LLMs are no longer limited to being mere chatbots but are evolving into something much more profound—an essential kernel process of a new Operating System.
Let's take a closer look at the emerging capabilities:
🖥️ Input & Output Across Modalities
LLMs now possess the ability to seamlessly handle various modalities such as text, audio, and vision. They can understand and generate content across these different formats, opening up endless possibilities for communication.
💻 Code Interpreter and Program Execution
LLMs can now write and execute programs, acting as a powerful code interpreter. They offer a dynamic environment for developers and users to explore creative solutions and automate tasks.
🌐 Browser and Internet Access
Imagine having a built-in browser within an LLM-powered system. It allows users to access information from the internet directly through the model itself, making it a versatile tool for research, content curation, and more.
💾 Embeddings Database and Memory Storage
LLMs incorporate an embeddings database that enables efficient storage and retrieval of files and internal memory. This feature enhances their ability to retain context, recall information, and provide personalized responses.
🔒 Computer Security Concepts
Security is a crucial aspect of LLMs too. Just like traditional computer systems, LLMs face challenges related to attacks, defenses, and vulnerabilities. Understanding these concepts helps ensure the robustness and reliability of these powerful language models.
🕹️ Operating System Analogy
Comparing LLMs to an Operating System offers a fascinating perspective. Just as Windows, OS X, and Linux are distinct platforms, we now have GPT, PaLM, Claude, and Llama/Mistral) shaping the landscape. Like an OS, LLMs have default applications and the potential for an app store (OpenAI GPTs), enabling customization and expanding functionality.
⚡ The Early Stage of a Computing Paradigm Shift
It's crucial to recognize that viewing LLMs solely as chatbots is akin to regarding early computers as just calculators. We are witnessing the emergence of a whole new computing paradigm, and it's still in its infancy.
While the full extent and impact of the recent events are still unfolding, reports suggest a disagreement within the company regarding the dangers of AI and the prioritization of fast market entry over proper security measures. This situation presents an opportunity to reevaluate our approach to AI development and focus on building responsible, human-aligned models with security and privacy features at their core. As AI becomes a new platform, distinct from traditional code-based software, it requires new security controls.
Inspired by Andrej Karpathy's analogy.
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