@CeoNoida and Noida Authority, blocking the construction of flats for which buyers are waiting for 15years deliberately despite Honorable SC clearing everything. Whether previous government or the current government, all are the same #NoHomeNoVote only NOTA
#NoHomeNoVote Unihomes Sector 117 are facing huge human right violations. Since 15years old and fundamental rights are not protected by government. Officials forcing residents to stop protesting. We have right to live with dignity and awaiting of registry of our flats. @CeoNoida
#NoHomeNoVote
The arrogance of @CeoNoida is quite visible seeing that despite assuring officials will visit and discuss on issues, the officials instead called to their office to discuss. Our fight for our home continues. Even our account is getting restricted now. (1/2)
15 years of no homes, everyone sitting like ducks. Hon SC given goahead but Noida Authority still arrogant. UP goverment knows everything, but still not doing anything. All other city projects started only Noida projects stuck. This time #NoHomeNoVote@myogiadityanath@PMOIndia
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Here are 8 incredible examples of what is possible:
Meta starts open-sourcing a lot and is now becoming one of the best companies in the world at shipping AI features. Coincidence? I don’t think so.
Contrary to popular belief, a company (or a country) sharing their research, models and datasets publicly in open-source makes them MORE competitive, not LESS, even more so in AI. IMO, that’s how the US and some companies like OAI & Google established their leadership in the past few years (even though they are not so open anymore).
Some of the reasons why open-sourcing makes companies more competitive:
- Open science and open source attracts and motivates the best talents who want to to contribute to the field
- It focuses organization on the speed of building - not on taking advantage of the current tech - especially important on a fast moving domain like AI
- It motivates the whole field to improve what you’re building on (bug fixing, optimization, new capabilities) that you can then really easily integrate in your products).
Is your company sharing their research, models and datasets? If not, they’re missing out!
Source: https://t.co/x1imHl9s7Q
I used to have one crippling addiction:
Planning.
My brain loved the cheap dopamine of gathering books to read, tasks to complete, and videos to watch.
But when it came to taking action, the euphoric rush faded.
What ended my addiction?
This story of two men learning to fish
--
The first fisherman was a planner.
He heads straight to the marina to buy the best fishing boat money can buy.
Then, he specs out an expensive, custom, carbon-fiber fishing rod.
And from there, he spends hundreds of hours reading up and watching videos on everything there is to know about fishing.
• Casting angles
• Weather patterns
• Baiting techniques
You name it, he's bought the book on it.
And of course, he's watching the fishing channel every night for hours, learning from the best of the best.
A few months later—after months of diligent preparation—he *finally* feels ready to fish.
So the next day, he heads out on the lake in his new boat with his fancy rod and wealth of fishing "experience" built up over the last few months.
But six hours in, nothing. Not even a nibble.
He fiddled with his tangled rod which was much more difficult to cast than it looked on TV.
Still nothing.
He moved to a spot upstream, just like his favorite guru would suggest.
Still nothing.
So—what happened?
Turns out, the second fisherman had already sucked the lake dry.
On day one, the second fisherman grabbed a shitty rod, sliced up a hot dog, and went to the lake.
The first day, nothing.
So he moved to a new spot.
Second day, nothing.
So then he moved again.
And on the third day? His first nibble.
From there it was time to iterate.
And every day after, he honed his technique.
He found a baiting technique that worked a bit better.
Or a new lake with a few more fish.
And after three weeks of iteration, he found the winning combination.
Before long, he was hauling in hundreds of fish every day.
To keep up with his daily haul, he hired a small team to help him.
And from there, he opened a restaurant with fat margins to sell his fresh fish.
And after that, he opened a fishing school to teach others his craft.
He did all of this while the first fisherman sat around gathering gear.
Sure, the first fisherman felt productive during those months of preparation, right?
He was "learning" after all, right?
But there was one difference: feedback.
Every day the second fisherman had an idea of something that might work better.
And he went right to the market to validate his assumption.
If it worked, his strategy improved.
And if it failed, he learned something new.
The moral of this story?
Get to action as quickly as possible.
When you find yourself gathering gear, stop.
Instead, grab a shitty rod and start fishing.
AI and Automation are not same:
AI:
• Learning Ability
• Decision Making
• Complex Tasks
• Data Analysis
• Adaptability
• Problem Solving
• Mimics Human Intelligence
Automation:
• Repetitive Tasks
• Rule-Based
• Fixed Operations
• Efficiency Improvement
• Time Saving
• Cost Reduction
• No Learning or Adaptation
What more you would add?
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