Naveen Rao ✓
@NaveenGRao · Incline Village, NV · joined 27 Feb 2009
CEO @unconvai. Former CEO MosaicML/Databricks & Nervana/IntelAI. Neuro + CS. I like to build stuff that will eventually learn how to build other stuff.
39 013Followers
975Following
4 999Posts total
18.7MViews on collected posts
Latest posts
Looking for new posts…
This might be the dumbest thing I've ever seen. Ok let's see here...let's ban the economic growth engine of the future and blow our entire lead. Sounds like a great plan for our citizens' prosperity!
3.6K views · 27 likes
· 4 reposts · 6 replies
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Say it with me: this. is. not. SaaS.
All these concentration metrics, CAC, blah blah are just remnants of SaaS dynamics. AI != SaaS. The market dynamics are different, and the concentration is different, the value prop is different, the supply is different (very tied to hardware
25.6K views · 113 likes
· 8 reposts · 29 replies
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Well, this aged well :) Compiler 2.0 is basically this. We just need to start applying some kind of guarantees to time or memory bounds to make it take on larger programs.
4.9K views · 22 likes
· 1 reposts · 2 replies
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@NaveenGRao @RoKhanna Should we just all move to Texas?
1.5K views · 22 likes
· 0 reposts · 7 replies
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@NaveenGRao @RoKhanna could be neurocysticercosis, trypanosomiasis, maybe even my favorite toxoplasma
4.1K views · 15 likes
· 0 reposts · 4 replies
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@NaveenGRao @RoKhanna He mentioned Lisa Su as a California Billionaire he’d tax, weirdly didn’t get the memo that Lisa lives in Texas. He’s the definition of a smart sounds dunce / talking head.
495 views · 5 likes
· 0 reposts · 0 replies
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Seriously worried for this guy’s health. Brain worm? Plaques and tangles? I’m not sure how a previously reasonable person can come up with this crap.
Don’t worry about me @RoKhanna you’ve already chased me out of the state. I just didn’t think it was worth destroying my company
55.1K views · 197 likes
· 11 reposts · 13 replies
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@mcuban Allow illiquid founders to pledge shares with a loan from the government to pay tax. The loan period is long but not infinite (e.g. 10 years). The loan is non-resource: at the end of the period, the loan is either paid back in cash, or the government assumes the shares.
6.2M views · 613 likes
· 27 reposts · 3.2K replies
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Churchill quote that works pretty well here (h/t CFO Ali) ... "Now this is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning." We are embarking on a fantastic journey 🚀
4K views · 21 likes
· 2 reposts · 1 replies
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Un-0 represents a big first step in changing the paradigm of compute to dynamical systems. We are connecting intelligence to dynamics with this model release. Dynamics are a natural framing for compute for AI; neural networks themselves are really dynamical systems so the mapping
4K views · 16 likes
· 2 reposts · 1 replies
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How does this relate to energy efficiency? Most energy in existing von Neumann machines goes into moving information between memory and compute elements. Dynamical systems combine compute and memory into a single entity. What’s more, dynamical systems can tolerate noise. This
5.7K views · 28 likes
· 2 reposts · 1 replies
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Why is this significant? It shows that computing is not some unique invention from humans; it’s present all through nature and physics. All physics of all physical entities has time; however, current computing systems don’t. We’re exploiting that time dimension.
9.5K views · 35 likes
· 3 reposts · 2 replies
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🧠 Today we introduce Un-0 from @unconvAI : the first large-scale generative model build on physics as a compute primitive. This represents a “hello world” moment for physics-based models. We use the inherent time-varying behavior of physical systems to do compute for us. The
11.3M views · 3.6K likes
· 259 reposts · 135 replies
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Can someone make an LLM that takes in Python and spits out optimized [X86, ARM, RISCV, *] assembler code?
That would be so cool. it could even go from [Python, C++, Java, *] to native assembler. Instruct fine-tune it to make PIC or arch-specific optimizations
1.2M views · 541 likes
· 31 reposts · 90 replies
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Against accounts of the same size
9 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.
Median views4 068this account924median for 10K–100K
Reach, %10.43%this account3.62%median for 10K–100K
Engagement, %0.51%this account1.52%median for 10K–100K
| Metric | This account | Median for 10K–100K | Ratio |
|---|---|---|---|
| Median views per post | 4 068 | 924 | 4.40× |
| Reach (views ÷ followers) | 10.43% | 3.62% | 2.88× |
| Engagement rate | 0.51% | 1.52% | 0.33× |
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
5.7K25 Jun
4K
4K
3.3K
2.5K
6.2M15 Aug
55.1K17 Aug
495
4.1K
1.5K18 Aug
4.9K2 Sep
25.6K
3.6K3 Sep
3.1K
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
0.56%25 Jun
0.47%
0.60%
0.27%
0.59%
0.07%15 Aug
0.41%17 Aug
1.01%
0.47%
1.96%18 Aug
0.51%2 Sep
0.60%
1.04%3 Sep
0.32%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes48.0%5 285 in total
Reposts3.2%350 in total
Replies31.5%3 465 in total
Quotes7.3%803 in total
Bookmarks10.0%1 105 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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