<?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://megadose.ai/i/7f3b82d5-ebf7-4114-9372-c4c870c49968</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-10T06:45:01+00:00</news:publication_date>
      <news:title>GeniosAI, which develops AI software for financial analysis and modeling, raised $19.1M across seed and Series A rounds; FactSet led the Series A (Ryan Lawler/Axios)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/b80d80de-0255-41c0-b5d3-8a135a2540e0</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-10T01:41:39+00:00</news:publication_date>
      <news:title>Filing: Anthropic now aims to raise up to $69.3B in its IPO (Reuters)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/231941d8-c1b9-4e04-a7b2-5b1f49d4ca7e</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-10T01:27:12+00:00</news:publication_date>
      <news:title>Anthropic reportedly plans to move forward with IPO plans</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/e5448488-bd34-433c-9495-188e4852afdc</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T22:50:44+00:00</news:publication_date>
      <news:title>Maket adds text-to-furniture feature for 3D Floor Plans</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/23daecdb-28ff-4bff-8d9d-b6337092af6e</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T22:32:09+00:00</news:publication_date>
      <news:title>Anthropic launches Claude Fable 5.2 and Mythos 5.2</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/b8aac2b5-c7f7-400b-939d-13b10cee1e8b</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T22:28:21+00:00</news:publication_date>
      <news:title>Meta launches Muse Ember for low-cost agentic tasks</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/ea7bdbde-94ae-4018-ae96-38022bb31425</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T22:26:02+00:00</news:publication_date>
      <news:title>Google Maps features come to Google AI Studio Build</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/ca9d8f73-11a6-4517-85d1-17589fc9acfc</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T21:00:48+00:00</news:publication_date>
      <news:title>SpaceX plans a gas-fired power plant and super-compute facility in Starbase, TX, with ~$24B of investment for initial phases, per a public hearing notice (Bloomberg)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/ac36a531-157b-4524-9f0a-54a1d60d025e</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T20:04:55+00:00</news:publication_date>
      <news:title>Claude Fable 5.2 Scores 65 on Artificial Analysis, Highest So Far</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/ce5eac04-9a2b-4e41-a80a-5ba951a58694</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T20:00:51+00:00</news:publication_date>
      <news:title>Anthropic prices Fable 5.2 and Mythos 5.2 at $8/1M input and $40/1M output tokens, down 20% from 5.1; fast mode costs $16/1M input and $80/1M output tokens (Frederic Lardinois/The New Stack)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/f3d1a179-83c4-4157-b214-f1e69ddf5eff</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T19:24:51+00:00</news:publication_date>
      <news:title>Anthropic releases new Mythos and Fable models amid RSI concerns</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/b2ad6f6f-46cf-4c1b-b3a4-e8a485c243df</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T19:15:01+00:00</news:publication_date>
      <news:title>Anthropic says during prerelease testing Mythos 5.2 and Fable 5.2 formalized the proof of Fermat's Last Theorem and solved two open black hole physics problems (Jay Peters/The Verge)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/e7a62971-c73a-4a4e-b16a-3f8e0b13c9d8</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T19:02:08+00:00</news:publication_date>
      <news:title>Anthropic releases Mythos 5.2 and Fable 5.2, saying they are "best for the most ambitious, open-ended technical work", for $8/1M input and $40/1M output tokens (Anthropic)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/bef25e13-0935-44c9-a8f8-db7e790e7280</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:59:40+00:00</news:publication_date>
      <news:title>Guiding Data Allocation for Robust Subpopulation Generalization</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/0e393845-2a22-4c19-9b05-d094510bcca6</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:59:13+00:00</news:publication_date>
      <news:title>Kolmogorov-Chapman Maps: Trajectory-Free Learning for Simulating Molecular Dynamics</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/073f799d-d749-4bfd-b6a4-05c37ca0ec34</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:58:41+00:00</news:publication_date>
      <news:title>Adaptive Quantization Preserves Fast Rates for TD Learning over Rate-Limited Channels</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/08947510-2400-4992-b49f-89ea6a4a4cc9</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:57:00+00:00</news:publication_date>
      <news:title>HiVe-Mem: Interleaving Horizontal Memory Expansion and Vertical Evidence Composition for Multimodal Agents</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/f60c3ccb-2e82-4775-989e-e0cd9e4519df</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:56:15+00:00</news:publication_date>
      <news:title>Vendi Anomaly Scores for Efficient and Accurate Anomaly Detection</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/17aa3921-d201-4660-aefe-992339b6c2b2</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:53:57+00:00</news:publication_date>
      <news:title>Where Does Alignment Emerge and What Does It Mean? A Closer Look at the Platonic Representation Hypothesis</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/684a050a-9767-4492-9f8f-7aef5d3f83ab</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:52:20+00:00</news:publication_date>
      <news:title>Shortcuts and Boundaries: Verifiable RL Misalignment and Contextual Safety Learning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/53ef95f2-ec56-47a1-bfc5-1541a4e2cb00</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:51:03+00:00</news:publication_date>
      <news:title>Is Persona Generalization Predictable?</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/7887eeb4-07dd-445a-b8a5-1f935a1c321d</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:50:03+00:00</news:publication_date>
      <news:title>Mavria, which aims to build modular data centers that can be shipped by trucks, raised $130M across pre-seed and seed rounds at a $1B valuation led by Paradigm (Jennifer Hiller/Wall Street Journal)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/cdae6e6d-b8c8-48b0-87f2-7d6c304f06a8</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:45:28+00:00</news:publication_date>
      <news:title>WorkflowArena: Benchmarking Executable Workflow Orchestration in LLM-Based Multi-Agent Systems</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/4b5569fc-3609-4ecb-8146-879938ddc9e8</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:44:37+00:00</news:publication_date>
      <news:title>What kills $v$-prediction? A Patch-wise PCA Perspective on Pixel-Space Flow Matching</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/6e60e815-c1d2-422b-8931-53496d77ec52</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:33:13+00:00</news:publication_date>
      <news:title>Mitigating Agentic Deception via Evaluation-Side Partially Observable Games</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/4bfdbf20-5d9e-4085-99d6-e62ea0e2efc3</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:30:41+00:00</news:publication_date>
      <news:title>What the Loss Curve Misses: FP4 Pretraining Slows the Acquisition of Rare Facts</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/6c94bc39-c723-487b-93ca-084eebe3d71d</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:25:42+00:00</news:publication_date>
      <news:title>MaxIM: Maximally Informative Incremental Summarization via Reinforcement Learning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/bae86539-369a-4860-9298-e1a65395cab5</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:22:19+00:00</news:publication_date>
      <news:title>How Well Does AI Peer Review Work? A Benchmark Built from 100 Planted Errors</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/2058c7ad-7be5-49e2-9e36-bede909e3706</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:15:00+00:00</news:publication_date>
      <news:title>Meta releases Muse Ember, its smallest and most cost-efficient AI model yet, saying it delivers more intelligence per dollar than Haiku 5.5 and GPT-6 Luna (Russell Brandom/TechCrunch)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/0783a4dd-820b-42b0-9dd1-785d82d524bf</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:07:42+00:00</news:publication_date>
      <news:title>Agentic-OPD: Recovering Forgotten Agent Capabilities via On-Policy Distillation for Agentic Tasks</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/f38f72c3-a248-49ae-b91f-124653422500</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T18:00:00+00:00</news:publication_date>
      <news:title>Meta releases Muse Ember, a new lightweight model for agent execution</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/79d8e86a-a56e-4836-9c89-c7e1ceca562f</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:58:46+00:00</news:publication_date>
      <news:title>Our Smallest, Most Efficient Model: Muse Ember</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/5c87a2db-b93a-4464-99fa-11fc0fa38b7b</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:58:38+00:00</news:publication_date>
      <news:title>Large Language Models as a Universal Searcher for Open-World Automated Machine Learning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/08b8ae25-21f6-4aea-80b2-581d339f0cfe</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:41:08+00:00</news:publication_date>
      <news:title>Learning Rate Decay Can Exponentially Accelerate SGD for Global Optimization of Nonconvex Functions</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/e6a8a18c-cd20-4000-a2da-0916e37e9cee</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:38:16+00:00</news:publication_date>
      <news:title>PORT: Preference Optimization via Robust Token-Level Reweighting</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/d8ab0f87-8dc0-4b4e-9690-46b3107df446</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:38:05+00:00</news:publication_date>
      <news:title>Sage-Taiyi: A Metacognitive Architecture for Scientific Discovery</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/056e29b3-cd1f-4778-9d6f-35c4ff2cb3f6</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:15:46+00:00</news:publication_date>
      <news:title>KiteNorm: Variance Regularisation for Stable and Scalable Post-LN Transformers</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/4ad835fa-25d3-49fd-87c7-41f438e6133e</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:14:40+00:00</news:publication_date>
      <news:title>Safe Reinforcement Learning for Multi-Turn Clinical Agents: When Dense Rewards Beat Outcome Rewards</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/8d9a5b51-76da-4386-83f0-b270ea9156c0</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T17:00:16+00:00</news:publication_date>
      <news:title>Multi-Agent Screening: What Agreement and Acceptance Cannot Tell You</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/6325862f-7cde-438b-81c6-7ba190b27652</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T16:57:25+00:00</news:publication_date>
      <news:title>GeoScope: Training-Free Program Execution beyond the Counting Horizon for Ultra-High-Resolution Remote Sensing Question Answering</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/0554674a-422f-4527-a564-686b5c16a68c</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T16:56:54+00:00</news:publication_date>
      <news:title>Anthropic joins AI’s natural gas frenzy, buys $3.4B worth of turbines</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/323731f3-7f5f-42bf-b749-69f4a6e53cee</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T16:56:19+00:00</news:publication_date>
      <news:title>Generalized Adaptive Boosting and the Geometry of Mistakes</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/6a4ddea0-3acd-4c0e-b78a-fc64574d1700</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T16:50:14+00:00</news:publication_date>
      <news:title>CoilStellaration: A Dataset and Benchmark for Engineering-Aware Stellarator Coilset Generation</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/42dae7c9-d68d-4bc5-9e0c-54e51f690360</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T16:50:08+00:00</news:publication_date>
      <news:title>ElevenLabs launches ElevenAgents Campaign Manager</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/e11f1955-4285-43ce-bd8d-12a1a230e31f</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T16:49:45+00:00</news:publication_date>
      <news:title>reComposer: Editable Planning for Controllable Image Generation</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/a8e73bda-9fea-44ab-82f1-1cc7dd238a3d</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T16:12:28+00:00</news:publication_date>
      <news:title>Medium’s new TK app brings AI assistance directly into the writing process</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/1dafa9ae-65c4-49ab-b090-2b2215bc1689</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T15:50:01+00:00</news:publication_date>
      <news:title>Disney and Adobe partner to develop proprietary "artist-led" generative AI models using Adobe Firefly Foundry to support Disney's production pipeline (Jess Weatherbed/The Verge)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/e7f90185-bfe4-4f2b-bfd0-22e04cf41a45</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T15:15:02+00:00</news:publication_date>
      <news:title>Medium launches TK, an AI-powered, minimalist note-taking, journaling, and private social networking app with daily prompts, its first major launch since 2017 (David Pierce/The Verge)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/cb450f0f-3d0d-4dd5-bc38-81ae43738b3d</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T14:30:00+00:00</news:publication_date>
      <news:title>Spines, which uses AI agents to edit and proofread amateur authors' books, design their covers, and handle the layout, raised $29M in equity and $35M in debt (Assaf Gilead/Globes)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/6aa6f789-ee96-4c05-92ac-be792ed09dda</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T14:00:00+00:00</news:publication_date>
      <news:title>Automattic debuts a platform to deploy vibe coding apps amid a changing internet</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/3537e83a-262d-4e56-b959-17f37b58b22c</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T13:11:52+00:00</news:publication_date>
      <news:title>Google adds new TPU 8tx and TPU 8i Max for AI workloads</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/de6f29b7-1739-430b-855b-5230e66c7da5</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T12:50:00+00:00</news:publication_date>
      <news:title>Google unveils two specialized TPUs, the TPU 8tx, to be paired with AMD CPUs, and TPU 8i Max, a dual-chip package for long-context window tasks, launching 2027 (Dina Bass/Bloomberg)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/c6172c5f-9f3b-49c9-b391-073f1d2724de</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T10:40:00+00:00</news:publication_date>
      <news:title>Nvidia drops ~5% pre-market after its board opens a probe into Jensen Huang; Nvidia previously dismissed the interactions as "nothing unusual or unexpected" (Demetri Sevastopulo/Financial Times)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/0c263b54-fd99-4168-a6dd-fcd1563c4a31</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T10:24:55+00:00</news:publication_date>
      <news:title>ICYMI: Meta rolls out specialized models for Muse and Meta AI</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/6543feea-f237-49c0-8d69-56835aa1df5f</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T08:46:41+00:00</news:publication_date>
      <news:title>Toronto-based Ada and SF-based Dialpad, both makers of AI customer service software, agree to merge in an all-share deal valuing Ada at ~$430M, sources say (Globe and Mail)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/00ce452a-6ff9-4013-8ff7-624b2412ef02</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T05:50:00+00:00</news:publication_date>
      <news:title>Sources: ByteDance seeks to expand its data center project in Ceara, Brazil, with a second phase larger than its ongoing $10B, 300MW project (Peter Millard/Bloomberg)</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/0cec4bad-e506-4253-abbf-7c78751d1a6b</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-09T00:00:00+00:00</news:publication_date>
      <news:title>Sage-Taiyi: A Metacognitive Architecture for Scientific Discovery</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://megadose.ai/i/32536012-e964-4529-ae8d-7bef52c7dd7a</loc>
    <news:news>
      <news:publication>
        <news:name>Megadose</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-11-08T15:05:01+00:00</news:publication_date>
      <news:title>Sources: Anthropic bought commitments for 1.7GW of gas-fired generators from equipment supplier OnePWR for $3.4B, the largest known such purchase by an AI lab (Martha Muir/Financial Times)</news:title>
    </news:news>
  </url>
</urlset>
