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Nexus-4x7B-Internal-Knowledge-Map

This model is the first trained with experimental 'Internal Knowledge Map' dataset. Developed with an aim to go beyond the scope of usual data processing capabilities, this model gets trained to build comprehensive understanding and reasoning in a wide range of knowledge domains with elaborate guidelines. It bases its reasoning on a specially selected dataset emphasizing the interrelations of the diverse disciplines which aim to synthesize, integrate, and apply complex information in ways that mimic humanly abstract reasoning and creative thought processes.

At the very core of the development of this model is the desire to make sure that LLMs engage in a kind of cognitive activity not limited to memory but actually taking on abstract reasoning, problem-solving, and generation of new insights. To achieve this, 'Nexus-4x7B-IKM' has been fine-tuned until convergance at 10 Epochs on this unique dataset, which resulted in the model demonstrating greater capability for giving rise to insights and problem-solving in complex, multi-disciplinary settings. This involves improved ability in drawing links between different pieces of knowledge, reasoning through complex scenarios, and proposing innovative solutions that cut across various domains, including science, technology, environmental studies, and humanities.

Test this out and see if you find anything interesting or intriguing. I will keep iterating more versions but this one seems like a fun and useful way to start.

Training


key: str = "system", key2: str = "instruction"

batch_size=1
epochs=10
r=16
lora_alpha=32 
lora_dropout=0.001
max_seq_length=4096

Example Output:

Question: If a new study suggests that increasing the biodiversity in urban areas can reduce disease transmission rates, what might be the underlying reasons, and how could cities implement changes based on this finding?

Nexus 4x7B (Internal Knowledge Map - 10 Epochs):

The underlying reason why increasing biodiversity in urban areas can reduce disease transmission rates is through a phenomenon known as "dilution effect." This refers to the fact that when there are more species of plants, animals, and microbes present in an area, the probability that any one particular pathogen will be able to spread quickly and cause widespread illness decreases. Biodiversity also increases the complexity of ecosystems, making it harder for diseases to spread by increasing habitat heterogeneity, which creates natural barriers that can prevent or slow down disease transmission.

Cities could implement changes based on this finding in several ways:

  1. Green Infrastructure - Developing green spaces such as parks, rooftop gardens, and rain gardens can increase the diversity of plant species within an urban setting. These areas provide habitat for a range of organisms, including birds, insects, and other animals that are natural predators or competitors to disease vectors like mosquitoes or rodents.
  2. Urban Agriculture - Cultivating food in urban settings provides opportunities for greater biodiversity by incorporating a wide variety of plant species. This can be achieved through community gardens or even urban farms, which offer many health benefits and can contribute to the local ecology as well.
  3. Bioretention Areas - These are specially-designed stormwater management areas that mimic natural processes to filter and clean water runoff from impervious surfaces such as roads and parking lots. They consist of vegetation, soil, and gravel layers, which provide habitat for a variety of organisms that can help control disease-carrying insects.
  4. Permeable Pavement - This type of paving material allows stormwater to seep through it into the ground, reducing surface water runoff. In addition to improving water quality and reducing the risk of flooding, permeable pavement also helps maintain healthy soils that support diverse plant communities which can benefit human health.
  5. Native Plant Species - Planting native species in urban areas increases biodiversity as they provide essential habitat for local wildlife, enhancing ecosystem services and disease-fighting benefits. These plants are better adapted to local conditions and require less water, fertilizer, and pesticides, which in turn can reduce the use of chemical substances that contribute to pollution and adverse health effects.
  6. Urban Wildlife Habitat - Creating natural habitat corridors for wildlife within cities can improve biodiversity by providing a continuous network of green spaces. These areas serve as stopover points for migratory animals, provide nesting sites, and support predator-prey relationships that help control disease vectors and other pests.

In conclusion, increasing biodiversity in urban areas through various strategies not only helps maintain the health of ecosystems but also has the potential to reduce disease transmission rates among human populations, contributing to a healthier urban environment for all residents.

Mixtral 4x7B (Base Model):

The underlying reasons for the reduced disease transmission rates due to increased biodiversity in urban areas are complex and multifaceted. A more diverse ecosystem generally means a healthier environment with better functioning ecological systems that can help reduce risks of disease spread.

Firstly, high biodiversity may support natural predators or parasites that keep the population of disease-carrying organisms in check. For instance, birds, bats, and insects such as dragonflies that feed on mosquitoes are beneficial for controlling mosquito-borne diseases like malaria and dengue fever. Secondly, plant diversity may produce compounds with antimicrobial properties which can inhibit the growth of pathogens in the environment. Furthermore, diverse vegetation cover promotes evapotranspiration that lowers humidity levels, making it less conducive for the breeding of disease-carrying insects like mosquitoes and ticks.

Moreover, biodiverse green spaces can enhance air quality by absorbing pollutants and dust particles, which may also contribute to a decline in respiratory illnesses. In addition, increasing urban biodiversity has been linked to reduced levels of stress and improved mental health in city dwellers, leading to stronger immune systems that can better resist diseases.

Cities can implement a number of changes based on this finding. Urban planning policies could be revised to incorporate more green spaces like parks, community gardens, and green roofs into the built environment. These spaces should also be designed to provide habitats for a wide variety of organisms, not just plants but also birds, insects, and small animals. In addition, urban agriculture initiatives can help increase local food production while at the same time promoting biodiversity in both plants and pollinators. Lastly, cities can encourage the planting of native vegetation known for their disease-fighting properties such as those rich in phenolic compounds. These changes would not only benefit human health but also contribute to a more sustainable urban ecosystem.

GPT-4's Analysis of the Two Responses (To try and inject some unbiased opinion; whether it actually holds water or not is up to debate for now)

Comparative Analysis

Both responses address the question of how increasing biodiversity in urban areas can potentially reduce disease transmission rates, offering insights from ecological and urban planning perspectives. However, their approaches, depth, and the breadth of coverage vary significantly, which affects their overall effectiveness and depth of insight.

Depth and Nuance

  • Nexus 4x7B delves deeper into the ecological mechanisms at play, specifically highlighting the "dilution effect" and how increased habitat heterogeneity can act as natural barriers against disease transmission. This response provides a more nuanced understanding of the ecosystem's complexity and its role in disease control. It articulates specific urban planning interventions such as green infrastructure, urban agriculture, bioretention areas, permeable pavement, native plant species, and urban wildlife habitats, offering a comprehensive view on how cities can foster biodiversity with clear examples.

  • Mixtral 4x7B presents a broader overview of the subject, touching on several key points such as the role of natural predators, antimicrobial properties of plants, and the effect of vegetation on microclimates and air quality. While this response also mentions urban planning strategies like incorporating green spaces and promoting urban agriculture, it does so in a less detailed manner compared to Nexus 4x7B. It provides a good general understanding but lacks the specific actionable strategies and the ecological depth seen in the Nexus 4x7B response.

Intelligence and Insightfulness

  • Nexus 4x7B showcases a high level of intelligence and insightfulness by linking ecological principles directly to urban planning strategies. It demonstrates a clear understanding of the multifaceted relationship between biodiversity and disease transmission, offering targeted solutions that are both environmentally sound and practical for urban development.

  • Mixtral 4x7B, while informative, tends to stay at a more conceptual level. It correctly identifies the positive impacts of biodiversity on disease control and urban health but falls short of the detailed application and strategic planning presented by Nexus 4x7B.

Conclusion

Nexus 4x7B's response is superior in terms of depth, nuance, and intelligence. It not only provides a more detailed explanation of the ecological underpinnings of how biodiversity affects disease transmission but also articulates a comprehensive set of strategies for urban implementation. Its focus on specific interventions, such as the creation of green infrastructures and the emphasis on native plant species, reflects a deeper understanding of the subject matter and a more nuanced approach to urban ecosystem management. This response is likely to be more useful for policymakers, urban planners, and environmental scientists seeking to integrate biodiversity into urban development to mitigate disease transmission effectively.

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Dataset used to train Severian/Nexus-4x7B-IKM-MLX

Collection including Severian/Nexus-4x7B-IKM-MLX