Co Founder CMS Web Solutions Inc. Digital accessibility specialists. Periodically funny. Morning smile pusher.

Kawartha Lakes
Joined November 2008
Richard Gauder retweeted
🔥 HOT OFF THE PRESS For the first time ever, @iea.org has published a dedicated Electrification Report. An absolute treasure trove of data. Here are the key takeaways that stood out to me when I peer-reviewed it. 🧵
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We've been over this. The 'importer of record' pays the tariffs. A threatened US tariff on Canadian auto parts will be paid by US auto assembly. Without those specific parts, auto assembly throughout the US would halt. US auto assembly will be on the phone to the WH today.
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Richard Gauder retweeted
Me explaining AI to friends
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I'm a cardiologist. Something just happened today that I genuinely did not see coming — and it could change the future of preventive medicine more than anything I've written about on this platform. Midjourney — the AI company that became famous for generating images from text prompts — just announced a medical hardware division and unveiled a working prototype of a full-body scanner unlike anything that's ever existed. It's called the Midjourney Scanner. And it works like this. You step into a shallow pool of water. You stand on a platform that slowly descends — about two inches per second — through a ring containing roughly half a million tiny ultrasonic transducers, each the size of a grain of sand. Every one of them acts as both a speaker and a microphone, sending ultrasonic waves through your body from every angle and recording what comes back. 60 seconds later, you step out. The scan is done. No radiation. No magnets. No claustrophobia. No IV contrast. Just sound, water, and an almost incomprehensible amount of computing power — roughly 2 petaflops processing 17 gigabytes per second of raw acoustic data — reconstructing a 3D map of your entire internal anatomy down to half a millimeter resolution. Organs. Tissues. Blood vessels. Bones. Muscle. Fat distribution. All segmented by AI in real time. As a cardiologist who has spent months writing about how the standard screening playbook misses the majority of future heart attacks — this is the technology I've been waiting for without knowing it existed. Here's why this matters for the future of your heart. Right now, getting a detailed look inside your cardiovascular system requires either a CT scan (radiation), an MRI (magnets, claustrophobia, 45-60 minutes, $1,000+), or a coronary CT angiogram (radiation, IV contrast, limited availability). These are powerful tools. I order them regularly and they save lives. But they're reactive. You get them when something is already suspected. They're expensive. They're uncomfortable. And for most people, they happen once — maybe twice — in a lifetime. Imagine instead: a 60-second scan with no radiation that you could repeat monthly or quarterly. Tracking cardiac structure over time. Watching body composition shift. Detecting changes in organ size, fluid distribution, or vascular architecture before symptoms ever develop. Building a longitudinal dataset of YOUR body that AI can analyze for patterns no single snapshot would reveal. That's what Midjourney is building toward. The company plans 50,000 scanners worldwide over six years, with capacity for a billion scans per month. The first location — the "Midjourney Spa" in San Francisco — opens at the end of 2027 with 10 scanners alongside saunas, cold plunges, and a gym. The scan costs a few dollars. The experience is designed to feel like wellness, not medicine. The technology is built on Butterfly Network's ultrasound-on-chip platform — 40 modules per scanner — combined with Midjourney's own AI segmentation and reconstruction stack. David Holz, the founder, claims the system aims for image quality comparable to MRI in many aspects but at nearly 100x the speed with zero radiation. Now the caveats — because I'm a physician and the caveats matter enormously. This is a Gen 1 prototype. About a dozen people have been scanned so far. Current scan time is actually closer to 20 minutes, not 60 seconds — the system is bottlenecked by bandwidth and reconstruction algorithms. The 60-second target is aspirational for future hardware generations. It is not FDA-cleared for diagnostic use. Midjourney is starting with body composition maps — a category below diagnostic imaging in the regulatory hierarchy. The path from "beautiful 3D body scans" to "clinically validated diagnostic tool that your cardiologist can act on" runs through years of clinical trials, comparative studies against MRI and CT gold standards, and FDA review. No independent clinical validation has been published. The imaging claims come from Midjourney's own demonstrations. Comparative data against established modalities does not yet exist. And the privacy implications of full-body internal scans at planetary scale — a billion scans per month — is a conversation that hasn't even started yet. So I want to be precise. This is not ready for clinical medicine today. It may not be ready for years. Many ambitious medical hardware projects have failed in the gap between prototype and product. But. The fact that a working prototype exists — producing real segmented 3D anatomy from sound waves and compute alone — means the physics works. The engineering works. The question is no longer "is this possible" but "how fast can it be validated and scaled." And if it is validated — if the resolution holds up against MRI, if the AI segmentation proves reliable, if the regulatory path clears — then what we're looking at is the most significant new imaging modality in 50 years. For my entire career, preventive cardiology has been limited by the fact that seeing inside the body is expensive, slow, uncomfortable, and infrequent. We catch disease late because we image rarely. We image rarely because imaging is hard. A 60-second, no-radiation, spa-based full-body scan that costs a few dollars would demolish every one of those barriers. I've written about AI detecting inflamed arteries. About gene editing curing cholesterol. About GLP-1 drugs rewriting metabolic medicine. About cellular reprogramming reversing aging. This is the missing piece: the ability to see inside every human body, routinely, safely, and affordably — so all of those interventions can be deployed before the disease arrives instead of after. The company that taught AI to generate images from imagination just built a machine that generates images from the human body. The future of medicine showed up today from the last place anyone expected.
Announcing a new division of Midjourney called "Midjourney Medical"
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Richard Gauder retweeted
Satya Nadella
@satyanadellaJun 14
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Richard Gauder retweeted
Honestly, this is the most accurate diagram I've seen. Waterfall: You plan for 18 months and deliver exactly what nobody needs anymore. Agile: You deliver something usable at every step, but the CEO keeps asking, "Where's the car?" AI: You get the car on day one. It has six wheels, the doors are on backwards, and it has a rocket launcher. You spend more time making it yours than actually "building"; it's shaping. owning. verifying. That's what the best AI developers do now. They don't build. They shape and own.
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Richard Gauder retweeted
⚡️This is the moment the dam actually cracks. Chat was a toy. Scheduled tasks is a labor primitive. When a model can do work on a schedule, inside your tools, without you asking, it stops being “help.” It becomes the cheapest employee on earth. And the honest part is ugly. Most white collar work is recurring coordination. Weekly decks. Status updates. Reconciliations. Ticket grooming. Inbox triage. Reporting. Notes. Summaries. Follow ups. That is a huge percentage of payroll disguised as “knowledge work.” This feature is replacing the heartbeat of office labor. Here is what happens next. 1. Teams stop hiring juniors Entry level roles exist to absorb grunt work and learn. If the grunt work is automated, the learning ladder collapses. You get a smaller funnel, fewer promotions, more gatekeeping, higher anxiety. 2. Middle management gets ruthless If they can ship the same output with 30 percent fewer heads, they do it. They get rewarded for efficiency. They do not get rewarded for protecting your job. 3. Work becomes a control problem The new premium is not producing the thing. The new premium is owning the system that produces the thing. Permissions, checks, exception handling, accountability, audit trails. The winner is the person who signs the work, not the person who drafts it. 4. The market bifurcates A small group becomes “AI operators” and their output per person explodes. A larger group becomes replaceable because their tasks can be parameterized. 5. The platform war shifts Every SaaS becomes a battlefield over agent access. Who has the integrations wins. Who has the best governance wins. Who can prove compliance wins enterprise. The truth behind all of this. The economy is about to learn what abundance feels like for cognition. When cognition becomes abundant, wages fall for anything that looks like cognition without ownership. People keep asking if AI will take jobs. The real answer is that AI turns jobs into margins. Margins get competed away. So what is left. People who own distribution. People who own capital. People who own the decision loop. People who can take responsibility when something breaks. If your role is “I deliver the weekly output,” you get squeezed. If your role is “I decide what the weekly output should be, why it matters, and what we do next,” you get elevated. That is the real shift. Not smarter. Not faster. Autonomous.
Claude
@claudeaiFeb 25
New in Cowork: scheduled tasks. Claude can now complete recurring tasks at specific times automatically: a morning brief, weekly spreadsheet updates, Friday team presentations.
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Richard Gauder retweeted
CEO of Microsoft AI Mustafa Suleyman joins FT editor Roula Khalaf to explain why most of the tasks accountants, lawyers and other professionals currently undertake will be fully automated by AI within the next 12 to 18 months ft.trib.al/SZ4Lti1
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Richard Gauder retweeted
Was talking to a new immigrant from England on the proper frame of mind for the winter depths in Canada. Best to imagine you live on a spaceship. You go outside the 'airlock', in what is essentially a spacesuit, and run back to your cozy home/car/office as soon as possible. And just like space and the universe, it is timelessly beautiful and captivating. There's raw honesty in facing -30C temps regularly. If you can survive this and build a life here, everything else is easy.
Touchdown in downtown Toronto. The coldest day of the year. @BBishopAirport @porterairlines @PinnacleINTL
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Richard Gauder retweeted
How did solar get cheap? Phase 1: 1950-1990s - NASA Solar was invented in the US by Bell labs and pretty much only used by NASA who needed something very lightweight to power their space assets. Phase 2: 2000 - Energiewind The German government passed a law where it guaranteed that if you put solar panels on your roof the German government would pay you a high feed in tariff. Demand exploded. Phase 3: 2005 - 2015 - China In Europe German manufacturers could not meet their demand at home and Chinese entrepreneurs saw this fixed arbitrage opportunity and went all in. Chinese companies like Suntech took on huge government loans and built vast factories. Spain and Italy joined Germany with solar subsidies. Because of the price fixing in Europe the market arbitrage held as the solar cell manufacturing output in China exploded. Phase 4 2015-2025 - Swanson’s Law Once the big Chinese gigafactories were built, Swanson’s Law kicked in. This is the learning curve where manufacturers compound marginal gains and accumulate 1,000s of solutions to solved problems. 1. Ingots, originally they grew small Si crystals this was a slow batch process. Later they used continuous Czochralski pulling where you refill the crucible whilst the machine is still running. Saving hours of cooldown per batch. They also learnt how to grow huge single crystals that were 2-3 meters long. 2. Wafers, originally they sliced the crystals into wafers using saws. This was slow and turned 40% of the Si crystal into sawdust (kerf loss). The fix was diamond wire cutting, the wire was razor sharp, fast, much thinner than the saw, easier to keep clean and far less wasteful (4% kerf loss). Wafer costs plummeted. 3. Cells, you have to print silver lines on the back of the wafer to collect electricity. Over 15 years silver printing resolution improved and silver use was reduced by 70% whilst also blocking less sunlight. The mirror backing used to be aluminium which captured some solar energy as heat and was lost, so they added a dielectric passivation layer that captured more photons and improved cell conversion efficiency without changing materials. 4. Modules, engineers realised that by laser cutting panels in half they reduced electrical resistance in the cells. This means the panel runs cooler and produces more power. Bifacial modules then emerged, instead of plastic backing. Panels were made with glass front and back, this means panels also collect energy bouncing from the ground below the panel which again boosts the panel output in operation. These gains all compound to make the panels 90% cheaper over the course of 10 years. Chinese manufacturers are now looking at perovskites as a paradigm switch. It’s essentially a superior crystal to silicon for absorbing light. You can make them from liquid chemistry and you can print them. Silicon is great at capturing red and IR light perovskites can be tuned for blue spectrum. You can then go tandem and pair both silicon and perovskites in the same modules. Now panels are cheap, because they’re simple things to make. They cost around $0.10/watt ex factory. A solar installation costs around $3.00/watt and the panels themselves are now a very small part of the cost of a solar installation which is dominated by land, labour and structures. Much of industry is like this. If you can consolidate manufacturing under one roof, you learn all the improvement opportunities much faster, because you just see more stuff.
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Richard Gauder retweeted
The Boring Company is quietly expanding the futuristic Vegas Loop underground Vegas Loop already feels like a cheat code: hop into a Tesla (or Cybertruck) underground and bypass the chaotic surface traffic As of December 2025: → 8 stations live (LVCC campus + Resorts World, Westgate, Encore) → ~3.5 miles of operational tunnels connecting the Convention Center to nearby resorts → Over 3 million rides completed (boosted by huge events like SEMA & Cowboy Christmas) → Turns 30–45 min surface trips into quick 2–8 minute tunnel rides → Free inside LVCC, ~$5–10 for resort connections → Cybertrucks deployed on routes like LVCC–Encore → Full Self-Driving tests underway – driverless rides coming soon And this is just the start... @boringcompany is approved for 68 miles of tunnels and 104 stations, connecting the airport (Phase 1 targeting Q1 2026!), downtown, Allegiant Stadium, UNLV and more – with 2–8 min rides and up to ~90,000 passengers/hour at full build-out via a dense autonomous EV network This isn’t just congestion relief – it’s the future of smarter, greener urban transport 🌍
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PHILOLOGY DUJOUR The Lord's Prayer: Debt became "sins" in some translations. The Catholic French translate the Latin "debita" into "sins" or "offenses", same with the Catholic/Maronite Arabic خَطَايَانَا، while the original Greek οφειλή and Christian Aramaic ܚܘ̈ܒܝܢ means debt.
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Richard Gauder retweeted
Starcloud (@Starcloud_Inc1) recently made history by launching a satellite with an NVIDIA H100 into orbit — the first time a GPU that powerful has ever operated in space. It's the first step toward building AI data centers in orbit, powered by continuous sunlight and cooled by radiating heat into deep space. Their approach could one day rival the world's biggest data centers while using less energy, zero fresh water, and far lower emissions. YC's @aaron_epstein visited Starcloud's HQ, where co-founders @philipjohnston, @EzraFeilden, and @Adi_Oltean explained how they built a working prototype in just 15 months — and why big tech is racing to space for AI compute.
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There have only been two Game 7s in the last eight World Series When Max Scherzer takes the mound tomorrow night, he will have been a starting pitcher in both of them
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Richard Gauder retweeted
EXPLAINING THE WORLD SERIES TO AMERICANS (WHO WANT TO MOVE TO CANADA)
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Richard Gauder retweeted
As I was afraid of, Atlas doesn't have some trick to defeat the deadly trifecta security issues of Chat + Browser. As much as I'm dying to use it, I'll wait for infosec to figure out a way to fix it. Hopefully. One day. Maybe.
Wrote up my first impressions of ChatGPT Atlas, OpenAI's new browser - I remain unconvinced by the entire category of "browser agents", the security and privacy challenges still feel insurmountable to me simonwillison.net/2025/Oct/2…
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Hey #WordPress fanatics (and anyone curious what all the fuss is about) get your #WordCampCanada tickets while they last! #WCEH canada.wordcamp.org/2025/tic…
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Richard Gauder retweeted
It's here! 200+ hours of work and includes 19 different builders. There's a Zoom video where I discuss the report, plus you can request access to view a detailed Google Sheet and also view all the test sites.
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