Загрузка видео...
Не удалось загрузить видео
Algorhythm Project “Schneider” Original Song “SCHNEIDER” DEC 24 2024 𝐘𝐨𝐮𝐭𝐮𝐛𝐞 𝐏𝐫𝐞𝐦𝐢𝐞𝐫𝐞: Schneider Ch.【ARP】 Time 21:00 (GMT+7) Let me write a song for myself 💜🐙 #Schneider_ARP #KrakenClass #OrionARP #ARProject #VtuberTH
199,882 просмотров • 1 год назад •via X (Twitter)
Комментарии: 11
Lawrenze l Blessing 【🍰Evergarden☕️✨】1 год назад
กิ๊ซซซซ ✨
Solar Heavy1 год назад
check this edm guitar track out
miyafem m1 год назад
@ARP_Vtuber คุณพ่อทรงเท่มาก แต่คุณลูกบอกว่าเพลงโกโกวา 😭😭
Kashi S. 🫶🏻🍒🥥 𐙚🍑🧁🎠1 год назад
นี่สินะคะที่เซอร์ไพรส์อยากจะบอก รอฟังน้าาาาาา it will be one of the best gift for this Christmasค่ะ💜🐙 แต่…แค่มือยังแอค ช่วยไม่ได้ ก็คนมันหล่ออ่ะเนอะ ตาบ้าเอ้ย ฉันเขินจนม้วนเป็นเพรซเซลแล้วนะ >///0///<
NaKa' นากะไม่ใช่นะค่ะ1 год назад
กี้ดด แอคมากกก
AnotherAri1 год назад
ว้าว ได้แต่งเพลงให้ตัวเองจริง ๆ ด้วยยย รอฟังเลยยยย 💜💜💜💜
Thalia.A✨1 год назад
รอฟังเลยค่ะ👀✨
Ginko 💚1 год назад
โอ้โหหห แอคมากกก
J ' kanghan✨️1 год назад
กรี๊ดดดดดด✨️
MaMeaw1 год назад
เรื่องดีจริงด้วย รอนะคะ 🥰
Nam1 год назад
อ๊าก รอฟังเลยครับ!!😭🫶
![[TRANS] Knetz comments on Kim Sejeong's A Capella Performance of Love Wins All (Original by IU) 1. This kind of song really suits Kim Sejeong.. Let's get another song like "Flower Way" for Sejeong ㅠㅠ 2. It's a cappella, but it feels like there's accompaniment. 3. She's so talented in musicals and everything... I wish she became more famous. 4. Sejeong's voice really fits this kind of song ㅠㅠㅠ 5. Please release another song like "Flower Way" or "Tunnel" ㅜㅜㅜ 6. This is the first time I've seen someone other than IU sing IU's song so perfectlyㅠ Kim Sejeong is the bestㅠ 7. Her expression shows she's giving it her all. 8. This song seems really difficult, but she sings it so well ㄷㄷ 9. She really enunciates every word, maybe because she does musicals, it's so good. 10. If she sounds this good with just a bit of practice, I want to hear a proper cover like with "My Sea." 11. I didn't expect her to sing this well. 12. As a true Uaena, she fully captures the feel of the song, making it great to listen to and watch. 13. She’s handsome (beautiful). 14. The way she emphasizes each word and note is so moving..ㅠ 15. She produces such rich tones... amazing..ʚ(ȉˬȉ⁎)ɞ˒˒ 16. It's a difficult song, but it's so easy to listen to~~ Always supporting actress Kim Sejeong. 17. She’s really good… To sing so cleanly a cappella..?? 18. Her cover of "My Sea" was amazing, and this is incredible too.. I hope she does a full cover ㅜㅜ 19. She winks every time she hits a high note. 20. She just sings so well. 21. Kim Sejeong is pretty. 22. I like how the lyrics are clearer. 23. I proudly declare this the best cover. 24. Sejeong, let's come back with this kind of ballad next. 25. She sings so well. 26. This song is really difficult, but to sing it this well a cappella... 27. But with so many fans ("Sesang" - Kim Sejeong's fandom name), you can't escape from "Sesang" ㅎㅎ 28. If Kim Sejeong is struggling with this, the song must be really difficult. #김세정 #KimSejeong](https://image.24vids.com/tw-1798235260360257602/ext_tw_video_thumb/1798235061684453376/pu/img/iIbM1tn9tQp6kCQ0.jpg)
![What could Alphafold 4 look like? (Sergey Ovchinnikov, Ep #3) 2 hours listening time (links below) To those in the (machine-learning for protein design) space, Dr. Sergey Ovchinnikov (Sergey Ovchinnikov) is a very, very well-recognized name. A recent MIT professor (circa early 2024), he has played a part in a staggering number of recent great papers in the field: ColabFold, RFDiffusion, Bindcraft, automated design of soluble proxies of membrane proteins, elucidating what protein language models are learning, conformational sampling via Alphafold2, and many more. Of course, all these papers were group efforts, but Sergey's name comes up astonishingly frequently! And even beyond the research that have come from his lab in the last few years, the co-evolution work he did during his PhD/fellowship also laid some of the groundwork for the original Alphafold paper, being cited twice in it. This is a two hour conversation with him, asking every question I could think of. We talk about his own journey into biology research, an issue he has with Alphafold3, what Alphafold4-and-beyond models may look like, what research he’d want to spend a hundred million dollars on, and lots more. Topics/institutions we discuss: Arc Institute's Evo models, Hannah Wayment-Steele's work, Isomorphic Labs's AF2/AF3, and EvolutionaryScale's ESM models Also, extremely grateful to Asimov Press (Asimov Press) for helping fund the travel + studio time required for this episode! They are a non-profit publisher dedicated to thoughtful writing on biology and metascience, such as articles over synthetic blood and interviews with plant geneticists. I myself have published within them twice! I highly recommend checking out their essays at or reaching out to editors@asimov.com if you’re interested in contributing. Timestamps: [00:00:00] Highlight clips [00:01:10] Introduction + Sergey's background and how he got into the field [00:18:14] Is conservation all you need? [00:23:26] Ambiguous vs non-ambiguous regions in proteins [00:24:59] What will AlphaFold 4/5/6 look like? [00:36:19] Diffusion vs. inversion for protein design [00:44:52] A problem with Alphafold3 [00:53:41] MSA vs. single sequence models [01:06:52] How Sergey picks research problems [01:21:06] What are DNA models like Evo learning? [01:29:11] The problem with train/test splits in biology [01:49:07] What Sergey would do with $100 million](https://image.24vids.com/tw-1915897678187372557/amplify_video_thumb/1915847249084456960/img/TnpQQQNlc88AcmQ2.jpg)