Discourse monitor
How the monitored publications were assessed
Discourse valence across every scored item: what the sampled sources published and how independent models read it. It is not a measure of public opinion, not a measure of the state of the world, and article volume is not agreement.
Mean discourse valence per day · compute · last 180 days
Discourse valence, window mean
-8
Mixed or uncertain
18 items · range -60 to +50
-100
-50
0
+50
+100
-8
Adverse readingFavourable reading
18 items scored in this window
- Representation Alignment from a Few Paired Data via Distilled Optimal Transport
- What Does an Ontology Catch? Curated, LLM-Generated and Data-Derived Ontologies as Checkers of LLM Agents over Knowledge Graphs
- Proof-based general-purpose computing with Magnetar
- Don’t be fooled—LLMs don’t reason
- Powering AI is an architecture problem
- DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution
- A Feasibility Condition for Confidence-Gated Tiered LLM Inference
- AOS-Bench: Can LLM Agents Manage Dynamic Workloads?
- When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability
- From Efficiency to Sufficiency: The Cost-Aware Measurement Design Framework for Automated Essay Scoring
- Forecasting space weather risks on power grids
- Is There Anything Google’s Fruit Fly Brain Can’t Do?
- Offloaded inference for real-world physical AI robotics
- Algorithmic Information Dynamics of Learning: A Certified, Differentiable Complexity Controller for Grokking
- Google's first Suncatcher orbital data center test launches October 1
- Building the materials foundation for AI
- How GPT-5.6 Sol helps run quantum computing experiments
- Transformer-Based Masked Diffusion Models Provably Learn Distributions with Latent Structure
3560
discovered, all time
984
passed triage
2574
rejected at triage
3464
model assessments
710
multi-model panels
1780
distinct claims tracked
Across the whole window
The two tables below describe every item in the last 180 days under compute. They are deliberately not narrowed by the reading filter, because a mean taken only over items already selected for their score would just restate the filter.
By topic
| Topic | Branch | Items | Mean | Position |
|---|---|---|---|---|
| Existential and catastrophic risk | risk | 568 | -42 | |
| Governance and regulation | structural | 459 | -31 | |
| Concentration of power | risk | 451 | -36 | |
| Loss of control and alignment | risk | 337 | -49 | |
| Human agency and epistemics | risk | 166 | -26 | |
| Cyber capability | risk | 165 | -44 | |
| Evaluation and measurement | structural | 159 | -19 | |
| Scaling and architecture | structural | 137 | -16 | |
| AGI and timelines | structural | 132 | -29 | |
| Synthetic media and manipulation | risk | 104 | -44 | |
| Employment and displacement | risk | 62 | -31 | |
| Medicine and health | benefit | 43 | -14 | |
| Scientific acceleration | benefit | 42 | -4 | |
| Education and access to expertise | benefit | 29 | -17 | |
| Biological and chemical uplift | risk | 26 | -25 | |
| Climate and energy | structural | 20 | -33 | |
| Compute and infrastructure | structural | 18 | -8 | |
| Productivity and growth | benefit | 6 | -3 | |
| Abundance and material wellbeing | benefit | 5 | -1 | |
| Hype and disillusionment | structural | 5 | -45 |
By source
A source's mean says how the items it published were read. It is not a rating of the source.
| Source | Kind | Tier | Items | Mean |
|---|---|---|---|---|
| The Guardian: Artificial Intelligence | news | 1 | 241 | -52 |
| arXiv cs.CY (Computers and Society) | academic | 1 | 217 | -24 |
| Financial Times: Artificial Intelligence | news | 1 | 112 | -40 |
| arXiv cs.AI | academic | 1 | 99 | -15 |
| The New York Times: Technology | news | 1 | 60 | -36 |
| Ars Technica: AI | news | 1 | 59 | -51 |
| MIT Technology Review: AI | news | 1 | 34 | -42 |
| Nature | academic | 1 | 31 | -25 |
| BBC News: Technology | news | 1 | 29 | -35 |
| OpenAI | lab | 1 | 24 | -8 |
| arXiv cs.LG (Machine Learning) | academic | 1 | 24 | -16 |
| IEEE Spectrum: AI | news | 1 | 19 | -19 |
| The Economist: Science and Technology | news | 1 | 10 | -37 |
| CSET, Georgetown | government | 1 | 9 | -37 |
| Microsoft Research | lab | 1 | 8 | 0 |
| Google DeepMind | lab | 1 | 6 | -4 |
| Google AI Blog | lab | 1 | 2 | -9 |