its_down_again

But let’s say you’re an elite marathoner running 100 miles a week. Maybe 20 are at low 5 or sub 5 pace. The other 80 are closer to 6:30/mile.

Then you might add more race specific work as race day gets closer. In one week you might do 2 days of track or threshold workouts before your long run of 14 miles at 6:00 pace with 8 at goal marathon pace (~4:50/mile).

Has anyone tried acoustic imaging for water leaks inside walls? I live in a multi-floor 1900s Victorian. A leak can affect several units, and tracing the source can mean opening walls or floors in multiple places, and coordinating access has been getting harder with less WFH.

Could one of these tools help map water pipe routes and trace a leak, or are they only going to be useful for air and gas leaks?

In my experience, knowing you have glaring UX problems, or that product does not have an easy intuitive user flow is rarely the bottleneck for developing new & useful user facing AI applications.

There’s usually a very real and very hard to describe data related impracticality that voids the usefulness of a design that appears well thought out and complete.

Additionally enterprise AI products are built on custom integrations, and complexity of maintenance overwhelms the engineering team and leaves very little time to build out new things.

The simplest changes that come from knowing insider customer experience have significant impacts. If the default range for a duration filter is 5-30min, and it turns out the most interesting data is really on 1.5hr+ rows. Or adding search across legacy platforms that bury uniform information under deeply nested modals, which people spend 20+ a week clicking through to collect a usable sample set based on existence of a few keywords. But building a system that returns good search results is the hard part.

I do like the “build on top” pieces in your gallery. If it’s fast and reliable enough to collab during a discovery meeting, or a customer success meeting, that would be genius. Because then you’d have a way to pull customers into the right mindset to articulate frustrations with their current software, iterate on getting those frustrations get translated into concrete designs together, and at the end you walk away with something that proves you both understand and can solve their problem to any audience.

There’s no point comparing apples to deep fried oreos for caloric density. The 919 Evo is a fully de-restricted prototype based off a legendary homologated race car, not remotely in the same category. The BYD U9 is a road-legal EV, comparing the two doesn’t mean much.

Funny you mention the Ford SuperVan because that’s much closer to the 919 Evo in the "no homologation no limits" category than anything you could register and drive off a lot. A fairer and much more impressive benchmark is the road-legal Ford Mustang GTD running a 6:52. That's still far quicker than the BYD, with roughly two thousand less horsepower.

Looks nice. For a true whiteboard experience, I think the 'Draw' tool should probably be the default rather than 'Select'. I was clicking around at first and couldn’t figure out why nothing was showing up.

The San Francisco marathon is this weekend and I think it’s going to break the city for this Robotaxi launch.

There's major road closures for key arteries like Market st, Embarcadero, fisherman’s wharf, and the Presidio. Traffic always crawls and downtown will become a maze. Even 'human' drivers struggle because you can't cross large boundaries of the city.

Waymo launched in the city about a month before last year’s race. I took one to the starting line, but it couldn’t reach the actual drop-off. It stalled about 0.3 miles away and I had to run the rest. The issue wasn’t the route, but the chaos. Dense foot traffic, impromptu street closure re-routes, and unpredictable crowd behavior were hard to autonomously solve.

Tesla's robotaxi launch will have to overcome the same challenging mix of realtime conditions: limited access to closure data, learning of impromptu re-routing logic, unpredictable human crowds.

Definitely it’s a bold move to launch this weekend. If it works, great PR.

Actually this sounds great. I got way more out of codecademy’s in-browser, interactive challenges than I did in my middle & high-school classes programming classes. The "learn by doing" process really built my confidence. If you could "demo" your docs directly in the browser it's much easier to learn by doing. I think that'd drive up adoption and you might even crowdsource bug discovery.

I used to have plenty of energy running 40-50miles per week, but when I ramped up to 80mpw I started nodding off in my chair by 1 PM. Then despite the higher mileage and more intense training, my race times slipped. My half went from 1:23 to 1:28, and I felt drained, irritable and angry unless I took a long break. After digging in, I learned that very high mileage can deplete iron levels. Once I focused on improving my iron absorption, I finally got my energy back and everything clicked. Even while holding 80+ mpw for the upcoming SF Marathon, I still knocked 5% off my Bay to Breakers time (48:51 this year) and cut my 5K PR from 19:17 to 18:37.

Curious how you landed on the idea to partner with local GCP/Azure reps. That’s a smart move, I didn’t realize they’d be open to helping. Did you pitch it as a way to help them close deals by offering custom solutions?

This is fascinating. Could the same machine (PRAD) be adapted to zap mosquitoes in flight and help control disease vectors? Nothing’s worse than waking up to multiple mosquito bites and dreading falling asleep knowing there’ll be more.

The current title “How aging stem cells fuel visceral fat gain in middle age” suggests that existing stem cells simply ramp up fat production as they age.

Single-cell RNA sequencing of APCs then identified a new committed preadipocyte population that is age enriched (CP-A), both in mice and humans. CP-As displayed high proliferation and differentiation capacities, both in vitro and in vivo.

It should read more like "aging triggers emergence of a specific stem cell type (APCs) which drives visceral fat expansion"

disclaimer: not data or advice.

We once interviewed a former national [racket sport] champion from [country] for a React/JS SWE role. Our in-house [racket sport] expert, who happens to be the best player among us, was sure they’d ace the coding exercise. The next day, when we asked for his verdict, he gave us a few words: “He sucks. He got absolutely nowhere.”

Lesson learned: extreme talent in one domain not always a predictor of aptitude in another.