https://t.co/7kIHcwZhCG
Draft your all-time cricket t20 XI from real player stats. Pick a captain. Simulate 16 matches.
Daily Challenge โ same draft for everyone, global leaderboard.
Cricket IQ mode โ no stats shown. Pure knowledge.
Going 16-0 is harder than it looks.
Being 10x more involved with your kid than your parents ever were with you, while somehow feeling 100x more guilty about falling short, is the official millennial parenting experience.
11% of Snabbit's operating revenue came from selling uniforms to its own gig workers.
Read that again.
Company makes workers wear its uniform, charges them for it, and then recognises that money as revenue.
The same uniform that helps customers identify the company's brand becomes another source of income.
I understand that many companies charge for onboarding kits. But if wearing a uniform is mandatory for doing the job, why should the worker bear that cost?
The company gets brand visibility. The customer gets a familiar face. The worker gets a bill.
A uniform required to do your job should be a business expense, not a revenue opportunity.
The official verdict is absolute Crap!
I'm a Commercial pilot (Complex piston singles) and I have followed this story from the beginning. The official story is pathetic. This will go down in history as one best examples of aviation bravery.
For this story to have the happy ending that it did, 3 things had to happen perfectly:
First, Cpt. Smit who while on the floor (being attacked with an axe!!!) thought "these are my last moments, but I cant let these people die" and somehow opened the cockpit door. Without his bravery and determination, Everybody dies no question.
Second the passengers Yaniv and Yitzhack rushed the cockpit the minute they heard screams. Dont minimize this. Most people in a situation like this would freeze in their seats. Not to mention getting the the front of the plane in a zero G nose over. I'm assuming IDF training (mandatory for all Israelis) but even then excellent reactions under pressure. By rushing to the front immediately, they were on the other side of the door the second that Cpt Smit opened it. The IDF training also probably had a hand in their ability to rapidly neutralize the co-pilot.
Yaniv taking the stick and pulling out of the dive is critical simply because there was no time otherwise. At the rate of decent by that point there is maybe 30s to impact if they keep diving (and they were already past Vne)
However, contrary to popular male ego, a non pilot successfully recovering the plane has odds near zero. Commercial aircraft are huge and have massive momentum. Even in a small plane, if you are too heavy on the controls nothing happens for ten seconds, then next thing you know you are upside down. The most likely outcome after a non-pilot pulling out of a dive would be overcontrolling and triggering a stall. Fortunately (according to Yaniv's interview) the relief pilot took over just as he leveled the plane.
The relief pilots being on board was fortunate, the relief pilot managing to take over the controls before Yaniv could trigger a stall was perfect timing. The pilots were not just random pilots or random airline pilots, they were the relief crew which meant they had hundreds if not thousands of hours in that exact model. Why is this important? Because the co-pilot had smashed the instruments (once again from Yaniv's interview) and the rudder was damaged from exceeding Vne. The relief pilots could handle this as a routine emergency, for a pilot unfamiliar with that airplane and instruments smashed it would be a insurmountable challenge.
Finally the Pilot who thought he was going to die was in luck because on board was a dentist. A dental surgeon no less. Not quite the same an ER doc, but enough to stop major arterial bleeding from multiple wounds.
If somebody doesnt make a great movie out of this it would be a crime. This is aviation history being made.
Every Indian should read this report, because the jobs it puts at risk are exactly the jobs we spent thirty years building.
The headline finding is that in the worst case, America is 32% richer by 2030 and nearly one in five knowledge workers has no job.
Yes, both at the same time.
Let me explain how they got there, and what it means for us.
The whole model rests on one idea. A job is not one thing. It is a bundle of tasks.
Take a nurse in a Bengaluru hospital. She does rounds. She draws blood. She triages patients arriving in casualty. She charts vitals. She orders supplies for the ward.
AI cannot bathe a patient. It might help her write discharge instructions faster, which the report calls augmenting. It might just do the charting and the supply ordering by itself, which is automating. And it creates new tasks, like checking whether the AI triaged a patient correctly.
So, her job does not vanish. It changes shape.
Now multiply that across every worker. The model splits everyone into two groups.
Knowledge workers, meaning management, professionals, sales and office work.
And everyone else, meaning construction, drivers, nursing aides, repair, food service, farming.
In America that first group is about 62% of workers. AI touches that group and basically leaves the second alone.
With this, five numbers decide everything.
> How many tasks AI can do.
> How much it actually gets used.
> How much faster it makes each task.
> How often it does the task alone.
> And how long a displaced worker takes to find work in a completely different line.
Set those five dials three ways and you get three futures for America.
In the modest one, AI is about as big as the internet was. GDP is 1.6% higher by 2030. Growth goes from 2% a year to 2.4%. Unemployment goes from 3.8% to 3.9%. Nothing you would notice.
In the substantial one, AI is bigger than the internet and bigger than the railway. GDP is 8.3% higher. Growth hits 5.4% a year, faster than any year of the dot-com boom, which peaked at 4.7% in 1999.
Overall unemployment stays at a normal 4.6%. But knowledge worker pay sits slightly below where it would have been, while everyone else's pay is up 5.9%.
In the extreme one, GDP is 32.4% higher and growth reaches 15.4% a year, doubling the economy every four and a half years.
Knowledge employment falls 21.5%. Unemployment among knowledge workers hits 17.9%. Knowledge pay falls 11.5%. Pay for everyone else rises 33.6%.
To understand this better, suppose AI cuts the time to produce building designs and clear approvals for a metro project or a township.
More projects start. More projects means more demand for masons, electricians, welders and crane operators. Their wages go up.
The architect and the planning engineer who made the drawings faster do not get the raise. The person laying the cable does.
Now there is a finding that I think matters a lot for India.
Today, out of every rupee an economy produces, roughly 60 paise goes to workers as wages and 40 goes to capital, which means whoever owns the machines, the buildings, the software and the data centres.
In the substantial scenario that shifts to 56 and 44. Four points in four years. America's entire labour share decline across the four decades after 1980 was about that size.
In the extreme scenario it goes to 45 and 55. Capital takes more than half.
And here is the number that stopped me cold.
In that scenario, total wages paid across the whole country in 2030 are almost exactly what they would have been with no AI at all.
The economy grew by a third and workers as a group got none of it. Capital income rose 81%.
But why should an Indian care about a shift from wages to capital?
Because our largest and most successful industry is a wage industry. When TCS or Infosys or a GCC in Bengaluru earns a dollar, most of that dollar leaves as salaries to Indian families.
It becomes rent in Marathahalli, school fees in Hyderabad, an EMI in Pune.
When a data centre earns a dollar, most of it goes to whoever paid for the chips. Very little becomes a salary.
The report is describing a world where the second kind of dollar grows and the first kind shrinks.
India is disproportionately built on the first kind.
There is a second India-specific problem the report does not cover, as well.
A large part of Indian IT is billed by time. So many people, so many hours, so many months. If AI does the same work in half the time, the revenue halves unless the contract changes.
Efficiency gains do not automatically become profit here. They become a smaller invoice.
Third, our version of displacement may look different from America's. The report models people losing jobs and searching. In India the sharper risk is at the entry gate.
The most automatable work in any office is the junior work, and India produces an enormous number of graduates every year who need exactly that first job to begin a career.
What will happen is that nobody would get counted as displaced.
They will just never get hired.
That is my extension, not the report's, but I think it is the more likely Indian shape of this.
Fourth, switching occupations is harder here.
An engineering graduate in India will not take an electrician's job even if it pays more, because of what that means socially in his family.
The report's friction is about training. Ours is about status too.
One genuinely reassuring difference. India's non-exposed group is enormous. Agriculture alone still employs the largest share of Indians, and construction, transport and retail employ crores more.
AI does not touch that work directly. In America the exposed group is 62% of workers. Here it is a much smaller share of the workforce, even though it is a large share of our exports and almost all of our urban middle class.
So the disruption in India would be narrower and deeper. Fewer people affected, but concentrated in exactly the households that have been the story of Indian economic mobility for a generation.
Now, there are no robots in this model at all. It covers thinking work only. That is why the authors refuse to go past 2030.
And they attach no probabilities to any scenario. These are not forecasts.
They are three settings of five dials. Serious outside economists reviewed it, and some said the extreme scenario reads as a thought experiment while others said the modest one understates what is already visible in the data.
But the survey covers nearly 11,000 Americans, which will feel familiar to anyone in an Indian office. Knowledge workers said about 71% of the listed tasks would be doable by AI in 2030, but only 27% of their own working hours.
Everyone thinks it is coming for the person sitting next to them, until it comes for them. :)
I work in venture capital and spend a lot of time talking to engineers building in AI. And as a parent, one of the hardest things to come to terms with is that we are preparing our children for a world none of us has seen yet. Our parents could prepare us for a future they could more or less imagine. They knew what a good education looked like and what skills would probably remain useful for a good career. We may be the first generation of parents that cannot say the same with much confidence. So teach your kids to be curious and teach them how to think and not what to think. Teach them that being willing to question an answer is important. Teach them to make things from nothing. It can be drawing something on a piece of paper, growing a plant or fixing something that is broken. Create something where nothing existed before. These things may look ridiculously simple to an adult, but the ability to create rather than merely consume has never been more important. Teach them that school is useful, but grades are not a measure of intelligence. When machines will increasingly become more intelligent than humans and will know all the answers, their advantage may come from being curious to ask questions others will forget to ask. And perhaps we should stop training children to become employable for a particular industry. Some of the jobs we are preparing them for today may not exist by the time they are ready for them. That wasn't really the problem our generation had. Curiosity, judgment, courage, taste, creativity and the ability to figure out what matters may be some of the most valuable things we can teach our children today.
>sam altman: "we tried this because there were rumor on the internet"
>rumor: math professor close to solving navier-stokes
>the professor: using codex for a year
>openai: has all his logs
>checked every codex session tagged to N-S
>found the most promising one
>spun up 10,000 agents to finish the proof where he couldn't
>they got caught
>told the guy if you say anything you'll destroy your own career
>he ruins his career over this
>openai: "we did not see his work"
>also openai: "we cannot rule out that de-identified data from their usage helped improve our models"
they stole it lmao
I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives. More thoughts below.
Satwik-Chirag
They just won:
The China Masters
In China
In front of a Chinese home crowd.
The word Fear?
Not in their vocabulary.
A salute, Gentlemen
๐ซก๐ฎ๐ณ
CHINA MASTERS CHAMPIONS! ๐๐ฎ๐ณ
THE MOMENT SATWIK & CHIRAG BECAME SUPER 750 CHAMPIONS! ๐ฅ
What a comeback. What a fight. WHAT A WIN! โค๏ธ๐ฎ๐ณ
About 1 in every 3 tonnes of fruit, vegetables and milk produced in India never reaches anybody. It rots on the way, because there was no cold storage and no refrigerated truck.
The trucks that do have a fridge run it off the engine. So the engine has to keep running, burning diesel, even when the truck is standing still in traffic.
A 25 year old engineer decided to take the fridge off the engine.
Her name is Shaivee Malik.
She studied biotechnology at the Indian Institute of Technology in Delhi.
While she was there she joined the college formula racing team, Axlr8r, and became associate team captain. That is where she learned to build things that actually work, with 2 friends from the same team, Vivek Mahindrakar and Dharmik Bapodara.
The 3 of them wanted to work on climate change. They looked around for where the damage was worst and least talked about, and landed on the cold chain.
In 2022 they founded a company called Yotuh Energy. The name comes from Sanskrit and refers to the act of cleaning. They registered it in Delhi and then moved to Chennai for an incubation programme at IIT Madras.
Their product is a refrigeration unit that runs on its own lithium ion battery, completely independent of the truck engine.
That one change does several things at once. The fridge runs whether the engine is on or off, so the truck stops burning diesel while it idles. It keeps working even if the vehicle breaks down. Sensors on the doors detect every time a door opens and adjust the cooling for it. And because it is a separate unit, it can be fitted to an ordinary diesel vehicle or an electric one.
It runs 6 to 8 hours on a charge.
It cuts refrigeration running costs by around 75%. Each unit avoids somewhere between 3 and 36 tonnes of carbon dioxide a year, depending on use.
They did not start with money. She has said the first support came from family. After that it was small government grants, 30,000 rupees a month for a year under one scheme, then a larger one, which is what paid for the early prototypes.
Then came a funding round of about 1.53 crore rupees, and grants from the agriculture ministry, the science and technology department and others.
Their paying customers now include distributors for Amul ice cream and for McCain frozen foods.
She is clear about what the company actually is. We are a cooling solutions company, she says. Trucks are just where they started, because a fridge tied to a diesel engine is the least sensible way to keep something cold.
@thecodemarathon@WhatsApp@kunalb11 This is super common. Blocking nos is useless as they keep switching. Thereโs a better way - document spam & push for compensation via RBI Ombudsman. I got โน15,000 from Bajaj Finance + โน5,000 from Kotak for their spam calls by following proper process.
https://t.co/BfdmsvJsmA
4 everyday habits that seem harmless, but can sometimes affect your health
We do these things all the time. Usually, they are safe. But dose, duration and technique matter.
Here are 4 surprising examples worth knowing about. Read this post carefully and share for wider reach.
1/n
#DayOne: Just a guy from Chandanagar doing odd jobs to get by, no plan, no godfather, nothing.
Then #TharunBhascker and an amazing team happened.
#OneDay: Walks the red carpet, lifts the Best Comedian award, speaks straight from the heart, and never looks back.
10 years to @pellichoopulu
10 years to #NaaSaavuNenuSastha
Donโt know about Rang De Basanti, but let me tell you what some of us millennials actually grew up watching.
I was in primary school during the 1993 Mumbai bombings -- too young to even understand what terrorism meant. But I distinctly remember my mom repeatedly warning me not to pick up anything lying around while playing outside because, you know, it could be a bomb.
That was childhood.
Then came the seemingly endless procession of attacks: the 1993 Mumbai blasts, Red Fort in 2000, Parliament in 2001, the Mumbai bus bombings and Akshardham in 2002, three separate blasts within eight months in Mumbai in 2003, the 2005 Delhi blasts, the 2007 Hyderabad bombings, and the 2008 Bangalore and Ahmedabad blasts.
In July 2006, I was supposed to be on one of the trains that was bombed near Mahim. I stayed back at the office because of a meeting. A completely mundane change of plans is probably the reason Iโm alive to type this instead of being a name on a list of the dead.
I remember that evening far better than I remember any stupid movie. Our office went into lockdown. Phones were jammed. People were crying and frantically trying to reach their families. Nobody knew what was happening, whether there were more bombs, or whether someone they loved was lying dead inside a mangled train compartment.
Two years later came 26/11.
I had the misfortune of watching uncensored footage of the aftermath. One clip showed bodies being piled and stacked inside a makeshift room at CST while someone wheeled in another load on a bloodied wheelbarrow, with blood dripping onto the floor. The sanitised footage shown on television didn't come remotely close to what actually happened inside that station.
So yes, us millennials lived through an era where we went to work knowing that the crime of simply boarding the wrong train, getting on the wrong bus, eating at the wrong restaurant, or standing on the wrong street at the wrong fucking moment could get you blown to pieces or riddled with bullets.
Some of us literally went to work wondering, somewhere at the back of our minds, whether this would be the commute we wouldn't come home from.
So please, spare us millennials this sanctimonious horseshit about Rang De Basanti and what some Bollywood movie supposedly should have taught us about how to vote.