@BioAI_Neuro
@BioAI_NeuralNet

@MIT trained Neuroscientist interested #Neural_Nets, #BioAI, #NeuroAI 🧠⚡🤖 substack.com/@bioai2neuro 🎯 aibio28ai@gmail.com

 Texas, United States
Joined April 2023
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Synthetic Data for BioAI and NeuroAI: From Mechanistic Simulators to Foundation Models

Abstract Synthetic data is only as good as the model that generates it, and in biology the best generators are mechanistic simulators whose parameters mean something. Foundation models for neural

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How Neuroscience Gave Birth to Artificial Neural Networks and AI ?

Abstract Artificial intelligence is often narrated as a story of computation of transistors, algorithms, and ever-larger matrices of numbers. But its origin are from neuroscientific principles. The

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Beyond the Connectome: Toward a Multidimensional NeuroAI

Abstract Connectomics has produced wiring diagrams of increasing scale and resolution, from the 302-neuron nervous system of Caenorhabditis elegans to dense reconstructions of the adult Drosophila

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World Models: A brief Review

1. Introduction In March 2018, David Ha and Jürgen Schmidhuber published a paper titled World Models (Ha & Schmidhuber, 2018), later published at NeurIPS under the more descriptive title "Recurrent
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The Transformer architecture and LLMs have transformed AI, but they may be only the beginning. What next? In this review, I explore emerging models, algorithms, and architectures that could define the post-Transformer era and shape the next gen of AI.
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From LLMs to World Models: The Future of Artificial Intelligence

Abstract The past decade of AI has been defined by the Transformer and its most visible product, the Large Language Model. Transformers made unprecedented scaling possible and now power reasoning,

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World Models in Biology: From Sequences to Simulated Cells

Over the past two years a specific architectural idea from reinforcement learning and robotics the “world model,” a learned system that predicts how an environment's state changes in response to an

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From Molecules to Platforms: The Evolution of AI Pharma Deals

1. Introduction For much of the past decade, the promise of AI-driven drug discovery revolved around a simple narrative: artificial intelligence would identify novel molecules faster and more

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Data Diversity Bottlenecks in BioAI: Stylistic and Semantic Constraints

Abstract The remarkable success of foundation models in language, vision, and structural biology has renewed interest in the role of data diversity as a determinant of model performance. While

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AI Can Accelerate Intelligence But Understanding Remains Human

Abstract Generative artificial intelligence (AI) systems built on large language models (LLMs) now perform many cognitive operations once considered hallmarks of human intellectual work: drafting

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Global Workspace Theory as a Blueprint for Biological and Artificial Intelligence

Abstract The emergence of large language models and multimodal foundation models has transformed artificial intelligence from a collection of narrow computational tools into increasingly
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The BioAI Data Economy

Abstract The rapid emergence of biological foundation models has transformed the landscape of artificial intelligence in the life sciences. Models trained on genomic sequences, protein structures,
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From Neurons to Neural Networks: What Biology Can Teach Artificial Intelligence

The 20-Watt Super Power in The Universe: Why the Brain Remains the Ultimate Computer The human brain is arguably the most sophisticated information-processing system known. Despite containing

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