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        <title>ENKAIDU lab notes</title>
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        <description>Dated working notes from the ENKAIDU research program: positions, method decisions, readings, and dead ends.</description>
        <language>en</language>
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            <title>Note 005: One intelligence, two examples of it</title>
            <link>https://enkaidu.com/lab-notes.html#note-005</link>
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            <pubDate>Wed, 26 Aug 2026 00:00:00 +0000</pubDate>
            <category>Position</category>
            <description>Adding a position to the record, because it changes what counts as evidence here. We have met intelligence twice: in animals and in the systems we have built. Each is particular, and treating either as the definition is a mistake we would rather make on purpose than by accident.</description>
        </item>
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            <title>Note 004: Choosing the first falsification target</title>
            <link>https://enkaidu.com/lab-notes.html#note-004</link>
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            <pubDate>Tue, 02 Jun 2026 00:00:00 +0000</pubDate>
            <category>Decision</category>
            <description>The first real test of the framework is whether it can reproduce what already works. Two model families have to fall out of the substrate definition as special cases: associative memories, which should appear when the field dynamics are driven to settle, and diffusion processes, which should appear when entropy production dominates transport.</description>
        </item>
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            <title>Note 003: Why waves</title>
            <link>https://enkaidu.com/lab-notes.html#note-003</link>
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            <pubDate>Sun, 26 Apr 2026 00:00:00 +0000</pubDate>
            <category>Position</category>
            <description>A physical field is an odd thing to build a learning system out of, so the three reasons should be on the record. Superposition lets one medium carry many signals at the same time. Interference computes correlations as a side effect of the waves propagating, with no separate step for it, although driving and maintaining the field still costs energy. And conservation laws and locality restrict the system for us: it cannot create energy out of nothing and it cannot act at a distance. We expect that to rule out classes of degenerate solutions before training starts, though we have not shown it for this setting.</description>
        </item>
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            <title>Note 002: The pieces already exist, scattered</title>
            <link>https://enkaidu.com/lab-notes.html#note-002</link>
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            <pubDate>Sat, 14 Mar 2026 00:00:00 +0000</pubDate>
            <category>Reading</category>
            <description>A pass through the literature turns up the same pattern repeatedly: the field reaches this foundation, notes it, and moves on. Landauer showed in 1961 that erasing information has an energy floor, and that the floor attaches to erasing rather than to computing. Hopfield showed in 1982 that inference can be a system settling into a minimum. Sohl-Dickstein and colleagues built generative modeling directly on nonequilibrium thermodynamics in 2015. Hughes and colleagues showed in 2019, in simulation, that a designed medium could classify spoken vowels from the way waves scattered through it. And in 2020 Ramsauer and colleagues showed that one step of transformer attention is one update of a modern Hopfield network, which makes the central operation of the dominant architecture an energy-model step that nobody had recognised as one.</description>
        </item>
        <item>
            <title>Note 001: What counts as a derivation</title>
            <link>https://enkaidu.com/lab-notes.html#note-001</link>
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            <pubDate>Mon, 09 Feb 2026 00:00:00 +0000</pubDate>
            <category>Method</category>
            <description>The whole program rests on the word &quot;derivation&quot;, so it gets pinned down before anything else, in four conditions. The assumptions are written down and countable. Every step can be checked by someone who did not write it. Systems that already work appear as special cases when you restrict the general structure. And the result disagrees with current practice somewhere a numerical experiment can settle.</description>
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