Interesting but scary Predictions for the Future (Part 2)
In 1980, Kodak had 170k employees worldwide & sold 85% of all film-rolls across the world.
Within just a few decades, their business model crashed & Kodak went bankrupt. Who would have thought of that ever happening ??
What happened to Kodak & Polaroid will happen to a lot of industries in the next 5-10 years & most don't see them coming.
Did you think in 2000 that five years later you would never take pictures using film again? With today’s smart phones, who owns a Camera these days ??
Digital Cameras* were invented around 1975. The initial models only had clarity/resolution of 10,000 pixels, but improved vastly following Moore's laws, as it happens with all futuristic technologies
It will now happen again (but much faster) with #AI Medical Diagnostics, Autonomous Electric cars, Online education, 3D Printing, Hydroponic Agriculture will change the world, beyond imagination.
Forget the old book Future Shock, Welcome to the 4th Industrial Revolution.
Artificial Intelligence, Robotics and 3D Printing have already disrupted and will continue to disrupt most traditional Manufacturing industries in the next ten years.
UBER is just a software company, they don't own any cars and Uber is now the biggest taxi company in the world. Ask any taxi driver if any of them, saw that coming.
AirBnB is now the biggest hotel company in the world, although they don't own any hotel properties. Ask Hilton or Meridian Hotels if they saw that coming.
#ArtificialIntelligence - Computers will become exponentially powerful & more accurate in understanding all facets of the world. This year, a computer beat the best Go-player in the world, 10 years earlier than expected.
In the USA, young lawyers already don't get jobs easily.
Because of IBM's Watson, you can get legal advice.
Facebook now has a pattern recognition software that can recognize faces better than humans. In 2030, computers will become far more intelligent than humans.
#Autonomouscars - In 2020 several models of self-driving cars are already launched. In the next 5 years, the entire industry will be disrupted. You don't need to own a car anymore as you will call a car and it will show up at your location and will drive you to your destination.
This will change our cities* because we will need 90% fewer cars. We can transform parking spaces into green parks.
About 1.2 million people die each year in car accidents worldwide including distracted drivers or due to drunk driving. We now have one accident for every 60,000 miles of driving. With Autonomous driving will probably drop to 1 accident in 6 million miles of driving saving lives!
Look at what Volvo is doing right now. No more Internal Combustion Engines in their Cars starting with the year 2025, using mostly Electric Motors, with the intent of phasing out Hybrid models.
Engineers from Mercedes, BMW, Volkswagen and Audi are completely terrified of Tesla.
Look at all the global companies offering Electric vehicles. They were unheard of, only a few years ago.
Insurance companies will have massive trouble. Without many road accidents, the Insurance Premiums will crash. The car insurance business will taper down with the passage of time.
Real Estate Business models will undergo drastic change. Because if you can work on your Laptop while you commute, people will abandon their down-town apartments, to move far away to more beautiful and affordable neighbourhoods in distant suburbs.
Electric cars will become mainstream by 2040. Cities will be less noisy because all new cars will run mostly on Batteries.
Cities will have much cleaner Ambient atmosphere, with no pollution. And clean air as well.
Renewable Power will become cheap, apart from being clean.
Solar power production has been on an exponential growth-curve for the last 30 years, but you can now see the burgeoning impact. And it’s just getting ramped up with the price of Solar Power( per Kilo-Watt-Hour) falling down every year.
Fossil Energy in trouble Tech companies are trying new methods to limit access to the power grid, to prevent competition from low-cost home-based solar installations.
Health: There will be Tech companies which will build Medical devices that work on your Mobile phone, which can take your Retina scan, your blood sample and you breath into it.
Then, they will analyse Bio-markers that will identify nearly any Disease. There will be dozens of Mobile phone apps for Medical Diagnostics.
WELCOME TO TOMORROW'S WORLD!!
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Allegations Of Fraud Have Now Wiped over $100bn From The #AdaniGroup, potentially making this the world’s largest corporate fraud as alleged and published by short-seller Hindenburg last week.
Hindenburg claims the Adani family has used offshore entities to artificially inflate Adani's listed company share prices, enabling them to take on more debt and leaving the group — according to the report — in a highly precarious position.
Hindenburg’s targets, which in the past have included convicted fraudulent trucking company Nikola, often see a swift share-price drop & Adani has been no exception. Indeed, the 10 listed Adani firms have now collectively lost more than $100bn in market cap since the allegations,
One cold night a billionaire met an old poor man outside. He asked him, "don't you feel cold being outside, & not wearing any coat?" The old man replied, "l don't have it but I got used to that." The billionaire replied, "Wait for me. I will enter my house now & bring you one. '
The poor man got so happy and said he will wait for him.The billionaire entered his house and got busy there and forgot the poor man. In the morning he remembered that poor old man and he went out to search for him but he found him dead because of cold,
but he left a NOTE, "When I didn't have any warm clothes, I had the power to fight the cold because I was used to that. But when you promised me to help me, I got attached to your promise and that took my power of resisting.
1. Training. To train a ChatGPT model, there are two stages:
- Pre-training: In this stage, we train a GPT model (decoder-only transformer) on a large chunk of internet data.
The objective is to train a model that can predict future words given a sentence in a way that is grammatically correct and semantically meaningful similar to the internet data.
After the pre-training stage, the model can complete given sentences, but it is not capable of responding to questions.
- Fine-tuning: This stage is a 3-step process that turns the pre-trained model into a question-answering ChatGPT model:
For example, the user data for a standard #Web2 service, like Twitter, is stored on centralized servers and is managed by a single organisation. Web2 apps are therefore vulnerable to censorship and one-sided control of user data, which makes them vulnerable to security flaws.
In contrast, #Web3 dApps are permissionless, open-source protocols that spread user data throughout the network. Dapps are therefore less vulnerable to security concerns and resistant to censorship because there is no single point of failure.