Shashi Jakka । శశి జక్క retweeted
If you really want to learn or achieve something, you will find a way. If not, you will likely find an excuse.
- "don't have the time."
- "job keeps me occupied."
- "will start when things settle down."
- "don't have the right resources."
- or the classic - "education system ruined me"
These are understandable, but if it truly matters to you, you will find time, energy, and resources. Simple.
- "don't have the time."
- "job keeps me occupied."
- "will start when things settle down."
- "don't have the right resources."
- or the classic - "education system ruined me"
These are understandable, but if it truly matters to you, you will find time, energy, and resources. Simple.
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Shashi Jakka । శశి జక్క retweeted
Shruti Telugu is 29.7 MB AI model by @udgamlabs. On real Telugu conversations with English mixed in, it makes fewer mistakes than Telugu models five and thirty times its size on speech to text.
One file that writes Telugu and English, offline, on your phone, laptop or browser. in English, the way people actually speak Telugu.
One file that writes Telugu and English, offline, on your phone, laptop or browser. in English, the way people actually speak Telugu.
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Shashi Jakka । శశి జక్క retweeted
If you're curious about how exactly Claude is making these incredible animated videos, I had Claude make a video explaining the process and what tools it's using...
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Shashi Jakka । శశి జక్క retweeted
Vibe coding a sub-task or feature worked surprisingly well for me with Opus 5.5 and GPT 6.1 Sol.
So I thought: Why not take it a step further? 🤔
What if I vibe-code an entire module or application using /loop or /goal with a list of tasks in spec.md?
Here's what I learned:
❌ DON'T DO IT 🙅♂️
👉 You get an application that almost works, but isn't what you actually expected.
👉 It can easily become over-engineered.
👉 Changing one behaviour can have a ripple effect across the codebase.
👉 You end up spending significant time understanding the code the AI generated.
My takeaway:
Don't ask AI to build everything in one go.
Go step by step, iteratively.
Smaller chunks of work make the code easier to understand, review, debug, and reason about.
So I thought: Why not take it a step further? 🤔
What if I vibe-code an entire module or application using /loop or /goal with a list of tasks in spec.md?
Here's what I learned:
❌ DON'T DO IT 🙅♂️
👉 You get an application that almost works, but isn't what you actually expected.
👉 It can easily become over-engineered.
👉 Changing one behaviour can have a ripple effect across the codebase.
👉 You end up spending significant time understanding the code the AI generated.
My takeaway:
Don't ask AI to build everything in one go.
Go step by step, iteratively.
Smaller chunks of work make the code easier to understand, review, debug, and reason about.
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the problem is no longer execution ,
it is thinking and visualising ,
if you are good at that , have some few dollars , you can build anything in todays world
it is thinking and visualising ,
if you are good at that , have some few dollars , you can build anything in todays world
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Shashi Jakka । శశి జక్క retweeted
Seamlessly share your app's capabilities with your own agent or system agents using Android MCP.
Officially in beta, the AppFunctions API is opening up powerful new ways to integrate your functionality.
goo.gle/4yUbOHz
Officially in beta, the AppFunctions API is opening up powerful new ways to integrate your functionality.
goo.gle/4yUbOHz
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Shashi Jakka । శశి జక్క retweeted
Maya-2 voice model weights are officially live! 🇮🇳🇮🇳
The frontier voice model for India is now completely open-weight.
• Outperforms ElevenLabs v3, Sarvam Bulbul v3, and Cartesia Sonic 3.5
• 1.5B+ people covered across all 28 states and 8 union territories
• SOTA voice icial languages
• 20 native speakers pre-loaded, ready out of the box
• Best-in-class zero-shot voice cloning
Built by a team of five from the land of languages.
Go build and have fun!
The frontier voice model for India is now completely open-weight.
• Outperforms ElevenLabs v3, Sarvam Bulbul v3, and Cartesia Sonic 3.5
• 1.5B+ people covered across all 28 states and 8 union territories
• SOTA voice icial languages
• 20 native speakers pre-loaded, ready out of the box
• Best-in-class zero-shot voice cloning
Built by a team of five from the land of languages.
Go build and have fun!
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Shashi Jakka । శశి జక్క retweeted
Vemana is out. It's a 278M Telugu model we trained from scratch, live, on one GPU, for about $69.
And I think the result surprised even me: on new Telugu Wikipedia pages it beats every open base model under 1B that we tested, including nanochat-telugu-560M, which is twice its ry checkpoint and the eval code are public. And you can run it right in your browser, on your own device, nothing gets sent anywhere.
And I think the result surprised even me: on new Telugu Wikipedia pages it beats every open base model under 1B that we tested, including nanochat-telugu-560M, which is twice its ry checkpoint and the eval code are public. And you can run it right in your browser, on your own device, nothing gets sent anywhere.
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Shashi Jakka । శశి జక్క retweeted
No, WebMCP isn't replacing MCP.
MCP connects agents to your services.
WebMCP connects agents to your website while it's open and the user's in the loop.
Here's how they fit together ⤵️
MCP connects agents to your services.
WebMCP connects agents to your website while it's open and the user's in the loop.
Here's how they fit together ⤵️
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Shashi Jakka । శశి జక్క retweeted
My prediction for software engineering over the next 3 to 5 years.
AI won't replace software engineers. It'll drive even greater demand for them.
A team of 5 experienced engineers using AI will outperform a team of 20 pre-AI.
Which will dramatically reduce the cost of building software.
I think we'll see Jevons paradox in action. As something becomes cheaper and more efficient to produce, demand for it can increase dramatically.
Thousands of software projects that previously weren't economically viable will become worth doing.
The winners will be companies, big and small, that behave like Google, Amazon and 3M, with a culture of experimentation, a willingness to try lots of ideas and the discipline to kill their darlings.
TL/DR: Smaller engineering teams, more innovation, more software products, and potentially more software engineers than ever.
What do you think?
AI won't replace software engineers. It'll drive even greater demand for them.
A team of 5 experienced engineers using AI will outperform a team of 20 pre-AI.
Which will dramatically reduce the cost of building software.
I think we'll see Jevons paradox in action. As something becomes cheaper and more efficient to produce, demand for it can increase dramatically.
Thousands of software projects that previously weren't economically viable will become worth doing.
The winners will be companies, big and small, that behave like Google, Amazon and 3M, with a culture of experimentation, a willingness to try lots of ideas and the discipline to kill their darlings.
TL/DR: Smaller engineering teams, more innovation, more software products, and potentially more software engineers than ever.
What do you think?
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Shashi Jakka । శశి జక్క retweeted
eMudhra certificate compromise: GraalVM Native Image advisory
TL;DR: native images don't use the jdk certificate chain so u need to patch and rebuild
graalvm.org/uploads/native…
TL;DR: native images don't use the jdk certificate chain so u need to patch and rebuild
graalvm.org/uploads/native…
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RT @levelsio: Maybe important to repost this now that everyone is getting hacked
If you have a VPS, I recommend you to get if off the publ…
If you have a VPS, I recommend you to get if off the publ…
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Shashi Jakka । శశి జక్క retweeted
🚀 Meet Qwen-Image-2.1-Turbo — create and edit images in just 8 denoising steps! Open weights now available!
Built on Qwen-Image-2.1, Turbo is an accelerated checkpoint on the same 7B visual generation architecture.
Fewer steps does not mean lower quality: it still generates strong 2K images from text, and supports continued creation through natural-language edits, from adding accessories to changing a scene.
Start directly with Diffusers: load QwenImage21Pipeline and the checkpoint’s recommended 8-step sampling schedule is ready to go.
🌐 Prefer an API? Qwen-Image-2.1 Pro and Turbo APIs are now officially live. Choose a hosted API for your application, or use the Turbo weights in your own workflow.
🤖 ModelScope:
modelscope.cn/models/Qwen/Qw…
🤗 Hugging Face:
huggingface.co/Qwen/Qwen-Imag…
🔗 Pro API:
modelstudio.console.alibabacloud.com/ap-southeast-1…
🔗 Turbo API:
modelstudio.console.alibabacloud.com/ap-southeast-1…
What will you create with 8 steps? Share your results with us!
Built on Qwen-Image-2.1, Turbo is an accelerated checkpoint on the same 7B visual generation architecture.
Fewer steps does not mean lower quality: it still generates strong 2K images from text, and supports continued creation through natural-language edits, from adding accessories to changing a scene.
Start directly with Diffusers: load QwenImage21Pipeline and the checkpoint’s recommended 8-step sampling schedule is ready to go.
🌐 Prefer an API? Qwen-Image-2.1 Pro and Turbo APIs are now officially live. Choose a hosted API for your application, or use the Turbo weights in your own workflow.
🤖 ModelScope:
modelscope.cn/models/Qwen/Qw…
🤗 Hugging Face:
huggingface.co/Qwen/Qwen-Imag…
🔗 Pro API:
modelstudio.console.alibabacloud.com/ap-southeast-1…
🔗 Turbo API:
modelstudio.console.alibabacloud.com/ap-southeast-1…
What will you create with 8 steps? Share your results with us!
Meet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨
A unified model for both generation and editing, delivering top-tier quality in a lightweight package.
Highlights: 👀
- Compact & exceptionally fast: A lire that outperforms most closed-source models, with drastically accelerated inference for multi-image inputs.
- Native transparency: Natively generates and edits RGBA layers, enabling seamless compositing and text editing within transparent images.
- Versatile, high-fidelity editing: Supports up to 10 reference images and precise local control while preserving strict fidelity for portraits and products.
- Broad coverage & stunning aesthetics: Excels at panoramas, infographics, and virtual try-ons, delivering realistic textures and elegant typography.
Start to create your next masterpiece with Qwen-Image-2.1! 🖼️
- Blog: qwen.ai/blog?id=qwen-i…
- GitHub: github.com/QwenLM/Qwen-Im…
- Model Scope: modelscope.cn/models/Qwen/Qw…
- Hugging Face: huggingface.co/Qwen/Qwen-Imag…
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Shashi Jakka । శశి జక్క retweeted
Tech companies trying to replace people with AI, only for people to start replacing tech companies with AI has gotta be the funniest plot twist of the century
Todos los productos de Adobe reimplementados desde cero, gratuitos y de código abierto
→ getartcraft.com/apps
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Shashi Jakka । శశి జక్క retweeted
Someone on Reddit reverse-engineered their LG TV because the Plex app took 30 seconds to load
Built an entire native Plex client from scratch using Claude Code, Opus, and Fable.
Started in C, moved to Rust, ended up building his own OpenGL UI framework along the way
Same TV. picker now loads in 3 seconds instead of 30. Runs at 60 fps. Supports 4K, Dolby Vision, Atmos. Fully open source
One person. One TV he was annoyed with. AI tools doing the work of an entire engineering team firmware reverse engineering, media playback, GPU profiling, shader optimization, UI architecture, all of it
Built an entire native Plex client from scratch using Claude Code, Opus, and Fable.
Started in C, moved to Rust, ended up building his own OpenGL UI framework along the way
Same TV. picker now loads in 3 seconds instead of 30. Runs at 60 fps. Supports 4K, Dolby Vision, Atmos. Fully open source
One person. One TV he was annoyed with. AI tools doing the work of an entire engineering team firmware reverse engineering, media playback, GPU profiling, shader optimization, UI architecture, all of it
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Shashi Jakka । శశి జక్క retweeted
Build and test native Android apps seamlessly with @antigravity.
By connecting the @stitchbygoogle MCP and the Android CLI, the agent imports UI designs, converts them into native Jetpack Compose components, validates everything in an emulator, and executes the final build device.
Get started with Antigravity today: goo.gle/4yCWX56
By connecting the @stitchbygoogle MCP and the Android CLI, the agent imports UI designs, converts them into native Jetpack Compose components, validates everything in an emulator, and executes the final build device.
Get started with Antigravity today: goo.gle/4yCWX56
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Shashi Jakka । శశి జక్క retweeted
Meet Brewlet! ☕ Introduced today at @Devoxx Belgium.
#Java on #Kubernetes, without bundling a JDK in every app image. Ship your JAR; manage JDKs on the nodes.
Learn more at brewlet.sh
#Java on #Kubernetes, without bundling a JDK in every app image. Ship your JAR; manage JDKs on the nodes.
Learn more at brewlet.sh
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