Quant mind. Human heart. AI - Markets. Building AgentZ from India → World
Bengaluru
Based in India
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Most trading ideas never make it to a proper backtest to Deployment cycle .
We have curated a solution to change that -
Agent Z
Describe your strategy in plain English, and Agent Z helps turn it into a structured workflow across research, backtesting, validation, and deployment readiness using AI agents and frontier models.
As a closed beta user, you get early access to an AI-native trading workbench designed to help you test strategy ideas in a fraction of the time.
You bring your market knowledge, Agent Z brings the agentic workflow, model access, coding support, and connected context.
The best part - you stay in loop at every step.
Apply for early beta access: tally.so/r/OD8ANK
AgentZ
#FirstLook
12 Agent collaborating and helping you from backtesting to deployment in live Markets.
You express!!
Agents implement!!
Coming soon!!
Algos Sabh ka hain boss
#NIFTY #systematicTrading #algo #agents #AI
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Neel Samadder retweeted
I've done a complete U-turn on my opinion on open source AI. We should be careful (and probably disallow release) of models on par with current open source Astra/Opus level models.
AI is now reverse engineering games from binaries and remaking them. Reverse engineering games is a very hard problem. If this is possible then reverse engineering banking software, ID systems (Aadhaar), flights, etc is possible too. A game ships its binary to every player. Bank and Aadhaar backends are protected by servers, but it's unlikely the security teams at these are smarter than advanced AI that can do this to games.
We are protected rn because a Claude will refuse to tick "I'm not a robot" on websites. When OSS models don't respect that, we have a looming cybersecurity problem. Apologies I didn't see this earlier.
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Neel Samadder retweeted
Release 🚨
America dot gov is boring. I am happy to release 275k public Indian gov documents parsed from 15k gov websites. 322k official PDFs and on 128 topics, available to plug and play into any RAG frameowrk of your choice. Both raw data and cleaned data available in csv, parquet and SQLite format. At least 50k pages are useful. :D
Will be updating this to 20 Million documents by month end (process running on JarvisLabs autonomously. Happy to share tracking link for those interested)
Go build your Indian gov chatbot. No license, no credits needed. <3
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AI-designed proteins are becoming real.
Bro’s first thought
we need to watermark this shit.
We invented DRM for the building blocks of life before GTA 6.
Capitalism remains undefeated.
Very happy to announce that our team @GoogleDeepmind has pushed the boundaries of generative biology, achieving the successful synthesis of AI-designed proteins that are both functional and watermarked.
This proof-of-concept watermarking of the building blocks of life is enabled by SynthID Bio, our new protein watermarking method. It is designed to safeguard the new era of AI-powered generative biology and strengthen global biosecurity.
You can read my thoughts here on why watermarking AI-designed proteins is an important research breakthrough: x.lingyaoai.com/pushmeet/status/210531…
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Where does money invested into the AI buildout actually go?
For every $100 flowing into the supply chain:
- $50 to chips
- $20 to power
- $15 to networking
- $15 to cooling, buildings, and land
More charts in State of Markets II: a16z.news/p/state-of-markets…
Introducing our State of Markets pt 2, along with a companion podcast where we unpack the data and discuss what comes next.
Tech is the everything cycle.
Supply: putting the buildout in context, just passed railroads as % of GDP. The wisdom of Elon is real: the factory (or the datacenter!) is the product.
Demand: diffusion is so, so early. Median AI vendor spending in the top 1% of companies is 8x that of the top 10%. Only about 30% of S&P 500 companies report a quantified AI impact, which means there’s a substantial opportunity in connecting models to a company's data and workflows. Diffusion into companies is one of the main themes of the next 5 years.
We’re entering the agent work period. Only a few million users today, but applicable to billions of internet users with massive surplus created. META/GOOG monetize US users at $200+ per year today. Agent opportunity is much higher.
Mega-trends the next 5 years: Consumer agents, Robotics, Autonomy, AI x bio, Personal health, Diffusion into enterprise, New era of American Dynamism.
Much more in our SoM report here - a16z.news/p/state-of-markets…
@a16z @sarahdingwang @aleximm @santiago__rdz
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all software is becoming malleable, so it was important for us to support this as a first class citizen in Claude Code, I hope more and more software becomes extensible like this!
here are some of what I'm most excited about with mods:
You can now mod Claude Code:
- Change how it behaves
- Customize the UI
- Swap in your own features
Write one with a few lines of TypeScript, or have Claude build it for you. Mods ship inside plugins, so you install them with /plugin in the CLI or desktop app.
A few examples:
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Build your own harness, folks!
One of the biggest benefits of building my own meta harness is how smoothly I can switch between models.
I feel like this is becoming more important as model release times shrink. RSI will only scale releases.
This has been one of the best decisions I made since last November.
Switching models can really break things, but it shouldn't. If it does, your setup isn't ideal for this insane release cycle we are in. You need to fix that now.
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If you can have a $20 AI subscription and haven’t taken one because the free version does it for you !
Trust me you have no clue what the paid versions can do!
Only when one start using
You learn the true limits of SOTA models #cheap intelligence
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There is no loyalty towards LLM models
It’s all abt productivity
if you deliver what you promise take my money simple!
Lots of discussion out there about our next model(!), so I wanted to give an early look as soon as possible. Introducing Gemini 4 Argon!
It shows frontier performance in complex workflows, cyber defense and software engineering. Teams are using it extensively at Google, from coding to quantum computing, great feedback.
Here’s a look at the benchmarks:
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company OS (org harness) vs personal agent, similarities and differences:
differences:
- Many principals (users), one actor (agent): will need to be multiplayer, handle multiple users (sometimes even in same thread), and as a result handle auth/memory correctly
- governance: observability, auditability, admin control plane matter way more
- interaction pattern: more event driven and async
similarities:
- should be able to write/execute code
- browser use likely very important! (key difference from a coding harness)
- skills/MCP as standards
- core agent loop/logic
what am i missing?
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Okay !
I think this is ChatGPT taking on google head on?
I’m excited to announce my partnership with OpenAI. We have some interesting things coming up, and I can’t wait to share them with you.
I’ve always been curious... One question usually leads to another, and ChatGPT has certainly encouraged that habit. But it has also proved useful when I’ve needed to get things done, like planning my last trip with the family.
That’s what I’m looking forward to with this partnership. Discovering what else I can do with ChatGPT, sharing what I find useful, and encouraging more people to give it a try with something they care about.
A question, an idea, something you’ve always wanted to explore. There are so many places to start.
Looking forward to exploring together.
#Partnership
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As of right now (no future talk), what digital tasks do you think the *average* human can do better than 5.5?
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