In this podcast, the hosts discuss the role of AI in cybersecurity. They cover topics such as learning about AI and its acronyms, artificial general intelligence, AI/ML in security products, different kinds of learning, and what's hot in the AI section. They also highlight the need to understand the principles and risks of AI, establish policies and procedures, and explore advancements in AI such as voice and image recognition.
Understanding the different types of AI, including ANI, AGI, and ASI, is crucial for grasping its potential and risks in cybersecurity.
Machine learning techniques, such as supervised learning and deep learning, are essential tools for achieving AI and developing advanced models in cybersecurity.
Deep dives
Approaching Learning AI
The speaker shares his experience of learning AI and suggests a strategy to approach learning. He started his journey by setting a goal to learn AI within a month and shared his progress on LinkedIn. He emphasizes the importance of understanding the principles of AI and the associated risks to effectively use it. He suggests building a knowledge foundation by understanding how the AI engine works and then moving on to understanding the controls and responsibilities associated with AI. Finally, he highlights the significance of developing policies and processes to effectively govern AI.
Different Types of AI
The speaker discusses the different types of AI, including artificial narrow intelligence (ANI), artificial general intelligence (AGI), and artificial super intelligence (ASI). He explains that ANI is the current state of AI, consisting of narrow specific tasks, while AGI is the desired goal of achieving human-like intelligence. He also mentions ASI, which signifies an intelligence surpassing human capabilities. The speaker compares the progress in AI development to the stages of human growth, with ANI being the early stage of AGI and AGI representing a mature adult. He also highlights the importance of language in AI development, as it enables AGI to perform various tasks.
Machine Learning Techniques
The speaker provides an overview of machine learning techniques and their role in achieving AI. He explains that machine learning encompasses various approaches and methods, such as supervised learning, unsupervised learning, and deep learning. These techniques use different models to solve specific problems, including spam detection, credit score assessments, and social analysis. He emphasizes that machine learning is the means to achieve AI, and the combination of different techniques can be used to create more advanced AI models.
Future of AI and LLMs
The speaker shares his insights on the future of AI, particularly in terms of large language models (LLMs). He discusses the evolving capabilities of LLMs, which currently rely on public data but are expected to utilize enterprise and personal data in the future. He also explores the expanding modes of interaction with LLMs, including text, images, video, and audio. The speaker predicts that LLMs will transition from creating and informing to acting and deciding, enabling them to manage and operate systems at scale. He envisions real-time data and physical interaction as the next frontiers for LLMs. He concludes by highlighting the rapid progress in LLM technology and the implications for AI security.
To understand what role AI will play in the world of cybersecurity, it important to understand the technology behind it. Caleb and Ashish are levelling up the playing field and laying the foundations with AI primers for cybersecurity in the season 1 of AI CyberSecurity Podcast.
What was discussed:
(00:00) Introduction
(02:36) Learning about AI/ML
(08:00) Acronyms of AI
(10:49) AGI - Artificial General Intelligence
(11:29) Three states of AGI
(13:48) AI/ML in Security Products
(17:03) Different kinds of learning
(21:51) Whats hot in the AI Section!!
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