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    Critics say tech sector profits from LLM inefficiency●But here we run up against an unpleasant reality: the tech sector values the # LLM craze chiefly because it's outrageousMmastodonEnvironmentEnergy595 min ago

    Commentators are arguing that the tech industry embraces the large language model boom mainly because it is so wasteful, not despite it. The claim is that AI systems constantly demand more computing power, energy and money, and that investors and company executives enrich themselves as ever greater resources are poured into the trend. The argument frames the AI surge as a speculative grift driven by escalating spending rather than genuine efficiency or usefulness.

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    Karpathy warns of widening gap in understanding LLM capabilities●The gap in shared understanding of LLM capability is wideningYhnBusinessEconomy103just now

    Andrej Karpathy says the gap in shared understanding of what large language models can and cannot do is widening. The observation has struck a chord among AI researchers and practitioners, who debate whether public perception of LLM capability is drifting too far from technical reality as models advance quickly.

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    Can ChatGPT Beat the Stock Market?●Can ChatGPT beat the stock market? AI stock trading now goes beyond research: LLM agents can analyze news, portfolios anMmastodonBusiness43 min ago

    Large language model agents are moving beyond research in finance: they can now analyze news, review portfolios and even connect directly to brokerages to place trades. Studies show AI systems can pick up real predictive signals in financial text, but there is still no proof of a machine that reliably beats the market. Observers are weighing the technology's promise against the risk of overhyping its trading abilities.

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    St. Joseph school board to tackle enrollment, facilities, finances●St. Joseph school board to discuss enrollment projections, facilities and finances Monday✉newsBusinessFinance2 min ago

    The St. Joseph school board is set to meet Monday to discuss enrollment projections, facilities and district finances. The agenda covers three of the most consequential issues facing the Missouri district, and residents are watching for how declining or shifting enrollment could shape decisions about school buildings and future budget priorities. No details of the proposals were available ahead of the session.

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    AirLLM runs 70B models on a 4GB GPU●lyogavin/airllm⬢github5418 min ago

    A new open-source project called AirLLM enables inference of 70-billion-parameter large language models on a single consumer GPU with only 4GB of memory. The Jupyter Notebook-based tool, hosted on GitHub, is drawing attention for dramatically lowering the hardware barrier to running top-tier open models locally, potentially letting hobbyists and developers experiment with large models without expensive data-center GPUs.

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    Samsung Labs releases sub-1-bit LLM compression method●Sub-1-Bit LLM Compression via Latent FactorizationYhnWorldUS Politics8821 min ago

    Samsung Labs has released LittleBit, a new technique for compressing large language models to less than one bit per weight using latent factorization. The method aims to shrink model memory footprints far beyond standard low-bit quantization, making it possible to run large models on much smaller hardware. It is drawing attention among machine learning researchers and engineers.

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    LLMs and Data Poisoning Weaponized to Manufacture Consensus●LLMs and Data Poisoning Are Weaponized to Manufacture ConsensusYhnLifeAutos3127 min ago

    A new commentary argues that large language models and data poisoning techniques are being deliberately weaponized by marketing and political interests to fabricate the appearance of broad consensus and bend public perception of reality. The piece warns that synthetic content injected into training data can make manufactured narratives look like organic, widely held views, raising concerns about trust in AI systems and online information.

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