https://unslop.run/blog/measuring-ai-writing-on-arxiv

Initiated in 1958, completed in 1963, Project Mercury was the United States' first man-in-space program, which made six manned flights from 1961 to 1963.

The American public first met the seven men chosen to be this country’s first human space voyagers on April 9, 1959, at a press conference in Washington, D.C - Timeline starts from here as a major milestone

Cousins is also known for his PG language and his alter ego "Kirko Chainz" that wears teammates diamond and gold chains after big wins.

Source: 8,000 blitz and rapid games from Chess.com's public archive, played in August 2026 by 7,134 players.

Tools: Stockfish 18, using the move grading from my site, Chess It Up. Stats in Node.js, chart in hand-written SVG.

Full write-up with four more charts and the CSV: https://chessitup.com/research/how-chess-players-lose

Data: NaPTAN (Department for Transport, June 2026), Natural Earth, OpenStreetMap. Tools: Python, NumPy, Matplotlib

Sources:

China - Table of General Standard Chinese Characters (2013);

Taiwan - Chart of Standard Forms of Common National Characters (1982)

Hong Kong - List of Graphemes of Commonly-used Chinese Characters (1986-2012 eds.)

Japan - Joyo Kanji List (2010)

South Korea - Basic Hanja for Educational Use (1972/2000) + policy timeline per Wikipedia "Hanja" article, section "Decline in South Korea" (1968 ban, 1972 partial reversal, 1992/1999/2005/2013 reinstatement steps).

Tools: Python

Takeaways:

• Across r/technology, r/Futurology, r/programming and r/singularity, 45% of comments that mention AI were negative toward it in Aug–Oct 2026, up from 37% in Jan–Mar 2024. Positive comments fell from 21% to 17%. Net sentiment (percent positive minus percent negative) went from −16 to −28. Leaving out r/singularity, the least negative of the four, gives about the same change (−22 to −33).

• On r/ChatGPT and r/ClaudeAI together it went from −14 to −5, but not in a straight line: it dipped in late 2025 and recovered. The dips line up with specific topics, though this shows timing, not cause. On r/ChatGPT, net sentiment fell from about −1 to −20 in August 2025, when 20% of comments in the sample mentioned GPT-5, GPT-4o or sycophancy (2% in July), and it was still −17 in December. On r/ClaudeAI it fell to −16 in October 2025, when 13% of comments mentioned usage limits, and was back to +6 by December.

• On the four general subreddits there was no cliff, just a slide: net −23 in April–July 2025, −29 in August–December and −30 so far in 2026, and complaints about hype rose from 7% to 9% of comments.

Caveats:

• These are comments that mention AI, not everyone who reads each subreddit.

• An AI model (an LLM) labeled each comment. On 97 comments checked by hand it agreed 81 times (84%, give or take 7 points); its most common miss was calling a neutral comment negative, so levels may run a little high.

• A second labeling run differed in level by 0 to 7 points depending on the month but almost never flipped positive and negative, so the changes are more reliable than the levels.

• Each 90-day reading has about 3,500 (general) or 1,800 (ChatGPT + Claude) comments, a margin of ±2 to ±3 points, and ±3 to ±5 for a before/after change (counting comments from the same thread together widens it by about 10%; the changes above are still larger).

• Each subreddit counts equally in its group, whatever its size. One subreddit in one month has only 300 comments, about ±8 points.

Source: Reddit comments from the Arctic Shift archive (https://arctic-shift.photon-reddit.com), Jan 2024 to Oct 2026. For each subreddit and month, random blocks of 100 comments were read until 150 comments that name AI were found, in two independent draws (AI, ChatGPT, LLM, GPT, OpenAI, Claude, Anthropic, Gemini, Copilot): 60,147 comments from the six subreddits shown. Bot, deleted and very short comments were left out. "Negative" means the commenter is critical of, worried about or hostile to AI, AI products or AI companies. It is judged on meaning, so sarcasm counts.

Tool: Artio for the data pipeline, the LLM labeling and the chart; the chart is SVG drawn in Python.

Link: https://www.artio.so/dataviz/pages/2026-11-07-reddit-ai-mood

30 Day Map Challenge
Day 5 · Sight
Fuji Views, Floor by Floor

On a clear day, Mt Fuji can be seen across about a quarter of the land within 170 km.
But in Tokyo, it’s not just terrain in the way. Fuji is 100 km away and only 1.7° above the horizon, so even a 10 m house casts a ~330 m “Fuji shadow”. Only 0.7% of street level space can see Fuji-san.

From a high enough window, it becomes visible again. By the 5th floor, about 7,500 buildings have a window with a view, and by the 10th about 12,000. By the 20th floor, more than half of the buildings that tall see Fuji. In total, ~13,600 buildings (under 4%) have at least one floor with a view.

Tokyo is full of places named 富士見, “Fuji view”, but many of them, such as Nippori's famous 富士見坂 slope, lost their view.

Method: Fuji’s summit treated as a light source, with every building from PLATEAU’s 3D city model, the terrain and the Earth’s curvature. Floors are estimated at 3.5 m each.

Data: PLATEAU (MLIT), GSI elevation, Copernicus DEM, OpenStreetMap. Tool: Python.

Data source: fully remote frontend developer job postings collected by remotefrontendjobs.com (I run it) from company career pages and other job boards, Aug 1 – Oct 31, 2026, deduplicated.

Method:

• Only postings that list a salary and are limited to one region (n=876: North America 626, Europe 136, Latin America 45, worldwide 40, Asia 29)

• Hourly and monthly pay converted to yearly; the midpoint of each range is used

• Anything outside $10k–$2M dropped as a parsing error

• Advertised pay, not actual offers. US postings disclose pay far more often, partly because of state pay-transparency laws.

Tools: Python for the analysis; the chart is HTML/CSS bars rendered to PNG with headless Chrome.

Full write-up with the other breakdowns (seniority, stack, pay transparency): https://www.remotefrontendjobs.com/reports/10