Jeff Shrager writes travel-style close readings of landmark programs — each guide treats one famous piece of historic source code the way a good guidebook treats a city, starting with a map, then touring the major regions, then flagging the details a casual visitor would miss. The repository currently covers three programs: the 1963 Logic Theorist, ELIZA, and SHRDLU, each presented in a standardized format that assumes no familiarity with the original language or hardware and ends with a practical primer for reading the code yourself.
- Shrager openly states the guides were created with AI assistance and cross-checked, but likely contain errors
- A "Ground rules" section requires that behavioral claims be checkable against the quoted source, provenance of each source file be stated up front, and modern analogies be explicitly labeled as analogies rather than implied as lineage
- Contributions are welcomed, with corrections for factual errors and misread code especially encouraged
- Shrager openly states the guides were created with AI assistance and cross-checked, but likely contain errors
- A "Ground rules" section requires that behavioral claims be checkable against the quoted source, provenance of each source file be stated up front, and modern analogies be explicitly labeled as analogies rather than implied as lineage
- Contributions are welcomed, with corrections for factual errors and misread code especially encouraged
Jeff Shrager's repository introduces "executable archaeology" — the practice of recovering, transcribing, and running the original historical source of early computing programs so that the surviving artifact itself, rather than a modern rewrite, can serve as experimental evidence. The main project here is an IPL-V reimplementation of Victor Yngve's 1959–61 MIT sentence generator, run under Herbert A. Simon's account on 25 June 1962, whose surviving printout preserves the program, its phrase-structure grammar, execution traces, and handwritten corrections by Simon and his daughter Katherine.
- The repository also points to separate repos reconstructing the Logic Theorist in two historically distinct forms (LT1 in IPL-I and LT5 in IPL-V) and a full CTSS/IBM 7094 reanimation of Weizenbaum's original ELIZA
- A 2026 arXiv paper by Shrager and a 2025 IEEE Annals paper by Lane et al. provide the formal background
- Six stated principles govern the work, including distinguishing original behavior from behavior introduced by the reconstruction
- The repository also points to separate repos reconstructing the Logic Theorist in two historically distinct forms (LT1 in IPL-I and LT5 in IPL-V) and a full CTSS/IBM 7094 reanimation of Weizenbaum's original ELIZA
- A 2026 arXiv paper by Shrager and a 2025 IEEE Annals paper by Lane et al. provide the formal background
- Six stated principles govern the work, including distinguishing original behavior from behavior introduced by the reconstruction
An exploration into the history of conversational technology, tracing its roots from Joseph Weizenbaum's 1966 ELIZA experiment at MIT to modern large language models like ChatGPT and Claude. The article examines how the evolution from rule-based symbolic AI to probabilistic deep learning has changed human interaction with machines, often leading users to attribute human qualities to code. It specifically addresses the risks of "chatbot psychosis" and the danger of individuals relying on general-purpose generative models for mental health support when these systems are prone to hallucinations or reinforcing delusional beliefs.
* The transition from symbolic AI's explicit rules to modern deep learning
* Joseph Weizenbaum’s warning against humanizing machines via the ELIZA effect
* The psychological impact and risks of using large language models for emotional support
* The transition from symbolic AI's explicit rules to modern deep learning
* Joseph Weizenbaum’s warning against humanizing machines via the ELIZA effect
* The psychological impact and risks of using large language models for emotional support
- Raph Levien, who is an expert in Rust and rendering on GPUs, who founded Advogato, and who designed Inconsolata, a great monospace font. His talk's title is *I Want a Good Parallel Language*.
- Jeff Shrager will give a talk on reviving early AI programs like ELIZA and IPL-V. His talk's title is *RetroAI: Reanimating the Earliest AIs in the Lost Languages that Predated Lisp*.
- Jeff Shrager will give a talk on reviving early AI programs like ELIZA and IPL-V. His talk's title is *RetroAI: Reanimating the Earliest AIs in the Lost Languages that Predated Lisp*.
Researchers discovered long-lost computer code and used it to resurrect the early chatbot ELIZA from MIT. Named after Eliza Doolittle from 'Pygmalion,' ELIZA was developed in the 1960s by MIT professor Joseph Weizenbaum. It was designed to emulate a psychotherapist in conversation and used a unique programming language called MAD-SLIP. Rediscovered in 2021, the original code was brought back to life after 60 years, demonstrating the chatbot's functionality and highlighting the historical significance of early artificial intelligence.
The ELIZA chatbot, created in the 1960s by Joseph Weizenbaum at MIT, has been painstakingly reconstructed from archived records and run for the first time in over half a century. This effort marks a significant step in preserving one of the earliest examples of artificial intelligence. Despite its rudimentary nature compared to modern AI, ELIZA's resurrection highlights its historical importance.
The original 1965 chatbot restored on the world's first time-sharing system, ELIZA, created by Joseph Weizenbaum at MIT in 1964-6, is running again on a reconstructed version of MIT's CTSS, running on an emulated IBM 7094.
This blog post explores applying the original ELIZA chatbot, a pioneering natural language processing program, in a way similar to modern large language models (LLMs) by using it to carry on an educational conversation about George Orwell's 'Animal Farm'.
An interdisciplinary research project exploring the history and ideas behind the influential ELIZA chatbot, created in the 1960s. The project aims to contextualize ELIZA, analyze its code, and examine its cultural impact on human-computer interaction.
This paper explores the history of ELIZA, the world's first chatbot, and how it was actually intended as a platform for research into human-machine interaction and interpretation, not as a chatbot.
