Scored 205 articles from 151 feeds; 15 included in digest.
Run ID: run-1792136867794
Generated: October 16, 2026 at 03:52 AM ET
Summaries: gemini-flash-lite-latest; enrichment 15/15 succeeded
| Source | Type | Included | Scored | 28d Digest Rate | 28d Avg Score | 28d Hotlist Hit | 7d Article Age | 28d Confidence |
|---|---|---|---|---|---|---|---|---|
| Bloomberg Markets | news | 1 | 10 | 2% | 0.02 | 0% | 4.3h | Stable |
| Guardian | news | 1 | 10 | 10% | 0.17 | 0% | 10.7h | Stable |
| Hacker News | commentary | 1 | 10 | 10% | 0.26 | 0% | 1.5d | Stable |
| Medium Artificial Intelligence (keyword) | commentary | 1 | 10 | 7% | 0.11 | 0% | 0.8h | Stable |
| Reddit AI Wars | news | 1 | 10 | ~9% | ~0.15 | ~0% | 10.3h | Low sample |
| arXiv CompSci CL | research | 1 | 10 | ~6% | ~0.09 | ~0% | 3.8h | Low sample |
| arXiv CompSci ML | research | 1 | 10 | ~6% | ~0.09 | ~0% | 3.8h | Low sample |
| Ars Technical All News | news | 1 | 9 | 13% | 0.13 | 0% | 8.4h | Stable |
| TechCrunch | news | 1 | 8 | 9% | 0.11 | 0% | 6.2h | Stable |
| The Verge | news | 1 | 8 | 12% | 0.15 | 0% | 8.1h | Stable |
| The Atlantic | news | 1 | 6 | 11% | 0.13 | 0% | 8.0h | Stable |
| Atlas Obscura | commentary | 1 | 1 | ~43% | ~0.66 | ~0% | 7.4h | Low sample |
| El Reg Offbeat | news | 1 | 1 | Collecting data | Collecting data | Collecting data | 7.8h | Collecting |
| Futurism | news | 1 | 1 | 12% | 0.17 | 0% | 5.7h | Stable |
| Silver Bulletin | commentary | 1 | 1 | Collecting data | Collecting data | Collecting data | 2.6h | Collecting |
| Bogleheads forum | news | 0 | 10 | 5% | 0.05 | 0% | 0.9h | Stable |
| MyFT | news | 0 | 10 | 6% | 0.05 | 0% | 4.3h | Stable |
| NYT front page | news | 0 | 10 | 6% | 0.06 | 0% | 7.3h | Stable |
| WSJ US Business | news | 0 | 10 | 5% | 0.05 | 0% | 9.7h | Stable |
| Zero Hedge | commentary | 0 | 10 | 2% | 0.01 | 0% | 8.4h | Stable |
| Medium AI (keyword) | commentary | 0 | 8 | 8% | 0.10 | 0% | 0.8h | Stable |
| WSJ Tech | news | 0 | 8 | 7% | 0.07 | 0% | 8.9h | Stable |
| Seeking Alpha News | commentary | 0 | 7 | 2% | 0.01 | 0% | 1.3h | Stable |
| India Times | news | 0 | 6 | 0% | 0.00 | 0% | 3.6h | Stable |
| WSJ Social Economy | news | 0 | 3 | 3% | 0.01 | 0% | 6.9h | Stable |
| FT Alphaville | news | 0 | 2 | ~10% | ~0.10 | ~0% | 5.2h | Low sample |
| Hugging Face | commentary | 0 | 2 | Collecting data | Collecting data | Collecting data | 3.7h | Collecting |
| MIT AI Research | research | 0 | 2 | Collecting data | Collecting data | Collecting data | 5.0h | Collecting |
| Reddit R/Ethereum | news | 0 | 2 | ~9% | ~0.07 | ~0% | 2.7h | Low sample |
| Reddit R/FuturesTrading | news | 0 | 2 | ~2% | ~0.02 | ~0% | 10.2h | Low sample |
| Wired AI News | news | 0 | 2 | ~16% | ~0.19 | ~0% | 9.4h | Low sample |
| AI Daily Brief YT podcast | commentary | 0 | 1 | Collecting data | Collecting data | Collecting data | 9.7h | Collecting |
| Closing Line Substack | news | 0 | 1 | Collecting data | Collecting data | Collecting data | 8.5h | Collecting |
| Daring Fireball | commentary | 0 | 1 | ~24% | ~0.20 | ~0% | 3.9h | Low sample |
| Debt Serious | commentary | 0 | 1 | Collecting data | Collecting data | Collecting data | 2.5h | Collecting |
| Latent Space | commentary | 0 | 1 | Collecting data | Collecting data | Collecting data | 7.6h | Collecting |
| The Onion | news | 0 | 1 | ~24% | ~0.46 | ~0% | 6.9h | Low sample |
Source: Bloomberg Markets
Type: news
Included: 1
Scored: 10
28d Digest Rate: 2%
28d Avg Score: 0.02
28d Hotlist Hit: 0%
7d Article Age: 4.3h
28d Confidence: Stable
Source: Guardian
Type: news
Included: 1
Scored: 10
28d Digest Rate: 10%
28d Avg Score: 0.17
28d Hotlist Hit: 0%
7d Article Age: 10.7h
28d Confidence: Stable
Source: Hacker News
Type: commentary
Included: 1
Scored: 10
28d Digest Rate: 10%
28d Avg Score: 0.26
28d Hotlist Hit: 0%
7d Article Age: 1.5d
28d Confidence: Stable
Source: Medium Artificial Intelligence (keyword)
Type: commentary
Included: 1
Scored: 10
28d Digest Rate: 7%
28d Avg Score: 0.11
28d Hotlist Hit: 0%
7d Article Age: 0.8h
28d Confidence: Stable
Source: Reddit AI Wars
Type: news
Included: 1
Scored: 10
28d Digest Rate: ~9%
28d Avg Score: ~0.15
28d Hotlist Hit: ~0%
7d Article Age: 10.3h
28d Confidence: Low sample
Source: arXiv CompSci CL
Type: research
Included: 1
Scored: 10
28d Digest Rate: ~6%
28d Avg Score: ~0.09
28d Hotlist Hit: ~0%
7d Article Age: 3.8h
28d Confidence: Low sample
Source: arXiv CompSci ML
Type: research
Included: 1
Scored: 10
28d Digest Rate: ~6%
28d Avg Score: ~0.09
28d Hotlist Hit: ~0%
7d Article Age: 3.8h
28d Confidence: Low sample
Source: Ars Technical All News
Type: news
Included: 1
Scored: 9
28d Digest Rate: 13%
28d Avg Score: 0.13
28d Hotlist Hit: 0%
7d Article Age: 8.4h
28d Confidence: Stable
Source: TechCrunch
Type: news
Included: 1
Scored: 8
28d Digest Rate: 9%
28d Avg Score: 0.11
28d Hotlist Hit: 0%
7d Article Age: 6.2h
28d Confidence: Stable
Source: The Verge
Type: news
Included: 1
Scored: 8
28d Digest Rate: 12%
28d Avg Score: 0.15
28d Hotlist Hit: 0%
7d Article Age: 8.1h
28d Confidence: Stable
Source: The Atlantic
Type: news
Included: 1
Scored: 6
28d Digest Rate: 11%
28d Avg Score: 0.13
28d Hotlist Hit: 0%
7d Article Age: 8.0h
28d Confidence: Stable
Source: Atlas Obscura
Type: commentary
Included: 1
Scored: 1
28d Digest Rate: ~43%
28d Avg Score: ~0.66
28d Hotlist Hit: ~0%
7d Article Age: 7.4h
28d Confidence: Low sample
Source: El Reg Offbeat
Type: news
Included: 1
Scored: 1
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 7.8h
28d Confidence: Collecting
Source: Futurism
Type: news
Included: 1
Scored: 1
28d Digest Rate: 12%
28d Avg Score: 0.17
28d Hotlist Hit: 0%
7d Article Age: 5.7h
28d Confidence: Stable
Source: Silver Bulletin
Type: commentary
Included: 1
Scored: 1
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 2.6h
28d Confidence: Collecting
Source: Bogleheads forum
Type: news
Included: 0
Scored: 10
28d Digest Rate: 5%
28d Avg Score: 0.05
28d Hotlist Hit: 0%
7d Article Age: 0.9h
28d Confidence: Stable
Source: MyFT
Type: news
Included: 0
Scored: 10
28d Digest Rate: 6%
28d Avg Score: 0.05
28d Hotlist Hit: 0%
7d Article Age: 4.3h
28d Confidence: Stable
Source: NYT front page
Type: news
Included: 0
Scored: 10
28d Digest Rate: 6%
28d Avg Score: 0.06
28d Hotlist Hit: 0%
7d Article Age: 7.3h
28d Confidence: Stable
Source: WSJ US Business
Type: news
Included: 0
Scored: 10
28d Digest Rate: 5%
28d Avg Score: 0.05
28d Hotlist Hit: 0%
7d Article Age: 9.7h
28d Confidence: Stable
Source: Zero Hedge
Type: commentary
Included: 0
Scored: 10
28d Digest Rate: 2%
28d Avg Score: 0.01
28d Hotlist Hit: 0%
7d Article Age: 8.4h
28d Confidence: Stable
Source: Medium AI (keyword)
Type: commentary
Included: 0
Scored: 8
28d Digest Rate: 8%
28d Avg Score: 0.10
28d Hotlist Hit: 0%
7d Article Age: 0.8h
28d Confidence: Stable
Source: WSJ Tech
Type: news
Included: 0
Scored: 8
28d Digest Rate: 7%
28d Avg Score: 0.07
28d Hotlist Hit: 0%
7d Article Age: 8.9h
28d Confidence: Stable
Source: Seeking Alpha News
Type: commentary
Included: 0
Scored: 7
28d Digest Rate: 2%
28d Avg Score: 0.01
28d Hotlist Hit: 0%
7d Article Age: 1.3h
28d Confidence: Stable
Source: India Times
Type: news
Included: 0
Scored: 6
28d Digest Rate: 0%
28d Avg Score: 0.00
28d Hotlist Hit: 0%
7d Article Age: 3.6h
28d Confidence: Stable
Source: WSJ Social Economy
Type: news
Included: 0
Scored: 3
28d Digest Rate: 3%
28d Avg Score: 0.01
28d Hotlist Hit: 0%
7d Article Age: 6.9h
28d Confidence: Stable
Source: FT Alphaville
Type: news
Included: 0
Scored: 2
28d Digest Rate: ~10%
28d Avg Score: ~0.10
28d Hotlist Hit: ~0%
7d Article Age: 5.2h
28d Confidence: Low sample
Source: Hugging Face
Type: commentary
Included: 0
Scored: 2
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 3.7h
28d Confidence: Collecting
Source: MIT AI Research
Type: research
Included: 0
Scored: 2
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 5.0h
28d Confidence: Collecting
Source: Reddit R/Ethereum
Type: news
Included: 0
Scored: 2
28d Digest Rate: ~9%
28d Avg Score: ~0.07
28d Hotlist Hit: ~0%
7d Article Age: 2.7h
28d Confidence: Low sample
Source: Reddit R/FuturesTrading
Type: news
Included: 0
Scored: 2
28d Digest Rate: ~2%
28d Avg Score: ~0.02
28d Hotlist Hit: ~0%
7d Article Age: 10.2h
28d Confidence: Low sample
Source: Wired AI News
Type: news
Included: 0
Scored: 2
28d Digest Rate: ~16%
28d Avg Score: ~0.19
28d Hotlist Hit: ~0%
7d Article Age: 9.4h
28d Confidence: Low sample
Source: AI Daily Brief YT podcast
Type: commentary
Included: 0
Scored: 1
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 9.7h
28d Confidence: Collecting
Source: Closing Line Substack
Type: news
Included: 0
Scored: 1
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 8.5h
28d Confidence: Collecting
Source: Daring Fireball
Type: commentary
Included: 0
Scored: 1
28d Digest Rate: ~24%
28d Avg Score: ~0.20
28d Hotlist Hit: ~0%
7d Article Age: 3.9h
28d Confidence: Low sample
Source: Debt Serious
Type: commentary
Included: 0
Scored: 1
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 2.5h
28d Confidence: Collecting
Source: Latent Space
Type: commentary
Included: 0
Scored: 1
28d Digest Rate: Collecting data
28d Avg Score: Collecting data
28d Hotlist Hit: Collecting data
7d Article Age: 7.6h
28d Confidence: Collecting
Source: The Onion
Type: news
Included: 0
Scored: 1
28d Digest Rate: ~24%
28d Avg Score: ~0.46
28d Hotlist Hit: ~0%
7d Article Age: 6.9h
28d Confidence: Low sample
This is a video titled "Woman who rescued injured crow keeps getting 'thank-you gifts' from birds," shared via Hacker News, with an associated comments link.
Keywords: crow, bird rescue, animal behavior, gifts, whimsical
An article published by The Atlantic, a paywalled news source, features the title "This Is Edgar Allan Poe, and I Am Begging Kelly Clarkson to Take My Bird" and the text "I eagerly await your response."
Keywords: Edgar Allan Poe, Kelly Clarkson, pets, birds, humor
Comedian and writer Scout Boxall describes participating in live action role play (Larp), specifically attending the Swordcraft Quest event in Victoria, Australia, where hundreds of players spend a week immersed in a medieval fantasy village called Sudenburg. Drawing parallels between the Larp and standup comedy communities, Boxall shares personal experiences serving as the town's tax-collecting Master of Coin, highlights how the game reflects real-world sociopolitical issues, and notes the broader cultural resurgence of fantasy and medieval aesthetics amid contemporary anxieties.
Keywords: Live action role play, Larping, Melbourne, medieval re-enactment, hobby
This is episode 5 of the "Still Couting" series from the Silver Bulletin, titled "Welcome to midterm silly season 🤡".
Keywords: midterm, silly season, comedy, humor
The provided text is a collection of headlines and brief snippets from an RSS feed covering topics such as AI experiments, security threats and patches, FOSS developments including NetBSD and Ubuntu beta releases, and various industry updates ranging from chip manufacturing to cybersecurity acquisitions.
Keywords: Palm OS, GitHub, retro computing, software development, nostalgia
At an event in Waco, Texas, Tesla demonstrated its next-generation Roadster electric supercar. During the presentation, the vehicle accelerated from zero to 60mph in under a second, drove upside down, and briefly flew, fulfilling Elon Musk's promise of a flying car.
Keywords: Tesla Roadster, Elon Musk, flying car, electric supercar, Waco Texas
Located in the Polish countryside, an abandoned early 20th-century agricultural mill complex resembles a grand estate due to its striking multi-story central tower and decorative roof. Inside, the facility retains vintage machinery, grain chutes, wooden sifting equipment, and a grand wooden and iron spiral staircase, serving as a capsule of Poland's rural industrial heritage despite signs of decay.
Keywords: Śmiałowice, Poland, agricultural mill, abandoned architecture, rural industrial heritage, vintage machinery
Researchers are investigating the sound of the Liberty Bell by conducting modal analysis on a 20th-century replica bell located at Penn State Behrend.
Keywords: Liberty Bell, Penn State Behrend, acoustics, modal analysis, replica
Tesla has revealed its redesigned second-generation Roadster featuring SpaceX thrusters during an event near Waco, Texas. CEO Elon Musk demonstrated the vehicle's capabilities, including driving up an inverted ramp, spinning, and lifting over other Tesla models using a system of thrusters and compressed air tanks. Scheduled for production in 2028, the car will be offered in three trims—Performance, Thrust, and Rocket—all boasting a 300-mile range and speeds exceeding 230 mph. Tesla is currently accepting reservations for the vehicle, which follows multiple delays since the car was initially unveiled in 2017.
Keywords: Tesla, SpaceX, Roadster, thrusters, Texas
Monty Python star and travel filmmaker Michael Palin, who has visited more than 100 countries, most recently traveled to the Philippines.
Keywords: Michael Palin, Monty Python, travel filmmaker, Philippines, China
A Reddit post on the r/aiwars subreddit discusses reports that China has issued an identification document to an AI-generated human, prompting the poster to suggest that this development could impact copyright arguments regarding AI works.
Keywords: AI, artificial intelligence, China, legal identity, ID, copyright
This hands-on review discusses seven AI story generators that can assist users in overcoming writer's block, building plots, and expanding short ideas into complete stories.
Keywords: AI story generators, artificial intelligence, writing tools, software review
Residents of Hazle Township, Pennsylvania, are organizing to oppose a proposed Amazon Web Services data center campus known as Project Hazelnut, rejecting a developer-backed proposal that would provide a $10,000 cash dividend to each resident. Many locals view the payout as a bribe that fails to offset expected drops in property values and the impact of a supporting power line infrastructure. Meanwhile, state officials including Governor Josh Shapiro have taken steps to fast-track data center developments, while local supervisors like Anthony Griguoli face scrutiny from residents over their handling of the project and zoning considerations.
Keywords: data center, Pennsylvania, residents, community, corporate development
The research paper investigates scale sensitivity in large language models (LLMs) used for text scoring of social and psychological constructs. The authors define numerical sensitivity and semantic sensitivity, and evaluate how variations in rating scale design—such as format, range, and sign—affect LLM-generated scores across multiple tasks, prompting strategies, and models. The findings indicate that altering scale design elements shifts normalized scores and affects text categorization, with the highest sensitivity observed in toxicity scoring. Additionally, rubric-based prompting did not decrease sensitivity compared to zero-shot prompting, leading the authors to offer practical design guidance and emphasize the need for robustness checks.
Keywords: Large Language Models, Rating Scales, Text Scoring, Computational Social Science, Scale Sensitivity
The article introduces SemTAC, an encoder model trained with a temporal-neighborhood contrastive loss designed to recover geometric structure in human motion data without relying on forecasting-based objectives. When evaluated on a five-step motion sequence discrimination task, SemTAC performs competitively with four baseline methods on full-length sequences but maintains a significant advantage on incomplete or truncated sequences, achieving a median F1 score of 0.77 one step prior to sequence completion compared to 0.27 to 0.70 for the baselines. Additionally, ablation studies attribute this performance to the temporal-contrastive objective, and SemTAC's representation trajectories exhibit interpretable geometric structures exceeding a no-structure chance baseline on a displacement-smoothness metric.
Keywords: human motion data, SemTAC, temporal-neighborhood contrastive loss, machine learning, time series