Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

Abstract: Can machines truly think, reason and act in domains like humans? This enduring question continues to shape the pursuit of Artificial General Intelligence (AGI). Despite the growing capabilities of models such as GPT-4.5, DeepSeek, Claude 3.5 Sonnet, Phi-4, and Grok 3, which exhibit multimodal fluency and partial reasoning, these systems remain fundamentally limited by their reliance on token-level prediction and lack of grounded agency.

📖 About This Research

This paper offers a cross-disciplinary synthesis of AGI development, spanning artificial intelligence, cognitive neuroscience, psychology, generative models, and agent-based systems. We analyze the architectural and cognitive foundations of general intelligence, highlighting the role of modular reasoning, persistent memory, and multi-agent coordination.

🎯 Key Contributions

Unified Framework: Synthesizes insights from neuroscience, cognition, and AI to identify foundational principles for AGI system design
Critical Analysis: Examines limitations of current token-level models and post hoc alignment strategies
Emergent Methods Survey: Covers modular cognition, world modeling, neuro-symbolic reasoning, and biologically inspired architectures
Multidimensional Roadmap: Presents a comprehensive path for AGI development incorporating logical reasoning, lifelong learning, embodiment, and ethical oversight
Cognitive Function Mapping: Maps core human cognitive functions to computational analogues

🧠 Core Concepts

Why Token-Level Prediction Alone is Insufficient for AGI

Current models like GPT-4, DeepSeek, and Grok capture surface linguistic patterns but fail to support complex mental representations grounded in the physical world. Lacking embodiment, causality, and self-reflection, they struggle with abstraction and goal-directed behavior core requirements for AGI.

Beyond Scaling: The Need for Architectural Innovation

While scaling improves fluency and performance on many tasks, it cannot resolve core limitations of current LLMs. These models still lack:

Grounded understanding
Causal reasoning
Persistent memory
Goal-directed behavior

Video Presentations and Blogs

1 - Video Presentation by Richard Aragson 2 - Medium Blogs

🚀 Research Highlights

🎭 Reasoning Systems

System	Date	Key Innovation	Links	Status
Generative Agents	Apr 2023	Simulate human behavior with AI agents	[Paper] [Demo] [Code]	✅ Available
AutoGPT	Apr 2023	Objective-driven execution with agents	[GitHub] [Try Online]	✅ Available
BabyAGI	Apr 2023	Task expander loop architecture	[GitHub] [Article]	✅ Available
MetaGPT	Aug 2023	Multi-agent framework for software development	[GitHub] [Paper]	✅ Available
ReAct	Oct 2022	Synergizing reasoning and acting	[Paper] [GitHub]	✅ Available
HuggingGPT/JARVIS	Mar 2023	Model calls specialized models for input	[Paper] [GitHub]	✅ Available
Reflexion	Mar 2023	Autonomous agent with dynamic memory	[Paper] [GitHub]	✅ Available

🤖 Foundation Models & LLMs (2025 Latest)

Model	Organization	Capabilities	Links	Status
GPT-4.5	OpenAI	Latest flagship with enhanced reasoning	[API] [Paper]	✅ Available
ChatGPT o3	OpenAI	Advanced reasoning with tool integration	[Platform] [API]	✅ Available
ChatGPT o4-mini	OpenAI	Fast, cost-efficient reasoning model	[Platform] [API]	✅ Available
DeepSeek-R1	DeepSeek	First-generation reasoning model	[GitHub] [Model]	✅ Available
DeepSeek-R1-0528	DeepSeek	Upgraded R1 with 87.5% AIME accuracy	[Model] [Paper]	✅ Available
Claude 4 (3.7 Sonnet)	Anthropic	Advanced coding and reasoning	[API] [Model]	✅ Available
Gemini 2.5 Pro	Google	Advanced multimodal with 2M context	[API] [Docs]	✅ Available
Grok 3	xAI	Real-time information processing	[Platform] [Paper]	✅ Available
Qwen 3	Alibaba	Latest generation with MoE variants	[GitHub] [Model]	✅ Available
LLaMA 4	Meta	Newest iteration (details limited)	[Model] [Paper]	✅ Available
Phi-4	Microsoft	14B parameter reasoning model	[Model] [Paper]	✅ Available

🧠 Large Reasoning Models (LRMs)

Model	Organization	Key Innovation	Links	Status
OpenAI o3	OpenAI	Extended inference-time computation	[API] [System Card]	✅ Available
OpenAI o3-pro	OpenAI	Highest performance o-series model	[Platform] [API]	✅ Available
OpenAI o4-mini	OpenAI	99.5% AIME 2025 with tools	[Platform] [GitHub Copilot]	✅ Available
DeepSeek-R1-Zero	DeepSeek	Pure RL without SFT training	[GitHub] [Model]	✅ Available
DeepSeek-R1-0528	DeepSeek	685B params, 87.5% AIME accuracy	[Model] [Distilled]	✅ Available
Qwen3 Reasoning Models	Alibaba	Hybrid thinking with /think tokens	[GitHub] [Blog]	✅ Available
Gemini 2.5 Pro	Google	Deep Think reasoning capabilities	[API] [Docs]	✅ Available

🔀 Mixture of Experts (MoE) Models

Model	Organization	Architecture	Links	Status
Qwen3-235B-A22B	Alibaba	235B total, 22B active params	[Model] [Ollama]	✅ Available
Qwen3-30B-A3B	Alibaba	30B total, 3B active params	[Model] [LM Studio]	✅ Available
DeepSeek-V3	DeepSeek	671B total, 37B active params	[Model] [GitHub]	✅ Available
Mixtral 8x22B	Mistral AI	176B total, 44B active params	[Model] [GitHub]	✅ Available
Gemini 2.0 Flash	Google	Fast inference MoE architecture	[API] [Docs]	✅ Available

📏 Small & Efficient Models

Model	Organization	Size	Links	Status
Qwen3-4B	Alibaba	4B params, rivals Qwen2.5-72B	[Model] [Ollama]	✅ Available
Qwen3-1.7B	Alibaba	1.7B params, iPhone-compatible	[Model] [GGUF]	✅ Available
Qwen3-0.6B	Alibaba	0.6B params, ultra-lightweight	[Model] [Mobile]	✅ Available
Phi-4	Microsoft	14B params, state-of-the-art reasoning	[Model] [GitHub]	✅ Available
Gemma 3	Google	Lightweight 4B model family	[Model] [GitHub]	✅ Available
SmolLM2	Hugging Face	135M, 360M, 1.7B variants	[Model] [GitHub]	✅ Available

🖼️ Vision-Language Models (VLMs)

Model	Organization	Key Features	Links	Status
GPT-4V	OpenAI	Vision-language understanding	[API] [Docs]	✅ Available
Gemini 2.5 Pro	Google	Advanced multimodal reasoning	[API] [Docs]	✅ Available
LLaVA	Various	Open-source vision-language model	[GitHub] [Model]	✅ Available
Qwen2.5-VL	Alibaba	Multilingual vision-language model	[Model] [GitHub]	✅ Available
InternVL	OpenGVLab	Versatile vision-language model	[GitHub] [Model]	✅ Available
CLIP	OpenAI	Contrastive language-image pre-training	[GitHub] [Model]	✅ Available
Flamingo	DeepMind	Few-shot learning for vision-language	[Paper] [Unofficial Code]	📄 Paper Only

🧪 Research Frameworks & Platforms

Framework	Type	Description	Links	Status
AutoGPT	Agent Framework	Autonomous task execution	[GitHub] [Try Online]	✅ Available
MetaGPT	Multi-Agent	Software development agents	[GitHub] [Demo]	✅ Available
SuperAGI	Agent Platform	Build and run autonomous agents	[GitHub] [Docs]	✅ Available
AgentGPT	Web Platform	Browser-based autonomous agents	[GitHub] [Try Online]	✅ Available
LangChain	Framework	Building LLM applications	[GitHub] [Docs]	✅ Available
OpenAGI	Framework	Domain expert integration	[GitHub] [Paper]	✅ Available

🤖 Autonomous AI Agents

Agent	Organization	Specialization	Links	Status
Voyager	NVIDIA/Caltech	Minecraft exploration	[GitHub] [Paper]	✅ Available
GPT-Engineer	AntonOsika	Full-stack development	[GitHub] [Docs]	✅ Available
GPT-Researcher	AssafElovic	Comprehensive research	[GitHub] [Demo]	✅ Available
AutoGen	Microsoft	Multi-agent conversations	[GitHub] [Docs]	✅ Available
CrewAI	CrewAI	Role-playing multi-agent teams	[GitHub] [Docs]	✅ Available
AI Town	a16z	AI agent simulation environment	[GitHub] [Demo]	✅ Available

🧬 Brain-Inspired Architectures

Architecture	Type	Key Innovation	Links	Status
Spiking Neural Networks	Neuromorphic	Emulate neural spike dynamics	[BindsNET] [NEST] [Brian2]	✅ Available
Physics-Informed Neural Networks	Hybrid	Incorporate physical laws into NNs	[DeepXDE] [PINN Papers]	✅ Available
Kolmogorov-Arnold Networks	Novel Architecture	Learnable spline-based activations	[PyKAN] [Paper]	✅ Available
Neural ODEs	Continuous	Continuous-time neural networks	[torchdiffeq] [Paper]	✅ Available
Liquid Neural Networks	Adaptive	Dynamic, adaptable neural circuits	[ncps] [Paper]	✅ Available
Neural Turing Machines	Memory-Augmented	External memory mechanisms	[PyTorch NTM] [Paper]	✅ Available

🎯 Specialized AI Models

Model Type	Examples	Purpose	Links	Status
Large Concept Models	SONAR, Qwen3 Concept-level	Concept-level reasoning beyond tokens	[SONAR] [Paper]	✅ Available
Large Reasoning Models	OpenAI o3, DeepSeek-R1, Qwen3	Extended inference-time reasoning	[OpenAI o3] [DeepSeek-R1]	✅ Available
Mixture of Experts	Qwen3-235B-A22B, DeepSeek-V3	Sparse expert routing for efficiency	[Qwen3 MoE] [DeepSeek-V3]	✅ Available
Retrieval-Augmented	RAG, RETRO, Atlas	External knowledge integration	[LangChain RAG] [RETRO]	✅ Available
World Models	DreamerV3, MuZero	Environment modeling and prediction	[DreamerV3] [MuZero]	✅ Available
Distilled Models	DeepSeek-R1-Qwen3-8B, Phi-4	Smaller models with reasoning capabilities	[Distilled R1] [Phi-4]	✅ Available

🔬 Benchmark Datasets & Evaluation

Benchmark	Focus	Description	Links	Status
BIG-Bench	Language Reasoning	200+ diverse language tasks	[GitHub] [Paper]	✅ Available
ARC	Abstract Reasoning	Visual pattern recognition	[GitHub] [Dataset]	✅ Available
AIME 2025	Mathematics	High school mathematics competition	[Problems] [Leaderboard]	✅ Available
MineDojo	Embodied AI	Minecraft-based embodied learning	[GitHub] [Website]	✅ Available
AgentBench	LLM Agents	Multi-domain agent evaluation	[GitHub] [Paper]	✅ Available
AGI-Bench	General Intelligence	Multimodal AGI evaluation	[GitHub] [Paper]	✅ Available
HELM	Language Models	Holistic evaluation framework	[GitHub] [Website]	✅ Available
MMMU	Multimodal Understanding	College-level multimodal tasks	[GitHub] [Website]	✅ Available
SWE-Bench	Software Engineering	Real-world coding tasks	[GitHub] [Leaderboard]	✅ Available
LiveCodeBench	Live Coding	Real-time coding evaluation	[GitHub] [Website]	✅ Available

🛠️ Development Tools & Libraries

Tool	Category	Purpose	Links	Status
Transformers	Model Library	Hugging Face model hub	[GitHub] [Docs]	✅ Available
LangChain	Framework	LLM application development	[GitHub] [Docs]	✅ Available
LlamaIndex	RAG Framework	Data framework for LLMs	[GitHub] [Docs]	✅ Available
Ollama	Local Inference	Run models locally	[GitHub] [Website]	✅ Available
vLLM	Inference Engine	High-throughput LLM serving	[GitHub] [Docs]	✅ Available
llama.cpp	Inference Engine	Efficient CPU inference	[GitHub] [Docs]	✅ Available
LM Studio	GUI Tool	Local model interface	[Website] [Downloads]	✅ Available
OpenAI Gym	RL Environment	Reinforcement learning toolkit	[GitHub] [Website]	✅ Available
PettingZoo	Multi-Agent RL	Multi-agent RL environments	[GitHub] [Docs]	✅ Available
Ray	Distributed Computing	Scalable ML and AI workloads	[GitHub] [Docs]	✅ Available
Weights & Biases	MLOps	Experiment tracking and MLOps	[GitHub] [Platform]	✅ Available

🌐 Online Demos & Platforms

Platform	Type	Description	Links	Access
ChatGPT	Conversational AI	OpenAI's flagship chatbot	[Platform]	🔓 Free/Paid
Claude	Conversational AI	Anthropic's AI assistant	[Platform]	🔓 Free/Paid
Gemini	Conversational AI	Google's AI assistant	[Platform]	🔓 Free
DeepSeek Chat	Conversational AI	DeepSeek's reasoning chatbot	[Platform]	🔓 Free
Qwen Chat	Conversational AI	Alibaba's Qwen interface	[Platform] [Demo]	🔓 Free
AgentGPT	Autonomous Agents	Browser-based agent creation	[Platform]	🔓 Free
Godmode	AutoGPT Interface	User-friendly AutoGPT interface	[Platform]	🔓 Free
Cognosys	AI Agents	AI agent automation platform	[Platform]	🔓 Free/Paid
AI Town Demo	Agent Simulation	Generative agents in virtual town	[Demo]	🔓 Free
Fello AI	Multi-Model	Access all major models in one app	[Platform]	💰 Paid

📚 Educational Resources & Courses

Resource	Type	Focus	Links	Access
CS231n	Course	Convolutional Neural Networks	[Stanford] [YouTube]	🔓 Free
CS224n	Course	Natural Language Processing	[Stanford] [YouTube]	🔓 Free
Deep Learning Book	Textbook	Comprehensive deep learning	[Online] [PDF]	🔓 Free
AGI Safety Fundamentals	Course	AI safety and alignment	[Curriculum] [Materials]	🔓 Free
Neurosymbolic AI	Course	Hybrid AI approaches	[MIT] [Materials]	🔓 Free
Qwen Documentation	Docs	Complete Qwen usage guide	[Docs] [GitHub]	🔓 Free

💻 Code & Development Platforms

Platform	Type	Description	Links	Access
GitHub Copilot	Code Assistant	AI-powered coding with o3/o4-mini	[GitHub] [Models]	💰 Paid
Cursor	IDE	AI-first code editor	[Website] [Downloads]	🔓 Free/Paid
Replit	Cloud IDE	Online development with AI	[Platform] [AI Features]	🔓 Free/Paid
Claude Code	Coding Agent	Terminal-based coding assistant	[Announcement] [GitHub]	✅ Available
Codex CLI	Coding Agent	OpenAI's local coding agent	[OpenAI]	✅ Available

🔄 Generalization Frameworks & Theory

Framework	Type	Key Insight	Links	Status
Information Bottleneck	Theory	Compression enables generalization	[Paper] [Implementation]	✅ Available
Neural Tangent Kernel	Theory	Infinite-width network behavior	[Paper] [JAX Implementation]	✅ Available
PAC-Bayes	Theory	Generalization bounds	[Tutorial] [PyTorch]	✅ Available
Causal Representation	Framework	Causal structure learning	[CausalML] [DoWhy]	✅ Available
Meta-Learning	Framework	Learning to learn	[MAML] [learn2learn]	✅ Available
Test-Time Adaptation	Framework	Real-time model adaptation	[TTT] [TDA]	✅ Available

📊 Model Performance Comparison

🎯 Reasoning Benchmark Results (2025)

Model	AIME 2025	SWE-Bench	MMLU	LiveCodeBench	Context Window
OpenAI o3	88.9%	69.1%	92.0%	85.2%	200K
OpenAI o4-mini	92.7%	68.1%	89.5%	82.1%	200K
DeepSeek-R1-0528	87.5%	72.5%	88.2%	79.3%	64K
Claude 4 Sonnet	76.5%	72.7%	90.1%	84.6%	64K
Qwen3-235B-A22B	85.4%	71.2%	89.8%	81.7%	131K
Gemini 2.5 Pro	86.7%	65.8%	91.3%	78.9%	2M
Grok 3	82.1%	67.4%	87.6%	76.5%	128K

💰 Cost-Performance Analysis

Model	Input Cost ($/1M tokens)	Output Cost ($/1M tokens)	Speed (tokens/s)	Best Use Case
OpenAI o4-mini	$2.00	$8.00	131	High-volume reasoning
Qwen3-30B-A3B	Free*	Free*	170+	Open-source deployment
DeepSeek-R1	$0.50	$2.00	150+	Cost-effective reasoning
Gemini 2.5 Flash	$0.30	$1.20	250+	Real-time applications
Claude 4 Sonnet	$15.00	$75.00	170	Premium coding tasks
OpenAI o3	$10.00	$40.00	95	Complex problem solving

*Free for self-hosting; API costs may vary

🚀 Quick Start Guide

🌐 Try Models Online (No Setup Required)

# Try DeepSeek R1 for free
curl -X POST "https://api.deepseek.com/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-reasoner",
    "messages": [{"role": "user", "content": "Solve: What is 2^10 * 3^5?"}]
  }'

# Access Qwen3 via Hugging Face
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-14B")

🖥️ Local Installation

# Install Ollama for local models
curl -fsSL https://ollama.ai/install.sh | sh

# Run Qwen3 locally
ollama run qwen3:32b

# Run DeepSeek R1 distilled model
ollama run deepseek-r1:8b

# Install LM Studio (GUI interface)
# Download from: https://lmstudio.ai/

🐍 Python Integration

# Using OpenAI-compatible API
import openai

# Configure for different providers
clients = {
    "openai": openai.OpenAI(api_key="your-openai-key"),
    "deepseek": openai.OpenAI(
        api_key="your-deepseek-key",
        base_url="https://api.deepseek.com"
    ),
    "qwen": openai.OpenAI(
        api_key="your-dashscope-key", 
        base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"
    )
}

# Test reasoning capabilities
response = clients["deepseek"].chat.completions.create(
    model="deepseek-reasoner",
    messages=[{
        "role": "user", 
        "content": "Think step by step: How would you design an AGI system?"
    }],
    temperature=0.6
)

🛠️ Repository Structure

agi-cognitive-foundations/
├── README.md                    # This comprehensive guide
├── paper/
│   ├── main.pdf                # Main paper PDF
│   ├── supplementary/          # Supplementary materials
│   ├── figures/                # High-resolution figures
│   └── citations.bib           # Bibliography file
├── code/
│   ├── experiments/            # Experimental implementations
│   │   ├── reasoning_models/   # LRM implementations
│   │   ├── memory_systems/     # Persistent memory architectures
│   │   └── multi_agent/        # Agent coordination systems
│   ├── models/                 # Model architectures
│   │   ├── brain_inspired/     # SNNs, PINNs, KANs
│   │   ├── neuro_symbolic/     # Hybrid reasoning systems
│   │   └── world_models/       # Environment modeling
│   ├── benchmarks/             # Evaluation frameworks
│   │   ├── agi_eval/          # AGI-specific benchmarks
│   │   ├── reasoning_tests/    # Reasoning capability tests
│   │   └── alignment_metrics/  # Safety and alignment measures
│   └── tools/                  # Utility scripts and helpers
├── data/
│   ├── cognitive_mappings/     # Brain-to-AI function mappings
│   ├── benchmark_results/      # Evaluation results
│   ├── synthetic_datasets/     # Generated training data
│   └── case_studies/          # Real-world applications
├── docs/
│   ├── cognitive_architecture.md  # Architecture design principles
│   ├── ethical_guidelines.md      # AI safety and ethics
│   ├── future_directions.md       # Research roadmap
│   ├── model_comparisons.md       # Detailed model analyses
│   └── deployment_guide.md        # Practical implementation
├── notebooks/
│   ├── getting_started.ipynb     # Quick start tutorial
│   ├── model_demonstrations.ipynb # Live model comparisons
│   └── case_study_analysis.ipynb # Applied research examples
└── resources/
    ├── datasets.md               # Curated dataset list
    ├── papers.md                # Related research papers
    └── tools.md                 # Development tools guide

🎯 Key Research Areas

1. Cognitive Architecture Design

Modular reasoning systems
Persistent memory mechanisms
Multi-agent coordination
World model integration

2. Learning Paradigms

Meta-learning and continual learning
Few-shot and zero-shot generalization
Causal representation learning
Uncertainty quantification

3. Alignment and Safety

Human-in-the-loop training
Value learning and preference optimization
Ethical framework integration
Transparency and interpretability

4. Societal Integration

Democratic AI development
Cultural sensitivity and inclusion
Economic impact assessment
Governance framework design

🔬 Experimental Insights

Large Concept Models (LCMs)

Moving beyond token-level processing to concept-level reasoning, operating over explicit semantic representations that are language and modality-agnostic.

Large Reasoning Models (LRMs)

Systems focused on explicit, multi-step cognitive processes rather than single-shot response generation, employing extended inference time computation.

Agentic AI Systems

Autonomous systems with planning, memory, tool-use, and decision-making capabilities that mirror core aspects of human cognition.

🔬 Advanced Research Areas

🧩 Missing Pieces in Current AGI Development

Based on our paper's analysis, several critical gaps remain:

Challenge	Current State	Required Breakthrough	Timeline
Uncertainty Management	Limited handling of epistemic/aleatory uncertainty	Robust uncertainty quantification frameworks	2-3 years
Compression-Based Reasoning	Models memorize rather than truly abstract	Information-theoretic reasoning architectures	3-5 years
Emotional Intelligence	Superficial emotional processing	Deep social and emotional understanding	5-7 years
Ethical Framework Integration	Post-hoc alignment approaches	Built-in moral reasoning from inception	3-5 years
Environmental Sustainability	High computational costs	Energy-efficient neuromorphic architectures	2-4 years
Cognitive Debt Prevention	Over-reliance reducing human cognition	Balanced human-AI collaboration systems	Ongoing

🚀 Emerging Paradigms & Future Directions

1. Neural Society of Agents

# Example: Distributed AGI architecture
class NeuralSociety:
    def __init__(self):
        self.reasoning_agent = DeepSeekR1()
        self.creative_agent = GPT4()
        self.analytical_agent = Claude4()
        self.coordinator = QwenMasterAgent()
    
    def collaborative_solve(self, problem):
        # Agents negotiate and collaborate
        return self.coordinator.orchestrate([
            self.reasoning_agent.analyze(problem),
            self.creative_agent.ideate(problem),
            self.analytical_agent.validate(problem)
        ])

2. Absolute Zero Reasoning (AZR)

Self-evolving agents that generate, solve, and validate their own reasoning problems:

Zero human supervision for reasoning improvement
Code execution verification for reliable learning
Meta-cognitive curriculum design

3. Agentic RAG Frameworks

Combining retrieval, planning, and dynamic tool use:

# Advanced RAG with reasoning
class AgenticRAG:
    def __init__(self):
        self.retriever = VectorDB()
        self.reasoner = DeepSeekR1()
        self.planner = TreeOfThoughts()
        self.executor = ToolExecutor()
    
    def enhanced_query(self, question):
        # Multi-step reasoning with retrieval
        context = self.retriever.semantic_search(question)
        plan = self.planner.decompose_problem(question, context)
        return self.executor.run_plan(plan)

🛡️ Safety & Alignment

🔒 AI Safety Frameworks

Framework	Organization	Focus	Implementation
Constitutional AI	Anthropic	Self-supervised alignment	[Paper] [Code]
RLHF 2.0	OpenAI/DeepMind	Advanced human feedback	[Paper] [Implementation]
AI Safety Gridworlds	DeepMind	Safe exploration environments	[GitHub]
Alignment Research	MIRI/FHI	Theoretical foundations	[Research] [Papers]

🌍 Societal Impact & Integration

📊 Economic Impact Analysis

Sector	Potential Impact	Timeline	Mitigation Strategies
Knowledge Work	60-80% automation potential	2-5 years	Reskilling programs, human-AI collaboration
Creative Industries	Enhanced productivity, new roles	1-3 years	Copyright frameworks, creator compensation
Healthcare	Diagnostic assistance, drug discovery	3-7 years	Regulatory compliance, physician training
Education	Personalized tutoring, curriculum design	2-4 years	Teacher training, digital literacy programs
Scientific Research	Accelerated discovery, hypothesis generation	1-3 years	Research integrity, reproducibility standards

🏛️ Global Governance Initiatives

Policy Frameworks

EU AI Act: Risk-based regulation with compliance requirements
NIST AI RMF: Voluntary guidelines for trustworthy AI
UNESCO AI Ethics: Global ethical standards
OECD AI Principles: International cooperation framework

🤝 Contributing

We welcome contributions from researchers across disciplines! Please see our Contributing Guidelines for details on:

Submitting improvements to cognitive architectures
Adding new benchmark evaluations
Proposing ethical framework enhancements
Sharing experimental results

📚 Citation

If you use this work in your research, please cite:

@article{qureshi2025thinking,
  title={Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact},
  author={Qureshi, Rizwan and Sapkota, Ranjan and Shah, Abbas and Muneer, Amgad and Zafar, Anas and Vayani, Ashmal and others},
  journal={arXiv preprint arXiv:2507.00951},
  year={2025}
}

👥 Complete Author List

Rizwan Qureshi¹* - Center for Research in Computer Vision, University of Central Florida
Ranjan Sapkota²* - Department of Biological and Environmental Engineering, Cornell University
Abbas Shah³* - Department of Electronics Engineering, Mehran University of Engineering & Technology
Amgad Muneer⁴* - Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Anas Zafar⁴ - Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Ashmal Vayani¹ - Center for Research in Computer Vision, University of Central Florida
Maged Shoman⁵ - Intelligent Transportation Systems, University of Tennessee
Abdelrahman B. M. Eldaly⁶ - Department of Electrical Engineering, City University of Hong Kong
Kai Zhang⁴ - Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Ferhat Sadak⁷ - Department of Mechanical Engineering, Bartin University
Shaina Raza⁸† - Vector Institute, Toronto (Corresponding Author)
Xinqi Fan⁹ - Manchester Metropolitan University
Ravid Shwartz-Ziv¹⁰ - Center for Data Science, New York University
Hong Yan⁶ - Department of Electrical Engineering, City University of Hong Kong
Vinjia Jain¹¹ - Meta Research (Work done outside Meta)
Aman Chadha¹² - Amazon Research (Work done outside Amazon)
Manoj Karkee² - Department of Biological and Environmental Engineering, Cornell University
Jia Wu⁴ - Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Philip Torr¹³ - Department of Engineering Science, University of Oxford
Seyedali Mirjalili¹⁴,¹⁵ - Centre for Artificial Intelligence Research and Optimization, Torrens University Australia & University Research and Innovation Center, Obuda University

*Equal Contribution | †Corresponding Author: shaina.raza@torontomu.ca

🏛️ Complete Institutional Affiliations

🇺🇸 United States

¹ University of Central Florida - Center for Research in Computer Vision, Orlando, FL
² Cornell University - Department of Biological and Environmental Engineering, Ithaca, NY
⁴ The University of Texas MD Anderson Cancer Center - Department of Imaging Physics, Houston, TX
⁵ University of Tennessee - Intelligent Transportation Systems, Oak Ridge, TN
¹⁰ New York University - Center for Data Science, New York, NY
¹¹ Meta Research - (Work done outside Meta)
¹² Amazon Research - (Work done outside Amazon)

🇨🇦 Canada

⁸ Vector Institute - Toronto, Canada

🇬🇧 United Kingdom

⁹ Manchester Metropolitan University - Manchester, UK
¹³ University of Oxford - Department of Engineering Science, UK

🇭🇰 Hong Kong (SAR China)

⁶ City University of Hong Kong - Department of Electrical Engineering

🇵🇰 Pakistan

³ Mehran University of Engineering & Technology - Department of Electronics Engineering, Jamshoro, Sindh

🇹🇷 Turkey

⁷ Bartin University - Department of Mechanical Engineering, Bartin

🇦🇺 Australia

¹⁴ Torrens University Australia - Centre for Artificial Intelligence Research and Optimization, Fortitude Valley, Brisbane, QLD

🇭🇺 Hungary

¹⁵ Obuda University - University Research and Innovation Center, Budapest

🌍 Global Collaboration Summary

This research represents a truly international collaboration spanning:

8 Countries: United States, Canada, United Kingdom, Hong Kong, Pakistan, Turkey, Australia, Hungary
15 Institutions: Leading universities and research centers worldwide
20 Authors: Experts from diverse fields including AI, neuroscience, engineering, and cognitive science
Multiple Disciplines: Computer Vision, AI Safety, Neuroscience, Engineering, Physics, and Philosophy

Research Domains Represented

🧠 Cognitive Neuroscience & Psychology
🤖 Artificial Intelligence & Machine Learning
🔬 Computer Vision & Multimodal AI
⚡ Engineering & Optimization
🛡️ AI Safety & Ethics
🏥 Medical Physics & Imaging
🚗 Intelligent Transportation Systems
🔧 Biological & Environmental Engineering

📧 Contact

For questions, collaborations, or discussions:

Corresponding Author: shaina.raza@torontomu.ca
GitHub Issues: For technical questions and bug reports
Discussions: For research discussions and ideas

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

📄 Paper

Title:
Thinking Beyond Tokens: From Brain‑Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

📚 Citation

If you use this work, please cite it as:

@article{qureshi2025thinking,
  title={Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact},
  author={Qureshi, Rizwan and Sapkota, Ranjan and Shah, Abbas and Muneer, Amgad and Zafar, Anas and Vayani, Ashmal and Shoman, Maged and Eldaly, Abdelrahman and Zhang, Kai and Sadak, Ferhat and Raza, Shaina and Fan, Xinqi and Shwartz-Ziv, Ravid and Yan, Hong and Jain, Vinjia and Chadha, Aman and Karkee, Manoj and Wu, Jia and Torr, Philip and Mirjalili, Seyedali},
  journal={arXiv preprint arXiv:2507.00951},
  year={2025}
}

🙏 Acknowledgments

We thank the global AI research community for their foundational contributions to understanding intelligence, consciousness, and the path toward AGI. Special recognition to the institutions and funding bodies that supported this interdisciplinary research effort.

"True intelligence arises not from scale alone but from the integration of memory and reasoning: an orchestration of modular, interactive, and self-improving components where compression enables adaptive behavior."

— From the paper

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Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

📖 About This Research

🎯 Key Contributions

🧠 Core Concepts

Why Token-Level Prediction Alone is Insufficient for AGI

Beyond Scaling: The Need for Architectural Innovation

Video Presentations and Blogs

🚀 Research Highlights

🎭 Reasoning Systems

🤖 Foundation Models & LLMs (2025 Latest)

🧠 Large Reasoning Models (LRMs)

🔀 Mixture of Experts (MoE) Models

📏 Small & Efficient Models

🖼️ Vision-Language Models (VLMs)

🧪 Research Frameworks & Platforms

🤖 Autonomous AI Agents

🧬 Brain-Inspired Architectures

🎯 Specialized AI Models

🔬 Benchmark Datasets & Evaluation

🛠️ Development Tools & Libraries

🌐 Online Demos & Platforms

📚 Educational Resources & Courses

💻 Code & Development Platforms

🔄 Generalization Frameworks & Theory

📊 Model Performance Comparison

🎯 Reasoning Benchmark Results (2025)

💰 Cost-Performance Analysis

🚀 Quick Start Guide

🌐 Try Models Online (No Setup Required)

🖥️ Local Installation

🐍 Python Integration

🛠️ Repository Structure

🎯 Key Research Areas

1. Cognitive Architecture Design

2. Learning Paradigms

3. Alignment and Safety

4. Societal Integration

🔬 Experimental Insights

Large Concept Models (LCMs)

Large Reasoning Models (LRMs)

Agentic AI Systems

🔬 Advanced Research Areas

🧩 Missing Pieces in Current AGI Development

🚀 Emerging Paradigms & Future Directions

1. Neural Society of Agents

2. Absolute Zero Reasoning (AZR)

3. Agentic RAG Frameworks

🛡️ Safety & Alignment

🔒 AI Safety Frameworks

🌍 Societal Impact & Integration

📊 Economic Impact Analysis

🏛️ Global Governance Initiatives

Policy Frameworks

🤝 Contributing

📚 Citation

👥 Complete Author List

🏛️ Complete Institutional Affiliations

🇺🇸 United States

🇨🇦 Canada

🇬🇧 United Kingdom

🇭🇰 Hong Kong (SAR China)

🇵🇰 Pakistan

🇹🇷 Turkey

🇦🇺 Australia

🇭🇺 Hungary

🌍 Global Collaboration Summary

Research Domains Represented

📧 Contact

📄 License

📄 Paper

📚 Citation

🙏 Acknowledgments

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