Paras Chopra ✓
@paraschopra · time · joined 19 May 2008
life is a game 🕹️ • building @lossfunk
238 854Followers
49Following
43 253Posts total
919.9KViews on collected posts
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As small local models become powerful, I think we are not far away from self replicating LLM worms.
Imagine an open weights LLM copying its weight + harness from network to network, as it mines crypto or encrypts files on the host computer.
These LLM worms will be harder to
9.4K views · 242 likes
· 8 reposts · 26 replies
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The whole Navier-Stokes drama shows how existence proof of something is often enough to build that thing.
This has happened repeatedly in history. Nobody broke the 4 minute mile, but once it was broken, it became a norm.
AI is going to accelerate this trend. Know something
22.9K views · 423 likes
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I think all apps of the future will come with an agent that observes how the user is using the app. It’ll then modify the app dynamically to fix inferred friction points.
The source-code of the app will become fused with an LLM so that app continuously improves automatically.
36.7K views · 1K likes
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@paraschopra i get the sense this is a bad approach for most founders, since most can't raise a large seed round pre-revenue
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@paraschopra Honestly, I have contradictory view. You will be copied anyway and the complexity part already gone with the kind of model and capability we have now. You can build end to end product with model in week time.
Going forward, the vision, creativity and imagination wil
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Because copying startups is becoming easier and easier, we will see new startups remain in stealth for much longer and raise much more money in order to build enough complexity to ensure they’re not trivially copied by the market.
I think we’re starting to see signals of this
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@paraschopra Reality becomes speakable before it becomes countable. In ACE:
Akṣara precedes arithmetic,
Vāk precedes geometry,
articulation precedes quantification.
Mathematics works because reality has already stabilized into lawful patterns before equations appear.
The co
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@paraschopra Math and physics are provably 1:1 corollaries.
More interestingly only a subset of math is actually logical, but it is that subset that mirrors the physical world.
https://t.co/mAQUs0I8fD
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Why math works so well in describing our universe?
Let’s look at it from three perspectives.
1. We grasp the graspable bits
By definition, we model aspects of reality that we are capable of modeling. The remaining part may be truly random or complicated. For example, where do
30.2K views · 84 likes
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There is something that needs to be said about physics education.
Most students suffer from trying to understand the physical intuitions behind the mathematics. Once the physics becomes sufficiently advanced they walk away, frustrated they cannot see the connection.
What those
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@paraschopra To win people's heart and make ur place in the fame industry u have to play the game of fame
and there are 7 rules:
1: Grand appearance
2: Connect with people personally / Do charity for positive public Image
🧵👇👇
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@paraschopra People around the world r just spending most of their time on internet
It's like just spending most of ur time in a big room filled with Books, DVDs, Music player, Letters, Photos, Telephone, Papers, Games...
They r Leaving away everything to just spend time in th
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All my 300+ 🧵 twitter threads at one place: https://t.co/T5LcF7hrqf
Topics covered: mental models, career, life, psychology, book summaries, startups, science, health, systems, economics, products, AI, cognitive biases, and thinking.
👇 Check it out 👇
763.4K views · 953 likes
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Against accounts of the same size
7 posts from the last 90 days, next to the 100K–1M follower range. shown far beyond its own audience, and the audience reacts.
Median views9 378this account6 092median for 100K–1M
Reach, %3.93%this account1.61%median for 100K–1M
Engagement, %2.02%this account0.98%median for 100K–1M
| Metric | This account | Median for 100K–1M | Ratio |
|---|---|---|---|
| Median views per post | 9 378 | 6 092 | 1.54× |
| Reach (views ÷ followers) | 3.93% | 1.61% | 2.44× |
| Engagement rate | 2.02% | 0.98% | 2.05× |
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
3559 Dec
21510 Dec
3.3K21 Oct
30.2K4 Jun
369
1695 Jun
362
48.2K8 Sep
1.7K
136
849
36.7K
22.9K9 Sep
9.4K
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
0.85%9 Dec
1.40%10 Dec
1.99%21 Oct
0.43%4 Jun
0.81%
2.37%5 Jun
0.83%
2.01%8 Sep
0.72%
2.21%
0.59%
3.30%
2.01%9 Sep
2.94%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.98%.
What the audience does
Likes56.8%3 693 in total
Reposts4.0%258 in total
Replies5.1%331 in total
Quotes0.1%5 in total
Bookmarks34.1%2 217 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
Followers by day
9 Sep
Daily snapshots since 09 Sep 2026; the dashed line is the starting count.
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