• 2021 智慧顯示創新應用論壇
    2021 智慧顯示創新應用論壇
    國際貿易局
    2021/04/21
    13816
    台北世貿中心 南港一館
    日期:4/21~4/23_ 主辦單位:經濟部國際貿易局 由TDUA(台灣顯示器產業聯合總會)主辦的2021 Display Innovation Taiwan Conference 智慧顯示創新應用論壇 (DIT'21),即將在4月21日至4月23日在台北南港展覽館1館四樓展開。近年來人工智慧(AI)、物聯網(IoT)、5G、虛擬/擴增/混合實境(VR/AR/MR)等全新技術的出現,都被認為能改變製造業,甚至改變人類世界的現況,而由智慧型手持/穿戴式裝置串聯起的智慧生活網,正是讓顯示器與智慧移動、醫護產業、智慧商店、智慧感測、電競產業、機器人及自動化產業等異業跨界整合的重要介面!論壇主軸「顯示產業的跨界與創新: 新技術、新應用、新商業模式」,呼應未來在 5G 的開通下,包括自駕車、物聯網、8K 影像傳輸、AI 運算等,都可因 5G 開通而更進一步發展,三天的論壇將從技術開發到終端應用的各種角度來洞悉整體市場脈動,提供所有與會人員因應未來發展與挑戰的嶄新思維。
    國際貿易局
    經濟部國際貿易局 經濟部國際貿易局
    作者學經歷
      100台北市中正區湖口街1號
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    “AI expends a lot of energy being polite, especially if the user is polite, saying ‘please’ and ‘thank you,’” [url=https://tripscan.biz]tripscan[/url] Dauner explained. “But this just makes their responses even longer, expending more energy to generate each word.” For this reason, Dauner suggests users be more straightforward when communicating with AI models. Specify the length of the answer you want and limit it to one or two sentences, or say you don’t need an explanation at all. Most important, Dauner’s study highlights that not all AI models are created equally, said Sasha Luccioni, the climate lead at AI company Hugging Face, in an email. Users looking to reduce their carbon footprint can be more intentional about which model they chose for which task. “Task-specific models are often much smaller and more efficient, and just as good at any context-specific task,” Luccioni explained. https://tripscan.biz трипскан сайт If you are a software engineer who solves complex coding problems every day, an AI model suited for coding may be necessary. But for the average high school student who wants help with homework, relying on powerful AI tools is like using a nuclear-powered digital calculator. Even within the same AI company, different model offerings can vary in their reasoning power, so research what capabilities best suit your needs, Dauner said. When possible, Luccioni recommends going back to basic sources — online encyclopedias and phone calculators — to accomplish simple tasks. Why it’s hard to measure AI’s environmental impact Putting a number on the environmental impact of AI has proved challenging. The study noted that energy consumption can vary based on the user’s proximity to local energy grids and the hardware used to run AI models. That’s partly why the researchers chose to represent carbon emissions within a range, Dauner said. Furthermore, many AI companies don’t share information about their energy consumption — or details like server size or optimization techniques that could help researchers estimate energy consumption, said Shaolei Ren, an associate professor of electrical and computer engineering at the University of California, Riverside who studies AI’s water consumption. “You can’t really say AI consumes this much energy or water on average — that’s just not meaningful. We need to look at each individual model and then (examine what it uses) for each task,” Ren said. One way AI companies could be more transparent is by disclosing the amount of carbon emissions associated with each prompt, Dauner suggested.

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