Generative AI: A Game-Changer in the Security Industry
生成AI:安全行業(yè)的游戲改變者
Founders of prominent security startups have recently shed light on the potential impact of generative AI in the tech industry. The discussion took place on the AI + a16z podcast, featuring insights from Dean De Beer of Command Zero, Kevin Tian from Doppel, and Travis McPeak of Resourcely.
著名安全初創(chuàng)公司的創(chuàng)始人最近闡明了生成AI對科技行業(yè)的潛在影響。討論是在AI + A16Z播客上進行的,該播客的見解是Zero的Dean De Beer,Doppel的Kevin Tian和Resourcelly的Travis McPeak。
Building with Large Language Models (LLMs)
使用大型語言模型(LLM)建造
The founders discussed their experiences in dealing with LLM-based threats and building with LLMs. They emphasized the complexity of the process and the multitude of considerations that come into play when choosing and operating a large language model.
創(chuàng)始人討論了他們在處理基于LLM的威脅和與LLMS建設(shè)方面的經(jīng)驗。他們強調(diào)了過程的復(fù)雜性以及選擇和操作大型語言模型時會發(fā)揮作用的眾多考慮。
LLM Operation: An Intricate Process
LLM操作:一個復(fù)雜的過程
De Beer compared the operation of a large language model to perceived waiting time for an elevator. He explained that as the use case becomes more advanced and more data is attached, the inference time changes. Despite the fact that generating an outcome might take longer than the user would prefer, the overall process is still significantly faster than undertaking the task manually.
De Beer將大型語言模型的操作與電梯的等待時間進行了比較。他解釋說,隨著用例變得更加先進并附加了更多數(shù)據(jù),推理時間會改變。盡管產(chǎn)生結(jié)果可能要比用戶想要的時間更長,但總體過程仍然比手動執(zhí)行任務(wù)要快得多。
Generative AI: A Double-Edged Sword
生成AI:雙刃劍
While generative AI offers numerous benefits, it also presents a new set of challenges. These include dealing with threats based on LLMs. However, the founders emphasized that understanding these threats and learning how to manage them is key to leveraging the full potential of generative AI in the security industry.
盡管生成AI提供了許多好處,但它也帶來了一系列新的挑戰(zhàn)。其中包括處理基于LLM的威脅。但是,創(chuàng)始人強調(diào),了解這些威脅并學(xué)習(xí)如何管理它們是利用生成AI在安全行業(yè)中的全部潛力的關(guān)鍵。
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