Climate Change is a serious and impending issue that has not been addressed properly, particularly by this current administration. According to sources, the U.S. is in danger of losing billions of dollars. This is obviously a serious issue, considering almost all U.S. citizens know that the U.S. National Debt is over $20 Trillion, and rising. Clearly, an issue that could cost the nation even more billions of dollars of debt. The GAO or Government Accountability Office reported, according to US News, that the U.S. faces economic catastrophe if President Donald Trump does not act upon the issue. The Office of Budget and Management showed that all the extreme weather conditions and damage caused by the definite climate change in the past decade, has caused the nation around $350 billion. This is particularly important because we, as citizens and taxpayers, are spending more and more due to a distinct lack of attention to the serious issue that faces not only our country, but the world. We already know that Trump is making it his prerogative to undo all of the acts and efforts under the Obama administration, especially those related to climate, and that Trump willingly admits that he does not believe in any such thing as climate change, despite the clear scientific signs and evidence of it. The economic impact of not changing our efforts on climate change will be catastrophic and has to outweigh and be prioritised over the current political affairs. In recent news, sample prototypes of the Mexican border wall that Trump envisioned have been erected, though with no funding or concrete plan for the wall, will not be happening any time soon. With that in mind, Trump chooses to focus his attention on building walls and deporting immigrants, all of which involves lots of spending, rather than focusing on the important issues at hand. Senator Cantwell, one of the senators who requested the study on climate change be performed, hopes the current administration will focus on climate change, as by the year 2100, numerous deaths are projected to occur in the Southeast due to heat, roads and infrastructure will be destroyed, as well as issues with wildlife populations and marine life. The study also showed that short-term effects of climate change are just as detrimental, as the nation could be responsible for $4 to $6 billion from 2020 to 2039 just because of storms and rising sea level. The GAO recommended to the Office of the President, particularly the Office of Science and Technology Policy, to determine the issues with climate, and respond appropriately. The administration needs to focus on climate change and realise how important it truly is, and that if nothing is done, at the very least, billions of dollars will be lost.
Animals are more reliant on the Earth’s survival and are merely victims of the destruction humans have wrought on the environment. They do not contribute to global warming, but it is their homes being burnt or, in the case of the polar bear above, melted. Because of global warming, this polar bear does not have the appropriate environment it needs to survive. The icebergs are not freezing until much later in the season and are melting much earlier in the spring. Humans are too worried about their homes to even think of helping or protecting defenseless animals and their ecosystems. Other animals threatened by climate change include orange-spotted file fish, a fish that lives in and depends on their coral reef habitats. The warmer temperature caused by global warming is causing the coral reefs to dry out and even bleach. This means the orange-spotted file fish, and many other marine animals, are not able to get their necessary nutrients from the coral and algae. This fish has gone extinct before as a result of warmer ocean temperatures in Japan in the late 1980’s. Another animal affected by the icebergs melting is the Adélie penguin. The krill the penguin is accustomed to eating only lives on the under side of icebergs near the algae it normally eats. However, since the icebergs are not forming as quickly or in the same areas, the krill are not where they should be. Thus, the penguins must spend more energy foraging for food instead of breeding or raising their young. This results in a decrease of Adélie penguins in the long-run. If something drastic is not done about climate change, these species could die off forever with no chance of coming back.
The animals stated above are not the only ones affected either; among others, sea turtles, moose, and even koalas are feeling the brunt of human mistreatment. The nesting site where sea turtles lay eggs are more vulnerable to flooding because of the rise in sea-level. The eggs laid could be swept away by the tide, by an especially crazy storm, or they could fry under the newly intense heat. Without a safe place to lay eggs, these sea turtles can one day become extinct. Furthermore, Australian koalas are feeling the effects of the rise in temperature. The video below highlights the struggles the koalas are going through because global warming that we caused is drying out their only source of hydration.
They are being forced to act out of character, like being awake in the day, which can expose them to predators, and it can have serious repercussions on their systems if they do not know what time they should be active. We have been too worried about what will happen to us if the world burns, that we have not even given a second thought to what may happen to these defenseless animals. If we cared half as much about saving them as we did ourselves, they may actually have a fighting chance.
Machine learning has a great amount of meanings to different people. It has been around for years and now it is getting the attention it deserves. The technical definition of machine learning is “the concept that a computer program can learn and adapt to new data without human interference. Machine learning is a field of artificial intelligence that keeps a computer’s built-in algorithms current regardless of changes in the worldwide economy.” Many people think of artificial intelligence when they hear machine learning, and those people are not wrong but they are not right either. Essentially machine learning entails programming but instead of using code, one uses images and videos to build a model. A training set is selected, and the programmer chooses what imitates a positive or a negative for that specific set. Then they assign a specific model to use. The data one works with effects the model type and the size and quality of the sets. Additionally, it impacts the outcome. The process and technology itself is extremely complex and if something does not work correctly, the operation begins all over again. On the other hand, Artificial Intelligence depends on feedback as it interacts with the world and continuously adapts to new changes. There are layers to the overall aspect of Artificial Intelligence, which can easily be explained by this graphic:
Each level is a subset of the one before it, meaning one cannot properly function without the other. Deep learning carries out the machine learning process using an artificial neural net that is composed of levels arranged in a hierarchy. The particular network will learn something simple at the primary level, and then it sends the data to the following level. At the next level, the simple information is mixed with more data and becomes a little more complex. Then, it is sent to the third level. This process repeats itself at every level as the hierarchy becomes more and more complicated. Deep learning is essential for machines to be able to learn without a human labeling every single type of information that comes in, which is supervised learning. For instance, an endless amount of personal data is collected from social media accounts, hardware and software service agreements, app permissions and cookies. Businesses use this information for many reasons and it can be extremely valued. Not every element of the data is labeled which means it cannot be used to teach the machine learning programs that depend on supervised learning. To have a programmer oversee every data set that comes through would be extremely time consuming and expensive. Luckily, deep learning can help. It excels at unsupervised learning where the data is not labeled. Overtime, with enough information, deep learning can determine what is what, which helps machines learn without a human programmer.
Shockingly enough a children’s animation movie illustrated the abilities a robot could possess through machine learning. The Incredibles, a Pixar movie introduced in 2004, provides a good visualization of how machine learning and artificial intelligence work and the speed at which it processes real time information. Over time, it learns how Mr. Incredible fights and is able to determine ways to beat him. The villain, Syndrome, designed these killer robots, The Omnidroid, to eventually eliminate Mr. Incredible. However, over the years he put his prototypes up against other Supers in order to perfect his creation. As Mr. Incredible goes up against The Omnidroid the first time, it learned how he moved and predicted what he would do next. By doing so, it was able to delay Mr. Incredible’s victory. Even in 2004, moviemakers implemented this advanced technology in a children’s movie in order to show its future capabilities. A machine being able to learn in real time. As you watch the video below, pay attention to how Mr. Incredible initially jumps over The Omnidroid and how it then predicts him to jump over again.
Google has successfully combined deep and machine learning into a new program called AlphaGo. Go is an ancient Chinese board game which is allegedly the most complex and subtle of all board games. This is not as typical as chess, where a computer can calculate every possible move thousands times fast than a human. In Go, the possible moves are endless, which means no computer can handle trying. However, researchers in the UK were able to teach a computer program to play Go, but it also has the ability to learn from its mistakes. It used deep and machine learn to study which moves left it vulnerable and which ones lead to victory. In the beginning, there were a lot of mistakes made, but this was a good thing because the program was learning. The more it played against humans, the more it learned. As time went on, it played against more skilled players, and in addition with those games, it played matches against itself. When the researchers put AlphaGo up against itself, the program became much better as it was able to compete against a player at the same skill level. Eventually they put AlphaGo against the number one player in the world, Ke Jie, and beat him in five games out of five. After that, there was no one else left to beat in the world. AlphaGo was able to learn from itself and become the greatest Go player in the world, and it is just a computer program. If it is already the best, how much better could it get? AlphaGo Zero.
The opportunities to use machine learning are endless and highly effective. If in 2004 a children’s movie can display its basic capabilities then it is astounding to see how far it has come since then in the real world. The news of AlphaGo and AlphaGo Zero are surprising because it was not expected that this technology would advance this rapidly. These machine learning programs is truly a breakthrough breakthrough and it will continue to improve in the future.
The history of machine learning begins in 1950 with Alan Turing and the “Turing Test”, a test he created to determine whether or not a computer has real intelligence. In order for a computer to pass the test, it must be able to fool a human into believing it is also human. The test basically was a guessing game. There was a judge, a female contestant and a male contestant and the based off the answers to a series of questions the judge had to choose which of the respondents was human and which was the computer. The most recent modification to the test however doesn’t involve contestants. Simply, it is a judge and a computer and the judge has to determine if the respondent is a computer or a human. Since Turing introduced this test, the results have proven to be highly influential and also regularly criticized. However, overall the test has become incredibly influential in the artificial intelligence and machine learning world.
Another major advancement that occurred in the machine learning world was in the 1990s when scientists began creating programs for computers to analyze. From the data, computers where able to draw conclusions based on the massive amounts of data they were presented with. Simply, the computers were able to “learn” from the data. Computers, like IBM Watson are now able to store endless amounts of data, ranging from different topics, and they are able to make connections between the data in order to draw conclusions. For example, in 2011 IBM Watson was put to the test. Watson went up against the two greatest Jeopardy champions. After the first round, Watson was ties for first with $5,000. However, Watson made an incredible comeback and entered into final Jeopardy with $36,681, the next player having only $5,400. This test was groundbreaking not only for the IBM team, but also for AI and machine learning. Watson was able to enter into its data base to collect data it needed to answer the question, analyze the data, and great an answer all within seconds.
In 2012, Google developed an algorithm that was able to autonomously look through YouTube videos to identify all the videos that contained cats in them. Similarly, in 2014, Facebook developed the DeepFace software which was an algorithm that was able to recognize and verify individuals based on their photos.
These singular advancements in machine learning have made huge impacts on technology today and how we use it daily. Seeing how computer intelligence went from the Turing machine up to iPhones with facial recognition is incredible and it just shows that it will continue to change rapidly and that there is still much more to learn.
The innovation of online banking truly changed the way we handle money, but did the banks ever think this invention could fall out of their own hands? Everyday, I can check my bank account from the tips of my fingers, but things were not always like this. Fifty years ago, you would have to walk into a bank to do what you can now do simply on your phone. And this applies to a variety of services: you can deposit checks, make appointments, and even handle disputes over the phone.
Without a doubt, this technology has made the world much more efficient, but it has led to a few unintended consequences. The increase of banking technologies meant there was less need for in-person banking, and as result this hurt that aspect of their business. There is almost no communication between the depositor and the bank anymore since everything is done over the phone or at an ATM. For the average person, there is no need for a bank, just a lot of ATM’s and internet connection. Minus a regular checking account, the other services of a bank are becoming accessible elsewhere too. Not only do banks provide loans and compile information for companies, but Amazon is starting to do these things too. Who’s to say the frightful 5 cannot do what the banks are already doing now?
The key difference between banks and a company like Amazon is customer satisfaction. They have both evolved to offer similar interactive experiences on the web (lots of AI), but companies like Amazon, Google, and Facebook interact with their users much more, and offer a more pleasurable experience. As shown below, the disruptive improvements made by technology companies heavily influence the bank’s return on investments.
(Note: If digital disruption stays on pace, it is likely we could experience another depression by 2025 because the banks would perform so poorly it would affect many other businesses and their finances ran through the bank).
This screams nightmare for the banks. The bank is becoming small competition to these technology companies, and already they offer many of the same services in their bank-like accounts. Even I am considering an Amazon Prime Visa Card, prime benefits could be more applicable to me than the typical benefits of a credit card.
Going into the future, banks need to develop better relationships with their customers in order to compete. Likewise, many other companies must adapt and form databases of their customers in order to develop long-lasting relationships. The more digitally ahead a company is, the more likely they are to survive in the future. Now is the time to transform with the customers awaiting change.
Despite the staggering number of applications for gene therapy that are currently being investigated, the list continues to grow almost by the day. MIT researchers have discovered a potential genetic link between ADHD and Autism, meaning that gene therapy may be helpful in curing if not improving care for both disorders. The research shows that there is potentially a relationship between the brain’s thalamic reticular nucleus (TRN), which blocks out sensory inputs that can be distracting, and both ADHD and Autism. Their research suggests that when the TRN activity is slowed, the brain has a harder time controlling distractions. This means that an adjustment to the TRN behavior could help control ADHD and Autism symptoms, as well as other attention-related disorders. The study is still in its infancy and the testing is being conducted on mice, but the results are very promising. The results suggest that a correction of one specific gene, Ptchd1, carried on the X Chromosome, can restore TRN functionality.
While the research is still in the early stages, the long-term implications of a successful TRN-correction procedure are huge. The CDC estimates that 11% of children ages 4-17, accounting for 6 million children, suffer from ADHD. That is 6 million students struggling to pay attention in classrooms, struggling to focus during exams, and ultimately struggling to find employment if the symptoms persist into adulthood. If a gene editing treatment is developed, there is a possibility that those children will be able to participate and even excel in the classroom in ways they could not have fathomed without the use of prescription medicine. By eliminating the need for drugs like Adderall and Ritalin, thus eliminating children’s dependency on them, the general health of those suffering from attention disorders will improve greatly. The unfortunate reality is that disorders like ADHD condition children to depend on medicine to function properly. It is not their fault because the medicine is necessary to focus and learn, that said, it is not healthy to develop a drug dependency at such a young age regardless of its purpose.
Gene therapy is already being applied to so many genetic disorders, with the possibility of curing ADHD and Autism, a new generation of smarter, faster, healthier, and stronger people seems inevitable. There will potentially be 6 million more students studying harder, retaining more information, and ultimately becoming better learners. If this trend is multiplied across generations, eliminating prohibitive, cognitive disorders in students, it could reshape the entire education system with many subsequent disruptions. There would potentially be less of a demand for remedial education and an increase in demand for higher education or a productive alternative. This will lead to a smarter overall population, a scenario that has countless positive implications. Once of which is increased economic stimulation, resulting from the inevitable increase in demand for employment. It may be a stretch, but it is possible that one genetic modification in 6 million students could transform the entire economy.
It is easy to become caught up in the seemingly infinite number of applications for gene therapy, but the price tag is certainly a reality check. The current price for Yescarta, a patient-specific gene therapy procedure designed to treat aggressive forms of blood cancer, is a whopping $373,000. At that price point, it makes far more sense to treat attention disorders such as ADHD with prescription drugs. However, as the technology evolves, the price will inevitably come down. We are in a strange transition period in many different industries and medicine is no exception. The new advancements being made are nothing short of groundbreaking, but it is no small task to bring a new procedure to the market. Due to FDA regulations, years of research and testing are required before the first human trials, and even then, successful implementation into the market is not guaranteed. In medicine, consumer demand for treatments is ahead of the technology, and the technology is way ahead of the FDA. This may slow down the implementation of new drugs and procedures, but their timelines do not detract in any way from the scope and severity of their implications.
With incredibly quick rise of Tesla, battery storage as a source of energy has quickly become a topic of discussion. Last week two energy companies announced their plans to combine battery power with solar and wind power to provide consistent energy to Australia. Australia is heavily dependent on the use of fossil fuels, 63% of energy use comes from coal, and is in need of alternate forms of energy. Combining battery, wind and solar energy is believed to be advantageous because it is more resilient and more adaptable than single source energy. For example, it can produce more energy during prolonged periods of cloudiness or low wind speeds.
Another company in the United States is attempting to something similar by combining battery storage with hydro-dams. Hydro plants store great amounts of energy, however they have slow response times; battery storage units have much faster response times. The main disadvantage with batteries is they have smaller storage capacities but the hydro plants will compensate.”By combining generation with storage, we can take advantage of the beneficial performance characteristics — fast response, fast ramp rate, low O&M costs, zero emissions — while using the generation asset to address the constraint posed by storage’s limited energy duration,” Combining battery storage with other forms of clean energy can potentially be an excellent way to maximize our energy efficiency while minimizing the trade-offs that result from using clean energy. We are continuing to learn more and more about batteries and it will be interesting to see their capabilities once they’ve reached their full potential.
Climate change is often thought of as the result of the greenhouse effect; and therefore, the cause of the rise in sea level, and bizarre weather patterns, such as extreme heat waves and record-breaking hurricanes. While all of this is true, the focus on climate change is centered on the weather occurrences being observed and experienced in the present. Climate change affects the Earth and its atmosphere. On a side note, the Earth’s upper atmosphere is a junk yard composed of remains of satellites, rockets, and other objects that have entered space. As a result of the increasing temperature of the lower atmosphere, where we live, the temperature of the upper-atmosphere is decreasing. The decrease in temperature causes the upper atmosphere to contract, thus removing some of the air; with less air, there is less friction in the upper atmosphere. If there is less friction in the upper atmosphere, less “space junk” falls back to Earth.
The following is an image of roughly the amount of space junk around the Earth:
There are those who think that less space junk falling back to Earth is a good thing because there is less to potentially cause damage upon re-entry. However, most space junk that does fall back to Earth burns up upon re-entry, an object would have to be significantly large in order to touch ground upon re-entry. In contrast, small objects in space can cause a lot of damage. There are roughly 520,000 trackable pieces, while millions pieces of debris that cannot be tracked. As a result of space junk building up, it has created a space junk yard, and imbedded in that space junk yard are communication satellites. Communications satellites play an integral role in daily activity. For example, without communication satellites technology like satellite internet, phones, satellite TV, GPS, weather tracking, and military communications would either not work or become over loaded with data and slow down. Imagine a world were cable internet would become so congested with data, it becomes almost impossible to use. Moreover, imagine a scenario where because weather patterns cannot be tracked, a hurricane like Maria hit Puerto Rico before people got any notice to take safety precautions. In addition, without TV it would become extremely difficult to notify people of such dangerous weather patterns. Without military communications, or at least slowed military communications, would leave, troops and the country vulnerable to attacks. With this said, these scenarios are only possible if all or at least most of the current communication satellites are wiped out. As a result of less space junk falling to Earth, the chance of satellites being damaged increase significantly. According to the Kessler Syndrome, the odds of damage to satellites increase with every collision of debris. The Kessler Syndrome states when one object bumps into another object, the momentum of those two objects increase the chances of the objects hitting into another two objects. Therefore, one object causes a total of two objects to be in motion, two becomes four, four becomes eight, eight becomes sixteen, so on and so forth. The initial bump between two pieces of space junk sets off a chain reaction substantially increasing the odds of any of the satellites in use becoming significantly damaged.
To no surprise, there is no immediate or fast solution for protecting satellites and clearing the “space junkyard.” For example, CleanSpace One has created a satellite with the purpose of grabbing debris and carrying it back in orbit, thus burning up itself and the debris upon re-entry. However, this cleaning satellite is not designed to handle like amounts of debris at once, and is a one-time use satellite. Multiples of these satellites would have to be shot into space to create any significant change, but remain a viable solution for getting rid of large debris in the case of an emergency.
The following is a video further describing how the CleanSpace One satellite works:
Moreover, it is equally important to make sure the issue does not become worse over time. To prevent more debris building up, future space vessels should be built with material that erodes easily in the presences of ultra-violet rays. Using such materials causes allows debris to break apart over time, and specifically helps with getting rid of smaller debris, thus allows satellites like CleanSpace One to focus on collecting larger objects. Without action now the issue will continue to grow, while it literally hangs over our heads.
Quantum computing could be coming sooner than anticipated. With Google’s recent announcement regarding the progress on their own Quantum Computer, the time period in which these supercomputers could make their debut may have shrunken exponentially. Though some say Google is premature in their predictions, they are yet another addition to the arms race for “quantum supremacy”. So why does everyone want to be the first? Quantum computing has long been synonymous with innovation. With increased computing power comes unlimited solutions to outstanding problems in our society. While this is true and something to look forward to, there is something far less beneficial coming with it as well, the need for quantum cybersecurity.
Almost everything we use today depends on our technological grid. As the Internet of Things grows and grid systems modernize, the susceptibility to cyber attack increases. The more access points, the better the chances that malware could be planted on devices that have the ability to destroy equipment, cause widespread outages, and threaten public safety. This can all done thousands of miles away in a secure environment with relative anonymity if done properly. To combat this, cryptography has become an integral component of our digital infrastructure. Effective encryption is not just important, it is necessary for government entities, businesses and individuals to protect their digital communication. Many of our core communication protocols rely on 3 functionalities in particular: public key encryption, digital signatures, and key exchange. With the advent of quantum computing, these forms of encryption are rendered completely useless. Because quantum computing is based on encoding data into the superposition of states and creating quantum bits rather than the ones and zeros in the binary digits of classical computers, quantum computers will have the ability to crack the large-scale cryptography that exists within our current grid system within seconds. Linus Chang, the founder of Australian software company Scram Software put it like this: If a classical computer and a quantum computer were given the same 56-bit encryption, it would take the classical computer, on average, 1 day to crack it while the quantum computer would take 0.322 milliseconds. Imagine that power in the hands of the wrong people.
ABI Research, the leader in emerging technology intelligence, predicts that the first attack-capable quantum computers will be on the market by 2030. That is a short time before every device we own and all the information and data accumulated by extension is immediately accessible if the attacker wants to target us, and there are plenty who do. What we need to do now is prepare ourselves for this imminent threat with quantum cybersecurity. While traditional cybersecurity addresses network breaches after they happen, quantum cybersecurity consists of implementing quantum security measures before the attacks occur. This can be done right now by adding quantum key distribution to existing encryption to strengthen it against potential attacks.
Quantum keys are the world’s only true random numbers and through this distribution, only the keys are shared using photons of light. While these photons can be intercepted, they cannot be cloned. This no-cloning ability is the fundamental principle behind quantum key distribution and its revolutionary abilities have already been recognized and implemented by Swiss banks and European governmental units. In the longer term, quantum networks must be integrated into our existing transmission lines and quantum-resistant algorithms must be deployed. Understanding that these cybersecurity measures must be taken now is crucial. The threat posed by the advent of quantum computers is imminent and affects all of us.
I’ve spent a number of my posts discussing Puerto Rico and the U.S. Energy issues, but there is a lot more to this project than just that (my team-mates have eluded to this as well).
“Production of fossil fuels is expected to rise, approximately doubling the amount of use of each fossil fuel. As world population continues to grow and the limited amount of fossil fuels begin to diminish, it may not be possible to provide the amount of energy demanded by the world by only using fossil fuels to convert energy” says this article. It goes on to say: “Countries must take action to promote a greater use of renewable energy resources, such as geothermal energy or nuclear power, so that we can be well prepared when the supplies of fossil fuels are not as plentiful as they seem today.”
Perhaps one country that might’ve read this article, is Morocco. See what they did below:
For the U.S. perhaps exploring our own deserts, such as in Nevada, might be a good idea. Furthermore, we can benefit as a world considering other locations/ways to naturally generate energy.
Before we get so desperate that we have to explore some outlandish options, our world leaders should seriously stop dismissing our climate problem and seek responsible, sustainable ways of producing and harvesting energy.