Tarun Chitra ✓
@tarunchitra · Brooklyn, NY · joined 05 Jul 2009
ヽ(⌐■_■)ノ♪♬ @gauntlet_xyz/@robotventures/@aerafinance/@_choppingblock/@zeroknowledgefm
83 840Followers
7 020Following
27 553Posts total
3.3MViews on collected posts
Latest posts
Looking for new posts…
Why is @hosseeb Dwayne the Rock Johnson and why do I look like I should be on Gilligan’s Island
3.7K views · 19 likes
· 1 reposts · 7 replies
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WAKE UP BABE, A NEW CHOPPING BLOCK JUST DROPPED.
$SOL $HOOD https://t.co/xVow847UUq
4.4K views · 3 likes
· 0 reposts · 1 replies
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Having spent my 20s writing many custom physics simulations, there was always the dream of making a “just in time” simulation for everything from hep-th to cond-mat (hell, half of my time @DEShawResearch was spent trying to do this)
Excited to back a team with the ambitions of
15.6K views · 107 likes
· 10 reposts · 7 replies
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Sounds like the FTC is joining the DoJ in learning that @ShengwuLi's notion of auction credibility is important in the wild
h/t @MatheusVXF
https://t.co/HKO9VWcBms https://t.co/cK9rAKYm4Y
2.6K views · 18 likes
· 0 reposts · 3 replies
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@tarunchitra Very cool analysis. This is similar to the literature on obfuscation is online commerce. A classic paper is Ellison & Ellison https://t.co/96c0smvVc0
FWIW, I view this as a ranking problem and designing a better ranker should solve this.
1.3K views · 9 likes
· 2 reposts · 1 replies
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@tarunchitra The 'dark forest' analogy for inference has a few more interesting tidbits:
- providers secretly quantize and reduce the quality of their models in order to serve more competitively
- verification costs on model quality are high. OpenRouter has tried to curb quality
205 views · 5 likes
· 1 reposts · 0 replies
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@tarunchitra Inference capital markets
@0xgilbert
323 views · 6 likes
· 0 reposts · 1 replies
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Every successful marketplace has winners and losers
But some participants make it more of a dark forest than a chessboard
We find some direct evidence for this — and some simple math to make these marketplaces more robust to rogue inference providers! https://t.co/Phgr7ktYdv
139.2K views · 349 likes
· 56 reposts · 42 replies
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Chips as an asset class will be the new crypto
1.5M views · 4.5K likes
· 296 reposts · 964 replies
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Deepseek V4 Flash 0731 Fast⚡️ on @vercel AI Gateway https://t.co/pyQLtIwY0U
192.4K views · 320 likes
· 17 reposts · 36 replies
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🚨 BREAKING:
DeepSeek-V4-Flash-0731-Fast⚡️ is live on @vercel AI Gateway!
pick @wafer_ai as your provider
(ss taken 8.15.26) https://t.co/Cs9M4Ap3EY
41K views · 175 likes
· 7 reposts · 22 replies
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You can see this dynamic pricing in action today for open-weight models on OpenRouter! https://t.co/i8o5zjVcVW
Expect to see other models adjust pricing structure in the coming months too https://t.co/i7KgiWvh9I
37.2K views · 103 likes
· 7 reposts · 5 replies
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the major ai companies should commit to a real time priced API product. ai demand varies wildly over a day/night curve and the industry is broadly extremely capacity crunched. meanwhile agents make dealing with variable pricing, batching, and projecting total costs very easy
265.5K views · 1.7K likes
· 65 reposts · 188 replies
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Introducing Smart Routing in Unity AI Gateway.
Stop overpaying for AI. Smart Routing matches each coding task to the right model and harness based on what the task needs, so higher-cost models can differentiate on intelligence while lower-cost models differentiate on cost and ht
126.4K views · 276 likes
· 48 reposts · 5 replies
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0:37
Ramp Router learns failure rates with an EWMA, models latency with Thompson sampling, then chooses the lowest-cost route to reliably meet each request’s deadline.
We route across providers, models, and service tiers, scoring each combination on reliability, latency, and cost.
4K views · 30 likes
· 1 reposts · 1 replies
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2000s: Conspicuous Consumption
2010s: Conscious Consumption
2020s: Conspicuous Consciousness?
0 views · 1.4K likes
· 193 reposts · 572 replies
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Against accounts of the same size
16 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.
Median views9 992this account924median for 10K–100K
Reach, %11.92%this account3.62%median for 10K–100K
Engagement, %0.74%this account1.52%median for 10K–100K
| Metric | This account | Median for 10K–100K | Ratio |
|---|---|---|---|
| Median views per post | 9 992 | 924 | 10.8× |
| Reach (views ÷ followers) | 11.92% | 3.62% | 3.29× |
| Engagement rate | 0.74% | 1.52% | 0.49× |
Others in this range → Compare with another account → How these benchmarks are built →
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
52614 Aug
37.2K
41K15 Aug
192.4K
1.5M
139.2K17 Aug
323
205
1.3K
2.6K2 Sep
15.6K
4.4K3 Sep
2.5K
3.7K
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
0.95%14 Aug
0.31%
0.50%15 Aug
0.20%
0.40%
0.35%17 Aug
2.17%
2.93%
0.91%
0.80%2 Sep
0.81%
0.09%3 Sep
0.97%
0.73%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes60.6%8 361 in total
Reposts4.6%639 in total
Replies9.3%1 288 in total
Quotes3.7%512 in total
Bookmarks21.8%3 007 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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