AI and the Future

There are many names that describe the field of computing which seeks to give computers the ability to deal with the real world intelligently.  Among them are artificial intelligence, machine learning, or just plain intelligence.  Computer scientists are now working on methods to build computers that can operate on a level past basic logical reasoning, like mathematical operations or games of chess.  Artificial intelligence instead seeks to build machines that can learn from the environment and real people, as well as learn from the mistakes it makes along the way (very much like real human beings have done for all of our existence).  In fact, a number of computer systems already achieve this kind of real-world interaction and application. Anti-lock brake systems, airplane autopilot systems, and even email spam folders that differentiate legitimate mail from spam are all examples of this type of technology.

So how do artificial intelligence machines work? It all starts with what is called a model, or an initial prediction for how the machine should work, and it is given by a human being to the computer.  For example, a teacher wanting to use artificial intelligence to determine the proper amount of time to study for an example will first enter a model like 2 hours for a C, 3 hours for a B, and 5 hours for a C.  From there, real data is input to the computer, which is then used by the “learner” to change the model accordingly for a more accurate prediction.  This simple cycle is repeated over and over again, with minute adjustments being made by the computer along the way to achieve incremental change.  Through observing more and more real data, the machine will develop the best model it can.

Google wants to make Star Trek technology a reality.

One application of machine learning is image recognition.  Obviously, computers do not have eyes and thus cannot identify pictures the way that we do.  As a result, machine learning can step in to give computers the ability to differentiate a picture of a cat from a hot air balloon.  To do this, a human must first enter a model for the characteristics that might make up a picture of a cat as opposed to the hot air balloon.  After that, the computer is given test sets of pictures so that it can develop a better sense of what makes up specific pictures, and change the model accordingly. 

Right now, many companies are devoting its resources to develop artificial intelligence machines that will function as natural human assistants.  Google, for example, likens its Google Assistant project to the intelligent computer famous from Star Trek.  “If the Assistant works as well as Google hopes, all you might have to do is say, ‘O.K., Google, I need to go to Hong Kong next week. Take care of it,’” according to a New York Times articial on the project. This technology has the power to make sci fi movie technology a reality.

Pictures & References:

http://marketingland.com/how-machine-learning-works-150366

http://www.nytimes.com/2016/09/29/technology/google-assistant.html 

Computers and Boats Collide

As self-driving cars will soon be hitting the road across the world, Amsterdam will be welcoming a fleet of experimental autonomous boat robots as part of a joint urban planning research project.  The project, to be launched in 2017, is being jointly run by MIT and the Amsterdam Institute for Advanced Metropolitan Solutions.  It will use the world’s first fleet of fully autonomous water-based robots called ‘roboats’ to examine new solutions to urban development and water systems efficiency.

Each roboat will have the capability to function as a goods transporter, a human transporter, and on-demand bridge building blocks.  In a matter of hours, floating bridges or stages can be constructed and dissembled automatically.  In addition, each roboat will constantly monitor the water quality of the canal it is floating on.  The functionality of the fleet and the data it collects will help researchers discover new solutions to urban development and urban efficiency.  Home to more than 1,000 kilometers of canals, 1,500 bridges, and a long history of canal-based commerce, Amsterdam is an ideal city environment to develop this technology.

On-demand bridges can augment the already existing network throughout the city.

As cities struggle more and more with population capacity and the stresses it puts on transportation, public health, and environmental systems, the data collected from roboats are expected to provide a reference for real solutions that will not only be effective, but also environmentally conscious.  “Water is the bearer of life. By focusing on the water system of the city, ROBOAT can create opportunities for new environmental sensing methods and climate adaptation. This will help secure the city’s quality of life and lasting functionality,” says Arjan van Timmeren, professor and scientific director at AMS.

References & Pictures:
http://senseable.mit.edu/roboat/
http://news.mit.edu/2016/autonomous-fleet-amsterdam-roboat-0919

Is this fruit ripe for eating?

Physically touching the fruit to evaluate can potentially become obsolete. 

Do you have a hard time determining fruit ripeness?  Do you have a smartphone?  Well, in that case, the 21^st century phenomenon of “there’s an app for that” has finally come around to addressing your issue.  Researchers out of MIT Media Lab have developed a spectrometer, a device that measures wavelength of light, and an algorithm executable on smartphones that effectively measure ripeness of various fruits, including apples, bananas, and oranges.  While working in tandem, the spectrometer and smartphone software can calculate the ripeness of the fruit in question, affording any human the ability to determine ripeness of fruit for eating.

MIT Media Lab's fruit spectrometer

Spectrometers have historically been expensive to produce and quite large; however, through the advancement of micro-electro-mechanical systems technology, scientists were able to shrink the size of the spectrometer chip to about the size of your average garage door opener.  Due to their accuracy in measuring objects without touching or disturbing them, spectrometers are indeed used in a variety of fields, including the use I outlined in my last blog post (reading books without opening them.  Similarly, the spectrometer designed by MIT Media Lab emits electromagnetic radiation and reads the radiation reflected back to it. 

In this case, instead of ink, the EM radiation is reflected by the chlorophyll within the skin of the fruit, and instead of terahertz waves, ultraviolet fluorescence is measured.  Researchers were able to design an algorithm to evaluate the amount of fluorescence measured and determine how ripe the given fruit is, and alert the user how much longer the fruit needs to ripen in the event it is not yet fully ripe.  The spectrometer can be assembled for about $250 and communicates wirelessly with the smartphone. 

The device is not yet available in the open market.  However, they have released an open-source platform online at hackaday.io, which provides all the information needed for someone to replicate the device or even develop it further. 

Pictures and References:
http://www.latimes.com/science/sciencenow/la-sci-sn-ripe-apple-app-20160910-snap-story.html
https://www.youtube.com/watch?v=uj8E8iOkU-w
https://en.wikipedia.org/wiki/Fruit

Making the Invisible Visible

    

    A research project at MIT has successfully developed a new method to read an unopened book.  Using computers, cameras, and physics, the MIT Research Lab scientists were able to read up to nine pages deep into a closed book.  They are currently still working to expand the capabilities of this breakthrough technology.

    Their method takes advantage of terahertz radiation and the way it interacts with the world around us.  As opposed to other wave frequencies, terahertz radiation can offer precise representations of the chemicals and objects it bounces off of.  We can measure these representations to see what was once hidden from our eyes, as the radiation is able to penetrate surfaces.  Terahertz waves are much more accurate than other waves, such as x-rays, which are useful to determine how many pages of a book there are but offer no capability to distinguish what is actually written on them.

 

The blue wave represents what was first emitted, and the red represents the waves that were bounced back.

    To determine which page the words read by the computer are on, the scientists use timing methods to track the time it took for the wave to get sent out, bounce off the page, then return to the camera. This system is based on the idea that between all pages is a 20mm deep air pocket, which refracts the terahertz waves in a way known to people learned in physics.  As a result, an algorithm was developed to interpret this data and pinpoint each individual page.

    An important application of this computing ability is reading incredibly old or delicate books that researchers are not willing to even touch out of fear of damaging it.  With this new method, we can decipher what is contained in ancient texts that before were mysteries to scholars who had no choice but to not touch them.  New York’s Metropolitan Museum of Art has already expressed interest in taking advantage of this technology to study pieces in its own collection. 

References and Pictures:

http://news.mit.edu/2016/computational-imaging-method-reads-closed-books-0909

https://www.youtube.com/watch?v=6i25SuJzb0A

The Business of Innovation

Some of my first memories are of using my PC as a young kid and trying to get connected to the Internet to play flash games.  I still remember waiting patiently for my mom to end her phone call so I could get online.  As a person born in the latter half of the 1990s, I grew up taking the fact that every home had a PC for granted.  What I never realized was the fact that it took a select few companies, and even just a few forward-thinking people, to make this reality possible.

Bill Gates co-founded Microsoft as a college dropout in 1975 in Albuquerque, New Mexico.  The company’s total revenue by the end of 1976 was just $16,005. Today, Gates is worth $90 billion and Microsoft has become the world’s largest PC software company.  In 1975, the idea that all business people needed a computer was considered far-fetched, and the idea of every home having a PC was even more so.  However, after Gates saw that kits were being made for building affordable personal computers, he decided to start his own venture with a friend and write software.  Gates took on role as CEO and himself wrote much of Microsoft’s code.

 

Microsoft staff in 1978

Steve Jobs grew up in Los Altos, California and also bears the title of ‘college-dropout'.  However, with a passion for electronics and a desire to change the world, he cofounded Apple in 1976, almost a year to the day after Microsoft was founded.  The revolutionary products rolled out by Jobs and his company have completely changed the world.  IPhones allow users to listen to music, browse the internet, place calls, text anyone in the world – the list goes on.  All of these incredible advancements in society were the result of a college dropout with an interest in a new type of machine.

Jobs' childhood home in Los Altos, CA

What is so exciting about computer science and its intersection with the business industry is the power computing innovation has on people all over the world.  With just a little ambition and some mechanical skills, ordinary people can take a hobby and use it to develop computers and software with unparalleled functionality.  It can also make you rich in the process.  Indeed, never before in human history has business and science come together to so suddenly create new industries and the daily lives of people around the globe.

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References:

https://en.wikipedia.org/wiki/Bill_Gates

https://en.wikipedia.org/wiki/Apple_Inc.

Pictures:

https://en.wikipedia.org/wiki/History_of_Microsoft#/media/File:Microsoft-Staff-1978.jpg

https://en.wikipedia.org/wiki/Apple_Inc.#/media/File:Apple_Garage.jpg

https://en.wikipedia.org/wiki/Silicon_Valley_(TV_series)#/media/File:Silicon_valley_title.png