There are references to the IBM 7090/7094 version under IBSYS online.
In this 7094 emulator package on Github: https://github.com/Bertoid1311/B7094 (in the zipped distribution files unfortunately) I think there is a copy that is runnable? see: Docs/Bamberger-MAMOS_docs/BAMBSYSLB1_patch_for_IPLV.txt
It describes patching the available binary to make it work, with the caveat that it's unclear if the interpreter is correct/intact (but it does run the demo programs).
On the provenance of the tape:https://retrocomputingforum.com/t/umes-resurrected-sort-of/3739
In this 7094 emulator package on Github: https://github.com/Bertoid1311/B7094 (in the zipped distribution files unfortunately) I think there is a copy that is runnable? see: Docs/Bamberger-MAMOS_docs/BAMBSYSLB1_patch_for_IPLV.txt
It describes patching the available binary to make it work, with the caveat that it's unclear if the interpreter is correct/intact (but it does run the demo programs).
On the provenance of the tape:https://retrocomputingforum.com/t/umes-resurrected-sort-of/3739
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 describes a computational cognitive model of instrument operations at the Linac Coherent Light Source (LCLS), a leading scientific user facility.
- The model simulates aspects of human cognition at multiple scales, ranging from seconds to hours, and among agents playing multiple roles.
- The model can predict impacts stemming from proposed changes to operational interfaces and workflows, and its code is open source.
- Example results demonstrate the model's potential in guiding modifications to improve operational efficiency and scientific output.
The model's primary focus is on the decision of what to measure when and for how long, made by the experiment manager in consultation with the team.
The model represents a rough approximation of the LCLS setting but produces sensible results that provide insights into human-in-the-loop instrument operations.
The model can help optimize scientific productivity at LCLS by enhancing aspects of the human-machine interface and cognitive factors.
Conclusions:
1. The model's primary focus is on the decision of what to measure when and for how long, made by the experiment manager in consultation with the team.
2. The model represents a rough approximation of the LCLS setting but produces sensible results that provide insights into human-in-the-loop instrument operations.
3. The model can help optimize scientific productivity at LCLS by enhancing aspects of the human-machine interface and cognitive factors.
4. Future work includes extending the model to capture more detailed measurements of individual and team behavior, inter- and intra-team communications, and learning at multiple scales.
- The model simulates aspects of human cognition at multiple scales, ranging from seconds to hours, and among agents playing multiple roles.
- The model can predict impacts stemming from proposed changes to operational interfaces and workflows, and its code is open source.
- Example results demonstrate the model's potential in guiding modifications to improve operational efficiency and scientific output.
The model's primary focus is on the decision of what to measure when and for how long, made by the experiment manager in consultation with the team.
The model represents a rough approximation of the LCLS setting but produces sensible results that provide insights into human-in-the-loop instrument operations.
The model can help optimize scientific productivity at LCLS by enhancing aspects of the human-machine interface and cognitive factors.
Conclusions:
1. The model's primary focus is on the decision of what to measure when and for how long, made by the experiment manager in consultation with the team.
2. The model represents a rough approximation of the LCLS setting but produces sensible results that provide insights into human-in-the-loop instrument operations.
3. The model can help optimize scientific productivity at LCLS by enhancing aspects of the human-machine interface and cognitive factors.
4. Future work includes extending the model to capture more detailed measurements of individual and team behavior, inter- and intra-team communications, and learning at multiple scales.
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.
