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: this week I explore the concept of examining the present to try and glimpse the future by looking back at the Video Toaster product from the 1990s, contrasting it with new transformer AI models that may have a similarly revolutionary impact on the world of design and engineering; hydrogen arrives in passenger train engines and Amazon's warehouses; California's new EV legislation is missing vehicle-to-grid charging; TikTok's impact on standup comedy; the risk of hiring a fake employee over video; tight labor supply in the heartland of America continues to hamper manufacturing growth; and, much more below...

Stuff about Innovation and Technology
Next Video Toaster?
Video Toaster was a hardware and software product from NewTek in the 1990s that allowed anyone with a PC to produce and edit professional quality video with computer graphics effects. The seeds of our prodigious video output today – 500 minutes of video uploaded to YouTube every minute, endless TikToks, Instagram, etc. – were planted with the Video Toaster. (Here is a promotional video for the Video Toaster 4000; fun fact, one of the product’s co-creators was Brad Carvey, brother of Dana Carvey and the inspiration for Garth in Wayne’s World). I was thinking about Video Toaster because it’s a great example of a broader trend we see across a number of industries: taking something expensive and exclusive and making it generally accessible. If we had accurately seen the power of the early, at-home software/hardware (PCs themselves are another example of taking something that was large, expensive, and exclusive and making it available to the masses) we would have foreseen many of the most powerful platforms on the Internet today. In other words, understanding Video Toaster in its heyday might have allowed us to peer down a probable future path. The question arises: what tools today are going from exclusive to inclusive that might inform how our future unfolds? One candidate I can think of is transformers, the new AI systems created from a 2017 Google innovation. Here is what I wrote about transformers in #349:
Google’s new text-to-image algorithm, Imagen, is capable of creating some rather strange but accurate representations, such as a “photo of a panda wearing a cowboy hat riding a bike on a beach”, or oil paintings of equally silly scenarios in the style of any artist. While the model has reached a breakthrough in language interpretation, the team is not releasing it to the public due to various ethical concerns over potential misuse. However, you might have a shot at creating your own weird art mashups using OpenAI’s Dall-E (Dalí + Wall-E), which is allotting access to 1,000 new users a week. Dall-E’s creators also have ethical concerns about how such models reflect society’s ingrained biases (e.g., CEOs are more likely to be imaged as male) or whether or not images should represent more idealized views of the world. These models are part of a broader set of transformer AI engines attracting a lot of attention and funding. After reading this Verge review of Dall-E, I can't help but wonder if programs like Photoshop, Canva, etc. will lose the majority of their design value when you can just say what you want and get it instantly. Could this eventually happen with not just images, but video? Give me a 90-minute rom-com starring Jeff Goldblum and Annette Bening with a spy thriller sub plot set in Berlin in 1983 with the style of Werner Herzog. It feels like we may be getting much closer to the computer interface in Star Trek being a reality. Could transformer models also ultimately replace other traditional apps beyond design software? What about architecture and engineering? Design me a three-bedroom house out of concrete and wood in the style of... Obviously the data and answers don't exist for many applications beyond images today, but it seems plausible given enough time. As I've noted in the past, context and the ability to analogize is key for AI, and maybe it's just a gimmick that is fooling us, but there seems to be some element of higher level interaction in these transformer models. Paradoxically, as these new models allow us to tinker, rather than remove agency and human influence, they might actually increase our ability to articulate more accurately what we envision in our heads.

Another application of transformer models could be in biology, e.g., designing a protein with specified characteristics, or simulating the interactions of two different drugs – based on no other input than basic commands. And, even software itself yields potential. Perhaps, in the not-too-distant future, I will be able to say: “create an app that...” and have it appear, ready to use. Today, semiconductor design is one of the most complex art forms, but perhaps one day it will be as easy as: “I need a chip that does...” Already, marketplaces for transformer model prompts are emerging to help people leverage these new platforms. Complex questions of prior art and ownership will arise as new designs are created on troves of data. Who owns a new creation if it's built on thousands of pieces of information, in some cases without us evening knowing how the AI built it?

More broadly, the democratization of complex simulations may also be enabled by transformer models. For example, IEEE reports on an AI-designed and 3D-printed heat exchanger that is 10x more energy efficient for heating and cooling. IEEE also reports on the new software-designed floating wind turbines that, if successful, would open up 60% of potential offshore wind real estate that is currently cost prohibitive and/or impractical for deployment of current designs. Sandia Labs developed an Offshore Wind Energy Simulator (OWENS) tool that engineers can use to create new designs.

A fascinating trend in design is the move from simulation to emulation, which recreates the hardware as well as the software environment. In the past, we might have sat down with a sophisticated design program, sketched out a theoretical wind turbine or heat exchanger, and then simulated how it might function in the real world. But, with machine learning and AI, we can instead say something more akin to: here is what the world looks like, now go and create the best solution. It effectively inverts the job of design from “I have an idea” to “what should my idea be?”. Microsoft’s head of the AI4Science research division, Christopher Bishop, describes this as the fifth wave of scientific discovery. With a little imagination, you can see how a transformer model and a large machine learning system could allow anyone to design anything. It feels like the Video Toaster moment could be coming to the world of design and engineering. The future is unpredictable, but one of the best ways to see where things might end up is to examine the present very closely for changes in behavior that might stick. Where else do you see the Video Toasters of today across the economy? Which new technologies are taking something complex and exclusive and opening it up to a new set of users, perhaps allowing us to glimpse the future based on where we stand today?

H2 Choo-Choo
Germany has started service with the world’s first hydrogen-powered trains. Fifteen diesel locomotives were replaced with fourteen hydrogen models for passenger train service. Fueled solely by hydrogen fuel cells with a 1,000-km range, the locomotives can run for an entire day before refilling. In other hydrogen news, Amazon has contracted with Plug Power for 10,950 tons of green hydrogen, enough to power 30,000 forklifts or 800 long-haul trucks annually.

De-ICEing
California will ban the sale of new gasoline cars starting in 2035, with a medium-term target of 35% of new vehicles being zero-emission by 2026. California is the largest market for cars in the US at around 1M per year, and around one-third of US states have historically followed its emissions policies. Missing in the new legislation is a requirement that EVs be equipped with bidirectional charging, which could have allowed this potentially massive fleet of vehicles to act as a decentralized vehicle-to-grid power plant, providing stabilization, storage, and generation when needed (see last week’s paragraph on Tesla’s VPP, which is also operational in Texas; notably, however, the company only uses Powerwalls because Tesla vehicles are sadly not capable of bidirectional charging). We’ve seen countries around the world talk about phasing out ICE vehicles, but, given the issues with power generation (see the drought section last week) and the increased burden on the grid to charge cars, a coordinated effort is likely going to be needed to manage charging.

AI Taking Orders
ConverseNow is a chatbot customized to take phone orders for restaurants or answer other questions customers have. The tool maker “claims its offering nearly doubles peak-hour volume ordering from restaurants’ voice channels, and that it has helped operators boost same-store sales up to 30%. ConverseNow can also raise average ticket prices up to 20% and provide up to 12 hours of additional labor per restaurant per week”. A topic I discussed in #339 was the potential for chatbots to evolve into vertically focused niches:
Smart assistants still seem pretty dumb to me. Because of an extreme lack of context, the current offering of broad, horizontal assistants like Alexa, Google Assistant, and Siri are essentially just voice-controlled versions of web search. A vertical, use-case approach is likely to take off and supplant these overly broad, utilitarian voice assistants. One example the Washington Post recently featured is ElliQ, a robot uniquely designed as a companion for elderly folks. We’ll also see chatbots optimized for customer service, kids, office, medical, personal companions, etc. Ultimately, it wouldn’t be surprising to have a platform for specialty AI assistants, offering open APIs to all sorts of resources like Google search, apps, media, enterprise software, medical devices, smart home automation, etc., that allows 3rd parties to build specific AI assistants on top of it. And, as I’ve noted before, these assistants will be walking around with us virtually in augmented reality in the next few years.

TikTok-Fueled Comedians
Amid all the talk of the zero-sum business model of TikTok, this CNET article on the app’s positive influence for performers at this year’s Fringe Festival in Edinburgh is enlightening. In some cases, shows themselves are designed to feel like the voraciously-paced TikTok app, but, primarily, the app has allowed a new group of performers to find their audience and hone their material for the real world.

Hiring Deepfakes
A new vector for hackers is to use deepfake technology to pretend to be legitimate job candidates in video interviews. Using images and/or audio along with the resumes of real people, nefarious actors can pose as someone else to land a job in the work-from-home world we find ourselves in. Once hired, the hackers may have access to internal systems capable of doing even more damage than a traditional phishing attack might yield.

Miscellaneous Stuff
Physical Activity Boosts Cognitive Function
Using your muscles is good for your brain: “Myokines are released into the bloodstream when your muscles contract, create new cells, or perform other metabolic activities. When they arrive at the brain, they regulate physiological and metabolic responses there, too. As a result, myokines have the ability to affect cognition, mood, and emotional behavior. Exercise further stimulates what scientists call muscle-brain ‘cross talk,’ and these myokine messengers help determine specific beneficial responses in the brain. These can include the formation of new neurons and increased synaptic plasticity, both of which boost learning and memory.”

“On the Road Again”
The NYT Magazine has an extensive profile, “Willie Nelson’s Long Encore”, about the 89-year-old’s inability to sit still as he works on his 98th studio album and resumes touring following a brush with COVID earlier this year that nearly took him out.

Stuff about Geopolitics, Economics, and the Finance Industry
Workers Wanted
The ongoing manufacturing renaissance in the US continues to be hampered by the dwindling labor force. In Ohio, Intel needs 7,000 employees to build its new fabs; however, state officials admit there simply are not enough people available to meet demand. Further, central Ohio labor is already tight due to a series of new plants being built, including a $365M Amgen biomanufacturing facility, three new Amazon and Google data centers, and various solar array projects. I spoke about the modestly growing number of examples of supply chain domestication in Reshoring Rising: "after decades of shifting overseas, deglobalization is a challenge given the lack of labor and infrastructure – not to mention the lost know-how – but there is clear evidence building that, at least in some cases, reshoring is economically and logistically feasible, in part thanks to technology. As I’ve said before, remaining largely a global trade society is far better for peacekeeping and progress, so finding an equilibrium between domestic and international trade/manufacturing would be ideal for ongoing prosperity."

✌️-Brad

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