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General culture in computer science & AI

For structured references see:

Computability

Computer Science

Machine Learning and Artificial Neural Networks 

Future Studies

Student project on Stat Mech applied to SLT and BL

A. Computer science 

Overview

I. Basic notions on computer architecture and function

1. Computer architecture

a.  Instruction set architecture

-Overview

-CISCRISC, VLIWEPIC

-x86 and ARM

b. Microarchitecture

The von Neumann and Harvard models

2. Programming language

a. Low level programming language

-Machine code

-Assembly languageassembler; disassembler

b. High level programming language

-Interpreter 

-Compiler

II. Networking

TCP/IP and the OSI model

WANISPs | FTTx5G

LAN: Ethernet (over fiber or twisted pair) | WIFI 

PANBluetooth

IoT: Thread and Zigbee protocols | The Matter standard (wiki) from CSA (wiki)

III. Free and Open Source Software

FOSS

Free: FSF; FSFe; GNU

Open Source: OSI; OFE

Unix and Linux

GitHub

People and movement

Stallman; RaymondTorvalds

The GNU Manifesto | The Cathedral and the Bazaar

IoT

Air Gradient | Home Assistant (wiki) and Nabu Casa

IV. Programming

1. The Church-Turing thesis

2. Classical models of deterministic computation

a. Turing machine

b. Lambda calculus

c. General recursive functions

3. The Curry-Howard correspondence

4. Formal grammar

5. Context-free grammars 

a. Backus-Naur form

b. Syntax diagram

5. Programming paradigms:

a. Declarative: logicalfunctional, AML, Query, Regexp

b. Imperativeprocedural, object-oriented

6. System programming; system programming language

7. General purpose language

8. Domain-specific language

9. API

10. Automatic programming

11. Evolutionary algorithms

a. Evolutionary programming

b. Genetic programming

12. History

V. Concurrent and distributed computing

1. Concurrency

a. Concurrent computing

b. Process

c. Thread

d. Parallel computing

e. Process calculus

f. The actor model

2. Real time operating systems (RTOS)

3. Distributed computing

a. Grid computing

b. Cloud computing

c. Edge computing 

-HBM

-NPU

-AI PC

d. IoT

e. Fog computing

f. Ubiquitous computing

g. Distributed algorithms

4. High performance computing (supercomputers & clusters)

a. History | FLOPS | Orders | CSNET | NSFNET

b. Exascale (DOEECP

-Europe (Euro HPC | PRACE) | Japan | China

- Frontier | Aurora | El Capitan | Jupiter (wikiJS @FZJ) | Fugaku

c. Resources: NESRC | ACM's SIGHPC | HPCwire | InsideHPCTop500

d. Companies: HPE | IBM | NVIDIA | Intel | AMD  | Dell | Atos (Eviden) | Fujitsu

e. Frontier: Zettascale | Neuromorphic | Superconducting | Beyond CMOS | Unconventional | Hypercomputation

VI. Influential people

1. Alan Turing

2. Alonzo Church

3. John von Neumann

4. Norbert Wiener

5. Claude Shannon

6. Richard Stallman

7. Bill Joy

VII. Resources

IEEE Computer Soc. ACM 

Berkeley | MIT | Carnegie Mellon | Stanford | Cambridge | Oxford | Melbourne

B. Artificial intelligence

Outline 

For structured introductions to AI see:

Russell & Norvig: Artificial intelligence: a modern approach

MIT courseware

I. Basic notions and techniques

1. The Dartmouth workshop of 1956

2. The cognitive revolution

3. Expert systems

4. Automated theorem proving

5. Natural language processing

6. Computer vision

7. Speech recognition

8. The common sense knowledge problem

9. AI winter

10. Distributed AI

a. Software agents

b. Multi-agent systems

c. Swarms

d. Artificial life

e. Artificial society | Social simulation | Computational sociology

f. Intelligent agents and agentic AI 

-Communicationorchestration & protocols

g. Agentic Web (a review)

-ProtocolsMCP | A2A | ACP  (IBM think) | ANP | Agora

-Agentic browsersOpen AI Operator (wiki) | Fellou |  Perplexity Comet | Opera Neon | Chrome add-on 

h. Agentic programming

11.  Neural networks

History

a. Neuronal models & computational neuroscience:

-Connectionism | Blue Brain (wiki) | Brain/MINDS (wiki) | MICrONS (wiki) | China Brain Project 

-Biological neuron models | Neural backpropagation

-Neural learning & computationHebbian | BCMGeneralized Hebbian (Oja's rule) | Synaptic plasticity (STDP, SNNs)

b. Artificial neurons | perceptrons 

c. Artificial neural networks

-Feedforward (MLP/FCN | Autoencoders | TDNN  | CNN & CapsNetPNNRBFN | ITNN)

-Recurrent (LSTM | BRNN)

-SVM

-GMDH-based (MNN, Polynomial, Abductive)

-Transformers | Attention is all you need (paper)

12. Machine learning

a. Paradigms (supervised | unsupervised | reinforcement | self-supervised)

b. Techniques: transfer | feature (geometric) | hyperparameter optimization | MTL | ZSL | OSLEBLauto | meta | NAS | neuroevolution

c. Backpropagation | Attention

d. Bayesian learning

e. History | Timeline

13. Deep Learning

-Deep neural networks

-Foundation models | Stanford CRFM

-Multimodal DL

-Feedback NNs

-Neural scaling laws

-Test time computationintro for RLMs

14. Generative AI

-SLMs

-LLMs

-RLMs

-DMs (LVM | HMM)

-GANs

15. Affective computing

16. Hybrid AI (wiki)

16. Narrow AI

17. The AI boom

A list of LLMs

-ML companies: DeepMind (Gemini) | Open AI (ChatGPT) | Anthropic (Claude) | MetaAI (Llama) |  IBM (WatsonX, Granite) | HuggingFaceMistralDeepSeek (homepage) | Alibaba Cloud (Qwen)

-Hyperscale computing | Hyperscalers

-Wafer-scale integration | Cerebras (wiki)

18. History 

-Timeline 

-Online briefs: GfG | SCI AI100 | IBM

-Nilsson, The quest for artificial intelligence

-Mitchell, Artificial intelligence: a guide for thinking humans

-Fradkov, Early history of machine learning

II. Ethics and safety 

Ethics of AI 

1. Explainabiliy

2. Mechanistic interpretability

3. Alignment

-General:

What is AI alignment ? 

Christian, The alignment problem: machine learning and human values

-Groups:

ARC (Berkeley) | Ada Lovelace Institute (UK) | The Future Society (US & EU)

4. Hallucinations

5. Deception

-Deceptive machines 

-AI deception: a survey

6. Machine ethics and friendly AI

7. Safety

The UK AI safety summit (UK, 2023)| The Bletchley Declaration

The AI Seoul Summit (South Korea, 2024) | The Seoul Declaration

The AI Action Summit (France, 2025) | The Paris Statement

The First International AI Safety Report

The AI Impact Summit (India, 2026)

AISI centers

US:  CAISI and AISIC (National, @NIST) | CHAN (UC Berkeley)| CAIS (San Francisco) | CAISER (Oak Ridge) | AI Action Plan

EU: European AI Office| AI Board

Some national AISIs: UK | Japan | South Korea | Singapore

China: CNAISDAAIDSN

Australia

Other:

US: IAPS | CSET | CHAI | RedwoodPalisade | FMF | Epoch | ARC & METR | ARI | CivAI | FAR | Apart | LawAI | AIFutures

UK: CLTR  | GovAI | ApolloCLTR | ForethoughtMATS | ARENA

EU: CFG  | Talos | CSH

Global: TFS | SAIF | Constellation | 80000hours

Some papers:

TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (2023)

Two Types of AI Existential Risk: Decisive and Accumulative (2024)

Mechanistic Interpretability for AI Safety -- A Review (2024)

Safety Cases: How to Justify the Safety of Advanced AI Systems (2024)

Gradual disempowerment: Systemic Existential Risks from Incremental AI Development (2025)

AI-Enabled Coups: How a Small Group Could Use AI to Seize Power (2025)

III. Governance and policy

Regulation of AI | Global governance [GAIGO]

EU: The EU AI Act (lawwiki) ] | AI Innovation Package [AI Factories, AI Gigafactories , Gen4AIEU, NoE]| The Continent Action Plan | European approach to AI | European AI Alliance | AI Forum

US: America's AI Action Plan | The Stargate project (wiki)

China: Global AI Governance Initiative | Global AI Governance Action Plan

UN: Independent international scientific panel on AI

IV. Frontier, speculative and philosophical

General interest books: 

Kissinger, Schmidt & Huttenlocher, The age of AI and our human future

Suleyman & Bhaksar, The coming wave

Russell, Human compatible

Ord: The precipice | revisted

Togelius, Artificial general intelligence

Bennett, A brief history of intelligence

Kurzweil, The singularity is nearer

1. Artificial General Intelligence (AGI)

a. The Turing test

b. Artificial consciousness

c. Computational neuroscience

d. Philosophy of AI and Philosophy of mind 

-The Chinese room argument and hard problem of consciousness

-Unified Theories of Cognition and The Conscious Mind

-The binding problem

-Situated cognition

-Self-awareness and NCC

2. Computational cognition

-The CRUM hypothesis

-Statistical learning and SLA

3. Cognitive models and architectures

- SoM, MDM, GWT, MPF and DCM, DC

-Conceptual spacescognitive maps, image schemas

-ACT-R, Soar, 4CAPS, DUAL, CLARION, LIDASDM

-MindModeling@home

4. Machine theory of mind

-A review

-ToM in cognitive science 

-Computational ToM (also here)

5. Superintelligence

6. Recursive self-improvement and Technological singularity

Some essays:

Situational Awareness | AI Futures

V. Socio-political

1. AI and elections

2. National Security

-The AI arms race  

-Hendricks, Schmidt & Wang's Superintelligence Strategy (expert version)

3.  Military applications

-JADC2

-CDAO (wiki)

-Project Maven

-5GW

4. Social

-Predictive analytics and policing

-Lawbots, computational law and legal informatics

-Automated journalism | Virtual assistants | Machine translation | AVs

-AI art: visual | music | film | architecture | games

-Digital twins  | digital cloning | deepfakes | companions

-UBI

5. Ontological security

-Overview

-Ontological security theory in International relations

6. Existential risk

-CSER

-FLI

-MIRI/Less Wrong

7. Ideologies and movements

a. Effective altruism (EA)

CEA | EV | Open Philantropy

b. Transhumanism

c. TESCREAL 

d. Luddism and neo-Luddism

-The precautionary principle and progress

-Movements: Post-development | Anarcho-primitivism | Degrowth | Collapsology | Survivalism

-Essays: Industrial Society and Its FutureWhy the Future Doesn't Need Us

VI. Influential people

1. Alan Turing

2. John McCarthy

3. Marvin Minsky

4. Geoffrey Hinton

5. Yann Le Cun

6. Yoshua Bengio

7. Kunihiko Fukushima

8. Ray Kurzweil

9. Eric Schmidt

VII. Resources

The Stanford AI index

IEE Spectrum | IBM Think | ASCl's State of AI

CSAIL (MIT) | Alan Turing Institute (UK) | HAI & SAIL (Stanford)