(relevance for the project + UX improvement) / (added complexity x speed impact x development time)

Here, we present the Digital Brain (DB), a platform for simulating spiking neuronal networks at the large neuron scale of the human brain based on personalized magneticresonance-imaging data and biological constraints. The DB aims to reproduce both the resting state and certain aspects of the action of the human brain. An architecture with up to 86 billion neurons and 14,012 GPUs, including a two-level routing scheme between GPUs to accelerate spike transmission up to 47.8 trillion neuronal synapses, was implemented as part of the simulations. We show that the DB can reproduce blood-oxygen-level-dependent signals of the resting-state of the human brain with a high correlation coefficient, as well as interact with its perceptual input, as demonstrated in a visual task. These results indicate the feasibility of implementing a digital representation of the human brain, which can open the door to a broad range of potential applications.

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ELIZA wasn't actually "smart" in the way we think of AI today. It used a very simple pattern-matching system and didn't understand language or context at all. The program basically worked by:

1. Looking for specific keywords in user input
2. Applying simple transformation rules
3. Reflecting statements back as questions
4. Using a few pre-programmed responses when it couldn't match patterns

For example, if you said "I am feeling sad", ELIZA might respond "Why do you feel sad?" - simply taking your statement and turning it into a question. Or if you mentioned your mother, it would ask about your family.

The fascinating thing about ELIZA was not its technical sophistication (which was very basic), but rather how people *responded* to it. Even though it was using simple tricks, people projected meaning onto its responses and felt like they were having a real conversation. This is known as the "ELIZA effect" - where people attribute human-like understanding to computer programs.

Regarding the 2023 study you mentioned - while interesting, it's important to note that ELIZA only performed better in very specific circumstances and the study has been subject to some criticism regarding its methodology.
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Model: Claude 3.5 Sonnet v2 (Balanced)

A 2-ply mini-max search chess engine in 84,688 regular expressions.
RegexChess is a complete chess engine that plays moves making regular expression transforms to a given board state. It implements a 2-ply minimax search algorithm and generates moves in about 5-10 seconds.