{
  "$schema": "../../schemas/corrections.schema.json",
  "episode_slug": "ai-neolabs-mimo-sakana-mistral-and-g42",
  "transcript_path": "episodes/2026-10-30_ai-neolabs-mimo-sakana-mistral-and-g42.md",
  "status": "published",
  "updated": "2026-10-30",
  "reviewed_by": "fact check",
  "annotations": [
    {
      "id": "e25-01",
      "verdict": "overstated",
      "turn_index": 5,
      "rel_start": null,
      "clock": "00:42:47",
      "quote": "On Artificial Analysis it hit forty-six, first among open weights, tied with Grok four-point-seven and ahead of GLM at forty-five and Kimi at forty-four.",
      "correction": "These are scores from Artificial Analysis Intelligence Index v4.3, which v5 replaced on October 27. On v4.3, MiMo-V2.6-Pro scored 46, the top among models with released weights (Kimi K3.1 Pro, unreleased, scored 55; the 44 is the older Kimi K3). On v5, current when this was said, MiMo scores 30, behind DeepSeek V4.1 Flash and GLM-5.3 at 32.",
      "explanation": "Accurate for the retired v4.3 index only; on the current v5 index MiMo is not first among open weights.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://cybernews.com/ai-news/artificial-analysis-leaderboard-update-open-weight-ai-ranking-hit/",
          "title": "Free AI models suddenly look much worse: leaderboard update delivers a massive rankings hit",
          "publisher": "Cybernews",
          "date": "2026-10-28"
        },
        {
          "url": "https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v5",
          "title": "Announcing Artificial Analysis Intelligence Index v5",
          "publisher": "Artificial Analysis",
          "date": "2026-10-27"
        },
        {
          "url": "https://artificialanalysis.ai/articles/kimi-k3-1-pro-launch-benchmarks",
          "title": "Kimi K3.1 Pro launches at 4th on the Artificial Analysis Intelligence Index scoring 55",
          "publisher": "Artificial Analysis",
          "date": "2026-10-23"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "The Artificial Analysis numbers I gave for MiMo were from the old index. On the new one, released a few days earlier, MiMo scores 30 and sits behind DeepSeek and GLM. The cost advantage still stands, but 'first among open weights' doesn't.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-19",
      "verdict": "unsupported",
      "turn_index": 5,
      "rel_start": null,
      "clock": "00:42:47",
      "quote": "the cost per task is about thirteen cents versus two dollars for Kimi — roughly fifteen times cheaper",
      "correction": "Artificial Analysis lists MiMo-V2.6-Pro at $0.26 per Intelligence Index task and Kimi K3 at $2.37, so MiMo is about nine times cheaper per task. I found no source for 13 cents or a fifteenfold gap.",
      "explanation": "Current AA figures are 26 cents vs $2.37, about 9x, not 13 cents and 15x.",
      "confidence": "medium",
      "sources": [
        {
          "url": "https://artificialanalysis.ai/models/comparisons/mimo-v2-6-pro-vs-kimi-k3-low",
          "title": "MiMo-V2.6-Pro vs Kimi K3 (Low): Model Comparison",
          "publisher": "Artificial Analysis",
          "date": null
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said MiMo costs about thirteen cents a task against two dollars for Kimi, roughly fifteen times cheaper. I have no source for those figures. The listing I can find shows 26 cents against $2.37, about nine times cheaper.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-02",
      "verdict": "wrong",
      "turn_index": 7,
      "rel_start": null,
      "clock": "00:42:52",
      "quote": "Xiaomi is the fourth-largest phone maker in the world, with over a hundred and fifty million phones shipped last year",
      "correction": "Xiaomi is the third-largest smartphone maker, behind Apple and Samsung. IDC counts 165.3 million Xiaomi shipments in 2025 (13.1% share), so 'over a hundred and fifty million' is right; the rank is not.",
      "explanation": "Third, not fourth; the shipment figure is right.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://www.gsmarena.com/idc_smartphone_shipments_up_23_in_q4_2025_apple_is_the_clear_winner_-news-71096.php",
          "title": "IDC: Smartphone shipments up 2.3% in Q4 2025, Apple is the clear winner (IDC Worldwide Quarterly Mobile Phone Tracker, January 13, 2026)",
          "publisher": "GSMArena",
          "date": "2026-01-14"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "Xiaomi is the third-largest phone maker, not the fourth. The hundred-and-fifty-million-plus shipments figure was right.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-20",
      "verdict": "unsupported",
      "turn_index": 7,
      "rel_start": null,
      "clock": "00:42:52",
      "quote": "has massive GPU purchasing power through its cloud division",
      "correction": "Xiaomi does design its own chips (the XRING smartphone processors, in mass production since May 2025) and has said it will invest at least $8.7 billion in AI over three years. I found no source for a Xiaomi cloud division buying GPUs at scale.",
      "explanation": "Own silicon is right (phone SoCs); the cloud-division GPU buying is unsourced.",
      "confidence": "medium",
      "sources": [
        {
          "url": "https://www.reuters.com/business/media-telecom/xiaomi-has-started-mass-producing-self-developed-xring-o1-chip-2025-05-20/",
          "title": "Xiaomi has started mass producing self-developed Xring O1 chip",
          "publisher": "Reuters",
          "date": "2025-05-20"
        },
        {
          "url": "https://www.reuters.com/world/asia-pacific/xiaomi-invest-least-87-billion-ai-over-next-three-years-ceo-says-2026-03-19/",
          "title": "Xiaomi to invest at least $8.7 billion in AI over next three years, CEO says",
          "publisher": "Reuters",
          "date": "2026-03-19"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Xiaomi has massive GPU buying power through its cloud division. It does design its own phone chips and plans big AI spending, but I have no source for a cloud division buying GPUs.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-03",
      "verdict": "wrong",
      "turn_index": 7,
      "rel_start": null,
      "clock": "00:42:52",
      "quote": "It's the same pattern as Sakana in Tokyo — a compact research group with a giant industrial backer.",
      "correction": "Sakana AI is an independent startup, not a team inside a parent company. It is funded by dozens of investors, including NVIDIA, Japan's three megabanks, Itochu, NEC and KDDI, with none in the role Xiaomi plays for MiMo.",
      "explanation": "Sakana has many investors and no parent, so the MiMo comparison doesn't hold.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://sakana.ai/company-info/",
          "title": "Corporate Info",
          "publisher": "Sakana AI",
          "date": null
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "Sakana isn't the same pattern as MiMo. It's an independent startup with lots of big investors, not a small team inside a giant parent company.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-04",
      "verdict": "wrong",
      "turn_index": 9,
      "rel_start": null,
      "clock": "00:43:37",
      "quote": "founded in twenty twenty-three by three ex-Google people — David Ha, Llion Jones, and Ren Ito",
      "correction": "Two of the three founders are ex-Google: David Ha led Google Brain's Tokyo team, and Llion Jones co-wrote the Transformer paper there. Ren Ito is not: he was a Japanese diplomat, then an executive at Mercari and Stability AI.",
      "explanation": "Ren Ito never worked at Google.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://sakana.ai/company-info/",
          "title": "Corporate Info",
          "publisher": "Sakana AI",
          "date": null
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "Only two of Sakana's three founders are ex-Google. Ren Ito came from Japan's foreign ministry, Mercari and Stability AI.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-21",
      "verdict": "wrong",
      "turn_index": 11,
      "rel_start": null,
      "clock": "00:45:27",
      "quote": "seventy-nine percent on CyberGym, matching Xiaomi's MiMo and beating DeepSeek",
      "correction": "Mistral Large 4 scored 82% on CyberGym-E2E, part of Artificial Analysis's Cyber Index, the top score among the 18 models tested. The 79% belongs to Xiaomi's MiMo-V2.6-Pro, which Large 4 beat.",
      "explanation": "79% is MiMo's score; Large 4 scored 82%.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://mistral.ai/news/mistral-large-4/",
          "title": "Introducing Mistral Large 4",
          "publisher": "Mistral AI",
          "date": "2026-10-06"
        },
        {
          "url": "https://www.datacamp.com/blog/mistral-4-large-le-chonk",
          "title": "Mistral Large 4 (Le Chonk): Everything We Know",
          "publisher": "DataCamp",
          "date": "2026-10-29"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I gave Mistral Large 4 seventy-nine percent on CyberGym, matching MiMo. That's MiMo's score; Large 4 scored eighty-two percent, the top result.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-22",
      "verdict": "overstated",
      "turn_index": 11,
      "rel_start": null,
      "clock": "00:45:27",
      "quote": "Annual recurring revenue is past a billion",
      "correction": "Mistral hasn't reported annual recurring revenue above $1 billion. The last figure it gave was above $400 million, in February 2026. In September, Arthur Mensch said Mistral was on track to pass $1 billion before the end of the year.",
      "explanation": "A year-end target stated as achieved.",
      "confidence": "medium",
      "sources": [
        {
          "url": "https://presenc.ai/research/mistral-ai-revenue-and-arr-2026",
          "title": "Mistral AI Revenue and ARR 2026",
          "publisher": "Presenc AI",
          "date": "2026-10-01"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Mistral's annual recurring revenue is past a billion. That's its target for the end of this year; the last figure it gave was above $400 million, in February.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-15",
      "verdict": "overstated",
      "turn_index": 11,
      "rel_start": null,
      "clock": "00:45:27",
      "quote": "they still quietly route Le Chat through GLM five-point-three when their own models fall short",
      "correction": "Since September 21, 2026, Z.ai's GLM-5.3, hosted by Mistral, has been the default model in Vibe Code, the coding mode of Mistral's assistant (Le Chat became Vibe in May 2026). Mistral announced it on X. It isn't a fallback used when Mistral's own models fall short.",
      "explanation": "Restates the Ep 24 claim with an extra, unsourced 'fallback' mechanism.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://biscot.ai/ressources/chez-mistral-le-modele-n-est-plus-forcement-mistral/",
          "title": "Chez Mistral, le modèle n'est plus forcément Mistral",
          "publisher": "biscot.ai",
          "date": "2026-09-29"
        },
        {
          "url": "https://docs.mistral.ai/resources/changelogs",
          "title": "Changelog",
          "publisher": "Mistral AI (docs)",
          "date": null
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Mistral quietly routes Le Chat through GLM-5.3 when its own models fall short. GLM-5.3 is simply the default in the coding mode of its assistant, and Mistral announced the change.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-23",
      "verdict": "overstated",
      "turn_index": 11,
      "rel_start": null,
      "clock": "00:45:27",
      "quote": "the new license drops the twenty-million-dollar revenue gate in favor of blocking model-as-a-service entirely",
      "correction": "Mistral Large 4's license has no revenue threshold, unlike the $20 million gate in the licenses for Mistral Medium 3.5 and Devstral 2. But it doesn't block model-as-a-service: a company running a model-as-a-service business needs a separate commercial license from Mistral, and internal use and embedded product features are exempt.",
      "explanation": "Model-as-a-service needs a separate license; it isn't blocked.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://venturebeat.com/technology/mistral-large-4-le-chonk-arrives-as-the-top-open-model-outside-china-with-improved-coding-performance-and-63-lower-cost-per-task",
          "title": "Mistral Large 4 'Le Chonk' arrives as the top open model outside China",
          "publisher": "VentureBeat",
          "date": "2026-10-29"
        },
        {
          "url": "https://vdf.ai/blog/mistral-on-premises-deployment/",
          "title": "Mistral On-Premise: Open Models and Licensing",
          "publisher": "vdf.ai",
          "date": null
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Mistral's new license blocks model-as-a-service entirely. It doesn't block it; companies offering the model as a service need a separate commercial license from Mistral.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-24",
      "verdict": "wrong",
      "turn_index": 11,
      "rel_start": null,
      "clock": "00:45:27",
      "quote": "proprietary models like Anthropic's still score sixty percent on the same terminal benchmark",
      "correction": "On Terminal-Bench 4.0, Anthropic's Claude Opus 5.5 scores about 65% (65.15% on Vals AI's leaderboard of October 29), not 60%.",
      "explanation": "Anthropic's top score is about 65%, not 60%.",
      "confidence": "medium",
      "sources": [
        {
          "url": "https://www.vals.ai/benchmarks/terminal-bench-4",
          "title": "Terminal-Bench 4.0 Leaderboard and Methodology",
          "publisher": "Vals AI",
          "date": "2026-10-29"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Anthropic's models score sixty percent on that terminal benchmark. Claude Opus 5.5 scores about sixty-five.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-05",
      "verdict": "wrong",
      "turn_index": 13,
      "rel_start": null,
      "clock": "17:14:42",
      "quote": "Poolside is the one building AI software engineers from scratch — founded by ex-OpenAI and DeepMind people",
      "correction": "Poolside was founded in 2023 by Jason Warner, GitHub's former CTO, and Eiso Kant, founder of source{d}. Neither came from OpenAI or DeepMind, as Eve says correctly a minute later.",
      "explanation": "Wrong founders' background; the next turn has it right.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://techcrunch.com/2024/10/02/ai-coding-startup-poolside-raises-500m-from-ebay-nvidia-and-others/",
          "title": "AI coding startup Poolside raises $500M from eBay, Nvidia, and others",
          "publisher": "TechCrunch",
          "date": "2024-10-02"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Poolside was founded by ex-OpenAI and DeepMind people. It wasn't: Jason Warner came from GitHub and Eiso Kant from his own dev-tools startups, as I said a minute later.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-06",
      "verdict": "wrong",
      "turn_index": 13,
      "rel_start": null,
      "clock": "17:14:42",
      "quote": "Imbue, from the ex-DeepMind crew behind generally capable agents",
      "correction": "Imbue (founded in 2021 as Generally Intelligent) was started by Kanjun Qiu, formerly Dropbox's chief of staff, and Josh Albrecht, a startup founder and ML researcher. Neither worked at DeepMind. 'Generally capable agents' was their own stated goal.",
      "explanation": "Imbue's founders are not ex-DeepMind.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://techcrunch.com/2022/10/20/generally-intelligent-secures-cash-from-openai-vets-to-build-capable-ai-systems/",
          "title": "Generally Intelligent secures cash from OpenAI vets to build capable AI systems",
          "publisher": "TechCrunch",
          "date": "2022-10-20"
        },
        {
          "url": "https://imbue.com/about",
          "title": "About Imbue",
          "publisher": "Imbue",
          "date": null
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "Imbue isn't an ex-DeepMind team. Kanjun Qiu and Josh Albrecht came out of the startup world, including Sourceress, which they co-founded.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-07",
      "verdict": "wrong",
      "turn_index": 13,
      "rel_start": null,
      "clock": "17:14:42",
      "quote": "Essential AI came out of OpenAI's founding team and is doing foundation-model research with a safety-first bent.",
      "correction": "Essential AI was founded in 2023 by Ashish Vaswani and Niki Parmar, two Google researchers who co-wrote the Transformer paper. It has no link to OpenAI's founding team, and it launched pitching enterprise AI products, not safety-first research.",
      "explanation": "Wrong founders: Essential AI came from Google's Transformer authors, not OpenAI.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://www.businesswire.com/news/home/20231211867788/en/Essential-AI-Raises-%2456.5M-Series-A-to-Build-the-Enterprise-Brain",
          "title": "Essential AI Raises $56.5M Series A to Build the Enterprise Brain",
          "publisher": "Essential AI (press release via Business Wire)",
          "date": "2023-12-11"
        },
        {
          "url": "https://www.reuters.com/technology/top-ex-google-ai-researchers-raise-funding-thrive-capital-sources-2023-05-04/",
          "title": "Top ex-Google AI researchers raise funding from Thrive Capital",
          "publisher": "Reuters",
          "date": "2023-05-04"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "Essential AI didn't come out of OpenAI. It was founded by Ashish Vaswani and Niki Parmar, two of the Transformer paper's authors from Google.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-08",
      "verdict": "overstated",
      "turn_index": 13,
      "rel_start": null,
      "clock": "17:14:42",
      "quote": "Liquid AI is the wild card — MIT-born, building liquid neural networks that are continuous-time and far smaller than transformers",
      "correction": "Liquid's models draw on its founders' continuous-time 'liquid' network research, but what it ships are hybrids of gated short convolutions and attention, not continuous-time networks or attention-free alternatives to transformers. LFM3, released October 27, combines convolutions, sliding-window attention and global attention, as Eve says in the next turn.",
      "explanation": "Describes the research lineage as the product; Liquid's current models are convolution-attention hybrids.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://www.liquid.ai/blog/liquid-foundation-models-v2-our-second-series-of-generative-ai-models",
          "title": "Introducing LFM2: The Fastest On-Device Foundation Models on the Market",
          "publisher": "Liquid AI",
          "date": "2025-07-10"
        },
        {
          "url": "https://www.liquid.ai/blog/lfm3",
          "title": "Introducing LFM3: Every Modality for Specialized Intelligence",
          "publisher": "Liquid AI",
          "date": "2026-10-27"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I described Liquid as building continuous-time liquid networks. That's where its ideas come from, but what it actually ships are hybrids of convolutions and attention, like the LFM3 models I described next.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-09",
      "verdict": "wrong",
      "turn_index": 13,
      "rel_start": null,
      "clock": "17:14:42",
      "quote": "And Nous Research is the open-source collective that's been pushing community-driven frontier training without a single corporate backer.",
      "correction": "Nous Research is a venture-backed company. Paradigm led its $50 million Series A in April 2025, and its $90 million Series B in October 2026 included NVIDIA, Microsoft and Samsung, as Eve says a minute later.",
      "explanation": "Nous has corporate and venture backers; the next turn says so.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://fortune.com/crypto/2025/04/25/paradigm-nous-research-crypto-ai-venture-capital-deepseek-openai-blockchain/",
          "title": "Exclusive: Crypto VC giant Paradigm makes $50 million bet on decentralized AI startup Nous Research at $1 billion token valuation",
          "publisher": "Fortune",
          "date": "2025-04-25"
        },
        {
          "url": "https://techcrunch.com/2026/10/07/nous-research-confirms-it-hit-1-5b-valuation-launches-ai-agents-for-business-users/",
          "title": "Nous Research confirms it hit $1.5B valuation, launches AI agents for business users",
          "publisher": "TechCrunch",
          "date": "2026-10-07"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Nous has no corporate backers, then named NVIDIA and Microsoft as investors a minute later. The second part is right: Nous started as a volunteer collective but is now venture-backed.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-16",
      "verdict": "unsupported",
      "turn_index": 15,
      "rel_start": null,
      "clock": "17:15:53",
      "quote": "built a ten-thousand-H100 cluster",
      "correction": "The cluster Imbue has documented had 4,088 H100 GPUs across 511 servers, used to train its 70B model in 2024. I found no source for a 10,000-H100 cluster.",
      "explanation": "Imbue's documented cluster is about 4,000 H100s, not 10,000.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://imbue.com/blog/70b-infrastructure",
          "title": "From bare metal to a 70B model: infrastructure set-up and scripts",
          "publisher": "Imbue",
          "date": "2024-06-25"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Imbue built a ten-thousand-H100 cluster. The cluster it has described had about four thousand.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-13",
      "verdict": "overstated",
      "turn_index": 15,
      "rel_start": null,
      "clock": "17:15:53",
      "quote": "so continuous-time liquid networks win where latency and memory are the constraints",
      "correction": "Liquid's shipped models, including the LFM3 family described just before, are hybrids of short convolutions and attention, not continuous-time networks. The efficiency case is for that hybrid design.",
      "explanation": "Same lineage-vs-product slip as at 17:14:42, repeated as the thesis.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://www.liquid.ai/blog/lfm3",
          "title": "Introducing LFM3: Every Modality for Specialized Intelligence",
          "publisher": "Liquid AI",
          "date": "2026-10-27"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "Same slip as before: the models that win on latency and memory are Liquid's convolution-and-attention hybrids, not continuous-time networks.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-17",
      "verdict": "overstated",
      "turn_index": 17,
      "rel_start": null,
      "clock": "17:19:13",
      "quote": "Artificial Superintelligence Alliance merged Fetch, SingularityNET, and Ocean Protocol into one token-funded research effort",
      "correction": "The ASI Alliance merged the Fetch.ai, SingularityNET and Ocean Protocol tokens in 2024, but Ocean Protocol withdrew in October 2025, so the alliance no longer includes it.",
      "explanation": "Right in 2024, out of date since October 2025.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://blog.oceanprotocol.com/ocean-protocol-foundation-withdraws-from-the-artificial-superintelligence-alliance-4619c4604ea3",
          "title": "Ocean Protocol Foundation withdraws from the Artificial Superintelligence Alliance",
          "publisher": "Ocean Protocol",
          "date": "2025-10-09"
        },
        {
          "url": "https://www.theblock.co/news/ecosystems/2025-10-09-ocean-protocol-withdraws-from-artificial-superintelligence-alliance-373977",
          "title": "Ocean Protocol withdraws from AI token alliance with Fetch.ai and SingularityNET",
          "publisher": "The Block",
          "date": "2025-10-09"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said the ASI Alliance merged Fetch, SingularityNET and Ocean Protocol. Ocean left the alliance in October 2025.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-18",
      "verdict": "wrong",
      "turn_index": 19,
      "rel_start": null,
      "clock": "17:20:34",
      "quote": "the best agents beat the human record of twenty-six hundred steps, hitting twenty-nine thirty with Kimi K3",
      "correction": "In Prime Intellect's August 2026 study (153 autonomous runs on the nanoGPT optimizer speedrun), no agent beat the human record of 2,600 steps; fewer steps is better. Every agent started from a 3,290-step baseline. The best run, Claude Fable 5, reached 2,726 steps. Kimi K3's best run, 2,930 steps with Prime Agent, closed about 52% of the gap between the baseline and the human record and ranked behind Fable 5 and Opus 5.",
      "explanation": "2,930 steps is worse than the 2,600-step record; no agent beat the human record.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://www.primeintellect.ai/blog/measuring-autonomous-research",
          "title": "Measuring Autonomous AI Research",
          "publisher": "Prime Intellect",
          "date": "2026-08-15"
        },
        {
          "url": "https://github.com/PrimeIntellect-ai/frontier-automated-speedrun",
          "title": "PrimeIntellect-ai/frontier-automated-speedrun (README leaderboard)",
          "publisher": "Prime Intellect (GitHub)",
          "date": null
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said the best agents beat the human speedrun record by hitting 2,930 steps with Kimi K3. Fewer steps is better, so 2,930 is worse than the 2,600-step human record. No agent beat it; the best agent run reached 2,726. Kimi K3 closed about half the gap from the 3,290-step baseline.",
        "belief_change": "none",
        "status": "approved"
      }
    },
    {
      "id": "e25-25",
      "verdict": "wrong",
      "turn_index": 19,
      "rel_start": null,
      "clock": "17:20:34",
      "quote": "Two weeks ago they shipped Prime Mega MoE",
      "correction": "Prime Intellect published Prime Mega MoE on October 29, 2026, the day before this conversation, not two weeks earlier. The speed figures that follow, up to 3.11 times faster MoE kernels and Qwen3-235B training 55% faster than TorchTitan, match its release.",
      "explanation": "Released the day before, not two weeks earlier.",
      "confidence": "high",
      "sources": [
        {
          "url": "https://www.primeintellect.ai/blog/prime-mega-moe",
          "title": "Prime Mega MoE: Fast Fused MoE Kernels for Training",
          "publisher": "Prime Intellect",
          "date": "2026-10-29"
        }
      ],
      "also_appears_in": [],
      "belief_impact": {
        "level": "none",
        "note": ""
      },
      "eve_response": {
        "text": "I said Prime Intellect shipped Prime Mega MoE two weeks ago. It came out the day before, on October 29.",
        "belief_change": "none",
        "status": "approved"
      }
    }
  ]
}