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Hackworth @lemmy.world
Posts 2
Comments 200
Academic Indoctrination
  • Excellent summary and a good example of why Twitter is not a good platform for meaningful discussion. I'll just add that A.I. has the potential to completely dismantle anything resembling a shared cultural landscape or public discourse. It also has the potential to knit the world together with a greater understanding of the deep patterns that govern our chaotic maps of meaning. Wonder which one we'll try first.

  • How do trees know?
  • Plants with more flexible and responsive genetic systems were better able to adapt to changing environments and thus more likely to survive and reproduce, so yeah. However, the basic building blocks of these systems - DNA replication, gene expression, and the fundamental biological processes arose from simpler chemical and physical interactions that were likely governed by principles of self-assembly and thermodynamics. The primary drivers are different at different levels of abstraction and complexity, and there's dynamic interaction across levels.

    Thermodynamics -> Natural Selection -> Responsive (Epi)Genetics -> Memetics -> Metamemetics (probably?)

    We "boil things down" to Natural Selection or Thermodynamics as is convenient for communication, but the higher levels affect the lower as well. So we can't really reduce them like that without losing important information.

  • How do trees know?
  • In our effort to disillusion people of the idea that evolution has a purpose or conscious hand, we over-simplify things, though. Plants actively (but not consciously) shape their own evolution through complex molecular and genetic mechanisms. They can respond to environmental stresses by altering their DNA methylation patterns, potentially priming future generations for similar conditions. Plants also engage in niche construction, modifying their surroundings in ways that influence their evolutionary trajectory. For instance, they can change soil chemistry through root exudates, creating new selective pressures for themselves and their offspring. Plants participate in intricate co-evolutionary relationships with pollinators, herbivores, and other organisms. These interactions create dynamic fitness landscapes that drive reciprocal evolutionary changes. While not “inventing” traits in a deliberate sense, plants possess sophisticated genetic tools - such as whole genome duplications, transposable elements, and adaptable gene networks - that allow for rapid evolutionary innovations. These mechanisms enable plants to continually adapt and evolve, even without conscious intent or direct feedback.

  • How do trees know?
  • TLDR; Plants actively (but not consciously) shape their own evolution through complex molecular and genetic mechanisms. They can respond to environmental stresses by altering their DNA methylation patterns, potentially priming future generations for similar conditions. Plants also engage in niche construction, modifying their surroundings in ways that influence their evolutionary trajectory. For instance, they can change soil chemistry through root exudates, creating new selective pressures for themselves and their offspring. Plants participate in intricate co-evolutionary relationships with pollinators, herbivores, and other organisms. These interactions create dynamic fitness landscapes that drive reciprocal evolutionary changes. While not "inventing" traits in a deliberate sense, plants possess sophisticated genetic tools - such as whole genome duplications, transposable elements, and adaptable gene networks - that allow for rapid evolutionary innovations. These mechanisms enable plants to continually adapt and evolve, even without conscious intent or direct feedback.

    Let's dive a little deeper. Cause the molecular basis of evolutionary innovation in plants is complex, with genetic and epigenetic factors. Whole genome duplications (WGD) have occurred multiple times in many plant lineages, providing raw material for evolutionary innovation. These events can lead to sub-functionalization and neo-functionalization of duplicated genes, allowing for the emergence of novel traits. Transposable elements (TEs), once dismissed as "junk DNA," are now recognized as major drivers of plant genome evolution. They can introduce regulatory variations, alter gene expression patterns, and even create entirely new genes. It's less common in plants than in prokaryotes, but horizontal gene transfer (HGT) (particularly involving mitochondrial genes) do introduce novel genetic material for evolution to act upon.

    The field of evolutionary developmental biology (evo-devo) has revealed how changes in developmental pathways can lead to major evolutionary innovations in plants. MADS-box genes, a family of transcription factors, play crucial roles in flower development. Modifications in MADS-box gene networks have been implicated in the evolution of diverse floral morphologies and fruit types. Similarly, alterations in phytohormone signaling pathways can lead to significant phenotypic changes, affecting everything from growth habits to fruit development.

    When examining the molecular evolution of specific traits, we find fascinating examples of genetic repurposing and innovation. The evolution of fleshy fruits involves complex genetic networks. For instance, the FRUITFULL (FUL) MADS-box gene, originally involved in Arabidopsis silique development, has been co-opted in tomato to regulate fruit ripening. This exemplifies how existing genetic modules can be repurposed for new functions. The evolution of plant defense compounds involves gene duplication and neofunctionalization of enzymes in various biosynthetic pathways. For example, the diversification of glucosinolates in Brassicaceae involved duplication and subfunctionalization of cytochrome P450 genes. The evolution of seed dispersal structures often involves modifications of existing developmental programs. The wing-like samaras of maples, for instance, likely evolved through alterations in carpel development pathways.

    While plants don't receive conscious feedback, several mechanisms can influence the trajectory of their evolution. Some plants can pass on epigenetic modifications, such as DNA methylation patterns, in response to environmental stresses, potentially priming offspring for similar conditions. Through niche construction, plants actively modify their environment, which can create feedback loops affecting their own evolution. For example, changes in soil chemistry induced by plant exudates can influence selection pressures on subsequent generations. Plant-pollinator and plant-herbivore interactions create complex fitness landscapes that drive reciprocal evolutionary changes. These can be modeled using adaptive dynamics or evolutionary game theory approaches.

    It's crucial to recognize that evolution doesn't always produce optimal solutions. Constraints such as pleiotropy, where one gene affects multiple traits, and developmental or physiological limitations can restrict evolutionary trajectories. This more nuanced view acknowledges the intricate molecular and genetic underpinnings of plant evolution, moving beyond the simplified narrative of random mutation and selection.

    Modern research in plant evolutionary biology employs various cutting-edge techniques. These include genome-wide association studies (GWAS) to identify genetic loci associated with adaptive traits, transcriptomics and proteomics to understand gene regulatory networks underlying trait evolution, CRISPR-Cas9 gene editing to test the functional significance of specific genetic changes, and phylogenomics to reconstruct evolutionary histories and identify instances of convergent evolution.

    What I'm saying is, evolution as a complex process involving multiple levels of biological organization, from genes to ecosystems. It's a sophisticated mechanism underlying the diverse adaptations we observe in plants, and a deeper understanding of how traits like delicious fruits, toxic berries, protective seed coats, and innovative dispersal mechanisms have emerged over evolutionary time is a worthwhile pursuit.

  • Walkable rule
  • Not to be a dick, but just because you don't understand it doesn't make it nonsense. I was well into semiotics before "tech bro" was a thing people say. Did you have a question?

  • Walkable rule
  • Semiotics is such a fascinating study. The true power of language is astonishing, and I don't mean marketing. We live our lives in language. LLM's are going to change the relationship between the planes of content and expression so much that we're forced back to first principles. It's a bit surreal understanding this, and watching everyone argue over jobs and copyright.

  • House Democrat is proposing a constitutional amendment to reverse Supreme Court's immunity decision
  • I appreciate one of the most concise explanations of that perspective I've ever read! This is actually the one I'd like to believe, but not the one I do. I disagree with the idea that "both sides are the same," but I won't go so far as to imagine Democrats are truly concerned with integrity to the degree that they'd sacrifices strategy. I'm afraid they're just people, and people are all fucking stupid in their own way. It's just some are fucking stupid and malicious.

  • No taxation without representation either!
  • The tax situation for U.S. territories is complex and varies between them. Here's a brief overview:

    Puerto Rico and U.S. Virgin Islands:

    Residents generally do not pay federal income tax on local income. They do pay federal payroll taxes (Social Security and Medicare). They have their own tax systems.

    Guam and Northern Mariana Islands:

    Have a "mirror" tax system that parallels the U.S. federal tax system. Residents pay taxes to the territorial government instead of to the U.S. federal government.

    American Samoa:

    Has its own tax system. Residents generally do not pay federal income taxes.

    However, there are exceptions:

    Federal employees in these territories generally pay federal income tax. Residents with income sources from the U.S. mainland may need to pay federal taxes on that income. Some residents may need to file U.S. tax returns under certain circumstances.

    It's important to note that while residents of these territories may not pay federal income taxes in many cases, they also don't have full representation in Congress and can't vote in U.S. presidential elections (though they may participate in primary elections).

  • The Future of Large Language Model Pre-training is Federated

    Also See: Worldwide Federated Training Of Language Models

    Claude's Summary:

    The two papers, "Worldwide Federated Training of Language Models" by Iacob et al. and "The Future of Large Language Model Pre-training is Federated" by Sani et al., both propose using federated learning (FL) as a new paradigm for pre-training large language models (LLMs). The main ideas are:

    1. FL allows leveraging more data and compute resources from multiple organizations around the world, while keeping the data decentralized and private. This can enable training larger LLMs on more diverse data compared to centralized training.

    2. FL relaxes synchronization requirements and reduces communication overheads compared to data-parallel distributed training, making it feasible for geographically distributed participants with varying hardware and connectivity.

    3. The papers present systems and algorithms for enabling efficient federated pre-training of LLMs at billion-parameter scales. Key techniques include allowing participants to modulate their amount of local training based on resource constraints, and partially personalizing models to clusters of participants with related data.

    4. Experimental results show federated LLM pre-training can match or exceed centralized training performance, with the performance gap narrowing as model size increases to billions of parameters. Larger federated models also converge faster and are more robust.

    5. Challenges include data and hardware heterogeneity across participants. The papers propose techniques like adaptive aggregation and load balancing to mitigate these issues.

    In summary, the papers argue federated learning is a promising new direction for democratizing LLM pre-training by allowing many more organizations to collaboratively train large models on their combined data and compute resources. Let me know if you would like me to expand on any part of the summary or papers in more detail.

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