Philip Marais retweetledi
If you're a founder, the to-do list never ends.
It's the job. I've made peace with it.
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Philip Marais
672 posts
Philip Marais
@fijnmin
Builder of AI workflows for scientific research support. https://t.co/DJol1TFYvI
Katılım Şubat 2015
2.3K Takip Edilen717 Takipçiler
Philip Marais retweetledi
Okay, here goes.
Random thoughts & takeaways from the 2026 Masters.
I hope you enjoy it and, as always, thanks for reading.
What a joy it is to be able to share these weeks and witterings with you all.
🌺⛳️
bunkered.co.uk/golf-news/the-…
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What a spectacular bit of analysis!
Dr Devavrat Harshe@DocDevavrat
We cricket fans will keep fighting to the death over who the best fielder in cricket is. AB de Villiers? Jadeja? Jonty Rhodes? Hold that argument. Because in 2018, three statisticians from Simon Fraser University — Perera, Davis, and Swartz — decided to end the debate with data. They built a metric called "Expected Runs Saved due to Fielding" (E(RSF)). And what they found? It will upset you. The best fielders in T20 cricket save... just 1.2 runs per match more than an ordinary fielder. That's it. While the best batters and bowlers contribute roughly 10 runs per match to their teams, the best fielder on the planet barely scrapes past a single run. But here's where it gets properly wild. The researchers didn't use GPS trackers. Didn't use hawk-eye data. Didn't even use video. They used commentary text. They parsed 160,247 balls of match commentary — from International T20s (about 750 T20 matches) and the IPL — and built a random machine learning model trained on 55 contextual keywords (words like "dive", "edge", "drop", "flat", "sharp") to predict what the batting outcome SHOULD have been on any given ball. Then they compared that prediction against what ACTUALLY happened when a specific fielder's name was mentioned. That gap — between what should have happened and what did happen — became the measure of fielding impact. Essentially a Moneyball approach. For cricket. For FIELDING. Now. The results. The best non-wicketkeeper fielder? Nathan Coulter-Nile (E(RSF) = +0.35). AB de Villiers, widely considered the greatest fielder alive? Ranked 21st. E(RSF) = -0.34. Negative. As in, on average, he cost his team runs while fielding. And the most shocking finding? MS Dhoni — the man with the fastest hands behind the stumps — was ranked the WORST wicketkeeper-fielder in the entire dataset. E(RSF) = -3.61. Dead last among 13 keepers. Behind Mark Boucher. Behind Brad Haddin. Behind everyone. How is this possible? The paper reveals a beautiful paradox: the best fielders are the ones whose names are NEVER mentioned. Think about it. When commentary says "brilliant diving catch by Kohli!", that's a notable event. But when a fielder simply... stops the ball cleanly, returns it accurately, and nothing remarkable happens — his name is never spoken. Another instance: a batsman drives a ball, but notices Jadeja standing at short cover or point and DOES NOT DARE to run a single. This does not get recorded as a fielding achievement. The study showed a clear decreasing trend: the less often a player's name appeared relative to fielding opportunities, the BETTER he was. In other words — excellence in fielding is invisible. We celebrate dramatic recoveries. Emergency interventions. The "brilliant diving catch" of a last-minute, a last ball run-out. But the real measure of good work — like good fielding — is also in what DOESN'T happen. The absence of disaster is the hardest outcome to measure. And the easiest to ignore. Perera, Davis, and Swartz tried to measure cricket's invisible skill. Their approach was not perfect, but, they opened a door that was considered closed, sealed and deemed never to be opened. This #IPL season, I will post one interesting cricket related research for fans to be amused, and get a different viewpoint on their beloved game. Enjoy! @ABsay_ek @AMP86793444 summit.sfu.ca/_flysystem/fed…
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Philip Marais retweetledi
QME
John McAfee revealed the creator of Bitcoin without directly saying it.
Do you think he was correct?
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Someone should send up a website dedicated to tracking South African media apologies.
Just to see if there’s some sort of ideological bias in our newsrooms or something…
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Philip Marais retweetledi
@fijnmin @wilkinsoncape Should name the site HelloPieter(duToit).com
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Philip Marais retweetledi
@fijnmin @wilkinsoncape Awesome work Philip.
We need to get this site known..
Speading it far and wide.
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Smart people are bad at assigning value to things that feel easy to them.
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🚨 STARTING DECEMBER 16TH, META WILL BEGIN READING YOUR DMs - EVERY MESSAGE, PHOTO & VOICE NOTE FED INTO AI FOR PROFIT
Meta is rolling out a new policy that lets them use your private conversations to train their AI - unless you manually opt out.
That means:
• Every DM you’ve ever sent
• Every photo
• Every voice memo
• Every private chat with friends, family, partners, clients
• Even messages people send to you
All of it can be fed into their AI models.
And yes - they made the opt-out process intentionally confusing and desktop-only so most people won’t do it.
This video explains exactly how to stop it.
If you don’t do this, Meta can legally use every private thing you’ve ever sent to train their AI - starting December 16th.
This is not a drill.
Would YOU trust Meta with your private DMs?
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Philip Marais retweetledi
Birth Rate Collapse & Economic Utility of a Birth
This is really weird, but I suspect it’s overlooked in socio-economic research literature.
Below I present 2 zones on the same chart.
The pink zone on the left chart shows the useful economic life of 1 human birth in the year 1851.
The green zone on the right chart shows the useful economic life of 1 human birth in 2011.
Now because of medical advances, sanitation, public health, etc, etc we have significantly improved life expectancy and reduced infant mortality. This means that a birth in 2011 has vastly more hours of economic output than a birth in 1851. Historic mortality rates really cut down the expected economic lifespan of a birth, but how much?
The pink area on left = 40 years * 40% + ( 40 years * 30% )/2
= 22 years of economic work per birth (yikes!)
The green area on the right = 51 years * 98%
= 50 years of economic work per birth.
These numbers are massively different.
The expected working lifespan of a human at birth has increased by 127% over 160 years. Even though we work to approximately the same age.
This means that in economic terms 1 birth in 2011 is worth 2.27 births in 1851. How does that gain in economic utility per birth compare to the collapse in volume of births?
Today there are 2.31 births per woman worldwide.
In 1850 there were 5.82 births per woman.
5.82/2.31=2.52
So we have 2.27x gain in utility per birth and a 2.52x fall in the volume of births? These ratios are within 10% of one another, they almost perfectly track inversely to give a fixed amount of ‘human economic utility birthed per woman’.
I find this to be a staggering coincidence.
Is the collapsing birth rate just supply and demand? Did longevity gains simply create a temporary oversupply of units of human utility?
The population crisis might just be market forces. Or rather, it’s just macro-ecology.
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I still use the OpenAI whisper API for TTS instead of reading long documents. But that is it.
And I am finding myself spending more time with Gemini 3.0 than with GroK.
And I see my Perplexity use has also tanked.
Claude still my #1 spend, followed by Grok-4-fast and then Gemini Pro
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@iruletheworldmo new nano banana is absurd. they packed a crazy reasoning model inside of that thing. anyone who hasn't played around with its reasoning capabilities in the form of images really should.
living in a strange world where i now don't use a single openai product somehow. kinda wild.
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sometimes sit there at night wondering what @mckaywrigley thinks about these latest models.
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💥 Pitch your startup:
- Max 4 words
- Add your link
Seen by 108,000 people last week.
Yes, it counts as marketing, go!🚀
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@sethsetse @elonmusk @nikitabier This will become increasingly important.
I even did a silly POC to that effect.
✓ Verified human-written
keyproof.io/verify/1b167c3…
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this country exposing feature is great
next let's use FaceId to nuke the bots
@elonmusk @nikitabier
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@goddek Hated she may be. Undeniably a generational talent. I consider myself a music purist. A music asshole if you were to ask my wife. But seeing your 5 year old daughter sing the lyrics to Fate of Ophelia ought to change your perspective, reliably.
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@pmitu I really wrote this with my own fingers.
✓ Verified human-written
keyproof.io/verify/755409b…
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It the API call latency improvement I noticed first.
Charly Wargnier@DataChaz
If you’re still sending raw JSON into your LLMs, you’re burning tokens, latency, and budget! Try TOON (Token-Oriented Object Notation). Clear like YAML, compact like CSV: • 30–60% fewer tokens • Up to 50% lower costs • Shines for tabular data. Free and Open source 🧵↓
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