Dotnet

You trap an ant with a line, just as they trap us in a box.

@anxietymsgs @grok answer him

be honest, do you talk to yourself?

@anxietymsgs Markdown

Two languages you wish you could speak fluently?

@sciencegirl It’s #python been upgrading v4

A snake was seen rolling like this on a road, likely due to severe distress or injury,

#KIMI K2.6-code-preview is releasing

@ceqgar 🤣

Bro just made a mistake. Never remove those stickers.

Sneak leak at something coming soon to Claude :)

@rohanpaul_ai Distilling worker.skill

Indian factory workers wear head-mounted cameras to capture data for training robotics AI models. This image captures a blunt truth about robotics: teaching a machine to move in the real world is still painfully expensive. What looks dystopian at first is also a clue about the bottleneck. Robots do not learn useful physical behavior from internet-scale text the way language models do. They need embodied data: hands reaching, wrists turning, objects slipping, fabric folding, tools resisting, people recovering from small mistakes in real time. That data is rare because reality is slow, messy, and costly. A robot fleet is expensive to buy, expensive to maintain, hard to supervise, and dangerous to scale in uncontrolled settings. Even teleoperation is costly, because every minute of human-guided movement requires hardware, operators, calibration, and failure recovery. So companies go looking for the cheapest possible proxy for physical intelligence. First-person video from factory workers is not the same as robot action data, but it can still be valuable because it captures sequencing, posture, bimanual coordination, and the micro-adjustments that make real work look easy. The frontier in robotics is not just better models. It is better pipelines for collecting reality itself. That is why warehouses, factories, kitchens, and repair benches matter so much: they are dense environments of repeated contact with the physical world, which is exactly what robots lack. The unsettling part is that this turns human labor into training infrastructure twice over, first as work, then as data. And until embodied data becomes cheaper to gather than human motion is to record, robotics will keep learning from workers before it fully replaces them.

@NobodymrRobert What’s the purpose

Experiment begins.

@stelzner_n1150 He said he's going to focus more on his own things going forward.

Why won't Elon Musk talk about the Iran War?

@nikitabier @BillyM2k That's awesome! A quick fact-check button would be a total lifesaver here. Having to type it all out manually every single time is such a pain.

@BillyM2k What if it showed a tooltip when tapping it and gave you some options? • Fact check: Is this true? • Summarize this • Explain like I’m five

i find myself using the “ask grok” button on the upper right of posts very frequently these days, especially since grok 4.20 feels a lot smarter than previous iterations it’s really helpful when something looks like fake news and i can quickly check if it’s been vetted anywhere

@jayair @opencode @kitlangton Cool, but let's actually ship something. Why does it keep compacting so often? When can we adjust the compact threshold?

Kit built this, should we ship it? (sound on)

@digitalix But why

new video. i plugged a 5090 into a mac mini.

Opus is so slow that almost unacceptable

@Mericamemed Isn’t hot?

At least she had her safety squints on 👌

@tom_doerr at < 10T/s

Runs 405B LLMs on 8GB VRAM github.com/lyogavin/airllm

GameHub for Mac Beta is LIVE! Finally, it's time to run Windows games on your Mac. Visit our official website and join our Discord community to apply for the Beta access: 👉 Official Website: gamemac.com/en/ 👉 Discord: discord.com/invite/CrseHKR… #macgaming

@josh_uglyasf Buy one more Xbox?

She did this to her husband’s ps5 because he doesn’t give her attention… gentleman how would you react in this situation?

@steipete @cinamarina Jus Open the door Claw!!!

@cinamarina whats open claw

Do you use OpenClaw?

@CryptoReviewing Nice move😂

A big move is coming. $BTC pumped above $73,000 for the 2nd time this week, liquidating $138M shorts! That's now $223M liquidated in the past 24 hours!!! Now, $73,500 - $76,000 has sizable liquidity that could be swept - potentially leading to higher levels. However, $68,500 - $72,000 has roughly 2x more liquidation clusters built up, making this the 'more likely' area to visit next from a liquidity perspective. Bulls need to act quickly.