Automation and growing population

Automation has been happening in different areas over time and with technological progress, it seems like a threat now. It is estimated that over two-thirds of the workforce will have no work in the next decade. While the population keeps growing around the world, the lack of work brings challenges for the future that need to be addressed today. While we will not have the same kinds of jobs in the future, there will be different jobs and we must train the future generations differently to tackle challenges of the future. However, our society has been designed around growth. Every country is ranked by growth numbers in the short and medium term. This forces everyone to keep churning good growth numbers year after year and ignore the bigger challenges that await in the future.

In order to tackle the dramatic shift in how future productivity will function – where more of the work is automated, we must be willing to take a hit on the meaningless yearly growth numbers and start working towards completely different metrics and frameworks that define growth and productivity in the future.

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Tesla taking on big oil

Tesla is a Silicon Valley company making cars. Companies in Silicon Valley have always been disruptive – changing behavior of people using technological innovations. We usually see companies making computers, software, processors, phone, etc. Tesla is focusing on transportation. Tesla is making desirable electric cars for the masses. Most cars on roads today are powered by gas, which is processed from crude oil. The world is dependent on cars for transit and hence on oil to keep people moving and countries progressing. Tesla is going to eliminate dependence on oil with move to electricity as fuel.

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Car vulnerability in the digital age

Car Security KitCars were a mechanical marvel. They were a combination of engineering breakthroughs integrated in a brilliant manner. The mechanical machines provided transportation within cities and long routes. They even got more economical over time and now most people on the planet own a car or have at least travelled in one. With the rise of technology, these mechanical machines evolved into technological instruments. Today, most cars are technology on wheels. There is not much mechanical left in them. Pressing the gas pedal does not move levers, but sends digital signals to the on-board processor. Everything from gas and break pedals, to the radio, to odometer and fuel readings is digital. There are various digital processors in the car and almost every action sends signals to different processors. These processors are similar to the ones on the computer or a smartphone. That means they are vulnerable to hackers. As we have moved to digital cars, the car makers have started hiring computer engineers and security researchers to prevent cars from being hacked. This has also given rise to car security companies that make devices to monitor cars with mobile apps and get alerts when theft occurs.

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Machine Learning and side effects of medicine

Machine Learning

Machine learning has a plethora of applications. One area in which machine learning is being used is the field of medicine. Researchers perform experiments in labs to study effects of medicine on different animals. When a drug works on a monkey or mice, they start a clinical trial on humans (after endless amounts of paperwork). If the clinical trial is successful on a diverse sample of subjects, then the FDA approval starts. After FDA approval, the drug can be marketed for mass distribution across the country. At this point, the drug makers spend money on marketing, sales representatives, providing incentives to physicians that agree to prescribe the drug, and advertising on TV and the internet. The drug is known to treat a certain condition, and has a list of known side effects. Millions of people across the country take this drug and it works for most of them. This is a system that has been in use for decades.

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Micro-sensors and the future of information

Micro-sensor chipWe live in the information age. You don’t need to go to the library for information. You can pull out your smartphone from your pocket and ask Siri or Google Now or Cortana, and it will read out the latest information for anything you ask. We have resources like Wikipedia for knowledge, Wolfram Alpha for mathematical information and countless news sites and blogs indexed by Google. All of this information is at our fingertips. But we are about to get a lot more information about a lot of new things. We have reached an era of powerful micro-computers that are cheap and affordable. They have a plethora of on-board sensors that can produce data. This data will give us an insight into a lot of topics that we did not know about. It will open up our understanding of the environment we live in, the factors affecting it, and we will learn even more after studying co-relations between the data we will soon have.

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Is Dreamcatcher the next level of CAD?

Autodesk Dreamcatcher BikeComputer Aided Design (CAD) has existed for a long time now. Designers learn how to use popular software like AutoCAD from Autodesk, and design products using the software. The traditional human designing process is now aided by computers. CAD enables designers to try out different designs on the computer and analyze them before they can settle on a design. Autodesk now has a new research project called Dreamcatcher. With Dreamcatcher, the fulcrum is slightly moved. Instead of computers providing help to the designer, the computer takes over and designs the product, while the human can propose tweaks and pick a design short-listed by the software. Dreamcatcher understands the product that needs to be designed, analyzes the different variables involved and does mathematical calculations to come up with the best design for the product. The human can then tweak or change the design and Dreamcatcher will finalize it.

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Genome sequencing: are we ready?

Genome Sequencing Technology is changing everything. Its changing how we think, how we interact, our social norms and every aspect of our life. It is also helping us progress in every field. One of the fields that has been completely changed by technology is genetic research. In the 1980s, the cost of whole genome sequencing was in millions of dollars. Over the years, the cost has been falling. In a few decades, the cost reached about $250,000. While that is still staggering, its much more affordable compared to millions of dollars. However, the cost has been falling steadily over time. It reached just $7000 a few years back and has just reached $1000 now. People can get whole genome sequencing for $1000. That is a more affordable price for people that would want their genome sequenced. Scientists and researchers have also been hoping to reach the $1000 price tag as it would make genome sequencing more accessible and would also allow us to gather more data from more people and use the data to make a difference. It can be used to understand diseases better, develop cures for the diseases and even enter the world of personal medicine. Its the beginning of the pharmaceutical revolution.

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Google Genomics and future of health

Google Genomics Technology has truly transformed mankind. Today, we live in a world of smartphones and clouds. Every question can be answered with a touch using Google search. You can find answers to almost anything in just a few minutes. People use Google search to find information on things ranging from physics to history. Some also look up medical information using Google search. This is about to change. Google has introduced a new venture – Google Genomics. It lets medical researchers store and evaluate genomic data in their cloud. The cost of storing and analyzing a genome has gone from millions of dollars to just under $1000 in the last 15 years. Its getting more affordable to store and analyze this data. What does this mean? It means that researchers can store more genomes and find interesting patterns in the data by analyzing a massive data sample. This can lead to all kinds of medical breakthroughs. We can cure diseases, identify likelihood of getting a disease for a given person, and even build custom medicine for a person. The ability to cheaply store and analyze this data will be a revolution in medicine.

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RoboBees and Colony Collapse Disorder

RoboBeesRoboBees are micro-robots designed by Harvard University researchers that push the limits of material science, fluid mechanics and computer science. They are tiny robots that are as big as honeybees and weigh less than 1 gram. They have wings similar to those of bees and can fly. The RoboBee made its first controlled flight about a year ago and has been under development so it can fly without being controlled.

Honeybees on the other hand are just bees popular for honey. However, they are also responsible for crop pollination. They play an important part in production of the food consumed by humans. Honeybees pollinate a third of the crops, which equates to $200 Billion worth of global crops and $15 Billion in the US. While they are a vital part of the food chain, they are at a threat. Honeybees have been going missing since the last few decades and this issue has been getting a lot attention since 2005 – 2006. One of the possible reasons for this occurrence seems to be pesticides. While pesticides protect crops from pests, they are causing adverse effects on honeybees and are a factor for Colony Collapse Disorder or CCD.

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WhatsApp as a social network

WhatsAppWhatsApp is one of the most popular messaging apps. In the early days, BBM (Blackberry Messenger) was used by everyone but was limited to Blackberry devices. WhatsApp provided a free messaging platform for Symbian (still popular in emerging markets), Blackberry, Android, Windows Phone and iOS. It was one of the first apps to be truly cross-platform, not just iOS and Android. With Symbian and Blackberry widely used in emerging markets, it got a lot of market share. Dozens of messaging applications have emerged since then, but there are two important aspects to such an application: (1) mass adoption by networks of people, and (2) being truly cross-platform (not just Android and iOS).

When using a utility application for Mail or IM, its easy to switch to a better application. With messaging, it does not make sense to switch when five of your contacts are using it versus hundreds on the other platform. So people are not likely to switch. What developers also forget is that Android and iOS are the major OSes, but only in North America. Asian and South American markets are still dominated by Symbian and Blackberry devices with Android gaining market share rapidly. Also when messaging patterns for WhatsApp is analyzed, its heavily used for international communication. When all of you contacts are in the US, you could use texting as most carriers now offer unlimited free texting. But for international messaging, apps like WhatsApp are used primarily. This means that supporting platforms in those markets is as important as iOS support.

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