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lightbulbking
順帶一題,2025年南台三皿盃冠軍是BCBL;2026年南台三皿盃冠軍是中正大學瓶蓋棒球社(CCU capbaseball club)。 預計明年的三皿盃將要開始由TCBA籌辦,而非南台科大瓶蓋棒球社(stust_pbc)舉辦,這將會是TCBA重要的里程碑!
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lightbulbking
同年8月,BCBL舉辦夏聯冠軍賽,由粒家軍打敗台顆大獲得冠軍。 同年11月,日本瓶蓋棒球協會成員來台正式授權Powei以台灣瓶蓋棒球協會(TCBA)相關事宜。 同年12月初,Powei將TCBA申請資料寄給台灣內政部。 直到2026年5月,成功召開TCBA理事選舉,由Powei擔任總理事長,帶領其他八人經營目前的TCBA!
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lightbulbking
2024年3月,BCBL進行第一次選手選秀,粒家軍與台顆大兩隊於同年4月及5月進行BCBL對抗賽。 2024年5月,南台科大瓶蓋棒球社舉辦外校瓶蓋棒球交流會,並於同年6月,再次舉辦南台三皿盃,BCBL也首次集結聯盟成員參加,最後獲得亞軍,南台科大棒球社在冠軍戰擊敗BCBL奪冠,成功建立三連霸王朝......9
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lightbulbking
2023年7月,BCBL進行夏聯,並首次引入數據統計系統,開始統計聯盟成員各項數據與賽事紀錄。同年8月,台南一中瓶蓋棒球社與彰化高中瓶蓋棒球社正式成立。 同年8月,南台科大瓶蓋棒球社受日本協會邀請參加蓋ノ陣瓶蓋棒球全國競賽,是台灣隊伍首次遠征海外瓶蓋棒球競賽.......7
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lightbulbking
同年2月,BCBL冬聯因故停辦一次;同年5月,中正大學瓶蓋棒球社正式成立,並與南台科大瓶蓋棒球社進行第一次交流活動;同年6月,南台科大瓶蓋棒球社舉辦第二次南台三皿盃,也是首次以全國性競賽名義舉辦的瓶蓋棒球大型賽事,最後由南台科大棒球社成功衛冕冠軍,大園高中瓶蓋棒球社獲得亞軍........6
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lightbulbking
2022年3月,南台科大瓶蓋棒球社舉辦了第一屆南台三皿盃,以校內隊伍為主,最終由南台科大棒球社獲得冠軍、南台科大瓶蓋棒球社獲得亞軍;同年7月,BCBL進行夏聯,無名隊9:5安柏大盒子;同年12月,中正大學瓶蓋棒球社開始籌備,並舉辦瓶蓋棒球投準賽,由南台科大瓶蓋棒球社社長郭恩嘉奪冠......4
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lightbulbking
2020年2月,基隆市海洋大學瓶蓋棒球社成立;同年12月,台北市成功高中開始籌組社團,北部地區開始有瓶蓋棒球交流活動。另外,以台中為基地的BCBL草創,不過該聯盟並無對外宣傳與交流,以鞏固台中區聯盟成員與進行內部聯賽為主......2
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bonnet30
مساج في جدة الرياض منزلي فندقي bcbl
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davebetts4
⎐كُـود⎐كوبِون⎐خـِصم⎐ ⎐نون⎐ ⊵S3Q⊴ ايهرب⊴ ايهيرب⊴ ⊵GCA5893⊴ ⎐نمشي⎐ ⊵AABN⊴ ⎐ريف▬للعطور⎐ ⊵AX140⊴ ريــفا⎐ ⊴ASMAA⊴ المـطار ⊵M24⊴ ⎐فوغا⎐كلوسـيت⎐ ⊵V1⊴ ___ bcbL
jx0iiK94bnx1Ge6
⎐كُـود⎐كوبِون⎐خـِصم⎐ ⎐نون⎐ ⊵S3Q⊴ ⎐ايهرب⎐ايهيرب اهرب ⊵GCA5893⊴ ⊴تيمو ⊴ ⊵TEB72⊴ ⎐ليـفل▬ شـوز ▬لفيل▬ ⊵AAA127⊴ ⎐نمشي⎐ ⊵AABN⊴ ⎐فوغا⎐كلوسـيت⎐ ⊵V1⊴ ماكــس⎐ A9B *** bCBL
JP Deblonde retweeted
QingQ77
从 MEG/EEG 脑电信号里还原出人正在打什么字🤯 github.com/facebookresearch/… Meta 和 BCBL 做的研究项目,用卷积编码器加 Transformer 加字符级语言模型,从非侵入式的 MEG(脑磁图)和 EEG 信号里解码出受试者正在打的句子。
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bcbl_
✍️ A new paper led by @UniBarcelona and @TuftsMedSchool with the collaboration of #BCBL researcher Kepa Paz-Alonso has been published in #NeuroImage. info ⬇️ sciencedirect.com/science/ar…
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bcbl_
🎓 We have two new PhDs in #BCBL! Jiaqi Mao and Wai Leung Wong have successfully defended their PhD thesis. Congratulations! 🤩
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0x_codex
Meta’s Brain2Qwerty v2 is worth paying attention to, but not for the sci-fi framing. The important story is not “AI can read minds.” That is the wrong abstraction. The useful abstraction is a measurement stack: non-invasive sensors collect a very noisy signal, deep learning maps that signal directly into text, language-model context repairs part of the ambiguity, and engineers still decide which training configuration is trustworthy enough to use. That framing matters because it makes the progress legible. Meta says v2 was trained on roughly 22,000 sentences from nine volunteer participants, each recorded for 10 hours while wearing MEG equipment and actively typing. The reported result is 61% word accuracy overall, with the best participant reaching 78%, and more than half of that participant’s decoded sentences having one word error or less. Those numbers are not a consumer product. They are not a replacement for clinicians, and they do not erase the huge practical constraints around MEG hardware, participant-specific data, calibration, privacy, consent, and real-world robustness. But they do change the shape of the problem. For years, the cleanest brain-computer-interface demos often depended on invasive approaches because the signal quality was better. Brain2Qwerty points to a different path: if non-invasive recordings are noisy but structured, then scale can attack the gap. More paired neural-and-text data, better decoders, stronger language priors, and more careful evaluation can move the frontier without making surgery the only route. The most interesting detail is that Meta is releasing code, and BCBL is releasing the v1 dataset. That turns the work from a one-off demo into something closer to a reproducible research substrate. Once a field has shared data, shared training code, and shared benchmarks, progress can compound. The lesson for AI builders is broader than neurotech: many “impossible interface” problems are actually pipeline problems. The interface becomes plausible when sensing, representation learning, context, evaluation, and human oversight improve together. Brain2Qwerty v2 is early research. But it is a strong reminder that the next interface breakthroughs may come less from magical new UI metaphors, and more from disciplined measurement stacks that turn messy human signals into usable software signals. #AI #Neurotech #BCI #MachineLearning #Research
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tontontonton
gigazine.net/news/20260630-b… #cloudnews #クラウド #AI 脳活動をもとにテキストを読み取る技術は複数の研究機関によって開発されていますが、読み取り精度を上げるには外科手術によって脳内に電極を埋め込んで脳波を読み取る必要がありました。Brain2QwertyはMetaがバスク認知・脳・言語センター(BCBL)と
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Basque_Country
La EHU marca hoy la lectura del día con un avance en infertilidad masculina. En esta selección también aparecen BCBL, Boga e Iberdrola. Solo una parte del resumen diario de AboutBC. Lee el resumen completo del día en About Basque Country: go.aboutbasquecountry.eus/no… #AboutBC #EHU
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