From solution build-out to production, we handle it end to end.🚀 Deploying AI in the real world means more than training a model. ⬇️see Demo youtu.be/683GDxk4rn4?si=JIFV… #Manufacturing #IndustrialAutomation #AIPlatform #AI

🔥 GitHub Trending #1 today: Alibaba’s DeepResearch @Ali_TongyiLab Auto-configure & reproduce it in minutes with Kepilot — then chat your way through any research task. ➡️ Paste the GitHub repo: github.com/Alibaba-NLP/DeepR… ➡️ Into here: kepilot.ai Happy researching! 🎉 #GitHub #DeepResearch #AIagent #Kepilot

Just reproduced DreamerV3 in under 20 mins on Kepilot — no coding background needed. Big thanks to @Danijar for the wonderful model 🙌 Sharing a quick run here 👇

→ Reproduce, run, and tune this repo instantly — zero setup, all via natural language using Kepilot. BCNet tackles challenging 3D object segmentation tasks with a bilateral architecture that excels at occlusions and fine detail. #ComputerVision #PyTorch #OpenSource #DevTools

Revolutionize face alignment with "cleardusk/3DDFA_V2" — offering high-fidelity 3D Dense Face Alignment. Solves precision challenges crucial for AR, VR, and biometric AI apps with its deep learning prowess based on #PyTorch. → Instantly reproduce, run, and tune with 0 Env setup on Kepilot! #AI #OpenSource #ComputerVision

Building environments & fixing dependencies shouldn’t take hours.With Kepilot, it runs in minutes. Try it here 👉 kepilot.ai/ Just message me "apply" We’ll send you an invite code so you can join early,and shape the future of AI together. #AI #Developers #Kepilot

Novena built a full cross-platform research assistant without writing a single line of code. If she can, so can you. Kepilot Private Beta — 100 seats only Reply apply below to join.

solved by us!

Try KePilot: docs.google.com/forms/d/e/1F… KePilot can reproduce complex GitHub repositories with a reproducibility rate of 60%, meaning it successfully runs most of the repositories without errors or manual configuration. On top of that, a growing database of preloaded environments for popular AI/ML papers allows you to launch them in minutes (currently, there are 9 papers available for you to try). #AIResearch #LLM #CUDA #Docker #GitHub #ArtificialIntelligence

We compared KePilot with Cursor and GPT5 by giving a random GitHub repo link. We asked to reproduce the results and here is what we got: 1) KePilot time: 10min, task completion: completed 2) GPT5 time: 1 min, task completion: failed 3) Cursor time: 25min, task completion: failed * This repo requires significant GPU resources to run. Cursor wasn’t able to execute it properly because of these limitations. Moreover, Cursor requires human supervision to complete the task. * KePilot advantage: - takes way less time to load and run the code - able to reproduce GPU intensive repos - 0 human supervision Fill out an invitation form to try it yourself: docs.google.com/forms/d/e/1F… Become an early user! GitHub repo used here as an example: github.com/AUTOMATIC1111/sta… #ML #AIresearch #LLMs #MLengineer

What’s one part of your AI/ML workflow you wish was automated by now?

Kepilot is a platform designed to simplify complex AI/ML research. It brings together all essential research tools in one interface and automatically sets up the environment for your project, which you can also customize directly in the web. Additionally, Kepilot includes a database of ready-to-run environments for trending AI papers, making experimentation fast and seamless. #AIResearch #LLM #largelanguagemodels #DataScience

𝐘𝐮𝐭𝐨𝐧𝐠, 𝐨𝐮𝐫 𝐒𝐲𝐬𝐭𝐞𝐦 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐌𝐚𝐧𝐚𝐠𝐞𝐫, 𝐬𝐡𝐚𝐫𝐞𝐝 𝐡𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐰𝐢𝐭𝐡 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 𝐬𝐞𝐭𝐮𝐩 𝐚𝐧𝐝 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐀𝐈 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬: "𝘚𝘦𝘵𝘵𝘪𝘯𝘨 𝘶𝘱 𝘦𝘯𝘷𝘪𝘳𝘰𝘯𝘮𝘦𝘯𝘵𝘴 𝘸𝘢𝘴 𝘢𝘭𝘸𝘢𝘺𝘴 𝘵𝘪𝘮𝘦-𝘤𝘰𝘯𝘴𝘶𝘮𝘪𝘯𝘨 𝘢𝘯𝘥 𝘧𝘳𝘶𝘴𝘵𝘳𝘢𝘵𝘪𝘯𝘨. 𝘐 𝘰𝘧𝘵𝘦𝘯 𝘴𝘱𝘦𝘯𝘵 𝘩𝘰𝘶𝘳𝘴 𝘳𝘦𝘴𝘰𝘭𝘷𝘪𝘯𝘨 𝘥𝘦𝘱𝘦𝘯𝘥𝘦𝘯𝘤𝘺 𝘤𝘰𝘯𝘧𝘭𝘪𝘤𝘵𝘴, 𝘤𝘰𝘯𝘧𝘪𝘨𝘶𝘳𝘪𝘯𝘨 𝘱𝘢𝘤𝘬𝘢𝘨𝘦𝘴, 𝘢𝘯𝘥 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘨𝘦𝘵 𝘱𝘳𝘰𝘫𝘦𝘤𝘵𝘴 𝘵𝘰 𝘳𝘶𝘯 𝘱𝘳𝘰𝘱𝘦𝘳𝘭𝘺. 𝘐𝘵 𝘴𝘭𝘰𝘸𝘴 𝘥𝘰𝘸𝘯 𝘮𝘺 𝘢𝘤𝘵𝘶𝘢𝘭 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘸𝘰𝘳𝘬." She also noted the difficulties in reproducing results from academic papers: "𝘔𝘢𝘯𝘺 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘱𝘢𝘱𝘦𝘳𝘴 𝘥𝘰𝘯’𝘵 𝘪𝘯𝘤𝘭𝘶𝘥𝘦 𝘦𝘯𝘰𝘶𝘨𝘩 𝘪𝘮𝘱𝘭𝘦𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯 𝘥𝘦𝘵𝘢𝘪𝘭. 𝘙𝘦𝘱𝘳𝘰𝘥𝘶𝘤𝘪𝘯𝘨 𝘵𝘩𝘦𝘮 𝘮𝘦𝘢𝘯𝘵 𝘴𝘱𝘦𝘯𝘥𝘪𝘯𝘨 𝘢 𝘭𝘰𝘵 𝘰𝘧 𝘵𝘪𝘮𝘦 𝘳𝘦𝘷𝘦𝘳𝘴𝘦-𝘦𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘪𝘯𝘨 𝘴𝘦𝘵𝘶𝘱𝘴, 𝘸𝘩𝘪𝘤𝘩 𝘰𝘧𝘵𝘦𝘯 𝘭𝘦𝘥 𝘵𝘰 𝘪𝘯𝘤𝘰𝘮𝘱𝘭𝘦𝘵𝘦 𝘰𝘳 𝘶𝘯𝘴𝘶𝘤𝘤𝘦𝘴𝘴𝘧𝘶𝘭 𝘳𝘦𝘴𝘶𝘭𝘵𝘴. 𝘋𝘦𝘣𝘶𝘨𝘨𝘪𝘯𝘨 𝘳𝘦𝘮𝘢𝘪𝘯𝘴 𝘢 𝘴𝘪𝘨𝘯𝘪𝘧𝘪𝘤𝘢𝘯𝘵 𝘤𝘩𝘢𝘭𝘭𝘦𝘯𝘨𝘦." Yutong joined KeploreAI to address the inefficiencies in AI/ML research workflows. She aims to transform how researchers from various fields manage replication, environment setup, and experiment execution. “𝘒𝘦𝘗𝘪𝘭𝘰𝘵 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘦𝘴 𝘦𝘯𝘷𝘪𝘳𝘰𝘯𝘮𝘦𝘯𝘵 𝘴𝘦𝘵𝘶𝘱, 𝘢𝘭𝘭𝘰𝘤𝘢𝘵𝘦𝘴 𝘮𝘦𝘮𝘰𝘳𝘺 𝘢𝘯𝘥 𝘎𝘗𝘜 𝘳𝘦𝘴𝘰𝘶𝘳𝘤𝘦𝘴 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘵𝘭𝘺, 𝘢𝘯𝘥 𝘦𝘭𝘪𝘮𝘪𝘯𝘢𝘵𝘦𝘴 𝘨𝘶𝘦𝘴𝘴𝘸𝘰𝘳𝘬. 𝘐 𝘤𝘢𝘯 𝘯𝘰𝘸 𝘧𝘰𝘤𝘶𝘴 𝘦𝘯𝘵𝘪𝘳𝘦𝘭𝘺 𝘰𝘯 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘳𝘢𝘵𝘩𝘦𝘳 𝘵𝘩𝘢𝘯 𝘳𝘦𝘴𝘰𝘭𝘷𝘪𝘯𝘨 𝘵𝘦𝘤𝘩𝘯𝘪𝘤𝘢𝘭 𝘪𝘴𝘴𝘶𝘦𝘴. 𝘔𝘰𝘳𝘦𝘰𝘷𝘦𝘳, 𝘒𝘦𝘗𝘪𝘭𝘰𝘵 𝘪𝘴 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘪𝘯𝘨 𝘢𝘯 𝘌𝘹𝘱𝘭𝘰𝘳𝘢𝘵𝘪𝘰𝘯 𝘛𝘢𝘣, 𝘢 𝘧𝘦𝘢𝘵𝘶𝘳𝘦 𝘢𝘭𝘭𝘰𝘸𝘪𝘯𝘨 𝘶𝘴𝘦𝘳𝘴 𝘵𝘰 𝘣𝘳𝘰𝘸𝘴𝘦 𝘢𝘤𝘢𝘥𝘦𝘮𝘪𝘤 𝘱𝘢𝘱𝘦𝘳𝘴 𝘢𝘯𝘥 𝘳𝘦𝘱𝘭𝘪𝘤𝘢𝘵𝘦 𝘦𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵𝘴 𝘪𝘯𝘴𝘵𝘢𝘯𝘵𝘭𝘺. 𝘈𝘭𝘭 𝘦𝘯𝘷𝘪𝘳𝘰𝘯𝘮𝘦𝘯𝘵𝘴 𝘢𝘳𝘦 𝘱𝘳𝘦-𝘤𝘰𝘯𝘧𝘪𝘨𝘶𝘳𝘦𝘥 𝘣𝘺 𝘈𝘐 𝘢𝘨𝘦𝘯𝘵𝘴 𝘪𝘯 𝘤𝘰𝘭𝘭𝘢𝘣𝘰𝘳𝘢𝘵𝘪𝘰𝘯 𝘸𝘪𝘵𝘩 𝘰𝘶𝘳 𝘵𝘦𝘢𝘮 𝘰𝘧 𝘈𝘐/𝘔𝘓 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩𝘦𝘳𝘴.” A free trial of KePilot will be available starting from July 30. If you currently have issues that need to be solved regarding your particular case, contact us for guidance. We will explain how to save a significant amount of time for your research. #MachineLearning #phdpositions #AI #ML #Research #researchsupport #AIResearch