Just sharing on how precise and sharp videos should be ..
India’s ₹37,500 Crore Coal Gasification Scheme Explained | Green Shift |... https://t.co/YcQvV8oU5K
A theme quietly building in 2026:
INR weakness + Yuan appreciation + Import Substitution.
The Chinese Yuan has appreciated nearly 20% against the INR over the last year, creating a reasonably meaningful shift in competitiveness if it sustains.
The market seems to be noticing.
The Nifty India Manufacturing Index is outperforming Nifty this year by a wide margin.
The logic is straightforward:
• A weaker rupee makes Indian exports more competitive globally. • A stronger yuan makes Chinese imports relatively more expensive. • Domestic manufacturers gain from import substitution. • Earnings often follow currency-driven competitiveness with a lag.
We've seen similar setups in previous cycles where currencies did the heavy lifting before profits and stock prices caught up.
Could manufacturing—particularly exporters and import-substitution beneficiaries—turn out to be this cycle's biggest surprise?
#Manufacturing #India #MakeInIndia #Investing #Markets #Exports
best accounts to follow from each frontier lab to stay constantly up to date
Anthropic
@karpathy - must-follow account for AI; recently joined Anthropic
@bcherny - Claude Code creator, always shares great tips
@trq212 - also a Claude Code developer; writes amazing articles on CC
OpenAI
@polynoamial - works on reasoning research, shares a lot of technical details
@gabriel1 - Sora developer, great career path
@jxnlco - works on dev experience, shares a lot about Codex
Google AI
@OfficialLoganK - all the major Google Gemini and AI Studio updates
@ammaar - product and design; shares great things about vibe-coding in Google AI Studio
@fofrAI - cool use cases for generative models
Cursor
@leerob - the loudest voice behind Cursor updates
@ericzakariasson - shares great insights on using Cursor
@mntruell - Cursor’s CEO; major releases and usage updates
xAI
@milichab - recently joined xAI, shares updates on Grok
@skcd42 - also covers major Grok releases
@elonmusk - Elon does a great job reposting and hyping all xAI products
who else did I miss?
I am getting some offers from finance people to teach them python after this went viral! Still waiting for a research lab to offer me a $100million so I can work for 2 years and retire 😂
New blackboard lecture w @reinerpope
How do chips actually work – starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do.
0:00:00 – Building a multiply-accumulate from logic gates
0:16:20 – Muxes and the cost of data movement
0:25:59 – How systolic arrays work
0:39:00 – Clock cycles and pipeline registers
0:51:40 – FPGAs vs ASICs
1:03:14 – Cache vs scratchpad
1:07:16 – Why CPU cores are much bigger than GPU cores
1:11:49 – Brains vs chips
1:15:22 – A GPU is just a bunch of tiny TPUs
Look up Dwarkesh Podcast on YouTube/Spotify/etc to watch. Enjoy!
Ashish Kacholia says his initial capital was only ₹3 lakh which he turned to ₹25 lakh in just 3 years. He also says that if his capital was small, he would do "ruthless churn" i.e. buy & sell, book small profits & not stay invested for long term. Trading gains created capital.
Jane Street just showed the inside of their AI training data center in Texas.
4,032 GPUs. 56 racks. 8,000 km of fiber. liquid cooling running through every server because air cooling can't handle the heat anymore.
but the part that got me was the origin story.
Ron Minsky, who co-heads their technology group. said their first compute cluster was literally six Dell boxes stacked on top of each other at the end of a desk row. they called it "the hive."
the trading systems sat out in the room with the traders because they wanted to be able to unplug them if something went wrong.
at one point, someone vacuuming the office unplugged a live trading system in the middle of the day.
from six Dell boxes and a vacuum cleaner incident to a liquid-cooled GPU data center processing trades in under 100 nanoseconds.
that's a 20-year arc.
Citadel pays $650k/year for quants who use Markov Chains to find regime-switching edges.
This 1-hour MIT 6.041 lecture on Markov Chains gives you the exact same framework quants get paid $54k/month to apply.
Bookmark & watch today. Then read the article below.
Been tracking international stocks using @PPLXfinance
Gives concalls, investor PPTs, Annual reports & latest earnings all at one place. Its the equivalent of stockscans and screener for US cos
A software engineer at Atlassian got laid off in March after 8 years. His response: a 38-minute YouTube video showing how the company's entire tech works, free for anyone to copy. That same quarter, Atlassian's revenue hit $1.79 billion, a record.
His name is Vasilios Syrakis. He worked in Sydney on Atlassian's digital plumbing: the system that handles the company's web traffic, made up of about 2,000 programs running across 13 regions of the world. Every time someone clicks on Atlassian's software, the system Syrakis worked on decides which of those servers answers. Atlassian's own engineering blog wrote about his team's work in February 2025. On Sunday, Syrakis walked through the whole architecture on YouTube, every box on the diagram.
The financial picture doesn't fit the layoff story. Atlassian's cloud business grew 29% year over year last quarter. The company has 350,000 customers, including 80% of the Fortune 500. None of that looks like a company that needs to cut a tenth of its staff to "self-fund AI investment," as the CEO put it in March.
In the six months before the layoffs, CEO Mike Cannon-Brookes sold 866,145 of his own shares for roughly $134 million. Co-founder Scott Farquhar sold exactly the same number on the same schedule. The board also approved spending $2.5 billion to buy back Atlassian stock from the market, a move that props up the share price. The shares still fell 56% this year. Investors think AI lets companies do more work with fewer employees, and Atlassian charges its customers per employee.
Sam Altman called this practice "AI washing" in February. Of the 1.2 million American jobs cut in 2025, only 55,000 blamed AI. The rest had different reasons, or none at all. The engineer who helped build Atlassian's plumbing is now teaching the internet how it works, for free, because he no longer has a paycheck to protect.
a hedge fund emailed me at 11:23 AM in the morning.
i just woke up, heard the email notification from the kitchen and went to check. thought it was something usual, a newsletter or github.
i open it, a recruiter from a hedge fund. checked the domain was real, everything checks out.
he read my article, went through my repo and wants to jump on a call. i never applied anywhere, never sent a cv, never networked, just built and published.
ai-quant-researcher, open source, claude generates strategies and the system kills the bad ones. deflated sharpe as a hard gate, purged cv, leakage detector, kill switch, 111 tests.
https://t.co/wdOteW78gl
in the email he quoted a line from my own article back to me: the deflated sharpe as a hard gate caught my eye, that's not something we see often from outside the industry.
a year ago i was reading lópez de prado on weekends and writing python in the evenings, just because it was interesting. nobody paid me, nobody asked, nobody knew i was doing this.
today there's an email in my inbox from one of the largest hedge funds in the world.
this is how it works.
𝐍𝐨𝐫𝐭𝐡𝐞𝐫𝐧 𝐀𝐑𝐂 𝐂𝐚𝐩𝐢𝐭𝐚𝐥 𝐋𝐭𝐝
𝑯𝒐𝒘 𝑵𝒐𝒓𝒕𝒉𝒆𝒓𝒏 𝑨𝒓𝒄 𝒊𝒔 𝒓𝒆𝒅𝒆𝒇𝒊𝒏𝒊𝒏𝒈 𝒍𝒐𝒂𝒏 𝒔𝒆𝒓𝒗𝒊𝒄𝒊𝒏𝒈—𝒑𝒐𝒘𝒆𝒓𝒆𝒅 𝒃𝒚 𝒄𝒖𝒕𝒕𝒊𝒏𝒈-𝒆𝒅𝒈𝒆 𝒕𝒆𝒄𝒉𝒏𝒐𝒍𝒐𝒈𝒚🤖
Northern Arc has 4 major business segments —
(1) D2C Lending,
(2) Intermediate Retail Credit
(3) Fund Management
(4) Placements — with Technology and D2C Lending is now the biggest driver at 55% of AUM and Concall notes discussed in 👇
Now, let’s look at how Northern Arc’s smart apps are redefining loan servicing.
1️⃣ NuScore – ML Underwriting (The Brain Behind Lending)
Think of NuScore as the brain behind lending — it studies data, learns patterns, and gives each borrower a fair risk score. It helps lenders say “yes” faster while keeping risks in check.
Tech Points:
▪️Pulls credit bureau data (CIBIL, Experian, Karza, Perfios)
▪️If no CIBIL score → uses alternate data (bank statements, utility bills, behavioral signals)
▪️Generates real-time numeric risk score
Result: API returns result instantly to nPOS
2️⃣ nPOS – Digital Loan Origination & Co-Lending (Friendly Front Desk)
nPOS is like the friendly digital front desk — it welcomes customers, collects documents, and connects with partner banks instantly. Everything from KYC to loan setup happens smoothly here.
Tech Points:
▪️Cloud-native, API-first platform; entry gate for loans
▪️Captures applications digitally (branch app, fintech partner, field officer mobile app)
▪️Integrates with Bharat Stack (eKYC, PAN, Aadhaar, Udyam verification, banking checks)
▪️Performs basic validations automatically → eligibility check before proceeding
Result: Sends customer data → NuScore (ML underwriting engine)
3️⃣ Nimbus – Debt Transactions (Engine Room)
Nimbus works quietly in the background — it’s the engine room where large debt deals are structured, tracked, and executed. It makes complex transactions simple, fast, and transparent.
Tech Points:
▪️Auto-generates loan documents, agreements, and e-sign
▪️Uses digital storage for compliance & audit trail
Result: Nimbus ensures funds availability by matching capital (institutional/placement if needed)
4️⃣ AltiFi – Open Marketplace (Investment Gateway)
AltiFi is the open marketplace — it lets everyday investors discover and invest in bonds or debt products with ease. It’s Northern Arc’s way of making alternative investments accessible to more people and Distribution channel for PMS / AIF to retail and HNIs.
Tech Points:
▪️API integrations (BSE, NSE RFQ platforms) → market connectivity for bond/securitised product placements
Result: Tracks performance & reports to investors; opens alternative investments to retail & HNIs
5️⃣ Cross-Segment Technology Backbone (Platform Power)
▪️Cloud-Native: API-first, scalable on Azure + Oracle Fusion
▪️Data: 47.5M+ borrower points → powers ML models
▪️Security: Microsoft Defender, Fortinet, SentinelOne → 24/7 multilayered protection
▪️Analytics & AI: Power BI, Tableau, Elastic → advanced reporting
▪️Omnichannel: Salesforce, Ameyo, CleverTap, WhatsApp → seamless communication
Result: Scalable, secure, data-driven platform supporting all layers (NuScore → AltiFi)
𝑨𝒍𝒍 𝒊𝒏 𝒂𝒍𝒍: Northern Arc Capital combines speed, technology, and human insight to make loan processing seamless. Their nPOS platform enables straight-through processing, handling 18,000–20,000 loans daily with a fully digital end-to-end journey—including OKYC/EKYC, digital verification, and AI/ML-powered NuScore credit underwriting, with disbursal via IMPS, RTGS, or NEFT. Hundreds of partners, from retail lenders to NBFCs, leverage these platforms through API-enabled co-lending or sole lending. By integrating cutting-edge technology with human judgment, Northern Arc accelerates operations while enhancing accuracy, scalability, and customer experience, setting a new benchmark in digital lending.
🚫No buy & Sell reco, DYODD.
𝑫𝒆𝒆𝒑 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝒊𝒏𝒔𝒊𝒈𝒉𝒕 𝒊𝒔 𝒕𝒉𝒆 𝒓𝒆𝒂𝒍, 𝒓𝒆𝒂𝒍, 𝒓𝒆𝒂𝒍 𝒗𝒂𝒍𝒖𝒆 𝒇𝒐𝒓 𝒂𝒏𝒚 𝒊𝒏𝒗𝒆𝒔𝒕𝒐𝒓🙏