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Achieving General Intelligence (AGI) and Super Intelligence (ASI): Pathways, Uncertainties, and Ethical Concerns

Towards AI

Originally published on Towards AI. Now, lets meet our first knight: Scaled-Up Deep Learning the tech equivalent of supersize me. The scaling hypothesis suggests that by simply increasing three factors model size, dataset size, and computational power you can unlock emergent abilities. Author(s): Mohit Sewak, Ph.D.

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End-User Programmable AI

Hacker News

We call the language Universalis in honor of Gottfried Wilhelm Leibniz, a 17th century German polymath who had an amazing vision long before our time. While this may seem like a whimsical example, it is not intrinsically easier or harder for an AI model compared to solving a real-world problem from a human perspective.

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Ask HN: Who is hiring? (August 2025)

Hacker News

Our stack: React (front-end), Node.js (API backend), Docker & Kubernetes for deployments, AI/LLM APIs. We invest a lot in our team. We spend half a day a week reading documentation and doing nothing else, and another full day coaching the team on cutting edge tech (how to design, build, train, deploy ai models).

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Ask HN: What Are You Working On? (June 2025)

Hacker News

All results are published openly. Do I need to submit my email to see the "openly published results"? Frankly, the biggest obstacle for desktop is not the app itself, but distribution and figuring out a pricing model. reply NotAnOtter 8 hours ago | parent | prev | next [–] What's your long term revenue model?

AI
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Visual Compositionality as a Case Study for Building AI Models to Produce Human Behavior

NYU Center for Data Science

As part of a symbiotic research agenda emblematic of CDS wherein human and machine intelligence is explored in tandem, a recent paper published in Cognition by CDS PhD student Yanli Zhou investigates how both humans and AI models achieve visual compositionality.

AI
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A new, better way to build Neural Networks for Machine Learning

Mlearning.ai

How taking inspiration from the design of our brains can lead to AI with better performance, for cheaper. Sure, it might work for biological systems, but what do we hope to attain by implementing a similar idea for our ANNs? Put plainly, every model/architecture decision imposes a certain inductive bias onto our system.

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#61: Are LLMs Entering the Age of Agents?

Towards AI

Author(s): Towards AI Editorial Team Originally published on Towards AI. to Artificial Super Intelligence and black box deep learning models. Whats AI Weekly The vast majority of what we call Agents are simply an API call to a language model. Our must-read articles 1. Good morning, AI enthusiasts! Enjoy the read!