vijendar kaira

[Monica @monicaa_AI]

50 Sites That Show What Billionaires Buy and Read for Free🤯

1.) https://t.co/mvAFha3UcY → Current portfolios of famous investors
2.) https://t.co/VjOIL5Kj7A → Quarterly fund trades
3.) https://t.co/pyHuR5ONhD → Stock transactions of US politicians
4.) https://t.co/2L2KSsXhOR → Executives' own company stocks
5.) https://t.co/U0eklGHXcn → Making fund filings readable
6.) https://t.co/lrMexKysa4 → Companies' official reports
7.) https://t.co/w1Em8oLpKl → Buffett's letters since 1977
8.) https://t.co/ext9919w8f → Video archive of Buffett meetings
9.) https://t.co/f2BkyzJiGf → Howard Marks' investor memos
10.) https://t.co/Pp3n1W0if7 → Research from Ray Dalio's firm
11.) https://t.co/8L1ngcmpun → Dalio's principles for free
12.) https://t.co/dno7ADFdiF → Jeremy Grantham's market notes
13.) https://t.co/a8rXDzONYd → Quantitative fund research
14.) https://t.co/mAUpmSgjEX → Damodaran's valuation data
15.) https://t.co/KBUGehAISK → Valuation professor's blog
16.) https://t.co/6SMvHvJlsr → Morgan Housel's money writings
17.) https://t.co/NMqdV93mXJ → Mental models for decision-making
18.) https://t.co/px8LaAqr6D → JPMorgan's free market guide
19.) https://t.co/ek9boIMk0V → Innovation-focused fund research
20.) https://t.co/Z0uXDnZMSk → Venture capital essays
21.) https://t.co/GX9jOaFzG6 → Value investing lecture notes
22.) https://t.co/hxvNeFPJ8M → Columbia's value investing archive
23.) https://t.co/BafbVYJP4x → Fed's economic data archive
24.) https://t.co/hKNAg2TfFf → Fed decisions and statements
25.) https://t.co/bNBsCvLcZh → European Central Bank data
26.) https://t.co/DOfFtQZpGy → Reports from the central bank of central banks
27.) https://t.co/BNCg0sGiUT → Countries' economic indicators
28.) https://t.co/pXQ2FkAO7f → Companies' long-term charts
29.) https://t.co/dEgHv3yC3E → Company financials for free
30.) https://t.co/9ixwpGlIHT → Companies' market cap rankings
31.) https://t.co/7MqH62ojVK → Stock screener and heat map
32.) https://t.co/6IdMnRTpi7 → Portfolio backtesting
33.) https://t.co/3CZcOYGdXT → Charts and market analysis
34.) https://t.co/WbRaajTSo7 → Professional market screener
35.) https://t.co/yYXBrk2AHB → Company activity reports archive
36.) https://t.co/NtKuBPtENy → SEC's investor education site
37.) https://t.co/OkbIKghb5c → Passive investing encyclopedia
38.) https://t.co/KOdlzRNGH8 → Financial terms dictionary
39.) https://t.co/t6ETCJ4rWm → Free finance guides
40.) https://t.co/kDj8uBsVIR → CFA research publications
41.) https://t.co/npCqge3hok → Fund and stock evaluations
42.) https://t.co/sJfn3Flo4t → Companies' visual analysis
43.) https://t.co/c1INhDEcGY → Archive of selected investment theses
44.) https://t.co/6usagzjipB → Seeing what's inside funds
45.) https://t.co/WG6x4PmYuA → European fund backtests
46.) https://t.co/tMK10BK7xU → Investment writings with data
47.) https://t.co/dlhu9JPkmM → Market history notes
48.) https://t.co/fmp9hAQK64 → Investor psychology writings
49.) https://t.co/DMaTpZMCB3 → Explaining the economy with charts
50.) ourfiniteworld? → (see note)

The rich don't hoard information. They just don't tell you where it is.

Save it, follow @monicaa_AI you'll need it.
Not investment advice.

[Swapna Kumar Panda @swapnakpanda]

The BEST one there for Agentic AI.

Absolutely beginner friendly. Covers every topic.

https://t.co/03jDhYP07L

- Langchain
- Langgraph
- RAG
- Vectorless RAG
- Deep Agents
- Guardrails
- LLM Evals
- LLM Gateways

Give 30 mins to 1 hour everyday. You won't regret at all.

[Swapna Kumar Panda @swapnakpanda]

Go GOD Level in Agentic AI by finishing these practical courses:

[Callan @callanxai]

Andrej Karpathy:

"Prompting is going away. Delete everything, keep Graph."

In 69 minutes he shows how to build Graphs, and why it's the only thing that will be left standing at the end

Prompts → Agents → Loops → Graphs

a loop keeps one agent working until the job is done

a graph decides which agents exist and what each one hands to the next

anyone can build an agent, almost no one builds the graph that runs them

watch it today, then save the full guide on Graphs below before everyone catches up ↓

[Sebastian Raschka @rasbt]

Reasoning from scratch, round number 5! This time, talking about log-probability scoring (also a great fundamental concept for loss functions like cross-entropy in pre-training and distillation) and self-refinement.

00:00 Introduction and inference-time scaling recap
05:02 Loading the pretrained LLM
08:00 Comparing and scoring model answers
10:18 Building a rule-based scorer
17:53 Token probabilities and sequence likelihood
26:47 Computing token probabilities in PyTorch
30:12 Token indexing and shifted targets
37:27 Log probabilities and numerical stability
45:57 Scoring answers with average log probabilities
56:24 How self-refinement works
59:07 Generating critiques and revised answers
1:01:00 Implementing the self-refinement loop
1:05:57 MATH-500 evaluation results
1:07:35 Takeaways and next steps

[Crypto Gideon(🧠,🧠) @CryptoGideon_]

Robotics sector is what AI was few years ago: GOLDMINE.⛏️👑

The whole sector has less than $900M MC.👀

Projects worth researching:

-> $VIRTUAL
-> $PEAQ
-> $CODEC
-> $WOON
-> $SR
-> $ST
-> $ROBO
-> $AUKI
-> $DEUS
-> $SAPIEN
-> $SLC
-> $ROBA

Anything else I missed?
Data: @coingecko 📊

[vijendar kaira @vijendargoudkai]

@theunipcs $dream @dream_cloud_inc

[Lukas Ziegler @lukas_m_ziegler]

Massive week in robotics.

I went through everything from Figure, Agility, Boston Dynamics and even more.

Get your coffee and see what happened in robotics space:

[Dustin @DustinHuntwn]

$META CEO, Mark Zuckerberg, basically said that the EASIEST way to get RICH is to buy the AI Bottleneck Suppliers to Meta.

Here are 5 stocks that can 10x:

1) $NBIS

[Shay Boloor @StockSavvyShay]

WHO GETS PAID TO BUILD A HUMANOID ROBOT

Who builds the robots | $TSLA, $XPEV, $MBLY, $CCXI
These are companies designing & assembling finished robot that ultimately gets deployed into factories, warehouses & eventually consumer environments.

Who gives the robot intelligence & compute | $NVDA $GOOGL $META $INTC $QCOM
These are companies building AI models, software & silicon that allow humanoids to understand instructions, reason through tasks, process their surroundings & control movement in real time.

Who lets the robot grip & feel | $NOVT, $VPG
These are companies building dexterous hands, force sensors & tactile systems that allow humanoids to grasp objects, control pressure & perform really precise physical tasks

Who lets the robot see | $OUST, $INVZ, $AEVA
These are companies supplying cameras, LiDAR & 3D sensing systems that allow humanoids to recognize objects, measure distance, navigate environments & understand whats happening around them

[mezma ⭕ @Mezma00]

@Geiger_Capital i am

[OpenAI @OpenAI]

This is GPT-6 Astra.

Anything you can do on a computer, Astra can do for you. Fast.

[Mr. Buzzoni @polydao]

I HAVEN'T OPENED CLAUDE AT MIDNIGHT SINCE I BUILT THIS FOLDER

I used to wake up, check what broke overnight, fix it by hand

-> now the receipts are already sitting there when I wake up. dated, graded, waiting on my review

what's actually inside the folder that took over the night shift:

• the contract
> CONTRACT.md - the shift rules, committed
> contract.local.md - my personal overrides, gitignored

• the harness (.claude/loops/)
> settings.json - spend caps and timeouts, set once
> schedule.yml - when the next shift fires
> rubrics/ - code.md, writing.md, safety.md - the graders catching what I'd miss
> pr-hunter/ - plan.md wakes it, https://t.co/VUDfqGE1Fp does the work

• the state
> receipts/ - one folder per shift, 5,382 kept so far
> trace.log - exactly what happened, no guessing
> checkpoint.json - resumes where the last shift stopped

• the edges
> https://t.co/agzjvw6VbF - my panic file, never once used
> .mcp.json - the tools it's allowed to touch

the folder runs the night shift now. I just read the receipts in the morning

[Rehan Sheikh @rehan_shei]

Minimax H3 Max has generates video faster than you can watch it so I hooked it to a twitch livestream! Now you can watch infinite interdimensional cable - link to the stream below

[Amisha Yadav @amisha_explains]

Officially from INDIAN IITs 🇮🇳

No fees. No entrance exam. No catch.

Here are 19 courses that are better than most paid bootcamps:

1. Artificial Intelligence: Foundations and Algorithms
🔗 https://t.co/oSYHBy2CAo

2. Introduction to Large Language Models (LLMs)
🔗 https://t.co/cb50yjV59U

3. Digital Marketing in the AI era
🔗 https://t.co/cY4BAnSMKI

4. Ethical Hacking
🔗 https://t.co/Vt6zK7tKzl

5. Generative AI for Computer Vision
🔗 https://t.co/GoFZOqhaOm

6. Cloud Computing
🔗 https://t.co/s3eKQ4kO5I

7. Data Science for Engineers
🔗 https://t.co/bc2P6F5Jsd

8. Computer Vision
🔗 https://t.co/sw0ODnKZkb

9. Cyber Security and Privacy
🔗 https://t.co/iqFHf8TPii

10. Corporate Finance
🔗 https://t.co/AMT78OsBlw

11. Database Management System
🔗 https://t.co/dFPgDFun9i

12. Data Structures and Algorithms using Java
🔗 https://t.co/X8UsoouHO6

13. Data Structures and Algorithms Design
🔗 https://t.co/kuixtbaTCD

14. Introduction To Operating Systems
🔗https://t.co/yq2e4gr2S9

15. Natural Language Processing
🔗https://t.co/NW57eofXXt

16. Programming In Java
🔗https://t.co/OAyT6kLYAz

17. Programming in Modern C++
🔗https://t.co/0E3lquqUpM

18. Programming with Generative AI
🔗https://t.co/MItYoWr2bF

19. Python for Data Science
🔗https://t.co/mCcMpCOsA3

[Noisy @noisyb0y1]

He is 18 works 10 jobs at the same time makes $200k a month - and AI makes all the decisions for him:

00:20 - how AI makes 1000 decisions for you and saves 90% of your time
34:36 - one agent makes better decisions than a person with 20 years of experience
01:09 - from zero to $200k a month - 10 businesses where AI does everything

after watching I realized I was spending 90% of my time on decisions that AI makes better and faster than me.

watch it - then read the guide below on how to delegate 1000 decisions to AI and free up 90% of your time.

[Ridark @ridark_eth]

I gave Elon Musk's new Grok Bot an org chart instead of a to-do list, and in one week I stopped being a founder who does the work and became one who assigns it.

eight bots. one org chart. nobody sleeps but me. here's the whole design, steal it.

step 1 → 0:01 What we're covering
step 2 → 2:01 Installation & Setup
step 3 → 3:14 Building the First Bot
step 4 → 8:18 Teaching by Screen Recording
step 5 → 14:18 Putting it All Together

THE ROSTER:

Atlas, chief of staff. the only bot I talk to. I give it outcomes, never tasks. it decomposes them and delegates to the team in group chat, and it never does specialist work itself. it posts the plan every morning and what shipped every night, and it only comes to me when a decision is irreversible or spends money.

Scout, research. finds and qualifies my ICP. every day: 25 verified prospects, one line on why they need us right now, and a source. if it can't verify, it marks it unverified. it never guesses.

Quill, content. turns what the company learned this week into 5 posts and 1 long piece, in my voice, matched from the last 50 things I wrote. drafts only, it never publishes.

Pitch, outbound. writes a first touch and two follow-ups for everyone Scout marks ready. 60 words max, one specific observation about their business, one clear ask. queued in drafts, I approve in bulk.

Vault, inbox and ops. triages everything into needs-me, needs-a-bot, needs-nothing. it handles the last, routes the middle, and gives me five bullets on the first by 9am.

Ledger, analyst. one report a night: what moved, what didn't, and the single number I should care about tomorrow. no dashboards, no adjectives.

HOW THEY'RE WIRED
one group chat per outcome, not per person. Atlas sits in all of them. the bots hand off inside the chat, so I only read the handoff, I never manage it.

two rules that made this actually work:
1. every charter ends with a hard "never do this without asking" line. autonomy without a fence is just chaos on a schedule.
2. show once, don't describe. I ran the full workflow on my screen one time. that single demo taught them more than a page of instructions ever could.

WEEK ONE
214 verified prospects delivered. 89 personalized outreaches queued and approved. inbox at zero every morning. 11 content pieces ready.

THE POINT
most people are still treating Grok Bot like a smarter chat window. it isn't. it's the first time one person can own an org chart instead of a to-do list. my bottleneck was never how much I could do, it was how much I could hand off.

bookmark this.

[Pritam Chauhan @Im_pritam18]

Day 27 / 100 of preparing for AI ML role

[Dipanshu Kushwaha @Dipanshu_AI]

INSTEAD OF WATCHING NETFLIX TONIGHT. Spend 2 hour with this. Claude AI FULL COURSE that teaches you how to BUILD and AUTOMATE anything. The people who watch this tonight will wake up tomorrow with a new skill. Watch it and bookmark it now.

[Daniro @Dan1ro0]

This trader used Claude to build a Quant Bot and made +$130,992 on Polymarket

29,721 predictions in 132 days with a 50% win rate

How is this account bringing in about $992 per day? The logic is simple:

1. It focuses on short crypto “Up / Down” markets, averaging roughly 9 trades per hour
2. Instead of relying on one entry, the bot appears to build its position gradually as the probabilities change throughout each window
3. It can take exposure on one outcome first, then wait for a favorable move before adding the opposite side and locking part of the position into a hedge

This trader’s Polymarket account: nagi777

Most profitable trades:
$54 → $1,165 (+$1,111 +2,077.2%)
$28 → $1,127 (+$1,100 +3,961.7%)
$234 → $1,311 (+$1,077 +459.8%)

A 50% win rate is enough for this system because the result depends on how each position is constructed and modified over time, not simply on finishing more markets on the winning side