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NVIDIA 工程師 Chris Alexiuk 分享開放模型理念與 Nemotron 應用方向
NVIDIA 對深度學習產品研究工程師 Chris Alexiuk 的人物專訪，談及他如何透過 YouTube 教開發者打造 LLM 應用與代理，也說明他對開放 AI 的看法。Alexiuk 將 Nemotron 3.5 Lightning 描述為適合開發者高頻執行工作的模型，並指出 Nemotron Ultra 可用於企業長時間運作的代理與深度研究。
完整報導
NVIDIA 於 2026 年 11 月 5 日刊出 Chris Alexiuk 的人物專訪。Alexiuk 是駐多倫多的 NVIDIA 深度學習資深產品研究工程師，並在 YouTube 教開發者如何建構、微調、評估及推出可投入生產環境的 LLM 應用與代理。
Alexiuk 認為，開放 AI 不只涉及模型權重，也需要取得訓練資料與訓練配方。專訪將 NVIDIA Nemotron 家族描述為面向長時間運作、自我演進及專業化 AI 代理的開源多模態模型；Alexiuk 表示，Nemotron 3.5 Lightning 可負責個別開發者重複且高頻的執行工作，而 Nemotron Ultra 則可供企業用於長時間自主代理、深度研究及企業任務。NVIDIA 的 Nemotron 3.5 模型頁另將 Lightning 描述為具 300 億參數、每次啟用 30 億參數的文字模型。
專訪也提到，Alexiuk 曾參與 GTC Berlin 的 Build-a-Claw 活動，與開發者交流。這篇人物介紹將開放模型的實際用途連結到開發者教育與代理工作流程；所列模型用途是 Alexiuk 的說明，並非新增的價格或供應資訊。
為什麼值得注意
這篇專訪補充了開放模型如何進入開發者工作流程的具體脈絡：Alexiuk 的教育內容涵蓋 LLM 應用從建構到部署，而他將 Lightning 與 Ultra 分別連結到高頻執行工作及企業級長時間代理任務。NVIDIA 對 Lightning 規模的說明，也有助讀者辨識其定位。
來源證據
先看主要證據，再查看佐證來源與來源脈絡。
主要證據
1The Wizard of Open Weights: Chris Alexiuk Makes AI Easy With Open Models
Matthew Leib
“Chris Alexiuk has a simple rule about open source AI: If you believe in it, be loud about it. “We should be shouting about this technology from the rooftops,” said Alexiuk, a Toronto-based senior product research engineer in deep learning at NVIDIA who specializes in making open large language models (LLMs) practical for working developers. [...]”
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