Ed Summers edsu

Feed digest — 2026-06-03 → 2026-06-05

288 unread articles spanning 2 days. Mode B (Curated TL;DR), aiming for ~⅓ coverage with selective theming.

Federal politics & Trump admin

Coal revival. Trump announced $700M to restart and prop up domestic coal, including specifically reopening the AES Warrior Run plant in Western Maryland (Maryland Matters has the regional angle); 350.org counters with what fossil fuel imports actually cost on electric bills.
Federal workforce squeeze. An executive order [strips civil-service protections from ~8,000 senior federal workers](https://marylandmatters.org/2026/06/04/trump-moves-about-8000-federal-jobs-to-new-category-that-strips-j

Claude Code Chat Transcript

Topic: Recovering audio from a Tascam DAW backup disk image

User: it looks like backup.bin may be from a tascam DAW in early 2000s. is there any way to recover this audio without access to the machine that created it?

Assistant: Let me start by examining the file to understand what we're working with.

(examined directory listing, README.md, backup.cue, hexdump.txt, convert.sh)

Conversation: HN Thread on Claude Opus 4.7

User: hey, can you summarize this hacker news thread? https://news.ycombinator.com/item?id=47793411?foo=barlksjlkjslkj

Assistant: Here's the summary of that Hacker News thread (same thread from your follow-up message too):

Article: Anthropic released Claude Opus 4.7, with "adaptive thinking" as its default (and only) thinking mode.

column	before	after
title	891351 (93%)	804262 (99.9%)
pub_year	893340 (99.8%)	803930 (99.9%)
open_access	589300 (65.8%)	618291 (76.8%)
apc	265024 (29.6%)	274282 (34.0%)
types	894525 (99.9%)	804498 (100%)
publisher	638311 (71.3%)	588595 (73.15%)
doi	553661 (61.8%)	563544 (70.0%)

	#!/usr/bin/env python3
	"""
	Extract all tracks from a Tascam DAW backup disk image, including individual
	tracks and the final mix (last track). This was only tested with Tascam 788 backup.

	Finds the audio start offset by detecting the end of the FAT region, then
	scans for silence gaps to locate track boundaries and writes each as a WAV file.

	Usage:
	python3 extract_tracks.py <backup.bin> [output_dir]

	#!/usr/bin/env python3
	"""
	Extract the final mixed track from a Tascam DAW backup disk image.

	Finds the audio start offset by detecting the end of the FAT region, then
	scans for silence gaps to locate track boundaries and extracts the last track
	(the stereo or mono mix) as a WAV file.

	Usage:
	python3 extract_mix.py <backup.bin> [output.wav]

	00000000 92 35 96 39 02 78 79 4b 00 00 00 00 00 00 00 01 \|.5.9.xyK........\|
	00000010 00 00 00 01 00 00 08 00 00 00 00 60 00 00 1d 48 \|...........`...H\|
	00000020 00 00 00 01 00 00 02 55 00 00 05 14 00 00 00 00 \|.......U........\|
	00000030 00 00 05 13 00 00 05 14 00 00 00 01 00 00 00 14 \|................\|
	00000040 00 00 00 01 37 00 00 00 00 57 46 da 57 48 45 52 \|....7....WF.WHER\|
	00000050 45 20 45 56 45 52 20 20 00 00 00 00 00 00 00 14 \|E EVER ........\|
	00000060 00 00 00 00 00 00 00 00 00 00 00 03 00 00 00 00 \|................\|
	00000070 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 \|................\|
	*
	00002750 00 00 00 00 ff ff ff ff ff ff ff ff ff ff ff ff \|................\|

	{
	"@context": "http://schema.org",
	"@type": "Person",
	"@id": "https://orcid.org/0000-0003-1279-3709",
	"mainEntityOfPage": "https://orcid.org/0000-0003-1279-3709",
	"name": "Timothy J Berners-Lee",
	"givenName": "Timothy",
	"familyName": "Berners-Lee",
	"alumniOf": {
	"@type": "Organization",

	#!/usr/bin/env python3

	# This is a simplistic Python program that will use Cloudflare's Crawl API [1]
	# to crawl a website, and then fetch the results to the filesystem once the job
	# is completed.
	#
	# You run it like so:
	#
	# uv run crowdflare_crawl.py https://example.com
	#

	#!/usr/bin/env python3

	# stream wikidata ntriples dumps for two snapshots and look for QIDs that have been deleted.

	import os


	def main():
	qids_before = get_qids("https://dumps.wikimedia.org/wikidatawiki/entities/20260123/wikidata-20260123-lexemes-BETA.nt.gz")
	print(f"before: {len(qids_before)}")