<?xml version="1.0" encoding="UTF-8"?>
<urlset
  xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"
  xmlns:news="http://www.google.com/schemas/sitemap-news/0.9">
  <url>
    <loc>https://hackobar.com/item/anthropic-news-higher-limits-spacex</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Anthropic takes SpaceX's Colossus 1 for 220,000 GPUs</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/corning-news-and-events-news</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Nvidia invests $500M in Corning for US optical manufacturing</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/fortune-06-trump-administration-embraces-ai-oversight-policies-it-on</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>White House drafts AI pre-release safety testing order</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/genesis</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Genesis AI unveils GENE-26.5 with human-shaped robotic hands</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/businessinsider-spacex-terafab-project-cost-texas-elon-musk-2026-5</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>SpaceX Terafab chip plant could cost up to $119B</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/bloomberg-2026-05-06-meta-backed-scale-ai-wins-500-million-defense-dep</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Scale AI wins $500M Pentagon contract for AI decision-making</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/bloomberg-2026-05-07-kimi-chatbot-maker-moonshot-ai-valued-at-20-billi</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Moonshot AI raises $2B at $20B valuation from Meituan</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/businessinsider-anthropic-ceo-dario-amodei-jokes-growth-too-hard-handle-conf</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Anthropic reports 80x Q1 revenue growth year-over-year</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arstechnica-05-anthropics-claude-can-now-dream-sort-of</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Anthropic introduces 'dreaming' for Claude agents</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/openai-index-mrc-supercomputer-networking</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>OpenAI unveils MRC networking protocol with industry partners</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/openai-index-new-ways-to-buy-chatgpt-ads</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>OpenAI launches self-serve ChatGPT Ads Manager for all US businesses</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-lowkey-one-of-the-easiest-ways-to-stand-out-at-work-rn-is-he-1350</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>lowkey one of the easiest ways to stand out at work rn is helping your manager use AI better</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-subquadratic-claims-to-break-llm-scaling-limits-1000x-less-c-abf5</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Subquadratic claims to break LLM scaling limits! 1000x less costs</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/hn-show-hn-social-network-for-corporate-cringe-9b32</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Show HN: Social Network for Corporate Cringe</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-silicon-oscillators-solve-computer-problems-that-would-take--fed7</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Silicon oscillators solve computer problems that would take thousands of years using semiconductors</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-we-built-a-way-for-two-peoples-ai-context-to-talk-to-each-ot-51d5</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>We built a way for two people's AI context to talk to each other (without sharing their conversations)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/gh-bigbodycobain-shadowbroker-ae83</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>BigBodyCobain / Shadowbroker</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-built-a-structured-adversarial-debate-layer-for-multi-agent--c8e5</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Built a structured adversarial debate layer for multi-agent decision systems, sharing architecture and open questions [P]</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/hn-how-unsloth-and-nvidia-made-llm-training-25-faster-on-consum-d625</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>How Unsloth and Nvidia made LLM training 25% faster on consumer GPUs</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-month-later-qubic-still-reads-to-me-like-an-unresolved-compu-f496</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Month later, qubic still reads to me like an unresolved compute-access experiment</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-i-am-not-an-anti-like-this-guy-but-still-an-interesting-vide-1ac2</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>I am not an "anti" like this guy, but still an interesting video of person interacting with chat 4o</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/hn-show-hn-agent-skills-eval-test-whether-agent-skills-improve--c4a7</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Show HN: Agent-skills-eval – Test whether Agent Skills improve outputs</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/hn-show-hn-trust-coding-rust-like-its-1989-18b4</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Show HN: Trust – Coding Rust like it's 1989</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/reddit-anthropic-researchers-detail-model-spec-midtraining-which-ad-edf0</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Anthropic researchers detail “model spec midtraining”, which adds a stage between pretraining and fine-tuning to improve generalization from alignment training</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-investigating-trustworthiness-of-nonparametric-deep-survival-7714</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysis</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-endogenous-regime-switching-driven-by-scalar-irreducible-lea-1c9b</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Endogenous Regime Switching Driven by Scalar-Irreducible Learning Dynamics</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-mp-ismoe-mixed-precision-interactive-side-mixture-of-experts-5466</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-a-self-attentive-meta-optimizer-with-group-adaptive-learning-3d61</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>A Self-Attentive Meta-Optimizer with Group-Adaptive Learning Rates and Weight Decay</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-lookahead-drifting-model-84dd</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Lookahead Drifting Model</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-single-position-intervention-fails-distributed-output-templa-06b1</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Single-Position Intervention Fails: Distributed Output Templates Drive In-Context Learning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-lcm-lossless-context-management-5ef0</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>LCM: Lossless Context Management</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-free-energy-driven-reinforcement-learning-with-adaptive-adva-8677</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-edgerazor-a-lightweight-framework-for-large-language-models--36fd</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-adapt-to-thrive-adaptive-power-mean-policy-optimization-for--675c</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-a-consistency-centric-approach-to-set-based-optimization-wit-7274</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>A Consistency-Centric Approach to Set-Based Optimization with Multiple Models of Unranked Fidelity</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-covariance-aware-goodness-for-scalable-forward-forward-learn-298f</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Covariance-Aware Goodness for Scalable Forward-Forward Learning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-improving-medical-vqa-through-trajectory-aware-process-super-8077</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Improving Medical VQA through Trajectory-Aware Process Supervision</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-a-provably-convergent-and-practical-algorithm-for-gromov-was-b9b0</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>A Provably Convergent and Practical Algorithm for Gromov--Wasserstein Optimal Transport</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-continual-distillation-of-teachers-from-different-domains-f32d</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Continual Distillation of Teachers from Different Domains</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-connecting-online-criminal-behavior-with-machine-learning-us-0538</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Connecting online criminal behavior with machine learning: Using authorship attribution to analyze and link potential online traffickers</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-validity-calibrated-reasoning-distillation-4f7a</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Validity-Calibrated Reasoning Distillation</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-retentivekv-state-space-memory-for-uncertainty-aware-multimo-7894</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>RetentiveKV: State-Space Memory for Uncertainty-Aware Multimodal KV Cache Eviction</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-confronting-label-indeterminacy-in-automated-bail-decisions-a0e0</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Confronting Label Indeterminacy in Automated Bail Decisions</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-laws-learning-from-actual-workloads-symbolically-a-self-cert-30a8</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>LAWS: Learning from Actual Workloads Symbolically -- A Self-Certifying Parametrized Cache Architecture for Neural Inference, Robotics, and Edge Deployment</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-designing-a-double-deep-reinforcement-learning-selection-too-a0bd</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Designing a double deep reinforcement learning selection tool for resilient demand prediction</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-sparse-autoencoder-decomposition-of-clinical-sequence-model--af1d</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Sparse Autoencoder Decomposition of Clinical Sequence Model Representations: Feature Complexity, Task Specialisation, and Mortality Prediction</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-flatascend-autoregressive-clinical-sequence-generation-with--dffb</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>FlatASCEND: Autoregressive Clinical Sequence Generation with Continuous Time Prediction and Association-Based Pharmacological Testing</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-structural-equivalence-and-learning-dynamics-in-delayed-marl-5bbe</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Structural Equivalence and Learning Dynamics in Delayed MARL</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-time-series-causal-discovery-with-variable-lags-2d83</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Time series causal discovery with variable lags</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://hackobar.com/item/arxiv-efficient-handwriting-based-alzheimers-disease-diagnosis-usi-e6c5</loc>
    <news:news>
      <news:publication>
        <news:name>Hackobar</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-05-07</news:publication_date>
      <news:title>Efficient Handwriting-Based Alzheimer,s Disease Diagnosis Using a Low-Rank Mixture of Experts Deep Learning Framework</news:title>
    </news:news>
  </url>
</urlset>