Elena AILL / Insights
Making research easier to understand.
Explore Elena AILL’s questions through its experiments: memory, learning, language, reasoning and what negative findings can teach.
What Counts as Learning in AI? Lessons from Elena AILL
What separates memory from learning? Elena AILL experiments F896 and F898 trace the path from available information to an answer.
- Memory and learning
- F896 / F898
- Results and limitations
Keep exploring
Memory, architecture, language, reasoning and negative findings: five paths to explore.
Persistent Memory: Can an AI Remember Over Time?
What survives a restart? F188 and F274 show how Elena AILL tests recall of consolidated information, including questions asked in different words.
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Learning Without Transformers: Possibilities, Evidence and Limits
Investigating AI without Transformers: Elena AILL’s tests of words, memory and component roles, from F235 to neural-core replays.
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Why Is It So Difficult to Make an AI Speak?
Understanding a request and finding the words are different problems. F896, F898, F315 and F578 follow Elena AILL’s work on language.
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Artificial Reasoning: What Do the Tests Actually Demonstrate?
From organised facts to requests that need interpretation: F896 and F885 show why test conditions matter when assessing artificial reasoning.
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Failed Experiments: Why Negative Results Matter
A completed update is not enough. F105 and F575 show how negative findings inform answer evaluation and the next research decision.
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Explore the evidence and research topics directly in the sources.
Persistent memory
What survives a restart, and how it is retrieved when needed.
Open the research page ↗02 / PUBLIC RESEARCHInternal mechanisms
How updates, feedback and consolidation are investigated.
Open the research page ↗03 / PUBLIC RESEARCHArchitecture and runtime
How components are organised and what they do in the operational path.
Open the research page ↗Elena AILL research
Research, from questions to evidence
Elena AILL is an independent AI research project. Insights explores its questions, experiments and decisions; the scientific archive lets readers return to the evidence and examine each finding in more detail.