Anand Doddur

AB | ಮಹತ್ವಾಕಾಂಕ್ಷಿ | views not to qoute |

[Anand Doddur @doddur]

🏏😊 #CricketTwitter

[Vala Afshar @ValaAfshar]

Never regret a day in your life. Good days give happiness, bad days give experiences, worst days give lessons, and best days give memories.

—Professor Richard Feynman

[Dr.A.P.J.Abdul Kalam Residential School Bagalkote @mmrsnavodayabgk]

Proud Moment 🎉

Dr. APJ Abdul Kalam Residential School, Bagalkote achieves 100% result in CBSE Class 10th Exam 2026.

Appeared: 63 | Pass: 63 | 100%

Congratulations to all teachers & students! 👏

#CBSE #Karnataka #CBSEResults2026 #Bagalkote #KarnatakaEducation
@DOMGOK

[Anand Doddur @doddur]

@sahneydeepak Sir, have you identified any stocks with growth potential by 2030?

[Anand Doddur @doddur]

@SamirPradhann Sir Kpitech?

[Anand Doddur @doddur]

Inaugurated the 2025-26 Annual Sports Events at @mmrsnavodayabgk

[Harsh Goenka @hvgoenka]

Frightening changes predicted by Vinod Khosla on the future of AI! Be prepared.

[Sachin Tendulkar Fan Club 🏏 @CrickeTendulkar]

In case you didn't see anything Great Today.

100 Sixes of Sachin Tendulkar.😍
Enjoy

[Black Hole @konstructivizm]

A visual model of the Earth from the beginning of time to the present day.

A ma is a unit of time corresponding to 1 million years. The plate tectonics reconstruction is based on paleomagnetic data, although it may be imprecise. The temperature, atmospheric composition, and length of day that might have existed at that time are also shown.

☄️ BLACK HOLE. Subscribe.

[Balaji @balajis]

What comes next for AI? Perhaps physically specific intelligence, more than artificial general intelligence.

Here’s a draft thesis.

(1) First, AI is now entering the trough of the hype cycle. Every tech, no matter how amazing, goes through this. It’s actually one of the best times to invest and build once the space begins to thin.

(2) Second, AI is both highly useful for search, summarization, visualization, and prototyping *and* a highly annoying source of spam, scams, and slop. Too many will focus solely on the downsides.

(3) Third, the exact plateau of AI is quite unexpected. The fact that current models seem to have topped out at “far better web search and summary” is not where most would have pegged it in 2022. Disrupting Google is a historical accomplishment, yet it’s not the machine god.

(4) One thesis for why models plateaued in this way is that LLM-style digital AI really *is* just repeating, rather than truly thinking. It is downstream, not upstream. Now, you can get much further with this than most thought. But you can’t get all the way to novel thoughts.

(5) That leads to another point: as I’ve said before, digital AI does it middle-to-middle, not end-to-end. Because the bottleneck for digital AI is prompting and verifying.

(6) However, *physical* AI — in the sense of robotic guidance — *can* feasibly do things end-to-end, albeit after the investment of a lot of energy on edge cases. For example, self-driving cars now truly can take you from point A to point B. They do it end-to-end.

(7) So, extremely well-specified and economically valuable physical world problems like “drive from point A to point B” are where we should see significant AI progress. Call this physical specific intelligence.

(8) Chinese robots in particular will nail task after task, in many form factors beyond just cars or humanoids. Sidewalk robots and delivery drones are already live in China, alongside self-driving cars, and their hardware sector is accelerating.

(9) One reason to be more short-term
bullish on physically specific intelligence rather than artificial general intelligence is that the physical world is real while the digital world can be fictional. @drfeifei made the related point that the textbook concept of simultaneous location and mapping (SLAM) is actually an explicit physical world model, something we’ve all known is lacking in the digital realm.

(10) In particular, if you have N different robots all doing SLAM (or equivalent) and uploading their sensor data to a central database, they are all in a sense learning from the same physical world and each other. The millions of training miles driven by self-driving cars show that this strategy works.

(11) Contrast this to the digital world. Text can be fake, it can be fictional, and indeed it is often so. And this is doubly so as AI text permeates the web.

(12) So N robots sensing the physical world will converge on a consensus reality. A Unitree robot and a Tesla robot will perceive the same objects. By contrast, N agents in the digital world just keep ingesting text and images, which can and will be inconsistent.

(13) In the absence of digital signatures, the online data used for AI training will be not just internally inconsistent but fake in subtle or deep ways. Indeed, widespread AI models ensure that much digital data (outside hard digital borders) will become fake, or slop, or AI agents talking to each other.

(14) Algorithmic breakthroughs could obviate everything I’ve just said. But at least right now, the field seems wide open for physically specific intelligence.

(15) The industrial version of physically specific intelligence is factory robots. The consumer version though is a garden of intelligent things: robot cars, dogs, drones, fridges, and the like that can talk to you and understand you. Amazon Alexa, but for everything?

[Naresh Nambisan I ValuationMantra I SEBI Reg RA @nareshbahrain]

If this story of Marvan Atapattu dosent motivate you, nothing might👇

Making his debut in Test cricket for Sri Lanka, Marvan scored a duck in his first innings & again, in his second innings.

They dropped him. So he went back to the nets for more practice. More first class cricket. More runs. Waiting for that elusive call.

And after 21 months, he got a second chance. This time, he tried harder. His scores: 0 in the first innings, 1 in the second. Dropped again, he went back to the grind & scored tonnes of runs in first class cricket. Runs that seemed inadequate to erase the painful memories of the Test failures.

Well, 17 months later, opportunity knocked yet again. Marvan got to bat in both innings of the Test. His scores: 0 & 0. Phew! Back to the grind. Would the selectors ever give him another chance? They said he lacked big-match temperament.

3 yrs later, he got another chance. This time, he made runs. He came good. And in an illustrious career thereafter, Marvan went on to score over 5000 runs for Sri Lanka. That included 16 centuries & 6 double hundreds & he went on to captain his country. All this despite taking over 6 years to score his second run in Test cricket.

How many of us can handle failure as well as he did? 6yrs of trying & failing. He must have been tempted to pursue another career. Change his sport perhaps. Play county cricket. Or, oh well, just give up. But he didn’t. And that made the difference.

The next time you are staring at possible failure or rejection, think of Marvan.

NEVER GIVE UP!
BELIEVE IN YOURSELF 😊

[Cricketopia @CricketopiaCom]

The most complete batsman?

Here is some of Sachin Tendulkar’s shots.

Which one you think was the best among these shots.

Can you pick just one shot?

[Curiosity @CuriosityonX]

Best Visualization of Multiverse.

#astronomy #Multiverse

[Harsh Goenka @hvgoenka]

The 80/20 of Life:

Health: 80% food, 20% gym
Wealth: 80% mindset, 20% skills
Relationships: 80% quality, 20% quantity
Success: 80% doing, 20% planning
Wisdom: 80% listening, 20% talking
Happiness: 80% gratitude, 20% fun

[Anand Doddur @doddur]

@Portfolio_Bull Name please 🙏

[Pratham khanna @Portfolio_Bull]

🔔Hidden Gem Alert :)

-A Turnaround Company
-Penny Stock
-Order Backlog~ ₹652 Cr
-CFO Increased (₹51 Cr. to 156 Cr.)
-Debt Reduced
-Already Completed 950+ Projects

Do 1000 Likes & 100 Reposts 🔂

Follow @Portfolio_Bull for knowing the name.

[Harsh Goenka @hvgoenka]

What do you want to be?

[Jayesh Thakkar | Share Market Research @Share_Market]

What if BRICS makes a new currency that beats the US dollar? Reason Why #Trump Is crying Laudly

Thread 🧵👇Retweet & BookMark to Read it later 🫴[1/10]

[Ramesh Srivats @rameshsrivats]

The SCO summit should end with the 3 leaders singing this song -
♫♫♫
Anhoni ko honi kar de, honi ko anhoni…
Ek jagah jab jama ho teenon...
Putin... Jinping... aur Modi.
♫♫♫

[Harsh Goenka @hvgoenka]

A trip to nostalgia

[Harsh Goenka @hvgoenka]

Trump’s 25% tariff on India? -opportunities:
- Pharma & steel largely safe
- IT exports untouched
- Scope for ‘Make in America’ via JVs
- Time to woo Europe, ASEAN
- Ride China+1 shift
India’s playbook: turn pressure into opportunity!