Hemendra Shekhawat

630 posts

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Hemendra Shekhawat

Hemendra Shekhawat

@Dormang0

Learning by doing, observing and conversing.

Jaipur, India Katılım Şubat 2019
258 Takip Edilen14 Takipçiler
Hemendra Shekhawat retweetledi
tetsuo
tetsuo@tetsuoai·
C Code to Assembly.
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Hemendra Shekhawat@Dormang0·
If you don't like opencode, we can't be friends.
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Harsh Bhatt
Harsh Bhatt@harshbhatt7585·
I am implementing and training diffusion language model from scratch. The challenge is to not eat my favourite food until I figure out obtaining a decent inference performance! > implementing training infrastructure and scaling the training. > I am optimising KV cache performance to speed up the transformers block > Implementing Diffusion Blocks which can predict tokens parallel! lessgoo!
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BijanBowen
BijanBowen@Ominousind·
GPT-5.5 Pro Moto GP game in a single script. One of the better results I've ever seen.
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dax
dax@thdxr·
deepseek is outrageously cheap even if you ignore the current 75% discount input token prices are 35x cheaper than opus cached tokens are 178x cheaper
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nexxel
nexxel@nexxeln·
theo gets a lot of hate but he was one of the first people to seriously bet on me i built create-t3-app as a random kid on the internet. he gave me my first internet money, distribution, and a network that changed my life cool to see him keep doing this. talent compounds fast when someone backs it early
Theo - t3.gg@theo

My man @uwukko is building my favorite browser (helium) on an M1 with 16gb RAM. I’m donating $2,000 to help him get a better Mac. If one of my rich friends wants to match it, he can get 64gb. If two do, he can do 128 👀

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xavier (jack)
xavier (jack)@KMkota0·
i just wanted custom cabinets this escalated quickly...
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Kit Langton
Kit Langton@kitlangton·
Now in 𝚘𝚙𝚎𝚗𝚌𝚘𝚍𝚎: Automagical Zed support. @opencode 🫶 @zeddotdev
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Fengzhuo Zhang
Fengzhuo Zhang@FengzhuoZhang·
The Newton–Schulz iteration coefficients optimized by DeepSeek-V4 are surprisingly strong: they effectively normalize all singular values to 1. This matches our previous intuition: a well-balanced spectrum may help strike a better balance across long-tail knowledge. Plot code: github.com/FengzhuoZhang/…
Fengzhuo Zhang tweet mediaFengzhuo Zhang tweet media
Fengzhuo Zhang@FengzhuoZhang

Why does Muon outperform Adam—and how? 🚀Answer: Muon Outperforms Adam in Tail-End Associative Memory Learning Three Key Findings: > Associative memory parameters are the main beneficiaries of Muon, compared to Adam. > Muon yields more isotropic weights than Adam. > In heavy-tailed tasks, Muon significantly improves tail-class learning compared to Adam. Paper Link: arxiv.org/pdf/2509.26030 A thread 🧵

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Fengzhuo Zhang
Fengzhuo Zhang@FengzhuoZhang·
Why does Muon outperform Adam—and how? 🚀Answer: Muon Outperforms Adam in Tail-End Associative Memory Learning Three Key Findings: > Associative memory parameters are the main beneficiaries of Muon, compared to Adam. > Muon yields more isotropic weights than Adam. > In heavy-tailed tasks, Muon significantly improves tail-class learning compared to Adam. Paper Link: arxiv.org/pdf/2509.26030 A thread 🧵
Fengzhuo Zhang tweet media
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DeepSeek
DeepSeek@deepseek_ai·
🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length. 🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top closed-source models. 🔹 DeepSeek-V4-Flash: 284B total / 13B active params. Your fast, efficient, and economical choice. Try it now at chat.deepseek.com via Expert Mode / Instant Mode. API is updated & available today! 📄 Tech Report: huggingface.co/deepseek-ai/De… 🤗 Open Weights: huggingface.co/collections/de… 1/n
DeepSeek tweet media
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Alex
Alex@mustache_dev·
no more a raycast vehicle but a shapecast vehicle, could have been a WR but failed miserably at the end #threejs #gamedev
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Hemendra Shekhawat@Dormang0·
@IAmManware Copilot is decent, I have been using it for past 3 weeks and I am very happy of the interface that it provides and the result it produces. It just overthinks sometimes.
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Ashikka
Ashikka@AshikkaG·
2nd place at @opencode Buildathon 🥈 @BansalRishit and I built openflip.io - a pocket AI red teaming agent that scans nearby signals (Sub-1GHz, Bluetooth, WiFi, NFC, RFID, IR), finds/generate the right exploit modules via @opencode, and runs them in real time. Flipper Zero… but it thinks for itself. 👉 Join the waitlist: openflip.io Huge shoutout to @GrowthX_Club, @opencode, @udayan_w, @nexxel and the entire team for hosting such an incredible event. Second win this weekend - we are working on building and shipping both these projects in the coming days! Stay tuned.💪
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Sebastian Aaltonen
Sebastian Aaltonen@SebAaltonen·
Normal day: Codex again wrote defensive code inside hot inner loops. All of the data is already validated when the object enters the data structure. Super important to always check AI written code and ask it to clean up all the mess. Otherwise technical debt increases gradually.
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