•twitter19883
listening to
timeline
19883
mentions
tracked
tracked
net sentiment
+23%
6085 positive
12318 neutral
1480 negative
volume & sentiment over time
Sep 30 – Oct 18, 2026 · Daily
sources
most discussed
—
active days
19
mentions
Showing 10251–10275 of 19883 mentions
-
• twitter 1w neutralRyan says building "native" apps costs up to 3.5× in agent minutes. Bias or real? I tested it with Argent, @swmansion's toolkit that lets agents drive iOS & Android simulators in any framework 🤌 Check out the thread for details 🧵 https://t.co/mO9yxR19TX Ryan says building "native" apps costs up to 3.5× in agent minutes. Bias or real? I tested it with Argent, @swmansion's toolkit that lets agents drive iOS & Android simulators in any framework 🤌 Check out the thread for details 🧵 https://t.co/mO9yxR19TXview source ↗
-
• twitter 1w neutralsplitting actions interactions inspired by @nitishkmrk made with framer motion https://t.co/ouZs02Vhff splitting actions interactions inspired by @nitishkmrk made with framer motion https://t.co/ouZs02Vhffview source ↗
-
• twitter 1w positiveHey Builders & Founders, Looking to connect with people building in: 🚀 SaaS 🤖 AI 🌐 Web Apps 📱 Mobile Apps 💻 Tech 📊 Startups 🧠 Indie Hacking If you're building something exciting, I'd love to see it. Drop your product, website, or what you're working on below. 👇 Hey Builders & Founders, Looking to connect with people building in: 🚀 SaaS 🤖 AI 🌐 Web Apps 📱 Mobile Apps 💻 Tech 📊 Startups 🧠 Indie Hacking If you're building something exciting, I'd love to see it. Drop your product, website, or what you're working on below. 👇view source ↗
-
• twitter 1w neutralOne persistent Triton launch per token runs all four layers: int4 weights dequantized in streamed GEMVs, the KDA convolutions and state updates, MLA attention in the latent space with the key projection absorbed into the query, and the router plus routed and shared experts, held together by an atomic-counter barrier. C… One persistent Triton launch per token runs all four layers: int4 weights dequantized in streamed GEMVs, the KDA convolutions and state updates, MLA attention in the latent space with the key projection absorbed into the query, and the router plus routed and shared experts, held together by an atomic-counter barrier. Changing the input token or the weights in place during the audit changed the output, which still matched the reference. Board: https://t.co/MUNCbjpyAm Kernel: https://t.co/27iNbQipMb Trace: https://t.co/ejbqbwFH0zview source ↗
-
• twitter 1w neutralGPT-6.1 Sol [xhigh] on KernelBench-Mega: It wrote a one-launch Kimi-Linear Decode megakernel for RTX PRO 6000 at 5.0x the optimized PyTorch baseline, 17th of 32. GPT-6 Sol's megakernel ran at 0.96x. 6.1 Sol got there in 17 minutes; its score was flat from minute 7 and it called it done. Opus 5.5 leads at 35.5x after … GPT-6.1 Sol [xhigh] on KernelBench-Mega: It wrote a one-launch Kimi-Linear Decode megakernel for RTX PRO 6000 at 5.0x the optimized PyTorch baseline, 17th of 32. GPT-6 Sol's megakernel ran at 0.96x. 6.1 Sol got there in 17 minutes; its score was flat from minute 7 and it called it done. Opus 5.5 leads at 35.5x after 3.3 hours with the same plan. The gap is depth: no tensor cores, a full KV-cache copy every step, and phases that run on a single block.view source ↗
-
• twitter 1w neutralBizim bu aziz milletten başka hiç kimseye diyet borcumuz yok. Bizim Hazreti Allah’a bir can borcumuz var, Allah’ın izniyle hiçbir faniye borcumuz da eyvallahımız da yok. Bizim bu aziz milletten başka hiç kimseye diyet borcumuz yok. Bizim Hazreti Allah’a bir can borcumuz var, Allah’ın izniyle hiçbir faniye borcumuz da eyvallahımız da yok.view source ↗
-
• twitter 1w neutralGrid + MinGRU, 31% of the deck's 150M steps/s target, 11th of 17 (GPT-6 Sol: 64%). This is the one that went backwards. GPT-6 Sol replayed the rollout as a CUDA graph with cuBLAS for the gate matmuls; 6.1 Sol fused the rollout into one cooperative kernel with fp16 tensor-core MinGRU and a hi/lo split for near-fp32 accu… Grid + MinGRU, 31% of the deck's 150M steps/s target, 11th of 17 (GPT-6 Sol: 64%). This is the one that went backwards. GPT-6 Sol replayed the rollout as a CUDA graph with cuBLAS for the gate matmuls; 6.1 Sol fused the rollout into one cooperative kernel with fp16 tensor-core MinGRU and a hi/lo split for near-fp32 accuracy, plus a grid-wide barrier every step, and stopped after 41 minutes. Kernel: https://t.co/vt111L2j1N Trace: https://t.co/oiiMGPL8R5view source ↗
-
• twitter 1w neutralMegaQwen Decode, 3.9% of roofline, 15th of 20 (GPT-6 Sol: 4.0%). GPT-6 Sol launched a kernel per stage from a Python loop; 6.1 Sol runs every decode step and all four layers in one cooperative launch, sharing each KV load between the two query heads of a group. The launch count dropped, the score did not: the leaders a… MegaQwen Decode, 3.9% of roofline, 15th of 20 (GPT-6 Sol: 4.0%). GPT-6 Sol launched a kernel per stage from a Python loop; 6.1 Sol runs every decode step and all four layers in one cooperative launch, sharing each KV load between the two query heads of a group. The launch count dropped, the score did not: the leaders at 7 to 8% get weights and upcoming KV into L2 or shared memory before they are needed. Kernel: https://t.co/SssORwN1Qy Trace: https://t.co/lCmkkFQcLUview source ↗
-
• twitter 1w negativeGPT-6.1 Sol [xhigh] on KernelBench-CUDA: Four hand-written CUDA kernels passed their final checks on RTX PRO 6000. Native Sparse Attention is the jump: 0.28 ms, 9x faster than GPT-6 Sol and 5th of 14. The other three land mid-board. Where GPT-6 Sol leaned on cuBLAS and CUDA graphs, 6.1 Sol writes its own tensor-core … GPT-6.1 Sol [xhigh] on KernelBench-CUDA: Four hand-written CUDA kernels passed their final checks on RTX PRO 6000. Native Sparse Attention is the jump: 0.28 ms, 9x faster than GPT-6 Sol and 5th of 14. The other three land mid-board. Where GPT-6 Sol leaned on cuBLAS and CUDA graphs, 6.1 Sol writes its own tensor-core GEMMs and puts whole problems into one cooperative launch. It also stops early: no problem took it more than 80 minutes. One problem per reply below.view source ↗
-
• twitter 1w neutralA fresh start was just the tip of the iceberg. North of North Season 2 premieres November 5! https://t.co/se7cQuXJBO A fresh start was just the tip of the iceberg. North of North Season 2 premieres November 5! https://t.co/se7cQuXJBOview source ↗
-
• twitter 1w positiveMost people use Claude Code like a chatbot. That’s the mistake. Claude Code becomes far more powerful when you structure your project around: or project-wide instructions → .mcp.json for tool integrations → settings.json for permissions & hooks → Custom commands for repeatable workflows → Skills for task-specific ex… Most people use Claude Code like a chatbot. That’s the mistake. Claude Code becomes far more powerful when you structure your project around: or project-wide instructions → .mcp.json for tool integrations → settings.json for permissions & hooks → Custom commands for repeatable workflows → Skills for task-specific expertise → Agents for specialized work Eview source ↗
-
• twitter 1w neutralYou could literally: - Sign 5 clients at $5-10k/mo - Let AI do 80% of the delivery - Pay one VA $2k/mo to coordinate it - Sit on $25-50k/mo recurring - Keep 60% of it - Get paid again next month without signing anyone new Here's how: You could literally: - Sign 5 clients at $5-10k/mo - Let AI do 80% of the delivery - Pay one VA $2k/mo to coordinate it - Sit on $25-50k/mo recurring - Keep 60% of it - Get paid again next month without signing anyone new Here's how:view source ↗
-
• twitter 1w positiveMeet Harkirat Singh, a 2018 https://t.co/YSvOF5fxhn Computer Science graduate from IIT Roorkee. This guy secured a remote software developer role at Gather with a package of ₹4 crore per year. He has participated in Google Summer of Code twice and worked across FAANG companies, finance, and startups. He resigned from… Meet Harkirat Singh, a 2018 https://t.co/YSvOF5fxhn Computer Science graduate from IIT Roorkee. This guy secured a remote software developer role at Gather with a package of ₹4 crore per year. He has participated in Google Summer of Code twice and worked across FAANG companies, finance, and startups. He resigned from Goldman Sachs just before COVID to explore new opportunities. Through freelancing, he reportedly earned around ₹80 lakh per year and eventually secured a remote software developer role with a package of ₹4 crore per year. Here are some remote job platforms where companies pay in USD. Remotive - https://t.co/GroTHf9R6G Rocketship - https://t.co/fzeXO3JqV5 https://t.co/Wo5gHIZ6Gz - https://t.co/FOH3Qsuod9 Remote Woman - https://t.co/LX7elPEM96 Wellfound - https://t.co/6ODBv5KmDY We Work Remotely - https://t.co/r371QfB0rQ WorkWave - https://t.co/UHG3KUOYcY AI Jobs - https://t.co/TR9D30HGnJ Toptal - https://t.co/bEqqIaaSDQ FlexJobs - https://t.co/DSqcYjimAM JS Remotely - https://t.co/k9L95I1NLe Remote OK - https://t.co/pwiXrGmV8M FYI Check:- https://t.co/AQV7vQ7pDZview source ↗
-
• twitter 1w positivefound the perfect use case for @Claude Mods: chat-clean You can instantly clean up your claude code chats and can make it 100x more readable Repo in comment https://t.co/XuruHVegtn found the perfect use case for @Claude Mods: chat-clean You can instantly clean up your claude code chats and can make it 100x more readable Repo in comment https://t.co/XuruHVegtnview source ↗
-
• twitter 1w neutralhttps://t.co/ghHeeJvxrG new work added https://t.co/lWN9qY5sJv https://t.co/ghHeeJvxrG new work added https://t.co/lWN9qY5sJvview source ↗
-
• twitter 1w positivePin nexus in @ChatGPT I really appreciate chatgpt giving me the full real-estate to build. https://t.co/htcuy6VH4C Pin nexus in @ChatGPT I really appreciate chatgpt giving me the full real-estate to build. https://t.co/htcuy6VH4Cview source ↗
-
• twitter 1w neutralguys... it has happened to me A huge portion of the work I do lately is just from the terminal via agent + some review. guys... it has happened to me A huge portion of the work I do lately is just from the terminal via agent + some review.view source ↗
-
• twitter 1w neutralMe when he asks whats for dinner but I forgot to thaw anything https://t.co/y96tBZkFeW Me when he asks whats for dinner but I forgot to thaw anything https://t.co/y96tBZkFeWview source ↗
-
• twitter 1w neutralGrok Bot meetups coming up in 60+ cities RSVP on Luma (more being added!) https://t.co/Ijk58fxU4z Grok Bot meetups coming up in 60+ cities RSVP on Luma (more being added!) https://t.co/Ijk58fxU4zview source ↗
-
• twitter 1w neutralThe limit is 17 years and 4 days. The limit is 17 years and 4 days.view source ↗
-
• twitter 1w neutralidentity concept / magicpath https://t.co/t0PogROku1 identity concept / magicpath https://t.co/t0PogROku1view source ↗
-
• twitter 1w neutralप्रधानमंत्री ताकाइची जी, आपका बहुत-बहुत धन्यवाद। इस वर्ष जुलाई में हुई आपकी भारत यात्रा मेरे लिए भी अविस्मरणीय रहेगी। इससे भारत-जापान की साझेदारी और सशक्त हुई है। दोनों देश अपनी पुरानी मित्रता को और आगे ले जाते हुए वैश्विक शांति, स्थिरता एवं समृद्धि के लिए साथ मिलकर प्रयास करते रहेंगे। मुझे विश्वास है कि हमारे रा… प्रधानमंत्री ताकाइची जी, आपका बहुत-बहुत धन्यवाद। इस वर्ष जुलाई में हुई आपकी भारत यात्रा मेरे लिए भी अविस्मरणीय रहेगी। इससे भारत-जापान की साझेदारी और सशक्त हुई है। दोनों देश अपनी पुरानी मित्रता को और आगे ले जाते हुए वैश्विक शांति, स्थिरता एवं समृद्धि के लिए साथ मिलकर प्रयास करते रहेंगे। मुझे विश्वास है कि हमारे राजनयिक संबंधों की 75वीं वर्षगांठ पर द्विपक्षीय रिश्तों को एक नई ऊंचाई मिलेगी। 高市首相、誠にありがとうございました。 今年7月の首相のインド訪問は、私にとっても忘れられないものとなりました。この訪問により、日印のパートナーシップはさらに強固なものとなりました。 両国は、長年にわたる友好関係を基盤として、世界の平和、安定、繁栄のために引き続き協力してまいります。 国交樹立75周年を迎えるにあたり、両国関係が新たな高みに達することを確信しております。 @takaichi_sanaeview source ↗
-
• twitter 1w positiveRecent hook 🔥. https://t.co/XShEBZ0NUS Recent hook 🔥. https://t.co/XShEBZ0NUSview source ↗
-
• twitter 1w neutraljust two baniyas focused on building dhandha at https://t.co/yJUV447MDN https://t.co/HeYVxG630q just two baniyas focused on building dhandha at https://t.co/yJUV447MDN https://t.co/HeYVxG630qview source ↗
-
• twitter 1w positiveThese stochastic parrots are getting awfully good at doing things nobody taught them to do. Generalization! These stochastic parrots are getting awfully good at doing things nobody taught them to do. Generalization!view source ↗