Briefs
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COP31 Sets a 35% Electrification Goal
COP31 wants electricity to supply 35% of final energy consumption by 2035. Grids and equipment must follow.
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The COP31 Presidency announced a Global Electrification Pledge on November 10 to raise electricity’s share of final energy consumption to 35% by 2035, from around 23% today. Final energy is the energy delivered to users such as households, businesses and factories. The target concerns replacing direct fuel use in transport, buildings and industry with electricity. It is not a target for renewables’ share of electricity generation.
The Presidency also announced an ongoing Electrification Forum, with the International Energy Agency tracking global and regional progress. An IRENA program will help developing countries identify distribution-grid investment needs, prepare projects and access finance. These measures address the infrastructure needed alongside electric vehicles, heating and industrial equipment.
The announcement establishes a goal and supporting initiatives, not an achieved shift in energy use. It does not demonstrate delivered investment, lower bills or emissions cuts; those depend on implementation and how the additional electricity is generated.
COP31 Presidency · Global Electrification Pledge · Source and announcement: .
First published: .
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AI Labs Sign Paris Safety Commitments
Ten AI firms pledge safeguards to pause systems they control. This does not prove models are safer.
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Eight governments and ten AI companies signed the Paris Call for AI Safety and Security on November 9, according to the declaration published by France’s presidency. The company signatories include Anthropic, Microsoft, Mistral AI and OpenAI. They support a common approach to evaluating AI risks, shared technical standards and publication of nonsensitive findings.
Developers commit to safeguards that can restrict, pause or shut down model operations within their control, including training and internal use. They also promise to disclose capabilities, limitations and known risks, and support qualified independent evaluation where appropriate and proportionate to the risk. The shutdown commitment does not extend to every third-party copy of an AI model.
The declaration also calls for incident reporting and early warning, while leaving the possible scope of a further cooperation mechanism to be explored. Signing is not evidence that models have become safer or that the safeguards have been demonstrated to work. The text specifies no common implementation deadline or sanctions.
Élysée · Paris Call for AI Safety and Security · Source and announcement: .
First published: .
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Anthropic Releases Fable 5.2 With Separate Mythos Access
Claude Fable 5.2 is now available. Direct access to Mythos 5.2 still requires a verification program.
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Anthropic announced Claude Fable 5.2 and Claude Mythos 5.2 on November 9. The company describes them as the same underlying model, with Fable adding safeguards for cybersecurity and biology. That is Anthropic’s description of the design, not independent proof that the safeguards prevent misuse.
Fable 5.2 is available across Anthropic’s platforms and through AWS, Google Cloud and Microsoft Azure, according to the announcement. Organizations and professionals seeking direct access to Mythos 5.2 can apply through Anthropic’s Cyber Verification or Life Sciences Verification programs. Applying does not itself guarantee approval.
The distinction is between direct model access and use through a separate product. Claude Enterprise customers can use Claude Security, which includes Mythos 5.2, without joining the Cyber Verification Program. Readers should therefore check which model and access route a product offers, rather than assume both releases are equally open. The announcement alone does not establish a general improvement in reliability, security or scientific results.
Anthropic: Claude Fable 5.2 and Claude Mythos 5.2 · November 9, 2026
Source and launch: . First published: .
Zolgensma Safety Review Continues
Cure SMA reports two treatment-linked tumor cases after Zolgensma. The wider risk remains unquantified.
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Updated November 10, 2026. Cure SMA says tumors from three of the nine reported cases have been tested: two were found to be related to Zolgensma treatment, while one appears unrelated. This is the patient organization’s account, not a finding that all nine tumors were caused by treatment. The wider treatment-related risk remains unquantified.
Cure SMA also reports that a November 6 FDA update confirmed an investigation and consideration of further action. According to Cure SMA, the FDA continues to find that the treatment’s benefits outweigh its potential risks and recommends monitoring recipients for tumors. This account is attributed to Cure SMA; the earlier company statement and background below remain part of the record.
Novartis says it has received nine reports of tumors in people previously treated with Zolgensma since the gene therapy’s first approval in 2019. The treatment is used for spinal muscular atrophy, an inherited disease that damages the nerve cells controlling muscles. A November 5 company statement shared by SMA Europe says health authorities were notified in each case.
The statement says two cases showed evidence that DNA delivered by the therapy had integrated into the patients’ DNA. That is not a regulatory finding that Zolgensma caused all nine tumors. Patient organizations say regulators are reviewing the reports; the public statements do not provide a complete case-by-case assessment or establish the size of the treatment-related risk.
The company says more than 6,000 patients have received the therapy across different access programs. Dividing the nine reports by that total would not produce a reliable incidence estimate: the statements do not give comparable follow-up time or show that every case has been captured. These are safety reports under review, not an instruction to change an individual patient’s care.
Novartis statement shared by SMA Europe · November 5, 2026 · Cure SMA community update · November 5, 2026 · EMA medicine overview · SMA background
First published: .
Updated: , with Cure SMA’s account of the tested cases and the FDA’s November 6 update.
Charts
Global Lifespan Recovered More Than Healthy Life Expectancy
WHO modeled estimates · World, both sexes · 2000–2023
Expected years at birth. Shaded bands show the original uncertainty ranges.
Healthy life expectancy weights years by health and disability severity, rather than counting only illness-free years.
By 2023, the point estimates were 0.1 and 0.4 years below 2019. This comparison does not establish a statistically significant difference in recovery.
Longer life and better health do not necessarily recover together. In WHO’s estimates, global life expectancy was almost back to its 2019 level by 2023. Healthy life expectancy remained further below its earlier level. Both measures had risen over the longer period shown.
The distinction is about population estimates, not the age at which one person becomes ill. A year lived with impaired health contributes less than a full healthy-equivalent year to the second measure.
More Detail, Sources and Data
Two Measures, Not Two Stages of a Life
Period life expectancy applies the mortality conditions of a given year across a hypothetical lifetime. It is not a prediction of the actual lifespan of babies born that year. Healthy life expectancy, or HALE, adjusts years lived for the severity of health loss. The gap between the measures is not a block of healthy years followed by a block of sick years.
Read the Estimates With Their Uncertainty
The lines use the same zero-to-80-year scale and show every annual point from 2000 through 2023. The bands preserve WHO’s published lower and upper bounds for each year. For 2023, life expectancy is 73.3 years [70.7–75.8] and healthy life expectancy is 62.8 years [57.9–67.4]. These are marginal uncertainty ranges, not uncertainty intervals for a change between years.
Vastkind compares the published point estimates. It does not reconstruct WHO’s population model or test whether the two recovery paths differ statistically. Overlapping ranges do not prove equality, and the point differences do not prove a significant difference. The chart does not identify the cause of the changes or measure the effect of any treatment.
| Year | Life Expectancy [Range] | Healthy Life Expectancy [Range] |
|---|---|---|
| 2000 | 67.1 [65.4–68.6] | 57.9 [54.0–61.4] |
| 2001 | 67.4 [65.8–69.0] | 58.2 [54.3–61.7] |
| 2002 | 67.7 [66.1–69.3] | 58.4 [54.6–62.0] |
| 2003 | 68.0 [66.4–69.6] | 58.7 [54.9–62.3] |
| 2004 | 68.4 [66.8–70.0] | 59.0 [55.1–62.6] |
| 2005 | 68.9 [67.3–70.4] | 59.4 [55.5–63.0] |
| 2006 | 69.4 [67.9–70.9] | 59.9 [56.0–63.4] |
| 2007 | 69.9 [68.3–71.4] | 60.2 [56.3–63.8] |
| 2008 | 70.2 [68.6–71.7] | 60.5 [56.6–64.1] |
| 2009 | 70.6 [69.1–72.1] | 60.9 [56.9–64.4] |
| 2010 | 71.0 [69.5–72.4] | 61.1 [57.2–64.7] |
| 2011 | 71.3 [69.8–72.7] | 61.4 [57.5–65.0] |
| 2012 | 71.7 [70.3–73.1] | 61.7 [57.8–65.3] |
| 2013 | 72.1 [70.7–73.4] | 62.0 [58.1–65.6] |
| 2014 | 72.3 [71.0–73.6] | 62.2 [58.3–65.7] |
| 2015 | 72.5 [71.1–73.8] | 62.3 [58.4–65.9] |
| 2016 | 72.7 [71.3–74.0] | 62.5 [58.6–66.1] |
| 2017 | 72.9 [71.6–74.2] | 62.7 [58.8–66.3] |
| 2018 | 73.2 [71.9–74.4] | 63.0 [59.1–66.5] |
| 2019 | 73.4 [72.1–74.5] | 63.2 [59.3–66.6] |
| 2020 | 72.7 [71.7–73.7] | 62.4 [58.7–65.8] |
| 2021 | 71.5 [70.2–72.7] | 61.4 [57.5–64.9] |
| 2022 | 72.7 [70.5–74.8] | 62.3 [57.7–66.5] |
| 2023 | 73.3 [70.7–75.8] | 62.8 [57.9–67.4] |
Original Data and Reuse
WHO, Global Health Estimates 2000–2023; Global Health Observatory indicators WHOSIS_000001 (life expectancy at birth) and WHOSIS_000002 (healthy life expectancy at birth), GLOBAL, both sexes. Both series carry the October 1, 2026 revision stamp; accessed November 7, 2026. We acknowledge the countries supplying the underlying national data, as described in WHO’s methods linked from the source page. These are global estimates, not an unweighted average of country values.
All 24 annual values and their original bounds are displayed for each indicator. Differences of 0.1 and 0.4 years are simple subtraction of the published 2019 and 2023 point estimates. The data period ends in 2023, not in the year of this chart’s publication.
Copyright remains with WHO. This editorial public-health display follows the WHO dataset terms; no unrestricted open-data license or WHO endorsement is claimed. No WHO emblem is used.
Expected years at birth · 2000–2023
Batteries Supplied 15% of California’s Evening Grid Demand
2025 reported averages · Report-defined western regions
Share of each region’s electricity demand during hours ending 18–22 (five hourly intervals).
Operator-reported battery schedules, not a guarantee of supply on every evening. Percentages use different regional demand totals.
Batteries already supply a meaningful part of evening electricity demand in parts of the western grid. The California group has the largest reported share in this comparison, followed by the Desert Southwest. These are shares of the electricity each region needs, not rankings of battery size or total electricity delivered.
That distinction matters: installing a battery and using it to meet demand are different measures. This comparison captures batteries’ reported role during the evening window, when California ISO says net demand is highest. It does not show where their charging electricity came from.
More Detail, Sources and Data
What the Percentages Measure
California ISO’s Department of Market Monitoring reports these four averages together on pages 3 and 16 of its 2025 Special Report on Battery Storage. Each value expresses reported battery supply as a share of the load, or electricity demand, of that report-defined region during hours ending 18 through 22 in 2025. The source discusses the figures in its five-minute-market battery-schedules section. These are published operator aggregates, not a new Vastkind calculation from raw meter readings.
The window contains five hourly intervals, not four hours from 18:00 to 22:00. The share passage does not specify a clock timezone or its precise averaging weights, so we retain the source’s hour-ending labels rather than translate them into local-clock times.
| Report Region | Share |
|---|---|
| California | 15% |
| Desert Southwest | 11% |
| Intermountain West | 3% |
| Pacific Northwest | 1% |
Comparable Shares, Different Regional Totals
All bars start at zero and use the same 0–20% scale. Vastkind transcribed the published whole-percentage values, checked both source passages and drew this comparison. No additional precision is inferred. The shares cannot be summed into a western-grid total or averaged without the underlying regional demand totals.
A larger share does not necessarily mean more electricity delivered in absolute terms. The comparison does not establish lower bills, avoided emissions, policy effects or reliable supply on every evening. The report discusses hybrid resources separately; the share passage does not establish complete coverage of every hybrid battery.
The Report’s Four Regional Groups
These are the report’s balancing-area groups on page 9, not a new Vastkind grouping of entire states. A balancing area is a part of the power system managed to keep electricity supply and demand in balance.
- California: California ISO; Balancing Authority of Northern California; Los Angeles Department of Water and Power; Turlock Irrigation District.
- Desert Southwest: Arizona Public Service; El Paso Electric; NV Energy; Public Service Company of New Mexico; Salt River Project; Tucson Electric; WAPA-Desert Southwest.
- Intermountain West: Avista Corporation; Idaho Power Company; NorthWestern Energy; PacifiCorp East.
- Pacific Northwest: Avangrid Power; Bonneville Power Administration; PacifiCorp West; Portland General Electric; Powerex; Puget Sound Energy; Seattle City Light; Tacoma Power.
Source, Dates and Reuse
California ISO, Department of Market Monitoring, 2025 Special Report on Battery Storage, pages 3 and 16 (values), page 9 (regions). The document is dated October 28, 2026; its official posting notice is dated October 30. The measurements describe 2025, not today’s grid.
Original factual comparison by Vastkind. Source: California Independent System Operator; copyright and other proprietary rights remain with their respective owners. Reuse follows CAISO’s public-information terms; no Creative Commons or public-domain status is claimed. No CAISO artwork or logo is copied.
Hours ending 18–22 (five hourly intervals)
Servers Take 56% of This AI Data Center’s Upfront Budget
Hypothetical U.S. site · 1 GW of IT capacity · May 2026 model
Share of an estimated $37.9 billion initial investment. GB200 NVL72 hardware, not an actual project’s bill.
Initial purchases and construction only, not annual operating costs. Hardware and construction inputs include 2025 estimates.
The computers cost more than everything else put together. In Epoch AI’s hypothetical U.S. AI data center, servers account for about $21.2 billion of the $37.9 billion initial investment. The facility, cooling, other IT equipment, land and utility works make up the rest.
This explains why a data center’s headline construction budget may describe only part of the investment. A building and its cooling systems are not the same purchase as a fully equipped AI computing site.
This is a model, not an average of real projects or a current price quote. It uses NVIDIA GB200 NVL72 systems and one gigawatt of rated IT capacity. That describes the computing equipment’s power rating, not the site’s electricity use over a year.
Updated explainer, November 3: For the separate question of energy needed to run a model, our Extropic analysis explains why a projected chip-energy saving is not yet a whole-task result.
More Detail, Sources and Data
What the Budget Includes
“Facility & Cooling” is Epoch’s facility category, including its liquid-cooling cost adjustment. “Networking & Other IT” is the source’s network-infrastructure category: a proxy for the cluster’s non-server investment, including networking, storage, service, software and installation. Land and utility works are separate inputs. A small budget share does not establish that land or a grid connection is easy to obtain.
| Component | USD Millions | Share |
|---|---|---|
| Servers | 21,188 | 55.9% |
| Facility & Cooling | 11,433 | 30.2% |
| Networking & Other IT | 4,925 | 13.0% |
| Land | 172 | 0.5% |
| Utility Works | 164 | 0.4% |
| Reported Total | 37,883 | 100% |
How We Calculated the Shares
Vastkind divided each component in Epoch’s upfront-investment CSV by its reported total of $37,883 million, then multiplied by 100. Bars start at zero and use unrounded shares; labels show one decimal place. The title rounds the server share, 55.93%, to 56%.
The individually rounded components add to $37,882 million, $1 million below the rounded total. The underlying model workbook totals approximately $37,882.5 million. This rounding difference does not change the displayed shares.
A Model of Purchases, Not Annual Spending
Epoch published the analysis on May 14, 2026; its upfront chart data were updated May 19. Hardware and construction assumptions include 2025 estimates. The model uses GB200 NVL72 systems and a hypothetical U.S. hyperscale site with 1 GW of rated IT capacity, powered entirely from the grid. It is not a November 2026 supplier quote, a measured industry average or a forecast for every future AI facility.
These are initial capital costs. Electricity bills and other operating expenses belong to a different comparison. Epoch’s separate annualized-cost analysis accounts for recurring costs and different asset lifetimes; its percentages must not be mixed with these upfront shares.
For the separate question of what a large chip count can enable, see our explanation of Colossus 2’s expansion plans. This chart does not estimate that project’s budget.
Data and model: Amelia Michael and Ben Cottier, Epoch AI, AI Data Center Cost Breakdown, reused with attribution under CC BY 4.0. Vastkind calculated the shares, clarified category labels and created this chart; no source graphic was copied.
Share of $37.9bn upfront cost · GB200 NVL72
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