RSS Parrot

RT by @jburnmurdoch: Today, my book finally enters the big wide world! Exciting and also nerve-wracking! I'm really thrilled with this lovely review in The Spectator today, which describes it as "powerful and refreshing". If that sounds like YOUR cup of tea, please buy a copy!

https://nitter.poast.org/sarahoconnor_/status/2062536258287554605#m

Published: June 4, 2026 14:05

Today, my book finally enters the big wide world! Exciting and also nerve-wracking! I'm really thrilled with this lovely review in The Spectator today, which describes it as "powerful and refreshing". If that sounds like YOUR cup of tea, please buy a copy!

RT by @jburnmurdoch: I believe we now have evidence of FIFA's World Cup ticketing shell game: FIFA is colluding with third-party resale platforms for its own supply management. Look at this SeatGeek map (secondary market!) for Saudi Arabia vs Cape Verde. The circled areas are not random single resale tickets, but large, contiguous blocks of seats: entire rows and swaths in sections 101/102, 112/113, 119/120, 134–137, 139, ... The blue circles appeared weeks ago, then the purple blocks suddenly showed up a day or two ago, and the red blocks seem to have appeared recently too. That's not what ordinary fan or even commercial scalper resale looks like who resell pairs, fours, and scattered seats. Instead, this looks like inventory being dumped in bulk onto secondary markets, at prices below FIFA's official site. Why doesn't FIFA just lower prices on its own site Probably because official price cuts could trigger refund demands, chargebacks, or consumer-protection headaches from fans who already bought at much higher prices. Instead FIFA keeps official prices high, avoids openly admitting the market-clearing price is lower, and moves unsold inventory through third-party resale platforms instead.

https://nitter.poast.org/florianederer/status/2061850661583532139#m

Published: June 2, 2026 16:41

I believe we now have evidence of FIFA's World Cup ticketing shell game: FIFA is colluding with third-party resale platforms for its own supply management. Look at this SeatGeek map (secondary market!) for Saudi Arabia vs Cape Verde. The circled areas are…

RT by @jburnmurdoch: This chart is bonkers. I think there's two possible explanations for why the UK runs so far ahead of other European countries – neither of them good. And the annual April jump speaks to a wider issue. For more detail, see my column in this weekend's Observer (link below).

https://nitter.poast.org/BenZaranko/status/2060637675023982904#m

Published: May 30, 2026 08:21

This chart is bonkers. I think there's two possible explanations for why the UK runs so far ahead of other European countries – neither of them good. And the annual April jump speaks to a wider issue. For more detail, see my column in this weekend's…

RT by @jburnmurdoch: Laura Gilbert built 10 Data Science and the Incubator for AI, which have both pioneered the deployment of technology across the British state. Few people have contributed more to improving the UK’s state capacity in AI than Laura and the teams she was a part of. 10DS modelling reportedly informed the choice to prioritise by age rather than occupation. This is widely credited with saving lives versus the occupation-based alternative being lobbied for at the time. 10DS and the brilliant folks there did a lot of other great stuff, including building live COVID data that policy teams and the public relied on, as well as releasing a lightweight data sharing tool on GitHub where anyone can access it free of charge. Today, it has amassed over 200,000 public downloads, used by teams across government and industry to make data sharing easy. Onto AI, where Zack has suggested that Laura doesn’t have lots to offer to public discussion. Whenever I speak with frontier labs, they tell me the U.K. now has the most ambitious and sophisticated approach to deploying AI in public services. With Extract (which Laura’s Incubator for AI team developed), planning documents are now converted into digital records in 40 seconds, versus the 1–2 hours of planner time it typically takes manually, with higher accuracy. That’s roughly a 100–180x speedup, and is contributing to a 45% reduction in processing time to build the housing and infrastructure the UK is sorely in need of. The public sector team who built Extract scaffolded Gemini so that it could orchestrate Segment Anything and pose estimation models to map geospatial information from text and diagrams in a way that even the GOOGLE DEEPMIND TEAM hadn’t worked out how to do at the time. So rather than outsourcing to big tech, which I’m sure Zack and many others are more than sceptical of, Laura helped build true public sector state capacity that reduced our reliance on the private sector, while also delivering a world class public service. Powerful AI systems are going to usher in a centuries worth of social and economic transformation within only a couple of decades. This requires a deep analysis of where capabilities will develop, an understanding of which externalities we want to mitigate, a vision of what a good life looks like, and amassing the people, tools, infrastructure, and institutions to build that vision.  Of course Laura is precisely the sort of person that has much to offer in answering these questions. We should be cherishing the tireless civil servants and incredible technical talent that have built capabilities that many folks think the public sector would never be able to do.

https://nitter.poast.org/Tom_Westgarth15/status/2059937303980622263#m

Published: May 28, 2026 09:58

Laura Gilbert built 10 Data Science and the Incubator for AI, which have both pioneered the deployment of technology across the British state. Few people have contributed more to improving the UK’s state capacity in AI than Laura and the teams she was a…

R to @jburnmurdoch: Honestly mindblowing stuff in there, including: • Revolutions in disease prevention mean lives are now getting dramatically healthier not just longer (big contrast with recent decades) • The prospect that we may have effectively cured cancer within the next decade

https://nitter.poast.org/jburnmurdoch/status/2059897874234695771#m

Published: May 28, 2026 07:21

Honestly mindblowing stuff in there, including: • Revolutions in disease prevention mean lives are now getting dramatically healthier not just longer (big contrast with recent decades) • The prospect that we may have effectively cured cancer within the…

New from me: I had the pleasure of sitting in as host of BBC’s Radical podcast this week, and had a fascinating conversation with leading geneticist Sir John Bell, where we explored the truly astonishing medical breakthroughs of recent (and coming) years https://www.bbc.co.uk/sounds/play/m002wt3d

https://nitter.poast.org/jburnmurdoch/status/2059896017668001964#m

Published: May 28, 2026 07:14

New from me: I had the pleasure of sitting in as host of BBC’s Radical podcast this week, and had a fascinating conversation with leading geneticist Sir John Bell, where we explored the truly astonishing medical breakthroughs of recent (and coming) years …

RT by @jburnmurdoch: Amid all the talk of freezing the price of groceries, I looked at what goes into the cost of a pint of milk. Two things jump out... 1/3

https://nitter.poast.org/TomHCalver/status/2058495810665390578#m

Published: May 24, 2026 10:30

Amid all the talk of freezing the price of groceries, I looked at what goes into the cost of a pint of milk. Two things jump out... 1/3

RT by @jburnmurdoch: Replacement fertility in one chart: Even if 90% of women have children and average 2.2 each, we still fall short. Why? The fertility rate of a population equals the product of the proportion of women who have children and the average number of children per mother. That is, if 90% of women have children and the average number of children per mother is 2.2, the fertility rate of this population is 1.98. This simple formula gives us the relationship between the proportion of mothers in a population and the average number of children per mother required to reach the replacement rate. As I explained two days ago (check my feed if you missed it), this replacement rate is 2.1 in Western countries, where sex selection and infant mortality are low. The figure plots the result (if you are technical, this is called the iso-replacement curve). Obviously, if 100% of women become mothers, the average number of children per mother required to reach replacement is 2.1. If we move to 90%, this average rises to 2.33. Notice that if we fall to 80%, the average increases substantially to 2.6. I selected 80% because it implies that one in five women never becomes a mother, close to what we now see in Japan and parts of Southern Europe. The current young cohorts in advanced economies seem to be on track to be well below 80%, but we will not know for sure for another 20 years or so. Having an average of 2.6 children per mother requires many very large families. And modern societies are not organized for this to happen.

https://nitter.poast.org/JesusFerna7026/status/2057462189070430425#m

Published: May 21, 2026 14:03

Replacement fertility in one chart: Even if 90% of women have children and average 2.2 each, we still fall short. Why? The fertility rate of a population equals the product of the proportion of women who have children and the average number of children…