Researchers at Harvard and Brigham and Women’s Hospital found that transplanted hearts shift toward the biological age of their recipients. Old hearts get younger in young bodies, and young hearts get older in older ones. Which is nuts. Today, we're launching a partnership with our friends @runwayml to, among other things, bring one of the stories from each week's Dose to life in video. I'm not great at it yet, but not bad for a few prompts! And I'm excited to get better. I have zero talent in film/video, but I can write, which now means that I can make movies. Age of miracles.

After 9 years. 16K+ family homes. 500M sqft inside real homes covered, we know home robots are being built in wrong order. So we built Matic the way nature grows a child. Finally, sharing our vision: 1.⁠ ⁠Why robots get stuck at the demo 2.⁠ ⁠Why labs can't ship robots 3.⁠ ⁠Why we started with eyes, not hands 4.⁠ ⁠The 99.999% rule in robotics 5.⁠ ⁠Where Matic is going next 1. Why most robots get stuck at demos Robot demos look brilliant in a room arranged around its limitations: familiar lighting, predictable furniture, nothing troublesome on the floor. A family’s home makes no such accommodations. There are cables, toys, shifting rugs and, occasionally, dog poop. Yes, humanoids will need to avoid that too. Repeating a task under familiar conditions of uncluttered floors is not the same as handling an unfamiliar home with all its chaos. 2. Why labs can't ship robots SLAM (Simultaneous Localization and Mapping) is how a robot maps its surroundings and locates itself within them. Ask most academics and they'll tell you it's a solved problem. But real homes are the most chaotic spaces that exist. There are glass doors that look like open doorways, mirrors, stairs, rugs, charging cables, and Legos placed all around. So ask yourself: if indoor mapping and navigation is "solved," where are the robots? Why aren't airports, hotels and grocery stores full of them? Calling it “solved” misses the question families actually care about: can I leave this thing alone and trust it? 3. Why we started with eyes, not hands Nature doesn't give birth to a fully working human. We took our cue from how nature develops humans: capabilities built on one another. Children learn to see before they learn to grab, and to grab before they learn to plan and handle the unexpected. Perception comes first. Manipulation follows. More complex responsibilities come after that. At every stage, the robot must earn the next job by doing its current one well enough. Before asking a robot to pick up a sock, we wanted it to understand where it was, where the sock was, and how to reach it. Most of the industry started at the top, with humanoids. We started at the bottom, with a robot whose job is to see and move through a home precisely with 1cm accuracy in any lighting condition. Floor cleaning gave that foundation an immediately useful job. It forced us to confront navigation, clutter, privacy and everyday reliability before reaching for more complex chores. The floor cleaner isn’t a detour from our larger ambition. It is how we’re building toward it. 4. The 99.999% rule in robotics At 90%, one in ten decisions is wrong, and a robot makes thousands in a single clean. That's the robot that bumps, gets lost, and falls down the stairs. Every extra nine is a new mountain. The failures get rarer, harder to find, and exponentially harder to fix. They barely even happen until they happen in your home. Matic's visual SLAM runs at 99.999% in 16K+ homes. We’re the ONLY unsupervised home robot at scale with pure vision-only full autonomy. If you ask us, the gap between 80% and 99.999% is where our 9 years of engineering went. We close that gap inside real homes. When Matic handles something imperfectly, it saves a short clip and keeps it on the device. It only leaves if the family chooses to share it. If they do, it gets labeled, fed back into the model, and every Matic gets smarter, including theirs. Families control what leaves their homes. We do the work of making the product better. Better robots earn trust > trust brings more homes > and more homes teach the robot more. 5. Where Matic is going next Phase one was perception and it's nearly done. Matic has covered 500 million square feet, 400K miles in thousands of real lived-in homes. Now phase two is going to be about manipulation. And our idea is to build a robot that doesn't just move through your home, but acts in it to eliminate even more chores. Each step must be useful today, not justified by something we promise tomorrow. The evolution of Matic is the revolution. The goal isn’t to put the most impressive humanoid in your living room. It’s giving your family time and energy back through robots that earn your trust, protect your privacy, and help without becoming another responsibility. More time for each other. Less work getting in the way. That’s Matic. Get yours today at

Today, we’re announcing Varda’s $250M Series D raise, bringing the total amount of capital raised to $598 million with a $1.6B valuation. This funding will help us build more vehicles, grow pharmaceutical partnerships, and advance toward the first medicine manufactured in space for patients on Earth.

"if you move mass more cheaply than anyone else, you win." Not Boring X @TheRealNamzoo was always going to be a banger. Beautiful piece from @packyM on one of Indian tech's finest -

There is no category that so physically reshapes the world as transportation technology. Where you live & work, what you can access, and who you spend time with, are all functions of your transportation technology. Imo improving the way we move will have a more positive & noticeable impact on our lives than AI, and whoever does it will build one of the world’s largest businesses. Naman’s aim is to move all movement to the sky. This is a Deep Dive on how he plans to do it.

NEW DEEP DIVE Airbound is my favorite kind of company. Naman Pushp is making an all-in bet that the bottleneck to moving all movement - of goods and people - to the skies is cost. He and Airbound are maniacal about lowering the cost per kg-km of flight. To lower it, they vertically integrate, devise novel uses of carbon fibers, and don’t allow themselves to get distracted by such trivialities as near-term commercial traction. Their newest aircraft - the V2 - carries more than it weighs (Amazon, for comparison, carries 5 lbs with a 78 lb drone). If they can make flight ridiculously cheap, the logic goes, cheaper than a delivery guy on a bike or scooter, then a car, then a van, then a truck, then a bus, then then then… then they can eat those vehicles’ markets, push an enormous amount of demand into just three platforms (Small, Medium, and Large), bring costs down even further, and create a world in which we fly wherever we want to go, and whatever we want flies to us. Then, the world reshapes itself around flight, and the earth around humans. This is a Deep Dive on how they plan to do it.

Today, Sculpta releases the first demonstration of bioorthogonal barcoding ("bobcoding"), the process by which we: 1) covalently attach oligonucleotide barcodes to RNA at multiple internal positions with two-step chemistry, and 2) perform a multiplexed reverse transcription reaction to generate barcoded cDNA libraries with >99% barcoding accuracy. To the best of our knowledge, it is the first time ever that either of these steps have ever been performed by anyone. No one has ever broken the barrier of multiplexing prior to any enzymatic step in library preparation, driving simplicity and higher data quality. Instead of other methods that add 0 or 1 barcode, we add one barcode every ~300bp, adding redundancy and fidelity to RNA measurements. In our first application described in our pre-print below, we used bobcodes to create the first RNA isoform-resolved drug screening platform. It beats Novartis' DRUG-seq platform by: - generating full length transcript capture of RNA isoforms, instead of just 3' end counting - capturing 25-fold more RNA splicing events - reducing barcode swapping by 10-fold - using 18 fewer PCR cycles (~250,000 less amplification) - reducing sample-to-sample variability in gene expression measurements - eliminating costly and cumbersome library fragmentation/tagmentation steps completely - reducing workflow complexity and number of steps - reducing overall protocol duration by ~25% Though our chemical barcoding method improved transcriptomic data quality while also being simpler and faster than all existing methods, the implications of this work go well beyond this particular use case: The gate to greater applications of AI in transcriptomics is not a lack of compute. Nor is it a lack of data volume. The elephant in the room has always been our limited ability to faithfully and accurately measure cellular RNAs. Sculpta now has line of sight to build what we call the first ground truth transcriptomics platform [for single cell, spatial and more] for the future of biological research, drug development and AI-enabled discoveries for the betterment of human health and longevity. [PS Until the kind folks at bioRxiv get through the apparent backlog of AI slop submissions, Sculpta will host the pre-print PDF on our website. You can sign up for product offerings and other updates at this link too]

"We can stop pretending that we can plan our kids’ lives and follow them into whatever lights them up." Ironically for at least two decades this has been the best way to get your kids to even conventionally successful outcomes (e.g. Ivy League admissions) Great piece by Packy and Danco.

"There is no safe career path today, let alone one that will remain safe for twenty years, which means that there is no set of schools and degrees that can guarantee a safe career into the 2040s and 2050s." "Pushing them to get really good at math seems silly, when AI is currently tornadoing through all of the field's hardest open problems. Should you push them to become a lawyer?... Doctor?" "You're basically paying $650k to make sure your kid is admitted to a good high school, which should, but certainly isn't guaranteed to, help them get into a really good college, at which point they'll probably get a good job, at which point, they're set for life." "The challenge with that, though, is that who knows what a good job will be in fifteen years?" "Expose your kids to a lot of things early, and then help them go as deep as they're able to on the things that excite them the most. It doesn't matter what those things are; cultivating curiosity and depth is the point." @packyM and @Alex_Danco on HAA, college, and their own kids:

Since I have two young kids and spend all day thinking about technology, I've thought a ton about how to raise kids given how fast everything is changing. So for the launch of HAA, Alex Danco and wrote about how we teach our kids & whether we'd send them there. (We don't think it'll be up to us to choose.)