Key Takeaways: A New Paradigm in AI & Software
This article outlines a shift in the software and AI landscape, moving beyond isolated applications and large language models (LLMs) towards a more interconnected, clever, and personal system. Here’s a breakdown of the key components of this emerging paradigm:
1. The Rise of Ontology:
* What it is: A shared,unified model of real-world objects (customers,assets,events) and their relationships,including security permissions and actions.Think of it as a common understanding of what things are and how they interact.
* why it matters: Currently, enterprises struggle with fragmented data and models across various applications and legacy systems. A unified ontology solves this, enabling AI to reason and act across entire organizations and ecosystems.
* Palantir’s View: Palantir CEO Alex Karp believes value will increasingly concentrate in “chips and ontology.”
* Impact: Essential for the effectiveness of “agentic AI” – AI that can proactively perform tasks and make decisions.
2. World Models & Continuous Learning:
* The Problem: Current AI models, even with large context windows, don’t truly learn in the way humans do. They often require retraining from scratch.
* Solutions being explored:
* Google’s Nested Learning: Aims to create durable memory and continual learning within existing LLM architecture, potentially eliminating the need for constant retraining.
* Meta’s H-JEPA (and V-JEPA/I-JEPA): A hierarchical approach using joint embeddings to build “world models” – representations of the world that allow AI to make predictions and understand context. Meta emphasizes that LLMs are good at language but not thinking.
* Goal: To create AI that accumulates understanding over time, rather than constantly resetting.
3. The Personal Intelition Interface:
* What it is indeed: A shift from treating AI as a tool we access to an always-on, context-aware system that integrates into our lives and work. It’s not just another app, but a primary way we interact with the “federated economy.”
* Key features:
* Always-on & Aware: Understands your context, preferences, and goals.
* Proactive: Capable of acting on your behalf.
* Federated: Operates across a network of interconnected systems.
* Example: Jony Ive’s io (now acquired by OpenAI) signals a move towards dedicated AI devices designed for this type of personal integration.
In essence, the article describes a future where AI isn’t just about processing details, but about understanding the world and acting intelligently within it, all centered around the individual user. This requires a fundamental shift in how we build software and train AI, moving towards unified ontologies, continuous learning, and deeply personal interfaces.
