Statistical Mashup

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These imgs would have uploaded better, although I had them backed up in a low resolution cloud when my initial node (with high resolution) broke surprisingly in an untimely manner, I’m just glad the data is readable and well… we didn’t lose it. Let’s notate with these stats that the world does not spin / revolve around me and / or you, but around the sun. And to that extent, we all have functions to fulfill.

Synthetic stats are becoming more important than ever.

Artificial intelligence is on pace to unlock over 30 trillion usd in new revenue. The AI market is growing by 39% per year and is expected to reach nearly $1T by 2028. The Internet of Things is going to add $19 trillion usd to the economy. And driverless cars are predicted to add 7 trillion usd. Once you add in the metaverses, the numbers get even bigger.

According to Emergen Research, “the global metaverse market size reached 47.69 billion usd in 2020 and is expected to reach $828.95 billion in 2028.” That’s a hefty compound annual growth rate (CAGR) of 43.3%.

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Energy usage is a good thing. You probably want to live in a place where there is a good amount of energy available to use and enjoy, rather than too little. It’s a good idea to be mining something data-wise. Take a look at CSC | CS Communication lifetime membership to utilize your data and get paid for it.

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Bitcoin uses only about 0.1% of global energy. Bitcoin’s energy usage will always be a rounding error with regards to global energy consumption. Bitcoin, in fact, may use too little energy for the value it may store in the future. We should invest and use more energy to protect the network than what we do currently.

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Fintech companies enable individuals and companies to conduct financial transactions without having to use traditional bank-based channels. There are about 3.5 Billion unbanked people in the world.

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In affiliation with Technology, Entertainment, and Design (TED) stats.

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Widespread adoption of AI has significant implications for every industry vertical. Most AI programs rely on labeled sample data for training purposes. For example, AI for autonomous vehicles uses data where cars, trucks, pedestrians, motorcycles and other objects are labeled, and the programs learn from the labeled data how to identify these objects.

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Via FastCompany: Industry 5.0 is a potential stepping stone towards a more sustainable, human-centric society. Emerging technology offers the real potential for humans to achieve a post-professional era where we are not defined by our jobs, but a new purpose to enhance the human condition and the world.

To achieve this future, issues of trust, risk and regulation of course need to be handled with care and forethought. Stanford’s one-hundred-year study on AI tells us that we are at an inflection point where the promise and perils of this technology are becoming real. While it is bringing innovations and benefits that we once could only dream about five years ago, using AI technology to replace human decision-making will inevitably create risks and unforeseen consequences.

Overall, the question isn’t whether machines will act with good intent, or eventually become more intelligent than people. In some contexts, they already are. The focus today should be what we can do now to make sure the path is set towards an optimistic future.

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