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Biological computing, exemplified by devices like Cortical Labs’ CL1 system, leverages the unique properties of live, lab-grown human neurons integrated on a silicon substrate. According to the information provided, each CL1 unit, which contains approximately 800,000 reprogrammed human neurons, demonstrates adaptive, learning-based responses to electrical stimuli while operating within a closed-loop system. A significant point is that a rack of these CL1 units consumes between 850 and 1,000 watts. This represents a dramatic reduction in power requirements compared to traditional silicon-based data centers. The ability to efficiently process information with a comparatively low energy footprint is largely attributed to the natural, evolved efficiency of biological cells. As noted in the article, biological neural systems operate similarly to a “glorified sugar water” setup, where the substrate is enough to power real-time, adaptive computations, showcasing an approach that is both efficient and sustainable^[1][2].

Traditional silicon-based computing systems, particularly those designed for artificial intelligence workloads, require substantial energy resources. For context, while the CL1 unit rack operates at under 1,000 watts, conventional AI processing setups housed in data centers typically draw tens of kilowatts of power. This discrepancy points to a major limitation in silicon computing: the scaling of energy consumption as computational needs increase. Furthermore, the widespread need for immense power generation to run advanced silicon-based machine learning algorithms sometimes involves the consumption of several million watts. In contrast, the reduced energy demand of biological systems may alleviate some of the environmental and economic pressures associated with powering large-scale AI infrastructures^[1][2].

The contrasting energy profiles of biological versus silicon-based computing carry profound implications for both research and practical applications. The relatively low energy requirements of biological systems—evident from the CL1’s performance—highlight their potential for extended experiments and sustainable large-scale operations. Given that a rack of CL1 units consumes only 850 to 1,000 watts, the prospect of deploying clusters of these biocomputers could transform experimental setups in drug discovery, disease modeling, and neurocomputation. This low power consumption could enable prolonged experiments in confined spaces or in settings where energy availability is a constraint^[1].

Moreover, the biological approach promises not only low energy consumption but also an adaptability that stems from the inherent properties of living cells. Biological neural systems display rapid and highly sample-efficient learning compared to their silicon-based counterparts. Reports suggest that even simple tasks simulated in a biocomputer can exhibit goal-directed learning behaviors that result from the natural minimization of prediction errors, aligning with theories such as the Free Energy Principle. This indicates that beyond energy efficiency, biological computing might offer a naturally adaptive framework that can adjust to varying environmental inputs in a more efficient manner than rigid silicon circuits^[2].

In summary, while both biological and silicon-based systems have their respective strengths and limitations, the evidence suggests that biological computing offers a very promising alternative in terms of energy efficiency. The CL1 units, by consuming only 850 to 1,000 watts per rack, stand in stark contrast to silicon-based data centers that require tens of kilowatts to support AI workloads. This energy disparity underscores the potential evolution in computing technology where sustainability and lower operational costs become driving factors. Furthermore, the inherent adaptive and learning properties of biological systems further complement this efficiency by enabling rapid, highly sample-efficient responses to environmental stimuli—a feature that is currently challenging to replicate in silicon-based models^[1][2].

As research continues, the integration of biological principles into computational designs could pave the way for systems that not only consume less energy but are also capable of exhibiting flexible, self-regenerating behavior. With ongoing developments, the energy efficiency of biological computing may well address the limitations of current silicon-based approaches, thereby ushering in a new era of sustainable and adaptive computing solutions.

The economic incentive for wrecking was particularly strong in areas where alternative means of sustenance were scarce. The text notes that some individuals did not hesitate to cause wrecks by displaying false lights to lure vessels to destruction^[1]. These wreckers then profited from the remains of the ships and their cargo. The book describes wreckers as 'a class of men who, in the absence of an efficient coast-guard, subsisted to a large extent on what they picked up from the wrecks that were cast in their way'^[1].

While the act of deliberately causing a shipwreck was undoubtedly criminal, the line between assisting distressed vessels and exploiting their misfortune was often blurred^[1]. The text suggests that 'not all wreckers were guilty of such crimes, but many of them were so, and their style of life, at the best, had naturally a demoralizing influence upon all of them'^[1]. This moral gray area was further complicated by the lack of effective legal oversight and the desperation of coastal communities facing economic hardship^[1].

The narrative provides a glimpse into the economic realities and moral compromises associated with wrecking through the character of Big Swankie. After a storm, Swankie and Davy Spink ventured out to the 'celebrated and much dreaded Inch Cape—more familiarly known as the Bell Rock' in search of wrecks^[1]. Their dialogue and actions reveal the opportunistic nature of wrecking, with the expectation of finding 'something' after a storm that ‘strewing the coast with wrecks’^[1].

Swankie's discovery of a dead man and his subsequent actions exemplify the ethical dilemmas inherent in wrecking. Initially, Swankie's impulse was to alert his companion, but he then checked himself and examined the dead man's pockets^[1]. Finding valuables such as a gold watch, rings, brooches, and sovereigns, Swankie attempts to conceal his find from Spink, illustrating the temptation and moral compromises involved^[1].

The encounter between Swankie and Spink highlights the tensions between their shared venture and individual greed. Spink's arrival leads to a dispute over the division of the discovered wealth^[1]. Swankie's rationalization and Spink's willingness to participate, despite initial reservations, underscore the complex moral landscape of wrecking^[1]. They found nothing more of any value, but a piece of paper was discovered, wrapped up in oilskin, and carefully fastened with red tape, in the vest pocket of the dead man'^[1]. This paper contained writing, but Swankie refolded the paper, and thrust it into his bosom, saying, Come, we're wasting time. Let's get on wi' our wark'^[1].

The narrative contrasts this era of frequent wrecks and opportunistic wrecking with a future where advancements in maritime safety would reduce such practices^[1]. The construction of lighthouses, such as the one on Bell Rock, symbolized a shift towards greater safety and regulation, challenging the traditional reliance on wrecking as a source of income^[1]. The decision to build a lighthouse on the Bell Rock illustrates an intention to mitigate the terror mariners faced^[1]. This initiative directly threatened the economic interests of those who depended on shipwrecks, signalling a changing attitude towards maritime activities and coastal economies.

Wrecking, as depicted in the book, was shaped by a complex interplay of economic pressures, moral ambiguities, and evolving legal frameworks^[1]. While providing a means of survival for some coastal communities, the practice also perpetuated a cycle of exploitation and danger. As technology advanced with the construction of lighthouses, and laws were put in place, the reliance on wrecking diminished, reflecting a gradual shift towards more regulated and ethical maritime practices^[1].