Deedy Profile picture
Sep 24, 2019 6 tweets 2 min read Read on X
1/ The Fairness of High-Skilled Immigrants Act, 2019, or #HR1044/#S386, which would've removed country caps on green cards in the US for Indian and Chinese nationals, particularly bringing the wait time for Indians from 150yrs to ~10...
2/ ... was blocked in the Senate by Sen. Dave Perdue after bipartisan support in the House. If you were Indian and moved to the US for an undergraduate degree in 2001, you'd be 36, have spent half your life in the country and not have a green card.
3/ You might be married with kids but if you lose your job, you might have to leave your family after paying for a college degree and 14yrs worth of usually fairly high taxes. Isn't that absurd?
4/ Despite being Indian, and a beneficiary of this bill, there are problems with this bill. One, most Indians in the backlog are not high skilled tech workers, but cheap outsourced labour from IT consultancies like Wipro and Infosys.
5/ Two, without a smoother cap removal transition plan, this would essentially flood the green card quota with Indians for the next ~10yrs, throttling competent candidates of other nationalities.
6/ If those two issues are fully addressed, I this bill will be unanimously favored and @sendavidperdue will let it pass and hopefully Trump will sign it!

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More from @deedydas

Jul 31
🚨Anthropic is at $4.5B annualized revenue and is the fastest growing software company in history!

They just overtook OpenAI to become the market leader in LLM API cost.

We just dropped this and more in our mid year Enteprise AI report:

1/7 Image
Enterprise LLM API spend has exploded from $3.5B to $8.4B by mid year, and that number is already stale!

2/7 Image
Enterprises and startups are choosing closed source models.

Only 11% of enterprises show high open source model usage.

3/7 Image
Read 7 tweets
Jul 31
Microsoft just leaked their official compensation bands for engineers.

We often forget that you can be a stable high-performing engineer with
great work-life balance, be a BigTech lifer and comfortably retire with a net worth of ~$15M! Image
On the top chart:
Blue is base, purple is stock, green is bonus
Read 4 tweets
Jul 22
The best open-source AI model just dropped a detailed report on how it was trained, a rare resource for students given no frontier lab is publishing!

Kimi K2's estimated total cost of training is ~$20-30M, roughly in line with pricing: $0.6/M in $2.5/M out tokens.

10 highlights:Image
1. Generating tokens by rewriting high-quality tokens with LLMs in pre-training
2.  Mining 3000+ MCPs and using LLM-generated personas to improve agentic tool calling
3.  10,000 parallel Kubernetes sandboxes to solve Github issues
4.  New scaling laws for sparsity in MoE models
5. RL with verifiable rewards (RLVR) for math, coding, safety with self-critique model with long-reasoning penalty, causing direct, desisive answers
6. Training recipe of 4k sequences, then 32k then 128k with YaRN
7. High temp during initial RL training to promote exploration
Read 5 tweets
Jul 18
The hardest high school math exam in the world, the 6 problem 9 hour IMO 2025, was this week.

AI models performed poorly.

Gemini 2.5 Pro scored the highest, just 13/42, costing $431.97, in a best of 32 eval. Bronze cutoff was 19.

Long way to go for AI to solve hard Math. Image
Here's a more beautiful visualization of model performance on MathArena Image
Read 5 tweets
Jul 16
Most important tech blog this year: OpenAI engineer and ex-founder of $3.5B Segment wrote a tell all post about how OpenAI works internally.

From obsession with X, devout use of Slack to engineering culture and tech stack.

A peek under the hood of a generational company. Image
"this company runs on twitter vibes" Image
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Jul 13
I'm using the best AI models to bet $1000 on Polymarket!

Asked it to use modern portfolio theory + bet sizing to make calculated bets. It chose everything from BTC price to Fed rates.

Expected returns:
o3-pro: +21.6%
opus 4: +41.7%
grok 4 heavy: +34%

Will report back who won. Image
Wanted to use Gemini 2.5 Pro too but on AI Studio, it did not search the web. I’ve kicked off a Deep Research and will report back under this thread.
Prompt:
“Check on the odds on Polymarket and tell me the most mispriced assets I should bet on from first principles reasoning. You have $1000.

Please do deep research and present precise odds on each bet. Use advanced math for trading. Draw research from authoritative sources like research and unbiased pundits. Size my bets properly and use everything you know about portfolio theory. Calculate your implied odds from first principles and make sure you get an exact number.

Your goal is to maximize expected value. Make minimum 5 bets. Write it in a table.”
Read 4 tweets

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