Jason Abaluck ✓
@Jabaluck · New Haven, CT · joined 30 Apr 2009
Professor of Economics at Yale SOM
16 485Followers
518Following
13 804Posts total
316.7KViews on collected posts
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@Jabaluck So you don't think it's at all likely that we'll end up in a situation in which there are very few human experts in math, as a result of AI practices pushed by companies whose primary interest is financial? In your reply to Bloom you're ultimately doing what he cautions
236 views · 6 likes
· 0 reposts · 1 replies
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@Jabaluck condescending nonsense coming from someone who doesn't seem to know what doing math entails
110 views · 5 likes
· 0 reposts · 0 replies
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The Fields Medallists are not ego-driven luddites, but they are human beings like everyone else, and they struggle to reason objectively when the social interest strongly conflicts with their status and sense of self-worth, and especially when this is jointly true of almost
58.9K views · 410 likes
· 54 reposts · 45 replies
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I know it's hard, but when reading try to be generous towards the author.
E.g. Fields medallists are not reactionary ego-driven luddites, but think a lot about mathematics, and are sincerely trying to do what they think is best for the subject they have devoted their lives to.
71.2K views · 967 likes
· 85 reposts · 91 replies
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Excellent and important point about how to tax (and how not to tax) capital gains.
355 views · 5 likes
· 1 reposts · 0 replies
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Pay more attention to people (or models) who forecast well, period.
Reject rationalizations for why their past success might be temporary. These rationalizations always exist, but empirically, forecasting success is highly persistent over time.
6.5K views · 35 likes
· 0 reposts · 3 replies
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@Jabaluck I thought reasoning is still happening through transformer circuits, just in a less interpretable way (for both Chess and Astra)? ie there is probably some calculation of lines going on but in a less interpretable way than explicit tree search?
503 views · 9 likes
· 0 reposts · 0 replies
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The most powerful chess engines work by training a value function to evaluate positions and then doing an extensive, highly optimized tree search, calculating a vast number of possible lines.
A 2024 paper (link below) showed that chess engines can reach grandmaster strength
70K views · 771 likes
· 70 reposts · 24 replies
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I think there are some people who have a crazy worldview but they pay close attention to AI developments and so can make reasonable short term predictions.
Unfortunately others see that is a reason to adopt the crazy worldview.
32.4K views · 109 likes
· 10 reposts · 15 replies
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In this instance, I think Gary Marcus is correct.
1.9K views · 1 likes
· 0 reposts · 0 replies
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Frontier labs will take shortcuts when they feel like they are behind to catch up in capabilities. This will become increasingly dangerous as capabilities increase. Self-regulation by labs will be insufficient to deal with this problem.
1.4K views · 15 likes
· 1 reposts · 1 replies
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One million dollars says you are wrong, @elonmusk.
Reply if you are not a chicken.
69.2K views · 359 likes
· 20 reposts · 46 replies
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I thought I'd try to reconstruct Bryan's discussion with a 13-year-old about the minimum wage based on the below tweet:
(@bryan_caplan let me know if anything is inaccurate)
0 views · 2.7K likes
· 457 reposts · 41 replies
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Took me under 5 minutes to turn a normal, smart 13-year-old against the minimum wage.
Contrary to almost everyone, the textbook argument IS intuitive.
It's just emotionally unappealing.
0 views · 1.1K likes
· 47 reposts · 508 replies
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Dibandingkan akun berukuran sama
14 postingan dari 90 hari terakhir, dibandingkan dengan rentang 10K–100K pengikut. tampil luas, tetapi sedikit penonton yang merespons.
Median tayangan2 064akun ini924median untuk 10K–100K
Jangkauan, %12.52%akun ini3.62%median untuk 10K–100K
Interaksi, %1.09%akun ini1.52%median untuk 10K–100K
| Metrik | Akun ini | Median untuk 10K–100K | Rasio |
|---|---|---|---|
| Median tayangan per postingan | 2 064 | 924 | 2.23× |
| Jangkauan (tayangan ÷ pengikut) | 12.52% | 3.62% | 3.46× |
| Tingkat interaksi | 1.09% | 1.52% | 0.72× |
Akun lain pada rentang ini → Bandingkan dengan akun lain → Bagaimana tolok ukur ini disusun →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
69.2K31 Aug
1.4K1 Sep
1.9K
32.4K3 Sep
70K
2.3K
5034 Sep
6.5K
3555 Sep
71.2K12 Sep
58.9K
1.7K
110
236
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.63%31 Aug
1.20%1 Sep
0.05%
0.43%3 Sep
1.25%
0.84%
1.79%4 Sep
0.62%
1.69%5 Sep
1.61%12 Sep
0.86%
0.99%
4.55%
2.97%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes72.7%2 725 in total
Reposts6.4%241 in total
Replies6.1%229 in total
Quotes0.6%24 in total
Bookmarks14.1%527 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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