Green Earth Initiative

The overall breath and scope of climate change is far too vast to cover, but we can at least go over a few of the basics that are backed with data and facts.

Before we continue, I want to point out a crucial mistake that I have seen far too many people make with climate change. There are way too many people on this planet that think climate change is false. The documentary below shows the role that big oil companies played in trying to discredit climate change. Another issue is that previous scientists were not always great at making projected guesses into the future and drawing accurate hypothesis based on data. Honestly, especially early on, there were just too many unknown variables and factors and we had no where near the technology we have now. Also, there are a numerous number of documentaries showing how people, companies, government, and even scientists have skewed data for personal gain. Because of those types of issues, we have had false predictions from scientists, reduced credibility, and misleading data and conclusions. Those issues have lead to skeptics and climate change deniers. We cannot make the huge mistake of arguing that incorrect predictions equates to incorrect data. 

The truth is that data all over the world has proven that we are dealing with climate change as a direct result of human actions. These human actions have lead to the climate weather patterns changing in many different ways, such as an increase in the number of floods, locations being flooded, species going extinct, wild biomass decline, higher and more frequent rates of class 5 hurricanes, stronger and more severe tornadoes, droughts, heat waves, storms, average rise in global temperatures, average rise in sear levels, massive rain storms, bigger and widespread fires, pollution, glacier and ice melt on unprecedented levels, coral bleaching, invasive species growth, decline in wild life, population crashes for species, increases in mudslides, rock slides, and avalanches, pollution, dust storms, and human loss and displacement as a result of all of these increasingly frequent disasters that we have either created or contributed to those effects.

All of those deniers are still living in a past in which we made predictions on far less data and did not have all of the AI models helping us make far more accurate predictions. Now, in this day and age, we have undeniable data from all different fields of science, AI models, and people from all over the world that have helped us understand that climate change from humans is an absolute fact.

Here is Google Gemini 's response to questions.

Question: Why do people deny climate change?

Gemini Response (2024):

The reasons why people deny climate change are complex and varied, but several key factors often contribute:

1. Economic Interests: Industries that rely heavily on fossil fuels may have a financial incentive to deny climate change, as addressing it could lead to increased costs or regulatory changes. 
2. Political Ideology: Climate change is often politicized, with some political groups or individuals viewing it as a threat to their ideology or worldview. 
3. Misinformation and Disinformation: The spread of false or misleading information about climate change can confuse the public and undermine the scientific consensus. This can be fueled by various sources, including some media outlets and individuals with vested interests. 
4. Cognitive Dissonance: The realization that climate change is real and caused by human actions can be psychologically uncomfortable. Some people may deny this information to avoid facing the implications or the need to change their behavior. 
5. Lack of Understanding: A lack of understanding of the scientific evidence or the complexities of climate change can contribute to skepticism.

It's important to note that the overwhelming majority of scientists agree that climate change is real, human-caused, and a serious threat. While the reasons for denial vary, addressing this issue requires a combination of scientific evidence, education, and policy changes. 

 Question: What are 20 important pieces of information that prove climate change is caused by human factors? 

Gemini Response (2024):

1. Rising Global Temperatures: The average global temperature has increased significantly since the Industrial Revolution, with the last decade being the warmest on record.
2. Ocean Warming: The oceans have absorbed most of the excess heat trapped by greenhouse gases, leading to rising sea levels and changes in ocean currents.
3. Sea Level Rise: Sea levels have risen at an accelerating rate, primarily due to the melting of glaciers and ice sheets.
4. Shrinking Ice Sheets and Glaciers: Arctic sea ice has declined dramatically, and glaciers and ice sheets around the world are melting at unprecedented rates.
5. Ocean Acidification: The absorption of carbon dioxide by the oceans has led to increased acidity, threatening marine ecosystems.
6. Extreme Weather Events: The frequency and intensity of extreme weather events, such as heatwaves, droughts, floods, and hurricanes, have increased in recent decades.
7. Changes in Precipitation Patterns: Rainfall patterns have shifted, with some regions experiencing more extreme droughts while others experience more intense rainfall.
8. Earlier Spring and Later Winter: Spring is arriving earlier and winter is lasting later in many parts of the world.
9. Changes in Plant and Animal Distribution: Species are shifting their ranges in response to changing climate conditions.
10. Rising Atmospheric Carbon Dioxide: The concentration of carbon dioxide in the atmosphere has reached the highest level in at least 800,000 years, primarily due to human activities.
11. Stable Isotope Analysis: Analyzing the isotopic composition of ice cores and tree rings provides evidence that the recent increase in temperature is primarily due to human-caused greenhouse gas emissions.
12. Climate Model Simulations: Complex computer models that simulate the Earth's climate accurately reproduce observed temperature trends when human-caused emissions are included.
13. Historical Temperature Records: Long-term temperature records from thermometers, tree rings, ice cores, and other natural archives confirm the warming trend.
14. Fingerprint Analysis: The specific patterns of warming observed in the atmosphere and oceans match the expected fingerprint of human-caused greenhouse gas emissions.
15. Ocean Heat Content: The amount of heat stored in the oceans has increased significantly, confirming the Earth's energy imbalance caused by human-caused greenhouse gas emissions.
16. Sea Surface Temperature Records: Sea surface temperatures have risen steadily, contributing to changes in ocean currents and weather patterns.
17. Glacier Mass Balance Measurements: Precise measurements of glacier mass loss confirm the accelerating rate of ice loss due to climate change.
18. Satellite Observations: Satellites provide detailed observations of changes in sea ice, glaciers, and the Earth's energy balance.
19. Paleoclimate Data: Studies of past climate records, such as those from ice cores and sediment cores, reveal that the current rate of warming is unprecedented in recent millennia.
20. Consensus Among Scientists: The overwhelming majority of climate scientists agree that climate change is real, human-caused, and a serious threat.

These indicators provide strong evidence that climate change is primarily caused by human activities, such as the burning of fossil fuels and deforestation, which release large amounts of greenhouse gases into the atmosphere. 

Undeniable

Although I chose to ask for 20 reasons, the reality is that different fields of science, data sets, and information from all over the world have shown the effects of global climate change as a result of human effects on our planet. 

Thinking about the climate issue as an increase in carbon dioxide, although true, may lead to misconceptions about climate change. We have to think about carbon dioxide in our atmosphere as an increase in contamination of our atmosphere and not merely as an increase in carbon dioxide. 

When we view the carbon emissions as an increase in carbon dioxide, we get caught up and distracted with arguments about the level of increase and the impact of that increase. How much are we increasing carbon dioxide? How large of an impact is the increase in carbon dioxide having on our planet? How much more can we increase the carbon dioxide? 

The reality is that we are literally contaminating our atmosphere and the air we breathe, as well as the air that much of the life on this planet breathes to survive. That human caused increase in contamination of our atmosphere is causing a reaction on our planet that is having profound results. One of which, is the fastest mass extinction event on our planet.

Climate change is not something in which we should "bend the rules." The truth is that, by pursuing this notion that we have "bent the rules," we have failed to acknowledge that we have actually broken things. We are breaking this planet. We are breaking and destroying the life on this planet. We have broken, not bent, ecosystems. We have broken, not bent, the biodiversity of life on this planet. We have broken the major components and mechanisms on this planet that are regenerating and maintaining all of the lives on this planet. We are disillusioning ourselves into debating how much of these things we can break and by how much we can break things.

Holocene Extinction - Also known as the Anthropocene extinction or the Sixth mass extinction, "is the ongoing extinction event caused by humans during the Holocene [our current] epoch. These extinctions span numerous families of plants and animals, including mammals, birds, reptiles, amphibians, fish, and invertebrates, and affecting not just terrestrial species but also large sectors of marine life. With widespread degradation of biodiversity hotspots, such as coral reefs and rainforests,  as well as other areas, the vast majority of these extinctions are  thought to be undocumented, as the species are undiscovered at the time  of their extinction, which goes unrecorded. The current rate of  extinction of species is estimated at 100 to 1,000 times higher than  natural background extinction rates and is increasing. During the past 100–200 years, biodiversity loss and species extinction have accelerated, to the point that most conservation biologists now believe that human activity has either produced a period of mass extinction, or is on the cusp of doing so." [Additional information]

Sixth Mass Extinction

Although this website has an emphasis on agriculture, we must absolutely understand that our very life, health, and well-being are inseparable from our planet Earth. The success of our planet is our own success, and the failure of our planet will be directly related to the demise of the human species. 

As of now, we have not found life on other planets, and we have not found a hospitable planet similar to Earth any where within traveling distance. Realistically, for us to propagate our species to another planet, we would need to either terraform that planet (possibly terraforming of Mars), or build enclosures on that planet (higher probability), mine the resources from that planet, and build closed Eco-systems. Myanmar's Future Vision is merely an extension of the idea of protecting this planet beginning from each individual, household, village, city, state, and country to joining others on this planet in protecting the Earth. 

Protecting the Earth may seem like too large of a problem, but if all of us play our part and protect what we can, we will join the larger fight to protect and preserve our planet. We are the stewards of not only ourselves, our children, and the next generations, but, as a the highest dominant species on the planet, we are the stewards of all life as we know it. We are responsible for every single life on this planet whether we choose to acknowledge or do something about that responsibility or not.

Until we discover life on other planets, we are the protectors and stewards of the only life in the entire universe! What if some of the life on this planet is perfectly suited for the atmospheres of other planets, but due to our own negligence, that species no longer exists on Earth. We could have had an abundant food source that would have thrived on that planet or, at least a species that would have made sustainable life on that planet far easier.

If you are not currently familiar withe the UN 17 goals, here is the website. [UN 17 goals to help save this planet]

For our own self-preservation of the human species, we must understand that our own existence is linked directly to life on our planet. We are a part of the food web. We are connected to all life on this planet. In chemistry, we use litmus paper to test the acidity of materials. During the late 1890's, American coal miners used canaries ("canary in the coal mine") to detect carbon monoxide in coal mines. All life on this planet is our "litmus" paper and our "canaries". What happens when Earth becomes less hospitable to life on our planet? Are we so arrogant to think that we are some type of exception? Do we not realize that human lives are being lost all around the world as a result of the current man made issues?  

Part of the deception that there are little to no issues is that our population continues to grow rapidly, and our food sources seem abundant. At least, for the developed countries.The reality is that our food variety is actually limited, and even smaller compared to all life. Most life on this planet is inedible, or we do not eat them. Our farming and agriculture has made us exceptional at growing and raising food, but we have decimated other life on this planet.

For significant reasons, in certain regards, we need to think of the importance and necessity of biological life as biological machines. If we think about the current level of robotic technology, these technologies are still a huge ways away from replacing even some of the most basic physical tasks. 

Imagine if we gave the best robotics companies in the world the challenge of making a small single robot about the size of a peanut or two. Easy. However, we told those companies that the single robot would then need to make other similar robots, program those robots with tasks, build or find a shelter, find energy sources, create and build a system to store energy for future use, be able to move on land and fly in the air, be able to navigate with their own location service without GPS, be able to cover miles and still be able to navigate back to the shelter through all kinds of weather conditions, regulate the temperature inside their shelter, communicate the identification of resources to other robots as needed, continue to maintain their own robotics facility for the continued production of more robots, and all of that without any human interaction. A complete self-sustaining system. 

Every single robotics company in the world, would not even be close to achieving most of those goals. In addition to all of those tasks, what if we gave the companies another requirement for those robots. Pollinate as many flowers within a few miles of their own robotics facility. The task would seem impossible to current robotics companies. Yet, we have bees. A single queen bee can accomplish every single task we have listed and more. That is a small glimpse into the importance of how big a difference a single piece of biomass about the size of a couple peanuts can make on an entire ecosystem. Bees pollinate approximately 35% of the worlds crops and are crucial worldwide. How much life have we eradicated on this planet and never even knew their importance to the world?

Nature has billions of years of engineering experience more than we as modern humans have had on this planet. Instead of destroying species all over the planet, we must learn to allow them to strive and utilize, cultivate, and enhance their capabilities. Instead of us trying to build robotics, we need to learn to work with these biological machines in far better ways. Thankfully, through conservation and the hard work of people all over the world, we are learning more about the ways in which these biological machines are working tirelessly all around us. We have the entire Amazon rain forest that is a self-sustaining system that is running entirely by biological machines constantly producing and maintaining that forest for us, and all we need to do is not destroy the planet.There is no amount of technology and money right now that can even begin to replace and accomplish what these biological machines are doing everyday. 

 Biology

We have to understand that as much as we value our current technology and progress, we are no where near any type of advanced civilization. We like to think that we have achieved so much, and in doing so, that we are and intelligent and advanced species. After all, what do we have to compare our intelligence against when we have surpassed the intelligence of every single species on this planet by exponential lengths and distances. The next closest most intelligent species on Earth after humans are chimpanzees. We need to do our part to reduce climate change, so we can continue to build our species in the right direction. We still have so much to do and accomplish.

The reality is that we are no where close to higher level intelligence and technology. Part of the reason of creating this website, among the many I have listed so far, is that my dream is that we will begin to truly unlock our potential. We have barely even begun to scratch the surface. For us to truly begin to become even remotely advanced, we need to absolutely ensure our planets survival. 

I will go over a few ways in which we must understand how far we are from actually being advanced, and what a glimpse into future technology will look like if we can actually get our act together. Also, these glimpses will show us how far behind our technology is in comparison to a possible future. 

We destroy nature. Yet, we have made some progress in utilizing nature to help us. We use bees and beehives to help us pollinate our food orchards. We have domesticated animals like dogs to assist us in our daily lives. However, these are just the basics because of our technology. We breed and have crossbred species for our benefit. Once we get into gene modification, we will truly be able to harness the very mechanisms themselves of biology, and more importantly, biological evolution to new heights. 

Imagine a world that, instead of killing mosquitos, we use mosquitos as delivery methods to vaccinate animal populations while controlling the mosquito's lifespan and remove their reproductive capabilities. For example, we engineer mosquitos to be carriers of certain vaccines for animals and the mosquitos cannot breed. We can use mosquitos to control certain invasive species of mammals. A mosquito that kills wild pigs, pythons, and iguanas. We can release millions of those mosquitos that live for a couple of weeks. 

Imagine a world in which we can modify bees to grow without stingers. We can modify trees to produce larger and sweeter fruits. We can modify the lifespan of animals so that these animals live longer, and eventually, practically forever. Imagine if we modified salmon to live hundreds of years, so the salmon can lay eggs, still live, and swim back into the oceans. We too will be able to live forever. We can create bacteria, fungi, algae, and a concoction of other organic life to breakdown our garbage and leave us the raw materials to repurpose and recycle. We can grow oranges the size of cantaloupes. What about removing the harmful chemicals in plants, or using plants to remove harmful chemicals from soil? Peanut plants are nitrogen fixers for soil. We can modify those plants to be nitrogen fixing and not produce peanuts. We can keep planting peanuts in our soil to constantly produce nitrogen for our other crops.  

We can make vegetables more nutritious. Imagine taking a cantaloupe and modifying the genes to take in other minerals and generate other vitamins. We could make a multi-vitamin cantaloupe. Breast milk is a specially made concoction of nutrients and vitamins based on the babies saliva to let the mother know what recipe to make for the breast milk. What is to stop us from using a saliva swab of our tongue, having our saliva analyzed, and then going to the grocery store to have milk specially infused and designed for our needs. We will be able to destroy viruses. We will also create viruses that help us. What about a virus that targets cancer cells and destroys them for us? We make medicine out of some plants by extracting the material. Why not make the plant produce more of the active ingredient, and we just eat the plant? We can grow our own medicine ourselves. We will design viruses that target and destroy other viruses.

In the ocean, we can modify the algae that removes carbon dioxide from the atmosphere and make them far more efficient and grow in larger numbers. We can start to take animals, their internal organs, and grow perfect matches for our own species. Imagine taking the best of every animal and having them transplanted into us. Eventually, we would modify our own genetics to remove deficiencies, grow larger hearts, stronger and better lungs, bigger brains, eyes with superior receptors even giving us almost night vision, better hearing, stronger bones and muscles, regenerative tissues, faster healing, remove genetic defects, and reverse aging. Our bodies go through an aging process, but there is nothing in the universe that states that aging is a law. We can turn off these mechanisms and reverse the aging process, and we will. We will be in control of our own evolution in every single way. 

We have a whole bunch of biological systems working inside of us that we are not utilizing to their full potential. We have an immune system that fights off diseases for us. We use some vaccinations that harness our own bodies ability to create mechanisms to destroy bacteria based on those vaccinations. However, we can design far more things within us by utilizing our own internal mechanics. We have hundreds of thousands of seabirds die every year from eating plastics. What if we inject or feed seabirds modified plastic eating bacteria for their stomachs and guts? That way, these birds not only do not die from eating plastics, and these birds help us clean up plastics from the ocean. We will make far superior and cost efficient bio-fuels.

We are just beginning to make more synthetic materials. We will get far better at making new things from new materials. We will make plastic substitutes from biological and organic materials. Trees generally take years to bare fruit. We will be able to speed up these processes. What is stopping us from modifying salmon and tuna to grow to the size of sperm whales? We can make cows grow the size of elephants. What if we design termites that live for a month and do not breed? We can put a tent around an abandoned house, unleash the termites to break down all of the wood, and make clean up far easier. We can modify animals to survive all kinds of harsh conditions. We will make organic pesticides instead of chemical pesticides. We have certain species that are great for nature, but are not able to survive in other climates. We can modify them to survive. Imagine making natural predators stronger at surviving and eradicating pests.

What if our pets live as long as we do? We will cure pets of all diseases and defects. We will cure animals. We can make elephants regrow tusks. What if we make octopus that regrow limbs? We can harvest octopus limbs for eating and not have to kill them every time. What about a frog leg farm where frogs regrow legs? What about abalone that takes a half a year to reach full maturity for harvest? What about us regrowing teeth? We will fix baldness. We will grow animals at far faster rates through artificial insemination and genetic modification.

I thought of the above examples in maybe a few hours. We have not even really accomplished anything close to some of the ideas listed above. Imagine what we will do when we unlock technology that allows us to unlock more technology. We still have a long ways to go. 

Technology

We spoke about biology, but what about other technology such as AI. Here are just a few ideas I thought about. This next list of ideas I brainstormed over a few years ago and some are already developed now. I barely scratched the surface of what is possible. I have ideas now that are decades ahead of these ideas. 

  Engine noises. Have AI listen to engine noise and make guess as to the issue. Maybe doesn’t matter so much now because you can’t really work on newer cars as a novice. Maybe good to at least have a second opinion. This is more for mechanical issues. The diagnostic tool reads the codes from the panel and tells you what a lot of issues are already. Question, why don’t car manufacturers have their own car app? Why doesn’t my Nissan have a Nissan app that when there is an issue, the car talks with my smartphone (it already can connect with Bluetooth) Nissan app and tells me what the issue is? What if, by syncing my phone app to the car through Bluetooth, the car sends my phone the diagnostic info such as what the heck the engine light means, what dates and times are available for maintenance at the dealership, and I schedule my car maintenance and the mechanic or mechanic shop is messaged the information of the diagnostic. 

ML (Machine Learning) is being taught things that were normally considered more creative. Things like painting, creating art, making music, etc. Things in this category that either do not exist or needs improvement can be book writing (they already write articles), product creation and design, recipes for cooking, mathematics equation creation, physics equation creation, gardening design, interior building design, exterior building design, musical instrument design (you pick or create a sound/tone, and the ML creates a physical instrument that can make that sound (a new musical instrument actually sounds fun), poetry, philosophy, modular urban area design, video game design, etc. Certain land is “owned” by city in certain areas as a modular land site. This site can be used to create things based on local population demographics. If there are a lot of children in the area, the modular land turns into a kid’s playground. If there are not many kids, and a lot of 20-year-olds, then that land is converted to BBQ pits and park benches. If lots of elderly, then exercise equipment and benches. If kids and elderly, then some benches and a smaller kids play area. Lots of ideas

ML can be trained to predict fire hazard and avalanche zones based on metrics. Maybe last time of fire, types of trees, temperature, humidity, elevation, and can be trained to make predictions as to likelihood of fire in a given area. Maybe a heat map with fire percentages. Can also be applied to avalanche areas for skiing. The last time an avalanche happened, amount of snow, rain, and sun within given times, elevation, terrain of mountain, and number, types, and density of trees. This data can be made public to warn skiers of areas that have a high possibility of an avalanche. Heatmap of avalanche zones. Rip tide hazards. What about Google maps alerting us that the trail that we are walking on has some reptile or plant species hazards like snake or poison oak warning.

Things will come that use ML/AI to run and control robotics for our entertainment. Eventually, we will see “nAIscar”. A race based on AI controlling the car (self-driving, but making decisions of when to pass, how to pass, which turns to pass up other cars. They have started with replacing, at least on the mechanical level, camel riders in camel races with little mechanical boxes that help people control camels. Later on, AI will control camel racing in this regard) and seeing which cars finish first. Planes during air show being controlled by AI and doing tricks and flying patterns. Eventually, these self-driving planes will be used for putting out fires. Helicopter tours based on self-flying helicopters. Package tours for self-driving vehicles. Let’s say I open up a Tesla app, choose “bay area tour”, Tesla car picks me up, takes me to golden gate bridge, when I’m ready, the next Tesla taxi picks me up to take me to Coit tower, then pier 39, and so on. The voice inside the car can even give information about the areas we drive through, as well as, give us information about our destination. Lots of things will come in this category too. 

Prisons will be AI controlled. Prisoners will report to designated cells. Cell doors will open and close based on AI. No need to have guards inside lots of areas of prisons. It will just be prisoners, cameras with AI watching, and smart devices controlling and guiding prisoners. IE, prison door opens, LED walkway lights up to cafeteria, prisoners line up and the next door doesn’t open until all prisoners are on designated squares, then door opens, previous door closes, next pathway lights up, positive affirmations are played along the way, if prisoners get out of formation, AI calls the prisoners name to get back into line, next door doesn’t open until prisoner gets back. If prisoner still does not comply, each prisoner is guided back to their cell, and that individual has a physical detention unit come get them. AI will talk to prisoners and make assessments on how to pair prisoners with other prisoners to increase behavioral modifications and separate violent individuals from non-violent individuals.

Psychologist and therapists. People chat with AI companions, but at some point, we will talk with AI therapists and psychologists. They will also recommend things for us and help us in cases of mental issues. These bots/AI will help us during times of loss, alcoholism, depression, and help with diagnosis and treatment. 

With technology like unreal engine, we will start to see porn actresses that aren’t real, but look like real people. We can pick between an archive of faces and features, and they will then be rendered onto our favorite scenes, fetishes, and is therefore limitless to the types and amounts of porn. I can choose to have new faces based on my previous likes and have new porn delivered to me every day based on exactly what I like. If combined with companion bots, we can now have a face to go with our companion and porn for intimate moments with our companion. We will reduce crime and forced sex labor. 

The huge thing about unreal engine is real life like graphics, but the issue is the complexity that mainly well-trained developers can use this technology to create content. Eventually, like websites, drag and drop and simplicity, we will have the ability to make movies, short stories, and games with easy-to-use designs for creating these graphics. Then, anyone with a great story or any story can create a movie. 

ML will, with a high and accurate degree, be able to age people based on childhood or younger pictures. Once this is accomplished, then with facial recognition, we should start seeing missing children being recognized even with falsified IDs. That can be expanded to a worldwide database for missing children. For long term, the aging and facial recognition could be used to search through Facebook, Instagram, and a lot of these companies that opt in to the “find a child” search that allows their pictures to be scanned for the only sole purpose of matching and finding missing children. Since China already does massive facial recognition, they most likely will be able to implement child searches. We can pair technology from Tesla vehicles that already have streaming video and image recognition to opt into an amber alert system. If you opt your Tesla into the Amber Alert system, while driving, any Amber Alert in your area will be paired with your vehicle's cameras to read license plates to check for that vehicle.

Such as spam filtering, identifying sentiment, and customer response, ML can be trained to assess the success and sentiment of larger events like speeches, art shows, and other things that can have microphones strategically placed throughout the art gallery, listen to conversations, convert speech to text, analyze the text and label a sentiment, then decide the likely outcome of the art show or speech that was given. You may be able to accurately gauge likelihood that people will purchase art work, likelihood that the artist will become more successful, or if it is worth giving them another art show. In the cases of speeches, the person can make alterations based on sentiment at different levels of their speech. IE, if the sentiment drops during the middle of their speech, then they can analyze the discussion material at that particular time and change or alter the topics of discussion. Can also use video. Total amount of time a person uses their phone, are on their phone, or are not paying attention. If facial recognition is good enough, can look at facial reactions for sentiment. Imagine giving a presidential speech with microphones laid throughout the venue and gives you a report on the sentiment of that location. You can analyze the data, make speech corrections, and by the time you are at the next city, you already have a modified speech that could result in more votes because you dropped certain topics the area did not care about, and focused more time on areas people did care about. Can even send a “test” candidate through areas before to gauge sentiment. Like a possible vice president before the presidential candidate to run through and have the audience video and audio analyzed. Can use facial recognition to check public sentiment. Are people frowning during a certain part of your speech?

ML can decide how to plant trees, vegetables, and plants for greatest number per size. Let’s say you buy a plot of land, but the land is irregular in shape, but you feed this shape into ML and select rubber trees, and the ML tells you the locations to plant the trees to be able to plant the most trees on your land. If you select agroforrestry, the AI recommends other types of plants and trees to plant with your current choices and increase your profits. Maybe can take into account sunrise, sunset, wind direction, shade, and decide highest yield locations for trees. Maybe the solution is to not plant so many trees in an area that is shaded by the mountain for most of the day, so planting trees in a normal configuration would have the trees reducing sunlight with each, in an already reduced sunlight location, and reducing yield significantly, while only returning marginal yields for the amount of water, fertilizer, and work put in, but putting less trees in that area, will produce more yield at half the cost and density. Like what if the solution is to plant the trees diagonally to the sunrise and sunset giving the most sunlight to each tree, as opposed to other directions where each tree provides shade to the other trees for 35% of the day and reducing yield by 50%. What if planting trees in rows pointing toward the mountain top on slopes produces highest yields because rainfall washes away soil, but placing trees in that manner helps reduce soil erosion and helps keep rainfall nutrients, or this allows for more water to run down the mountain and reducing over saturation of soil. 

Can expand that for building materials like interior flooring. You put in the measurements, select the type of building material, this will give you the total cost of material, the direction to lay out the material. Like if you are doing wood laminate flooring, then based on your dimensions of the living room, hallways, and rooms, this will tell you to start at this angle, this will give you the least amount of material used as well as least number of cuts, and fastest time to finish the floor. Or, best way to put drywall, siding, roofing, tiles, bricks, carpet, etc. What if I take a live video of my room, select objects in my room and change the color of those objects, change the color of my wall, add or remove objects, and get recommendations on furniture rearrangement.

Video recognition software will start to watch and train people. IE a kpop group dancing. The ML can watch each member dancing and point out issues like a person missing their step, queue, out of sync. This can be great for analyzation of group synchronizations. Football, basketball, choreography, ballet, and lots of areas. If students are practicing a basketball drill, the video can watch and make a beep when there is an error and say the jersey name or name of the player, re-run the video and show the mistake, then have them repeat the drill. Coaches can slowly be assisted by the “best ML coaches”. Ice skating. Synchronized swimming. These things can easily highlight errors. ML can also make corrective advice. If an ice skater jumps too early, doesn’t bend down low enough, the foot angle is off, the ML can point these out and give the correct advice like lower you hip, bend your knees more, arms are not high enough to generate lift, arms are not tucked in enough to generate spin. Even audio. Can eventually have music teachers that are AI. The camera and microphone watch and listen to you play a guitar. The ML then runs the correct finger placement video using Unreal Engine real time processing to show you an animated video of the finger placement and the ML playing the guitar, so you can pick any song, and the ML can render the correct finger placements for you to follow along. Can be applied to all musical instruments. Can train martial art forms to make sure you are doing them correctly. 

Like any game, ML has learned to play games. ML will start to make play calls. Football is just a game like any other game. You can feed plays into ML, and eventually, you can have a ML football play caller. You can take footage of real games at the NBA level, use that professional training data, and use that data to train you students those plays. Imagine an ML football coach that takes a HS team to the championships. News: First ML high school football play caller. Students at this high school have their plays called by a ML AI and have started to win more games as a result. They went from a 1-12 record to the current season of 5-8. Depending on how well the ML is trained, the metrics can be player heights, speed, power, least number of errors during practice, strong front line, players injured, ML can take all these metrics and information and make best play calls. IE you have a front line with a total calculated value of 10, but one main player is injured, so now your front line has a value of 6. Then the ML will know that the front line is weaker, time taken for quarterback is less, so play calls are for faster short passes and running plays to get the ball out of the quarterback’s hands and moving forward as fast as possible. ML can also analyze the opponent’s team and make calls based on their players. ML can learn to call pitches in baseball. ML can teach which players to pair with opposing team. Lots of possibilities. 

ML fly fisherman. Can train ML and a robotic arm how to fly-fish, where to put the fly, how much fishing line slack to give, and can ride around in a boat, park the boat, let the ML robotic arm do fly fishing by selecting locations to land the fly. On a more sophisticated scale, can tell you which fly to use, can read the river current, which types of fish at location, factor in time and date (depending on time, and fish, can tell you that there is only a 5% chance that this species of fish, at this particular time, during this season, would be eating at this time), and fish for you.  

Rip tides and sharks on beaches. Can train ML to read waves and predict likelihood of a rip tide area. Can use your phone to scan the beach area or where your kids are about to swim. Can eventually expand to 24 hours beach surveillance at popular areas to identify sharks by dorsal fins too. Use the US beach app, anywhere the beach surveillance camera is set up, can tap into with the app and get information like rip tide, shark, wave height, and set up phone push notifications for alerts while on the beach, as well as, tsunami warning. Plus, if something does happen, anyone checked in on the beach can be automatically reported missing, can have emergency contacts listed in app that get texted. Can check for anyone drowning or need help. Should be good in general to have emergency contact app. 

Law. Going to see a lot more ML in the field of law. Imagine that the ML tells you that 90% of people on trial were decided to be not guilty had used these top 5 buzz words repeatedly throughout their statements. IE Imagine training your client to say these words more “remorse, regret, innocent, victim, accident” can increase their chance to be found innocent by a jury. What if cases that used less data during trials of theft and more emotion won their cases by 75%. 90% of cases were won by lawyers that linked the criminal to the crime scene. 60% of cases were won focusing on these laws and their relation to this case. Lots of stuff here. What if we trained AI to read every single transcript of cases won in a particular field to give us the average number and types of statements to increase the chances of winning.

Teachers will be assisted, same as coaches. Why do we have thousands of math teachers all over the US teaching Math to 5th graders in over-crowded classrooms? Does their coursework change that drastically each year? If we are to really talk about having no bias, discrimination, equality, then all public-school kids should be taught math with the same lecture videos, homework assignments, and material. There is no prejudice because they are all receiving the same lessons. Their papers are all graded through ML, and there is no bias. ML can easily be taught how to read papers and grade based on understanding of the book assigned. As students all over the US submit their papers, ML gets better and better at grading. Math is the easiest because the answer either is or isn’t. 

Meal plans for people. ML will look at your physical, maybe genetics, maybe blood work, and start to make you meal plans based specifically to your needs. Maybe you go do blood work about once a month, and the ML gives you re-adjusted meal plans based on your current needs. For example, maybe you are low in iron, so the ML gives you meals that raise your level of iron. There are nutritionists that work in this field, but ML will do this a lot better. ML will sync with grocery stores in your area to help you order food or create a shopping list and price total. Work with your budget for more realistic options.

Planet finders through ML. Many possible ways. As of now, we are using the wobbles and dimming of suns to calculate planets in orbit, but ML will do this to a higher degree, faster, and more accurate, as well as, identify all objects within its “vision” in near real time like comets and meteors. In regards to the dimming of a sun as a planet passes in front of the sun, the biggest issue is that we only detect planets when that planet passes around that planet's sun in between that sun and Earth. That means that planets that pass around the sun with orbits that do not align with our direct line of sun do not really get detected (aside from the wobble method.) However, with improved resolution, we should be able to detect more planets that pass around their sun and reflect the light of their sun toward the Earth. That would mean that the sun's cumulative brightness would be detectable. For example, let us imagine a planet going around a sun, the planet is not passing in between the Earth and their sun, but the plant is going around their sun and having their sun shine light on that planet, the light from the planet is reflected toward the Earth. That cumulative planet brightness with the sun's brightness is another way to detect planets. Think about AI doing a calculation stating that a sun based on that distance and size should have this amount of brightness, detecting that brightness, and then checking for increases of total cumulative brightness within a pixeled area boundary. Another way, if not already in place, is checking objects for spherical shape. Stars for the most part are spherical. Planets are spherical. However, as a planet is going around a sun, the light that is reflected to the Earth is based on the position of that planet. For example, a planet could be at a 90 degree angle from the sun and us. That would illuminate half of the planet from our perpendicular perspective. That would make the source of light a non-spherical shape. We could easily modify AI to search for these types of non-spherical shapes and identify planets. 

  Vehicle traffic grids. Currently, we are working to get self-driving cars that work independently. Eventually, we will start to see larger control systems where all cars, maybe in a given area, are networked together to work as a hive to eliminate traffic as a whole. Image going to a ball game, afterwards, you get into your car. Normally, you need to wait, form orderly lines, hopefully, they have someone guiding traffic, other cars that are not using google maps will drive toward that area, some cars may avert the area seeing the streets marked as red, just a lot of overall disorganized and independent systems and drivers. However, in the smart grid system, all cars not from the game are diverted automatically away from that area, leave paths open for people from the game to leave that area, and now you have a smart traffic grid system that changes the orientation of lanes. For example, let’s say that a freeway had 4 lanes each way, but now the traffic automatically changes to 6 lanes one way and 2 the other for 3 hours. For us, this takes a long time, move traffic, change dividers (some are concrete and cannot be changed), but with ML and a hive system, these cars can easily change and adapt. Let’s say for the streets near the game, some streets are dedicated to traffic leaving that area and are no longer two-way streets, at least until, traffic has reduced or is gone. This in turn will reduce costs overall throughout. Why do we need street signs for cars when no one is driving? Self-driving vehicles will start to have their own indicators from the street. Maybe a stop sign later becomes a huge QR code for the car to understand speed limits, street names, and any other information. Self-driving cars won’t need traffic lights, and the costs related with creating and maintaining those structures. 

MX and AR reality glasses:

Farmers will be using these glasses to learn more about their crops and fields. A farmer will walk along their crops, the AI will do recognition of plants and trees, identify that the plants are asparagus, if the leaves are a bit yellow, the AI will tell the farmer that the asparagus leaves are yellow because of a lack of nitrogen, and therefore should remediate with this and that method. The MX glasses will keep a schedule of watering and tell farmers when to water which plants and trees. Also, the MX glasses will recommend layout patterns for future planting. Tell the farm that based on their land and size, that they could plant these plants here for higher yields and capacity, or better usage of land space. AI will manage farm lands, and help organize farmers together. Tell all the farmers that there is a global demand for this vegetable, and to start planting this vegetable here now, and AI will handle all of the transportation logistics. All of these physical laborers will be controlled by AI. At least until robots themselves can do more physical work. 

Classrooms will be all MX. No more trying to cheat on tests. Tests will all be given individually through their hololens. The huge benefit is working with special technology. Students will be learning in 3-dimensional space. Way more interactive projects and learning tools. Imagine building or cooking things while AI teaches us how to cook. Cut vegetables this way using this method, and watches our technique and critiques us. All learning will be MX. Visual interactive learning. What is the problem for undeveloped countries? They will still be learning through whiteboards. What is the issue? As MX technology comes into play, more students will learn through MX hand gestures and functionality. The issue is that GUI will become designed with MX interface gestures. This means that students that do not use MX interface, will not know how to use all of the technology to build and make the next future products. Think of Microsoft Office. Do you know how many people in SEA do not know how to use Microsoft Office and Google Workspace. That means that they do not know how to do any of the jobs that use those products, which is practically billions of jobs worldwide. If people in SEA do not know how to use the latest technology that these products are dependent on, then they will not be able to use the latest technology and products, let alone get jobs using that technology. What the people of SEA may not know is that there is a huge shift in jobs that is happening and that divide is being created by AI. As of right now, AI is splitting all the jobs in the entire world into two parts. One part is physical jobs, and the other is intellectual, creative, abstract, and less quantitative jobs. Everything in the middle is slowly being taken over and automated with AI. As more and more people in SEA fall into physical jobs, this will only be available until our robotics starts to catch up to human level abilities. If you want to know where robotics is at, watch the latest Boston dynamics videos, Amazon warehouse robotics videos, Tesla warehouse robotics videos. 

Animal training. AI will train animals with interactive learning and provide treats as feedback. Imagine a pet store that had a bunch of parrots trained in in English that are guaranteed to know how to say these words. Imagine every single dog you adopt is already trained with the basic sit, stand, paw, and roll over commands. Even better, imagine if all dogs came trained with basic mental health detection to spot if you are sad or unhappy and come assist you with a hug. AI will work with smarttech to open the door for your dog to go out and use the bathroom. The dog will be trained to bark commands to the AI. For example, the AI will have voice recognition of the dog, the dog will bark twice, and the doggie door to the backyard will open. The dog collar will be synced to the AI, so the front door can open, the dog walks outside, the AI with a camera and speaker on the collar tells the dog to turn right, go straight, walks the dog around the neighborhood, gets the dog to recognize street lights or tells the dog to sit, wait for crosswalk sign, and brings the dog back home. We can sync the dog with a self-driving car. Have the dog come outside, a self-driving car picks up the dog and takes the dog to a dog park, lets the dog run around, then brings the dog back home. 

AI will enter into every single field, career, sector, and technology, and automate so many of the things we do. The major difference with AI is that we have a harder time judging the impact of AI. If we see a line of cars being fixed, and our car is the next car, then we can easily see that our car will be worked on soon. However, in terms of AI that is conceptual, there is no “line” that we can see, so many do not know that their jobs will be replaced soon enough. The issue with AI is that once AI is better at things then we are, that AI is will soon be better than all humans. However, if an AI is better at a certain task, then that AI is better at doing similar tasks in every single job all around the world. That is another reason why AI is so powerful. If an AI becomes great at prediction, then AI will be able to make predictions in every single field, sector, and technology that makes predictions. If AI becomes great at being an assistant, then AI will be great at being a dental assistant, office assistant, executive assistant, medical assistant, psychology assistant, legal assistant, childcare assistant, and so on until this AI assistant surpasses the profession the assistant is helping. Then, these AIs will become professionals. In fact, this has already begun.

We even have AI models that have passed law exams to be a lawyer and medical exams to be a doctor. What will happen when the AI doctor is better than the best human doctor? Would you want your doctor to be any less than the best? What about for our children? Would you want less than the best doctor for your children? What about people in low income and poverty areas? They should have access to the best doctors in the world. AI will change all of that for them. Would you want the best lawyer? At a certain point, AI will be the best at many things, and we will have access to the best. Even most of the poorest people in the world, will begin to have access to the best AI models. 

Imagine the poorest village in some countries buying a smartphone and instantly having access to the best AI doctor in the world to help diagnose everyone in their entire village. What about the best AI English teacher? Would you want your children helped by the best AI tutors that are experts in every single subject? What about the best AI financial manager (FM)? We enter our income and expenses into the AI financial manager app, the AI FM manages our money for us, works with us to create a budget, tells us how much we can spend, how much we should save, helps us invest our money, we input that we need to buy new pants, the AI FM allocates a certain amount of money each paycheck for us to buy new pants by a certain date, shops online for us searching for the best deal for pants that we like and based on our current wardrobe. After we have enough money, the AI FM buys us the pants and has the pants shipped to our house, and continues to manage, save, and invest our money for us. AI will do all of these things and more. 

What about AI working and collaborating with other AI? What about a nutrition AI working with our financial manager AI? Our nutrition AI works with our financial manager AI to create a budget for us to incorporate more nutritious meals into our diet. What about the financial manager AI, the nutrition AI, and the virtual assistant AI working together to assess our budget, decide our meal plan, and the virtual assistant ordering those fruits and vegetables for us. The virtual assistant will handle the shopping, ordering, and payment of our meals for us and find us the best deals. What about a dietician AI working with the nutrition AI to help us choose foods that are diabetic friendly? What about a doctor AI that works with our virtual assistant to schedule medical appointments for us to get lab testing? What if the dietician AI works with the nutrition AI to set us a meal plan, the doctor AI schedules lab testing to monitor our over health levels, our smart glucometer sends our daily sugar level readings to the doctor AI, dietician AI, and nutrition AI to make any adjustments to our meal plan, works with our virtual assistant AI and financial manager AI to make sure our medical bills and insurance are covering everything, we have our copay budget, and the virtual assistant letting us know when our medical appoints are, when to take our meals, when to take our smart glucometer test, working with all the other AI to generate reports for us, working with the visual presentation AI to make us visual slides based on the reports, the virtual assistant AI will schedule an appointment with us, and give us our weekly update with a visual presentation on our finances, health, and the data from our lab tests. 

Powering all of those technologies like AI, ML, DL, and Gen AI, and many of the technologies we use on the internet and through our internet connection is the “Cloud”. The cloud usually consists of “networked computing [processing] facilities providing remote data storage and processing services via the internet.” Technically, this could even mean a single computer at another location that provides remote data storage and processing. In many cases today, the “cloud” basically refers to huge data centers full of computers networked together doing large amounts of storage, processing, and distribution of the stored data. However, even this terminology is no longer entirely accurate. The cloud has grown to encompass running entire programs, AI, ML, DL, and Gen AI models, software, applications, and provide us all kinds of services (tools) in almost every way imaginable.