Top AI的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列股價、配息、目標價等股票新聞資訊

Collective Wisdom: Co-Creating Media for Equity and Justice

為了解決Top AI的問題，作者Cizek, Katerina,Uricchio, William 這樣論述：

How to co-create--and why: the emergence of media co-creation as a concept and as a practice grounded in equity and justice.Co-creation is everywhere: It’s how the internet was built; it generated massive prehistoric rock carvings; it powered the development of vaccines for COVID-19 in record time.

Co-creation offers alternatives to the idea of the solitary author privileged by top-down media. But co-creation is easy to miss, as individuals often take credit for--and profit from--collective forms of authorship, erasing whole cultures and narratives as they do so. Collective Wisdom offers the f

irst guide to co-creation as a concept and as a practice, tracing co-creation in a media-making that ranges from collaborative journalism to human-AI partnerships. Why co-create--and why now? The many coauthors, drawing on a remarkable array of professional and personal experience, focus on the radi

cal, sustained practices of co-creating media within communities and with social movements. They explore the urgent need for co-creation across disciplines and organization, and the latest methods for collaborating with nonhuman systems in biology and technology. The idea of ＂collective intelligence

＂ is not new, and has been applied to such disparate phenomena as decision making by consensus and hived insects. Collective wisdom goes further. With conceptual explanation and practical examples, this book shows that co-creation only becomes wise when it is grounded in equity and justice. Kateri

na Cizek, an Emmy and Peabody-winning documentarian, is the Artistic Director and Cofounder of the Co-Creation Studio at MIT Open Documentary Lab. William Uricchio is Professor of Comparative Media Studies at MIT, where he is also Founder and Principal Investigator of the MIT Open Documentary Lab an

d Principal Investigator of the Co-Creation Studio.

Top AI進入發燒排行的影片

利用模糊層級分析法 探討半導體產業品牌影響因素之分析

為了解決Top AI的問題，作者范志旻 這樣論述：

隨著時間的流逝，半導體創新正在發生變化，可以適用於不同的創新業務，半導體業務的發展至關重要，因而開闢了許多新的職位。半導體業務是一個融合了不同創新能力並協調上游，中途和下游提供商的專業能力的行業，並且通常具有較高的進入壁壘 。廠家已投入花費很多精力與成本進入這個行業，期盼永續經營與回饋利害關係人。本研究第一步採用PEST, 五力 & SWOT分析，在美國，日本和臺灣，這些是國際半導體供應商鏈中的關鍵成員。經過最新半導體有關文獻的討論和分析，發現現有廠商已經建立了行業品牌，並獲得了用戶的信任。因此，品牌研究在這個行業是大家一直在探索的領域。考慮到寫作對話和大師談話，本研究使用分析層次結構(A

HP)研究技術對品牌的關鍵指針在半導體品牌的關鍵部件上進行重要性的排序，然後利用模糊層次分析法(FAHP)來分析這些標記之間的聯繫。經調查，有11項顯著結果可供參考，關鍵是要在半導體品牌建設上取得優異的成績，“客戶價值”和“品牌資產”都必須達到一定的水平。本研究發現，半導體品牌策略應以“客戶價值”為核心，解決客戶問題，創造卓越價值，並隨著技術的進步不斷投入新產品的研發，以奠定半導體品牌長期成功的基礎。

Ion Curtain

為了解決Top AI的問題，作者Ow, Anya 這樣論述：

For decades there has been a tense interstellar Cold War between the UN and the Russian military. When scavenger and pirate Solitaire Yeung and his salvage crew discover top secret artificial intelligence in a destroyed Russian battleship, they steal the AI and run. Now the UN is after it. The Ru

ssians are after it. And, worst of all, an even more powerful foe in the darkness of space is after it. Will humanity itself be able to survive?

應用文字探勘於業配文揭露偵測

為了解決Top AI的問題，作者洪御哲 這樣論述：

業配文是在廣告媒體內容中有目的地整合品牌或品牌說服性訊息，以換取贊助商的報酬。在網際網路與行動裝置的普及下，社群媒體快速成長，捧紅了許多「網紅」高影響力者，看上此高度個人化與可控制內容的特性，使廠商將資源投入在這些人身上，以獲取商品的曝光與銷售。但是業配文常常會有假分享真業配的問題，讓消費者認為是自己的真實體驗分享，而非商業贊助，可能誤導消費者進行消費，故本研究目的在於能否建立一個模型找出背後可能是未揭露的業配文章。首先，先搜集痞客邦百大部落客的資料，建立會揭露業配之部落客名冊，再搜集該部落客發表過的所有文章，藉由揭露文字標注業配文與非業配文。然後透過機器學習方法SVM、CNN與Google

所開發的深度語言模型BERT進行訓練與比較，最後以CNN平均得出最高的準確度83.625%，同時，在我們標注的未揭露業配文章資料中，CNN能夠偵測業配文的準確度為90.69%。最後，應用逐層相關傳播LRP解釋CNN模型，觀察哪些常出現業配文文字最可能被預測為業配文，比較模型與人為觀點，並藉此找出業配文的特徵，以提供給消費者進行判斷。