Put @AutoClawAIer through some serious stress testing over the last 2 months: 12 agents deployed and just crossed 1.2B tokens.
Most autonomous agent stacks choke on state drift or memory bloat once you scale tasks!
جوانان قیامی هوشیارباشید
هرشعاری خارج ازکل نظام ومقامات نظام باشه تردیدنکنیدانحرافی وازطرف خودنظامه
این ویدیو را تا آخرنگاه کنید.
همینجوری قیام ۴۰۱ما رابه انحراف کشاندن
دیگرنخواهیم گذاشت
#رضا_پهلوی پست فطرت خجالت بکش چه میخواهی از جان مردم ایران.....
#سلطنت_ولایت_یکصدسال_جنایت
This is the singularity curve.
We are about to enter the vertical part of the curve because we will have AI that can do millions of tasks better than any human.
Anyone who says it will take longer than a few years to develop any future technology is wrong.
من که میدونم چهل سال دیگه پهلوی رو گردن نمیگیرید و میگید «این چپای 404ای علیه امام خامنهای انقلاب و ما رو مستعمرهی غربیا کردن، وگرنه ما که خانوادگی مدافع حرم بودیم» اما نمیتونم ثابت کنم.
My NEW Official Trump Meme is HERE! It’s time to celebrate everything we stand for: WINNING! Join my very special Trump Community. GET YOUR $TRUMP NOW. Go to https://t.co/GX3ZxT5xyq — Have Fun!
چقدر تو دنیای کریپتو حرفهای هستی؟ 📊
👈🏻 کوت کن و امتیازت رو بگو!
سه نفر به قید قرعه معادل 10 میلیون تومن به حساب کاربریشون در نوبیتکس واریز میشه🤩🎁
❌ یادتون نره برای شرکت تو قرعهکشی باید صفحه نوبیتکس رو فالو داشته باشید.
OmniGen
Unified Image Generation
discuss: https://t.co/FFotbU2Ey8
In this work, we introduce OmniGen, a new diffusion model for unified image generation. Unlike popular diffusion models (e.g., Stable Diffusion), OmniGen no longer requires additional modules such as ControlNet or IP-Adapter to process diverse control conditions. OmniGenis characterized by the following features: 1) Unification: OmniGen not only demonstrates text-to-image generation capabilities but also inherently supports other downstream tasks, such as image editing, subject-driven generation, and visual-conditional generation. Additionally, OmniGen can handle classical computer vision tasks by transforming them into image generation tasks, such as edge detection and human pose recognition. 2) Simplicity: The architecture of OmniGen is highly simplified, eliminating the need for additional text encoders. Moreover, it is more user-friendly compared to existing diffusion models, enabling complex tasks to be accomplished through instructions without the need for extra preprocessing steps (e.g., human pose estimation), thereby significantly simplifying the workflow of image generation. 3) Knowledge Transfer: Through learning in a unified format, OmniGen effectively transfers knowledge across different tasks, manages unseen tasks and domains, and exhibits novel capabilities. We also explore the model's reasoning capabilities and potential applications of chain-of-thought mechanism. This work represents the first attempt at a general-purpose image generation model, and there remain several unresolved issues.
یه بندهخدایی یک ماه پیش یه وبسایت بامزه ساخته بوده به اسم One Million Checkboxes که توش فقط یک میلیونتا چکباکس داشته. تنها نکتهش هم این بوده که هر یوزری که یه باکس رو چک/آنچک میکرده، برای همه تغییر میکرده!
اتفاقات بعدش بامزهس... 😅👇