JayS

@ClemetineII @coldcallsniper Beat me to it - was my first thought

The way I see it, there is only one good option to handle this. Aden Holloway will be allowed to play in the tourney under one condition: he has to smoke the whole pound before the game and play the entire game

@shane_shidaker @Underwood_szn Bama best three point shooter just arrested with a pound of weed. Not sure he’s playing…

@Underwood_szn They play no defense though. Michigan control the game inside agaisnt them. Saint Louis and Iowa state play some defense

Here is Michigans bracket 1 Michigan vs 16 play in winner 8 Georgia vs 9 St Louis 5 Texas Tech vs 12 Akron 4 Alabama vs 13 Hofstra 6 Tennessee vs 11 play in winner 3 Virginia vs 14 Wright State 7 Kentucky vs 10 Santa Clara 2 Iowa State vs 15 Tennessee State Thoughts?!

@anothercohen What do you mean? An excel spreadsheet? Hard drive?

@Suav40 Local db

Finally finished vibe coding my personal health app built with Claude. Here's what it does: - Connects to the Oura API to sync sleep, recovery, steps, and exercise data - Tracks my monthly bloodwork via Rythm Health CSV uploads - Uses Playwright to scrape Chronometer daily nutrition and water intake - Uses Gemini to OCR Ladder workout screenshots and track my lifts - Full dashboard with weight trends, calorie balance charts, macro tracking, and a tabbed daily log It's completely interactive and honestly, pretty fucking cool. Blood markers even have visualizations based on what's in range and out of range.

Mckinney. He’s starting to do it but recall he was more slasher than a shooter - if he can do that and effectively replace Cason we are in business. Right now we have limited slashers. I’d like it to be Gayle but he dribbles into trouble and not a great / bad passer on those situations.

Who needs to step up the most for #Michigan to advance and make a deep run in the NCAA tournament?

@smdcapital @grok what cars have this chip?

$tsla part 2 translation: Elon just expanded on the Macrohard / Digital Optimus vision with two new pieces: 1. Every AI4-equipped Tesla is a Digital Optimus node. Your car can do office work when it's not driving. The AI4 chip that runs FSD is the same chip that runs Digital Optimus. When parked, the car switches from processing road video to processing screen video + keyboard/mouse tasks. This means there's no new hardware to buy. Every Tesla with AI4 (all new vehicles) is already a Digital Optimus unit. The installed base becomes the distributed compute network — same playbook as Robotaxi (your car earns when you're not using it) but for digital work instead of rides. 2. Millions of dedicated units at Superchargers with 7 gigawatts of available power. Tesla is deploying purpose-built Digital Optimus compute at Supercharger sites. This turns the charging network into a distributed data center — with the power infrastructure already built and paid for. For context: 7 GW is roughly equivalent to 7 large nuclear reactors running at full capacity. That's more power capacity than most cloud providers have at any single region. And it's already deployed across thousands of locations worldwide. ━━━━━━━━━━━━━━━━━━━━ Why This Matters The original Macrohard post described the architecture (System 1 local + System 2 cloud). Today's update reveals the distribution strategy: Fleet as compute grid: ~420K new AI4-equipped cars delivered per quarter. Each one is a potential edge node. At scale, that's millions of distributed inference units with zero additional hardware cost to Tesla. The marginal cost of adding compute capacity is literally $0 — it's already in the car. Superchargers as data centers: Zero new real estate. Zero new power infrastructure. The charging network was built for EVs, but the power is available 24/7 — cars only charge for 20-40 minutes. The rest of the time, that power can run Digital Optimus workloads. Two revenue streams from one asset: A Tesla owner's car earns via Robotaxi when driving autonomously AND earns via Digital Optimus when parked. The car never stops generating revenue. Cost structure no one can match: Competitors building AI data centers pay billions for land, construction, power interconnects, and cooling. Tesla already has the sites (Superchargers), the power (7 GW), and the hardware (AI4 in every car). Their cost per inference unit is a fraction of traditional cloud. ━━━━━━━━━━━━━━━━━━━━

@nisten @grok where is the value right now for most of the benefits at lower cost?

Comparison of apple M1-M5 Chips at max ram configs. M5 Max is not actually that good in raw float16 (same as M1 Ultra lol) but should go 2x+ faster in int8. Every single ai websites deep research results hallucinated wrong numbers while making this ( grok, opus, qwen g3.1pro), fixed it manually😠:

@EXM7777 This is outstanding. It’s a great LLm framework for drafting the skills for review.

@iruletheworldmo @SSharmagg Well said. Have seen this repeatedly. Have even been asked for my prompts as if that’s the problem….

@SSharmagg you can write with ai but if you use a lazy prompt and aren't involved in the process at all. it's painful to read. it's not just painful, it's revolting. another key factor is, and this is important because vomit vomit vomit

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@damianplayer RALPH

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@DavisMoseley Issue with Gayle are his turnovers. Dude is a turnover machine. He can’t be handling the ball other than on clear drives. He goes through spurts of just disaster drives.

Some quick thoughts: - Cason needs more minutes off the ball next to Cadeau and the two bigs. Gives UM such a different dynamic. - McKenney needs minutes where he is the go to scorer. That is where he is comfortable. - More Gayle mins if he continues to hit shots.

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@MattSwartz723 Makes me quite nervous with Semaj back there.

two fair catch decisions that have collectively cost Michigan probably 30 yards. special teams remain uncoached.

@MarktheNomad Which time?

I mean at the very least taking a fair catch on the kickoff was one of the dumbest things I’ve ever seen, but how can Semaj not know where he’s at on the field and catch that ball on the 3 yard line?