Kate Huggins @Huggette

@emptingto @cusackandrew Yes

AI investment is not a capital budget it’s a loan book. Long but worthwhile read. open.substack.com/pub/groundbrea…

@buccocapital I buy it

@DaveTaylorNews The Range Rover post made me laugh. No fun getting hacked though.

Mixed feelings about this. Every service previously provided for love is having to be repurchased from a private company (albeit in this case via gov spending). Governments love the GDP boost. The family is measured as better off but ends up paying more to enrich investors.

Forbes @Forbes

2 weeks ago

Havi Nguyen grew up managing Medicaid for her family while working at her parents’ nail salon. Now the Abby Care founder is helping others navigate America’s byzantine health care programs by using her AI-powered app to become paid caregivers for loved ones.

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Similar discrepancy in Australia. Reversed if you show this for the median household of course.

Stephen Moore @StephenMoore

2 weeks ago

Americans now pay more in taxes than they spend on food, clothing, and shelter combined. Think about that. Government has become so big and bloated that taxes cost more than life's basic necessities. Every American taxpayer should be outraged.

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@bowtiedstocks Hyperscalers are subsidising these deals to such an extent it’s hard to resist. Companies will live to regret it when their growing tech costs massively outpace the labour cost saving and performance flatlines.

@SenSanders Elon’s income from wages is nowhere near the tax cap. Payroll taxes are now how you tax the rich. Unless you’re talking payroll taxes on A.I. agents (which would look more like a tax inference).

Articulate defence of short sellers

zerohedge @zerohedge

2 weeks ago

Leopold Aschenbrenner's Short Seller Fairy Tale zerohedge.com/markets/leopol…

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“In Australia, the cash rate transmits through variable mortgages within weeks. In America, the long bond is the transmission mechanism. Warsh is imposing genuine rate hikes on the parts of the economy that need them without ever touching the funds rate” afr.com/markets/equity…

@Quillette I thought Page captured Nolan’s version of Sinon brilliantly

@xiaowang1984 ‘Hidden’ advantages of gas infrastructure.

Big red pill moment for me is realizing that that $50 a MWh fuel price for natural gas that everyone says is a disadvantage relative to "zero marginal cost" solar and wind gen actually embeds the cost of the entire storage (order 100s TWh) and transport infrastructure (all those pipes) to move it from the Marcellus to you 🤯

New York Energy Alliance @NYEnergyAllies

3 weeks ago

"Just add storage." It's worth slowing down on that sentence, because we're now in day two of a stretch of rain. Yesterday, every solar panel in New York: utility-scale and rooftop together, produced 4% of the state's electricity. At its single best hour, 11%. Think about the

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Recently I've flipped from being bullish to being bearish about AI. I think I'm updating my bearishness to be more solidly bearish. Early thoughts (which I hope to be disproven in the next year or so, I would prefer progress) and my reasoning: The whole 'it turns out if you keep training and scaling the models more they develop broad new capabilities in lots of domains' thesis is wrong (sorry Demis). The recent batch of models haven't got more general, they've got less general. This is most obvious in the fact that their language outputs have got much worse in comparison to e.g. o3. If they were gaining generalist capacities we would expect them to be describing their work in ever more graceful and comprehensive prose! The image that was being shared as the AGI thesis (November 2025, Tomas Pueyo) was the spiky bubble that has a current spike or two out past human capabilities (e.g. on coding or math) but below human on other capabilities on the other spikes - the future prediction was that as the models scale/advance, every spike would grow bit by bit until the whole center encompasses the human capabilities, with super-superhuman on some spikes. I think it seems like what's actually happened in the last few models has been that the coding/math spike has grown, but leaving behind or even at the cost of the other spikes. The models are no better at some simple logic, language (and sometimes worse!). This makes sense from a simple RL perspective; you can't RL something endlessly on one domain of tasks and expect it to improve on the other tasks. The fact that early LLMs did seem to improve generally was a byproduct of the written language corpus covering everything - that corpus is general, so training it on that gave the appearance of something generally intelligent and becoming more generally intelligent as it got better at replicating that corpus. But the actual logic and underlying ground truths behind the language aren't captured efficiently enough and weren't effectively RLd in - they top out at some point (I guess this happened around the time that there was the 'has scaling hit a wall' discussion in late 2024). Chain of thought was then a genuine breakthrough, along with web search, which plugged into that general LLM global-corpus intelligence to lead to post 2024 gains. The AI companies have since worked out that coding works (and pays) really well (basically this is because the entire job is nearly perfectly recorded and exists as training data, and you can set up clear benchmarks and rewards). The recent models (and benchmarks) have been maxxing that and we've seen degradation on normal English use for that reason. This could still be transformative, leading to extremely powerful (and potentially dangerous, particularly in cyber security) models but it's not a pathway to AGI. I'm probably at about 40% confidence about this. It fits my current observations of AI progress and has a basic explanatory model. It doesn't account for potential breakthroughs, which is a major reason for discounting. To make some predictions, I guess if I'm right this will become broadly apparent and more widely acknowledged in the next year or two, as we see how the spikiness of models that keep getting released develops. Maybe there will be efforts to concentrate on specific spikes e.g. health or law which require going back to earlier models and RLing on a different data set/with different rewards/benchmarks. Maybe those separate models can be linked together to give a more apparently general model. How capital intensive that is/the potential profitability will be a defining question. But I just don't see general abilities emerging atm, and I don't think we will any time soon. Good news - a whole industry of tackling important specific problems/sectors can open up!

@TheEconomist @elonmusk @zannymb But he thinks money matters right now. The point is be sees A.I. driven productivity as the only way to address the debt crisis / trajectory. As he says, getting from here to there will be ‘bumpy’

I asked Grok to review my history and tell me what priors needed updating. You should try it. I am susceptible to crash predictions and underestimate the way complex systems adapt / muddle through.

It’s not a ridiculous idea but can’t see it working. Knowledge is inherently cumulative, non-rivalrous, and not “owned” like finite physical assets. Fair Use will continue to be interpreted in favour of model owners based on A.I. being transformative not substitutive.

Katherine Brodsky @mysteriouskat

3 weeks ago

Hunter Biden thinks that because AI uses our collective knowledge throughout civilisations, companies that use it should share their profits with us. Do you agree?

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Postponing having kids doesn’t always mean fewer kids

Cameron Murray @DrCameronMurray

4 weeks ago

Really interesting article today from the ABS on Australia's fertility trends. Complete Cohort Fertility is much more stable than the overall fertility rate. abs.gov.au/articles/compl…

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It’s happening isn’t it?

zerohedge @zerohedge

4 weeks ago

Carnage in hyperscaler bond land: IG bond spreads exploding every day, as credit investors refuse to fund memory chip purchases any longer. CDS are following. For now, stocks are completely ignoring what is going on wit bonds

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@PinguCapital @simongerman600 I think so. It’s so hard for kids now. Social media make them feel like they’re learning the rules of the social game but then when they try it out IRL, one humiliating moment and they withdraw to phone. Alcohol softens the edges, helps them take more RL social risk 🤷‍♀️