[#IDOLSTABLE#/EP.04] 𝟰𝙩𝙝 𝙏𝙖𝙗𝙡𝙚 𝙊𝙪𝙩𝙛𝙞𝙩 #MnetPlus_Original# The fourth Gathering: Travel✈️ The CREW's TMI overload, watch the FULL VOD on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀! Hotspot where Korean food unites the world beyond borders🍽️ Global Food Talk Show where your bias shares their fave K-FOOD 〈IDOL'S TABLE〉 on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 👉 📍 Every Tuesday 8PM (KST) 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 Release 📍 Watch on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 📺 Every Wednesday 8PM (KST) 𝗠𝗻𝗲𝘁 On Air == [IDOL'S TABLE/EP.04] 𝟰𝙩𝙝 𝙏𝙖𝙗𝙡𝙚 𝙊𝙪𝙩𝙛𝙞𝙩 네 번째 모임: 여행✈️ 식구들의 TMI 대방출, 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀에서 FULL VOD로 만나보세요! 국경을 넘어 한식으로 하나 되는 핫플레이스🍽️ 최애의 K-FOOD 취향이 펼쳐지는 글로벌 푸드 토크쇼 〈IDOL'S TABLE〉 on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 👉 📍 매주 화요일 저녁 8시 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 공개 📍 Watch on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 📺 매주 수요일 저녁 8시 𝗠𝗻𝗲𝘁 본방송 #KIMPOONG# #LEEEUNJI# #BamBam# #JAEMIN# #CHENLE# #KIMJAEHWAN# #MINNIE# #TOMOYA# #YU# #아돌테# #IDT# #엠넷플러스오리지널# #MnetPlus# #엠넷플러스# #Mnet# #엠넷#

[#IDOLSTABLE#/EP.05] 𝟱𝙩𝙝 𝘾𝙍𝙀𝙒'𝙎 𝙏𝘼𝘽𝙇𝙀 #MnetPlus_Original# A table full of fun K-FOOD TMI from the 𝘾𝙍𝙀𝙒'𝙎 𝙏𝘼𝘽𝙇𝙀🍴 What are the dishes the new CREW member drew and introduced themselves?! Watch on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀👀 Hotspot where Korean food unites the world beyond borders🍽️ Global Food Talk Show where your bias shares their fave K-FOOD 〈IDOL'S TABLE〉 on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 👉 📍 Every Tuesday 8PM (KST) 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 Release 📍 Watch on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 📺 Every Wednesday 8PM (KST) 𝗠𝗻𝗲𝘁 On Air == [IDOL'S TABLE/EP.05] 𝟱𝙩𝙝 𝘾𝙍𝙀𝙒'𝙎 𝙏𝘼𝘽𝙇𝙀 다양한 한식 TMI가 가득한 식구의 테이블🍴 새식구가 직접 그리고 소개한 음식의 정체는?! 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀에서 확인해보세요👀 국경을 넘어 한식으로 하나 되는 핫플레이스🍽️ 최애의 K-FOOD 취향이 펼쳐지는 글로벌 푸드 토크쇼 〈IDOL'S TABLE〉 on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 👉 📍 매주 화요일 저녁 8시 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 공개 📍 Watch on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 📺 매주 수요일 저녁 8시 𝗠𝗻𝗲𝘁 본방송 #KIMPOONG# #LEEEUNJI# #BamBam# #JAEMIN# #CHENLE# #CARMEN# #HASUNGWOON# #MINAMI# #아돌테# #IDT# #엠넷플러스오리지널# #MnetPlus# #엠넷플러스# #Mnet# #엠넷#

God. I try not to vent too much on here but I’m really struggling right now just with stress, pressure, life. (This is probably tmi.) I took a big break off in July & didn’t shoot other than social media content for about 4 weeks, which was really good for me. (You probably didn’t even notice which was the goal! I pre-film so I’m able to do this.) I came back excited and ready to work and was working for about 5 days until early last week when I faced a really scary health issue (I found out I have a really horrible allergy to a medication that resulted in my entire body & inside my mouth breaking out in PAINFUL hives & my entire body shutting down) I just started feeling 80% better today, but I’ve definitely lost some stamina and am still feeling weak which isn’t something I’m used to. I also work really really hard to maintain my body and keep muscle and I lost a bit of weight which I don’t feel very good about. Because of the break and then the health issue I’m just so behind in work, getting back to people, I had to reschedule a ton of shoots which means now I’m working double overtime, I feel so much pressure to be this perfect and beautiful sexy person and to be a perfect friend and react to things perfectly and be a perfect wife and a perfect family member and be able to handle all of this with strength like I always do, and I am so happy to have so many people who rely on me to be stable, but I’m stretched so thin right now it feels impossible I’m just trying to get through this day by day. I love my job more than anything but I don’t think people know what it takes very often and how so much of it also involves perception and interpersonal relationships and balancing things and my usual bubbly happy self feels so drained and there’s nothing I can do to control it other than keep a smile on my face and try to keep filling my life with happiness.

This is one of the most effective ways to improve your agentic workflows. If you are building computer-use agents, this one is worth your time. Task Model Induction takes a raw recording of someone working, just screenshots and mouse and keyboard events, and turns it into a symbolic model of how the work was actually done. The hard part is that real recordings are multi-threaded. People switch between goals mid-task. TMI first discovers the latent tasks inside an unconstrained trace and separates them, hitting 0.974 agreement against ground-truth groupings. Each recovered task then gets two things. A hierarchical objective model of how the goal decomposes, and a procedure model of the control flow that organized execution. It reconstructs 74.9% of observed execution steps, and skills derived from these task models lift held-out task accuracy by 30.0% over the strongest workflow induction baseline. Passive traces are sitting on most work laptops already. This work just shows how to mine them into auditable, reusable skills. Paper: Track more trending AI papers in our academy: