headoffatness

@88888sAccount But Sportsbet can’t give matched bets anymore. COME ON.

Must follow account for Australians. By these projections we are going to run out of diesel by May 19th. Think about what that means for the economy.

@hot_rails Meanwhile Snowy2.0 is expected to cost $12 billion (without Humelink) and be 7 years late

Australia has plenty of gas, but most of it is in the Northwest Shelf, isolated from the populated east coast. The West-East Pipeline would unify the national market, connecting cheap WA gas to the expensive eastern states. A 2017 feasibility study estimated construction would take two years and cost $5.8 billion, and reduce east coast gas prices by $3/GJ - a benefit of over $2 billion per year! That’s narrow peacetime benefits only, ignoring the project’s strategic value and national resilience. If coupled with a gas-to-liquids plant in South Australia, it would underpin true liquid fuel security for a nation increasingly aware of its dependence on maritime trade.

@plebcapital correlation not causation

Fake tan causes brain damage. Convince me otherwise.

@WhiteHouse Is the war over?

President Trump Delivers an Address to the Nation, Apr. 1, 2026 twitter.com/i/broadcasts/1…

@sir_relaxacat @thmsenglsh winston peters in carbonite, above the entrance to parliament house

@thmsenglsh Capturing Chris Luxon and chaining him to Albo’s desk in Canberra like Princess Leia was chained to Jabba would be great for the national self esteem imoh

"Moi phellow Awstwalians. Twoday oi am announcying that we will be invading nyoo zeelend"

@rationalaussie "Have a good easter. Go on holiday. Nothing to worry about mate"

What's really important in Albo's announcement was what he didn't say. He did not say the war would end soon. He did not say Australia would not send in ground troops. He did not say we have enough fuel long term. That's the signal. Information by omission.

@michellegrattan @ConversationEDU its a good qualification saar

Nearly half our permanent migrants are working below their skill level: former Treasury Secretary theconversation.com/nearly-half-ou… via @ConversationEDU

@10footinvestor goldman interns and vail ski patrol have more solidarity than this lot seem to be able to muster

@headoffatness Get fit or die trying

One thing that's really interesting you are going to see a lot more of in the next few years - is white collar unions Firstly, white collar unions are fucking hopeless. Bankers, professionals, software devs, game devs. Blue collar unions are incredibly evolved by comparison

@horriblelizard Has the PM been taken hostage? Is this a prerecorded doomsday message? Why is the ABC playing Swan Lake?

Did some fucking staffer decide we need a state of the fucking union address

Service station opening times. Send tweet.

@plebcapital I know an OOM when I see one

Lol that was a fat nothing burger. Brb going to drain my swimming pool and fill it up with diesel.

@dannolan Feds trying to figure out who is getting thrown under the bus

ten guys reading news com au are gonna save us

@88888sAccount Love it, but can’t Fkn miss the irony of the AFR productivity summits never arguing for more judges, faster cases, or reforming inefficient judicial practices among these… public servants…

@JoshFrydenberg I was trying to @google your public statements about Christchurch from 2019 when you were Treasurer but couldn’t find anything. AIsaid something about calling for unity, but couldnt provide links 🤷‍♀️ Can you or your office @GoldmanSachs send us a copy ? Cheers mate

@mmjukic Or is that those who actually deploy capital believe AI is sharpe optimal and push messianic narratives to consolidate power via mass unemployment, offshoring, tax evasion, anti-competitive behaviour, defanging regulators, and undermining the social contract? Plus ça change 🤷‍♀️

It's not messianic religious expectation, it's just bug-eyed desperation. An economic deus ex machina from AI is the only remotely plausible way to pay the bill for infinite entitlements, deindustrialization, mass immigration, regulatory strangulation, and collapsing fertility.

A lot of great opinions the last 24 hours guys! Keep em coming!!

@JesusFerna7026 In the words of Oscar Wilde: “Nothing succeeds like excess”

If you're an economist and haven't heard about the double descent phenomenon, you might be overlooking one of the most interesting developments in computer science and statistics today. Personally, I haven't come across anything as fascinating since I first learned about Markov chain Monte Carlo in the fall of 1996. Let me walk you through the idea with an example and a figure from my recent survey “Deep Learning for Solving Economic Models” (check my post from yesterday): 🔗sas.upenn.edu/~jesusfv/Deep_… ◽ Step 1. Draw 12 random points from the function Y = 2(1 - e^{-|x + \sin(x)|}) and plot them in red (panel 1, top left, in the figure I include). ◽ Step 2. Train a very simple single-hidden-layer neural network with a ReLU activation and 31 parameters on these 12 data points. This is a “simple” network, and if some of the jargon is unfamiliar, do not worry; the key is just that this network is small. The result is the blue line in panel 2 (top right). The network captures the overall shape of the data but lacks the capacity to interpolate all points. ◽ Step 3. Increase the network’s size to 2,401 parameters. Now we hit the interpolation threshold: the network can perfectly fit the training data. The blue line in panel 3 (bottom right) does interpolate all 12 points, but it becomes wiggly, oscillating wildly outside the observed data (see the fluctuations between the second and third points on the left). This is the textbook warning we teach in econometrics: overparametrization fits the training data beautifully but performs poorly out of sample. This is the U-shaped bias–variance tradeoff curve in action. ◽ Step 4. Now do something insane: push the network to 12,001 parameters for just 12 data points. Surely disaster must await. Instead, panel 4 (bottom left) shows the opposite: the network fits all the data perfectly and creates a smooth, intuitive curve. It reminds me of the old connect-the-dots puzzles from childhood: instead of drawing a wiggly mess, the network finds the “right” curve you would have drawn by hand. This is the double descent phenomenon: the classical U-shaped bias–variance tradeoff extends into a double dip, where performance out of sample improves again once models become massively overparameterized. So, the solution to too many parameters might be…even more parameters! Or, as we say in Spanish: if you don’t want broth, you’ll get two cups! Why does this happen? I will try to explain our current (incomplete) understanding of this phenomenon tomorrow in another post, as it involves quite a few ideas. But in the meantime, three key points to keep in mind: 1️⃣ We only have 12 points — double descent is not about large datasets. 2️⃣ We are using a single-layer neural network — this is not about depth. 3️⃣ The effect is not even specific to neural networks — you can find similar behavior with high-degree polynomials. 👉 This is why double descent is so surprising: it challenges decades of conventional wisdom in statistics and econometrics. Finally, let me thank @MahdiKahou, my coauthor on much of my recent work on machine learning, for his help in preparing this example. He is the one who truly masters these methods and patiently teaches me about them every day. Anyone who wants to understand this material in depth would benefit greatly from talking to him.