t predict the future of the search/AI markets in detail, we do know that government regulation of large industries is always a fruitless effort, with regulatory capture inevitably cementing monopoly power. If this topic is of interest, we have an overview and two whitepapers on regulating digital industries available here. 
 
Dream Big, But Keep an Eye on the Sky
Back in May, I discussed the risk of particularly dangerous situations (PDSs), alluding to the euphoria in the markets, particularly centered on AI. Longtime readers know that we’ve been discussing the exciting potential for transformer models (the basis of today’s LLMs) since 2019, and I am likely on the far positive extreme of the spectrum in terms of my expectations for the new technology over the next decade and beyond. But, history teaches us to always be situationally aware of where expectations sit relative to reality during technology hardware hype cycles. One of the ways to gauge the wild expectations in such technology investment cycles is to reverse engineer the implications. Over the Northern Hemisphere summer, as AI stocks were precariously perched atop steep stock increases, I read about predictions like Nvidia becoming a $50T market cap and GPUs garnering a $10-20T investment (which also implies a very lofty market value for Nvidia). While I wouldn’t rule anything out (that’s another important lesson from the history of technology investment cycles!), I think it’s important to remember the Catch-22 of a rapid rollout of AI. All technology investment cycles come with turmoil in the job market, which, historically, has played out over long time periods. The Industrial Revolution, for example, took centuries. Combustion engines took decades to replace horses. Even the wheel’s arrival around 6,000 years ago probably took a while to obsolete all the boulder luggers. Adoption of AI technology, however, has, at first pass, the potential to be dramatically compressed. For one, AI is the first technology that has a chance at replacing human brain power both computationally and at the executive function level, including reasoning, creative thinking, etc. Further, embodied AI operating in the physical world will replace human brains and brawn. And, unlike many other technology transitions, AI runs on existing cloud infrastructure, networks, and devices. However, in order to believe the multi-trillion-dollar investment figures being casually thrown around, you would have to reconcile those numbers with the extreme job destruction they imply, which would send the economy (which is ~70% consumption based) into a tailspin. In that instance, CEOs really could blame the consumer! Thus, a rapid deployment of AI to replace human brain and muscle power would cause a circular reference failure in the economy due to job losses. Further, you need to explain where the power would come from to replace all the metabolically efficient human workers. Therefore, rather than bank on AI displacing humans wholesale, you instead need to believe AI will have minimal (or slow) impact on human jobs and instead focus on new inventions and the next waves of scientific revolution in sectors like healthcare, energy, and material science (which might create net new jobs overall). We can also envision AI hardware markets in the trillions if they are underpinning an entirely new agent-based digital economy that does not take jobs away from humans. I don’t believe we are out of tornado season yet for the AI expectations bubble. As I noted in PDS regarding weathering storms: 1) always have access to a safe space, and 2) make sure you are looking in the right direction; you might think the storm is up ahead, but it could be funneling down on you from above. And, always lean on those lessons from complex adaptive systems. It’s important to balance skepticism and fear with optimism and hope for those AI-driven inventions we can’t even dream of yet.

✌️-Brad

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