Steve Jobs never left a will.
But before he died, he transferred all of his shares to a trust.
That single move made her wife a billionaire overnight
And saved his family billions in taxes.
Here’s how the world’s most iconic CEO hacked estate taxes forever:
As per data from RSS General Secretary Dattatreya Hosabale, Adani company earns ₹1,600 crores per day, while 22 crore people in India earn less than ₹375 per day. Article 38,39 of the Constitution state that wealth should not be concentrated in the hands of a few people.
Rear Admiral Grace Hopper was born on this day in 1906.
She programmed the first computer.
Q: “How’d you know so much about computers?”
A: “I didn’t. It was the first one.”
It's time we reclaim our narrative!
Our new Prachyam Original series with Shri Chandrahas Halai challenges the Western monopoly on mathematical history. Discover how ancient Indic Maths shaped the modern world - a story untold, until now.
Releasing On 21st Nov 2023 on #Prachyam OTT
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🔒 The Lesser Know Story of SSH Port 22 🔒
Ever wondered why SSH port 22 is the default choice for secure remote connections? 🤔
Finnish computer scientist Tatu Ylonen wrote the initial version of SSH in the Spring 1995.
Telnet and FTP were widely used at that time and SSH was written to replace both.
Interestingly, the port number 22 was free andit was right between FTP port 21 and Telnet port 23.
Tatu took the opportunity and used port number 22 to beta test SSH.
The port number remains the default port for SSH till day.
Here's the email announcing the SSH project 👇
After a wait of more than a century, our beloved sport is back on the Olympic stage at @LA28. This marks the dawn of a new era for cricket as it will be a golden opportunity to foster inclusivity and showcase new talent from emerging cricketing nations. A start of something truly special! ✨
Rome was not built in a day, but grep was (sort of) 😎
The origin story behind the creation of grep utility is fascinating.
The co-creator of the UNIX operating system, Ken Thompson, developed grep 'overnight'.
Actually, he had a personal tool for searching for text in files.
His department head Doug McIlroy came to him and said, "You know it would be really great if we could look for things in files".
"I'll think about it overnight", said Thompson.
He went back home and modified the code in his tool to fix bugs. Took him an hour at most.
The next day, he presented it to McIlroy and he exclaimed,
"This is exactly what I wanted"
And the rest is history.
If you are wondering why the utility is called grep and not search, there is perfectly good logic behind it 👇
Prof Raju's @CKRaju14 point is valid.
Why use the term "Pythagorean theorem" indiscriminately in Class X book when the theorem has a much earlier history in India?
If the answer is: Well that is how school math is taught in Euro-America, that means one is still propagating a colonial view of science.
Decolonization of science education ought to be done as soon as possible.
Today we're announcing #GAIA1: a 9B parameter world model, trained on 4,700 hours of driving data, able to simulate complex and diverse driving scenes from video, text and action inputs. This model is 480x larger than the preview we shared earlier this year and the results are incredible.
These videos are entirely synthetically generated by @wayve_ai's generative AI, GAIA-1. But there is more here than just generating videos, GAIA is an entire world model. A world model allows us to simulate the future, conditioned on video, text and action inputs, which can be leveraged for making informed decisions when driving.
Why is this game-changing for autonomous driving?
1. Safety. One limitation with AI systems like today's Large Language Models is that they are autoregressive, next-word prediction algorithms, but aren't necessarily aware of the implications of their decisions. A world model allows us to give our AI the capability to be aware of its decisions, by simulating the future, which is important for self-driving safety.
2. Synthetic training data. I believe synthetic training data is the future for AI, because it is safer, cheaper, and infinitely scalable. GAIA-1 unlocks unprecedented realism and diversity of synthetic data for self-driving.
3. Long-tail robustness. One of the biggest challenges for self-driving is long-tail robustness: dealing with the enormous magnitude of edge cases we see on the road. An advantage of generative AI is its incredible ability to recombine experiences in new ways. This is exciting for self-driving as it means we can learn from two edge case scenarios, and combine them to become a corner case. For example, we can experience driving in fog, and experience of jay-walking pedestrians, and GAIA can learn from these experiences to understand how to generate a fog+jay walking scenario.
Check out many more videos in our blog https://t.co/U44HQ82qeC or further technical details in our paper: https://t.co/w4nrPCy3Ph
Or come chat with our team who are at the International Conference on Computer Vision (#ICCV2023) this week in Paris in Booth 32 @Jamie_Shotton