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Powering India's electronics manufacturing ecosystem… with four new units in Telangana: ✅ Giga Factory-1 ✅ Critical Minerals Refining & Battery Recycling ✅ Cell Casing Manufacturing ✅ LFP-CAM Giga Factory

42,835 次观看 • 1 年前 •via X (Twitter)

11 条评论

Harish 的头像
Harish1 年前

Dear sir please do pending railway projects in Telangana.armoor to via Nirmal to adilabad railway projects,since long back years pending projects,it's very use full multiple purpose railway project

ACCIONA (English) 的头像
ACCIONA (English)1 年前

This is great news for the US's renewable energy industry 🇺🇸⚡️ @ACCIONAEnergia's largest photovoltaic plant globally has begun supplying renewable energy to Texas, the heart of the U.S. oil industry ⤵️

Aditya Narayan B 的头像
Aditya Narayan B1 年前

You received the RS seat from Odisha, but there was no manufacturing. Even manufacturing in Odisha is not being promoted. @CMO_Odisha @dpradhanbjp @sambitswaraj

Hemant Chamle 的头像
Hemant Chamle1 年前

Electronics man of India

Gandhi-mentality 的头像
Gandhi-mentality1 年前

woh kavachh system ka kya hua?

Nihar 🇮🇳 的头像
Nihar 🇮🇳1 年前

Sir, pls update the status of train number 12414, the online data on NTES is fake.. parents are struggling to get any update. What kind of digitalization is this?? @narendramodi

Tanmoy samanta 的头像
Tanmoy samanta1 年前

Stop every investment going to Tamilnadu,then they brag that North GDP contribution is low

Abhishek Sharma 的头像
Abhishek Sharma1 年前

Sir, while it's great to see progress in manufacturing, why is there no similar push for digital self-reliance? When will we see real promotion of BOSS OS as a Windows alternative, Bharatiya apps over Google, and updates on Bhar OS

Kiran Kamath 的头像
Kiran Kamath1 年前

Namaskar Sir. Appreciate your efforts. Kindly introduce better waste management practices in the trains so that people stop littering inside trains or make railway tracks/railway properties garbage dumps.

AV 的头像
AV1 年前

ok Sir... Khush Raho.

दया शंकर 的头像
दया शंकर1 年前

माँ के Ortho treatment के लिए #Cuttack जाना था l केवल एक टिकट confirm हुआ, दोनों भाई - बहन उनके पास बैठकर चले गए l So according to your new guidelines, no one can enter the station without confirm ticket . 🖕इस हालत में क्या Patient को अकेले भेज दें ? @narendramodi जी 😇

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Tesla Owners Silicon Valley

100,170 次观看 • 2 个月前

A team tested Pi0, Pi0 Fast, Gr00t, and ACT on real robot arms in manufacturing tasks. (🔖 Bookmark this for later!) The task was precise: place thin rectangular frames from a messy stack into a holder. The team fine-tuned each model on 100 real trajectories and compared training time, inference speed, motion quality, and success rates. ⬇️ Here’s a breakdown of what they found Pi0 (Original) ✅ Strongest overall performance in precise pick-and-place ✅ High success rate even in edge cases ✅ Longest training time (~11 hours, ~$30 per run) ✅ Inference time of 80 ms causes short pauses between actions Despite delays, it handles complex scenarios well… solid for high-precision tasks, but slow to train. Gr00t ✅ Trains fast (~2 hours, ~$5 per run) ✅ Performs almost as well as Pi0 on large-object tasks ✅ Struggles with fine precision; random movement in some trials ✅ More training didn’t fix jitter or random offsets Best suited for tasks where exact precision isn’t critical. Not ready for manufacturing-grade accuracy without more tuning. Pi0 Fast ✅ Promised faster training, but results were underwhelming ✅ Training at 6 hours still showed low success rates ✅ Inference was slower than expected ✅ Not reliable for generalizing even slightly new tasks Currently too unstable for real-world deployment. Doesn’t live up to the “Fast” name yet. ACT (Baseline) ✅ 200MB model—lightweight, but limited ✅ Struggles with stacked objects or ambiguous scenes ✅ Success rates around 70% in best-case setups ✅ Can’t match newer models on precision or generalization Still a solid baseline, but clearly a generation behind in robustness. 🚨 Extra Notes All newer models share a common issue: •Inference takes longer than a frame (80 ms vs 33 ms), so robots “pause” between chunks. •This results in jittery movements, but not a dealbreaker unless tasks are time-sensitive. Language-conditioned tasks also fell short: after training on two labeled tasks, the model couldn’t generalize to a third unseen combination using only text prompts. ✅ The good news? These models adapt well to new robot arms with quick fine-tuning. ❌ The bad news? There’s still no plug-and-play solution for improving performance after deployment. Reinforcement learning or DAgger-style data collection during real-world operation may be the next big step, something many teams in robotics are actively working on.

Ilir Aliu

21,844 次观看 • 1 年前

17 June 2026 Giga Texas Snapshots! I’m back after a few weeks away in Europe & visiting Giga Berlin (a fantastic factory too!) so today I decided to try and get a good overall look at the activity & changes here since I was away, and there is really a lot to cover … almost too much! Cybercab production continues with many of these vehicles lined up at the factory exit point & more int the outbound lot. I saw a Model Y production going strong too, with several in the new shades of blue recently announced too! The 4680 battery cell portion of the factory was getting concrete delivered inside where I’ve observed demolition & expansion work underway to increase production capacity & this is backed up with several new permits filed over the past few days! The Test track has had more work on it including paint marks, dedicated lanes w/ dividers & a Cybercab testing office & vehicles that have been recently observed driving on the track for some kind of testing. The E side where the new joint venture with SpaceX Advanced Chip fab is being constructed was getting GeoPier work, while more preparations were underway to relocate active workshops & recycling yards further to the N to clear space for additional construction. Cortex 2 part 2 chiller system fan tower seems nearly completed structurally, while more pipes, vale’s & wrapped items remain to be installed. The N Optimus factory shows significant work with steel erection (up to 4 floors), GeoPier work on the N end, grade work on the S end, land reclamation on the extreme S & footing construction in the middle. This will truly be a massive factory once completed w/ floor space a significant % of the main factory! Much more going on today! It’s great to be back!

Joe Tegtmeyer 🚀 🤠🛸😎

14,419 次观看 • 1 个月前