Manuel L. Quezon III

"Out from some timeless wintry fog shambled the hairy old beast - history - big with memories." --Simon Schama, on Churchill's funeral.

@Talon_Haribon It was almost entirely Gilbert Perez then Galo Ocampo. When we updated the presidential seal etc., the then-head begged me not to use heraldic language. The current crop seem interested but institutional drift means no one will take orders or even suggestions from them anymore.

They need to come back, the ship's heraldry of the PN needs their help.

In South Korea 🇰🇷, the solar panels in the middle of the highway have a bicycle path underneath - cyclists are protected from the sun, isolated from traffic, and the country can produce clean energy.

"Hurt" is not an original by Johnny Cash. The song was written by Trent Reznor (Nine Inch Nails) in 1994 for the album The Downward Spiral. Rick Rubin had to insist several times on Cash recording his version, at first Johnny found the idea completely insane because the original version is industrial and noisy. At 71, already very ill, almost blind and with trembling hands, Cash completely transformed the band. The iconic video, directed by Mark Romanek, was filmed at the House of Cash (his own museum). June Carter Cash appears looking at him fondly, the video was shot in February 2003, a few months before she died (May) and Johnny himself (September). Trent Reznor was so moved that he declared, "This song is not mine anymore." It is considered one of the best covers of all time.

@escalonamar Downgraded and folded into NHI with fixation of New Society on logos.

The loss of the Philippine Healdry Committee has been a disaster for Filipino heraldry and seal-making.

As always it will be of interest to see how they treat the Philippines. "The War" by Ken Burns was interesting.

Just a reminder to all that "World War II with Tom Hanks" premiers at 8pm May 25th on @HISTORY with a 3-episode drop followed by 17 more episodes on a once a week release schedule. I am one of a great many contributors. I hope you'll check it out! #WorldWarIITomHanks @NutopiaTV

I hope at least part of the goal here is to protect antiquities found in the Philippines from Chinese efforts to illegally seize them. Few people know this, but the largest collection of priceless Ming Dynasty ceramics outside of mainland China resides in the Philippines- all which belong to Filipinos and Fil-Am families. China is spearheading efforts in the UN to seize legally acquired antiquities under false pretenses from their lawful owners.

This is what the Earth will look like in 250 millions years according to plate tectonics theory.

JUST IN: Inside “Magnifica Humanitas”: Pope Leo XIV Rejects Transhumanism: dianemontagna.substack.com/p/inside-magni… Italian journalist Nico Spuntoni offers an exclusive preview of the Pope’s first encyclical on safeguarding the human person in the age of AI. @nicospuntoni

Go check out the Austronesian Migration map on the Maptism site! We're featuring guest authors too, and they get full control over how their work appears. They can publish pseudonymously or under an ORCID in our Zenodo community with a DOI; write an accompanying article and link their socials; hold complete control over licensing and attribution; and even specify the steganographic trustmark embedded in the maps.

Berlin’s transport network still carries the scars of the Cold War. West Berlin largely ripped out its tram network and replaced it with an extensive U-Bahn system, while East Berlin kept its trams running. After reunification, the tram lines started making a comeback. Even cities can end up with split personalities. Source: linkedin.com/posts/tim-tens…

So I spent some time studying the new Twitter/X algorithm today since the latest version was published about a week ago on Github (#updates--may-15th-2026" target="_blank" rel="nofollow noopener">github.com/xai-org/x-algo…). My goal was to answer why so many people have seemingly seen such a dramatic drop in their posts' reach. The first answer, which is actually somewhat unrelated to the ranking algorithm on Github, is the auto-translate feature, rolled out worldwide on April 7, 2026 (x.com/nikitabier/sta…). Before that date, if you wrote in English about, say, the Trump-Xi Beijing summit, you were competing for attention with maybe 5,000 other English-language accounts writing on geopolitics. After that date, your post is competing for attention with other posts on the same topic IN EVERY LANGUAGE ON EARTH. For some topics that do command global attention like geopolitics, that's a very brutal multiplier: you used to be one of 5,000, you're suddenly one of 50,000 (something of that order): MUCH more difficult to stand out. Secondly, the number of followers you have matters far less than it used to: each post now has to earn its audience reader by reader, on the predicted engagement of the post, and how its topic matches what each reader has recently been engaging with. Here is how the algorithm works, in simple terms: when you, as a reader, open your feed, the algorithm doesn't load "posts from accounts you follow." Instead it runs a 2-stage prediction of what posts you're likely to engage with in that very moment. The first stage is the retrieval stage. The system narrows billions of posts on X/Twitter that day down to roughly 1,500 candidates by matching the semantic content of each post - what it's about - against what you as a reader have recently engaged with. Some candidate posts come from accounts you follow; others are pulled from across the platform by pure topic similarity to your recent interests. You can test this retrieval stage easily: start disproportionally engaging with - say - Brad Pitt videos and you'll bit by bit see your timeline flooded with Brad Pitt content, most of it from accounts you've never followed and never heard of. Then there's the ranking stage. Each of these candidate posts for your feed is fed through a Grok-based model that tries to understand if you'll engage with the post. It looks at 15 engagement metrics: 1) P(favorite) — the reader likes the post 2) P(reply) — the reader replies to it 3) P(repost) — the reader reposts it 4) P(quote) — the reader quote-tweets it 5) P(click) — the reader clicks a link in it 6) P(profile_click) — the reader taps through to your profile 7) P(video_view) — the reader watches the video 8) P(photo_expand) — the reader expands an image 9) P(share) — the reader shares it (DM, off-platform, etc.) 10) P(dwell) — the reader stops scrolling and lingers on the post 11) P(follow_author) — the reader follows you after seeing it 12) P(not_interested) — the reader marks "not interested" 13) P(block_author) — the reader blocks you 14) P(mute_author) — the reader mutes you 15) P(report) — the reader reports the post Fifteen predicted actions, each multiplied by a weight, summed: that sum is the score that determines in which priority a post will be seen among other candidates. Please note that posting something with a video or an image can give your post an advantage as 2 actions are specifically for these: video_view and photo_expand. No video or photo and you don't get a score for these. Also, naturally, having a video maximizes the chance that a user will "dwell" on your post to watch it. Also note that 4 of these actions carry negative weights (not_interested, block_author, mute_author and report): meaning that if the model expects a post to generate a lot of negativity, it'll get de-boosted quite dramatically. But note, first and foremost, what's NOT in there: none of the things that, naively, one might think a serious information platform would weigh. There is no P(this post is true and well-sourced). No P(the author actually knows what they're talking about). No P(this person has spent a decade building a body of work that has held up). No P(this account has earned the right to be taken seriously on this topic). No P(the author has a large following from credible people). The model does not seem to care - at all - about any of that. Every post starts from zero. You could have ten years of rigorous, well-sourced analysis behind you - or you could be just an uneducated rando who registered yesterday. To this algorithm, you're both just a bag of engagement probabilities. Now, sure, to be fair, there is a "brand" effect that's not covered by the algorithm: someone who has in fact built a brand will naturally have better engagement metrics because people recognize their account. But that's an indirect, second-order effect. And crucially, it's legacy: those "brands" were built under earlier versions of the algorithm that gave followers and reputation more weight. Lastly, several other features of the new algorithm compound the dilution, none of them visible from outside but all consequential. The May 15 update added an "impression bloom filter," tightening the rule that once a reader has been served a post, the system won't serve it to them again. Before, a strong post could marinate in someone's feed across multiple refreshes and accumulate engagement on the second or third pass. Now it basically gets one shot. Also, your own posts compete with each other. An "Author Diversity Scorer" inside the ranking stage attenuates the score of every subsequent post of yours that ends up in a reader's candidate pool. In plain terms: if multiple of your posts land in a reader's candidate pool, the system shows one at full strength and dampens the others. So don't post several times consecutively on the same topic. And, last but not least, another huge impact on reach is that, in the old algorithm, when someone reposted or quote-tweeted you, your post was broadcast to their followers' timelines - a repost from an account with 100,000 followers was a huge boost. In the new algorithm, that mechanism is vastly demoted: reposts - like every post - need to go through the retrieval and ranking stage mentioned above, so a repost from a big account is a long way from the boost it used to be. This is especially brutal for low-effort quote tweets, which used to function as cheap amplification: now they often can't even clear the retrieval stage - they simply don't contain enough novel semantic content for the system to match them to anyone's interests. So, putting it all together, the reach collapse comes from many forces stacking at once: - Auto-translate makes your posts compete for attention against an order of magnitude more content - The retrieval stage matches posts by topic, not by who follows you - The ranking stage scores purely on predicted engagement with no weight for credibility, expertise, or track record - The bloom filter narrows every post's window to one strong shot - The diversity scorer penalizes prolific posting - Reposts no longer carry much distribution power Each of these alone would dent your reach. Combined, they amount to a complete reset: your audience that you built painstakingly over years basically doesn't matter much anymore, and it's much - much - harder to stand out even if you're a big account. People structurally rewarded by this algorithm are folks who: - Post visually (videos/images) - Post on globally popular topics because they clear the retrieval stage easily - Provoke strong emotional reactions - likes, replies, reposts - Don't care about accuracy or seriousness because the algorithm doesn't measure it - Don't care about their existing audience because every post is judged in isolation anyway In short this new algorithm, like so many on social media, is all about maximizing whether people will engage with something - not about whether they should.

My column today looks at trauma in the Senate --and how useful it could be, to some in the same coalition. A quarter century, a generation, is long enough for legislators to have no memory of how to handle danger.

To add, when Seoul did this, Koreans discovered that there was a natural water source in the middle of the highway, so they enhanced this, and incorporated it in their urban planning. Nature should be given primordial importance, not treated like a nuisance.

@qui_quiqui40157 You should talk to Patis Tesoro who is helping set up a piña museum

Really hope a museum would open in the future that focuses on the history of the traje de mestiza / baro't saya / terno, beginning from the pre-colonial era to contemporary times.

A superloser is a leader of a great power, or (onetime) superpower, whose disastrous choices lead to a crash. He possesses a combination of skills that allow for a rise to personal power and the collapse of state power. I spell out the phenomenon in this video: snyder.substack.com/p/the-era-of-t…

Hopefully they will do their part to fix a longstanding crime against Filipino artists: the lack or disadvantageous application of royalties to performers.

This is an extraordinary document written by the research arm of China's spy agency (the powerful MSS, basically the CIA and the FBI all wrapped in one) that absolutely zero media has picked up on. As far as I can see, I'm the first person to write about it even though it was published (in Chinese) on May 13th on chinadiplomacy.org.cn, a website of China's Ministry of Foreign Affairs. The document contains perhaps the most authoritative description of where China thinks its relationship with the U.S. stands, and where it’s headed. The title of the report is “The Great Global Transformation and the Path to U.S.–China Coexistence” and I provide a full translation of it in my article, the link of which is at the bottom of this post. To summarize briefly the most important - and, perhaps, surprising - aspect of the document: China's spy agency - the one institution whose entire job is to worry about the U.S. threat - has largely stopped worrying. That's really what transpires from the document. They use a strategic framework borrowed from Mao's "protracted war" theory and, according to this framework, America's offensive phase is finished and China weathered the storm intact. The question is no longer "how do we survive America?" but "how do we manage America?" - and they're proposing a six-step relationship recovery program. I'll let you read the full document as well as my analysis of it here: open.substack.com/pub/arnaudbert…

When Humans Went Away, the Wildlife Strayed nytimes.com/2026/05/21/sci… via @NYTimes

フィリピンは毎年人口が100万人増え、中央年齢も26歳の人口ボーナス期。ただ、2021年に出生率が2.0を割り、国連の2100年時点の人口予測は、1.8億人→1.15億人へ大幅下方修正。2057年の1.35億人をピークに人口は減少へ転じる見通しです。