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1.1 - Why Study Algorithms - Introduction - [DSA 1] By Tim Roughgarden

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1.1 - Why Study Algorithms - Introduction - [DSA 1] By Tim Roughgarden

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Data Structures and Algorithms Complete Tutorial Computer Education

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1.1 -  Why Study Algorithms - Introduction - [DSA 1] By Tim Roughgarden

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Compiler Theory: https://www.youtube.com/watch?v=6NKi7eCabzo&list=PLLH73N9cB21W1TZ6zz1dLkyIm50HylGyg&index=1 For any query you can comment it! We try our best to answer them! Please do "like" this video and "subscribe" the channel if you want more of this which we will be uploading very soon!! About Tim Roughgarden: https://plus.google.com/114760238653960137483 http://theory.stanford.edu/~tim/ http://en.wikipedia.org/wiki/Tim_Roughgarden http://www.cs.cornell.edu/timr/ Index Data Structure And Algorithm 1: 1.

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YOUTUBE : Algorithms Are Taking Over The World: Christopher Steiner at TEDxOrangeCoast

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YOUTUBE : Algorithms Are Taking Over The World: Christopher Steiner at TEDxOrangeCoast

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MIT Technology Review and Skiing Magazine

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Algorithms Are Taking Over The World: Christopher Steiner at TEDxOrangeCoast

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Christopher Steiner is the author of Automate This (2012) and $20 Per Gallon, a New York Times Bestseller (2009). He is a cofounder at Aisle50, a Y Combinator company that sells grocery deals through the Web. Before starting Aisle50 in 2011, Steiner was a senior writer covering technology at Forbes magazine for seven years.

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Google DeepMind's Deep Q-learning playing Atari Breakout

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Google DeepMind's Deep Q-learning playing Atari Breakout

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Google DeepMind created an artificial intelligence program using deep reinforcement learning that plays Atari games and improves itself to a superhuman level. It is capable of playing many Atari games and uses a combination of deep artificial neural networks and reinforcement learning. After presenting their initial results with the algorithm, Google almost immediately acquired the company for several hundred million dollars, hence the name Google DeepMind. Please enjoy the footage and let me know if you have any questions regarding deep learning!

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Google DeepMind's Deep Q-learning playing Atari Breakout!

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We've reached a defining moment in our collective human history.

It's time to decide whether we should give machines the option of purposefully killing us - if the alternative results in more human casualties.
The test is simple: if a self-driving car had to choose between ramming into a wall and killing its sole passenger, or flying into a crowd of 10 people, which should the computer choose?
The logical answer, assuming the car has performed optimally, is that this is an unavoidable, tragic accident where someone is going to die. Generally we can agree that, when these are all nameless, faceless strangers, 10 lives are more valuable than 1. But this 'utilitarian' approach to human lives is only so clear cut and simple when we pose the question to control groups with little stick figures representing the victims. As soon as this a real situation, it's hard to find anyone advocating a car that will kamikaze them into a wall at a moment's notice.

People crave agency, especially in life-or-death situations. It's the reason people can happily and recklessly drive a car down a highway but sit white-knuckled during an airplane flight - even though the plane is statistically much safer than the car. On the plane, if something goes wrong, you can scream, you can put on your life vest or oxygen mask, but you can't change the outcome. Your life is in someone else's hands. With self-driving cars, we've taken this a step further - your life is in a computer's hands.

We indirectly put our lives in computers' hands all the time, sometimes without realizing it. Algorithms run medical systems, university admissions, life support systems. Robots are doing surgery, your position on the kidney donor recipient list is determined by an algorithm. Computers are working right now to cure diseases that millions of people have, military drones are performing autonomous missions, taking human lives without direct human input. None of this is as immediate to us, as relatable, as the example at the top. The car does not have to kill you. It can easily keep you alive, at the expense of the pedestrians' lives.

Would you buy a car that would trade your life for someone else's? I certainly would never get in a car that would trade my life for a stranger's life. If one of us has to die, I'd rather it be someone else. I'm not buying a car as a moral statement. I want to live through an accident.

Maybe you consider ten human lives ultimately superior to one human life. That's a stance a lot of people already disagree with, at least when theirs is the life in question. Human self-preservation is a powerful instinct. While you may be fine with a nameless stranger crashing into a wall to protect 10 nameless strangers, how would you react to hear your loved ones were killed by their vehicle? That they were the only casualties in an accident, quite literally executed by a piece of code.

Personally I think an ethical car would be fine. The backlash for implementing such as system would depend on how good the system was, and whether or not we had 'smart' cars on the road or not (more on that later).

The utilitarian argument may still catch on. I suppose a happy medium would be giving the driver control of the car at such critical moments, but people can panic in an emergency and make things worse than they have to be. It's a losing situation where you want a perfect computer or no computer, but you're never going to have either of those in your autonomous car.
Uncaught Exceptions
When an algorithm kills someone, who is to blame? The programmer? The manufacturer?

Or is nobody to blame, the passenger assuming all risk by entering the vehicle? In that case, should a child waive their life in the same way? What should the computer do if there are children in the car and the 'pedestrians' to be hit are adults?

Is 1 child > 1 adult a true statement?

If a child runs onto the road, should the car risk the lives of the passengers to try to avoid the child, or is it not worth the risk because the child is 'at fault'?

What if it's an adult recklessly crossing a highway?

What lengths should the car go to to find the 'mathematically' correct option? E.g. the car decides we can have a rollover crash by swerving out of the way to not hit two people, ends up with you in a coma. The alternative would have been to hit them at a reduced speed and probably not kill either, but because 2 > 1 ⇒ you got fucked. Is it your moral duty to pay for other people's mistakes on the road?

If it were a human driver, most would not hesitate in choosing the option that kept them alive. Should self-driving cars try to emulate human behavior, or aim for a collectivist approach? Or should you just have a choice of ethics modules when you purchase your car?

The answer is that we, as a society, need to be mature enough to address these issues sooner rather than later. Nobody is going to buy a self-driving car that's programmed to kill you - that is unless every self-driving car is programmed to kill you. It's an all-or-nothing situation - the first self-driving car that advertises 'self-preservation' technology is going to popularize the selfish algorithm over the ethical one. Given the choice of offering a boilerplate collectivist AI or a 'safety-conscious' AI that will preserve the lives of the passengers at all costs, everyone is going to choose the one that keeps them alive, while simultaneously wishing everyone else had the collectivist AI. Is it short sighted? Maybe. Can you blame us? Not really.
New Software, Same Old Problems
The fact is that a self-driving car, in 2015, with our current technology, is better at (simple) driving than a human driver. The majority of accidents involving these vehicles are caused by human drivers. The importance of reaction time in the act of driving cannot be overstated, and a human will never react as fast as a car CPU. The lack of control of the vehicle is what is keeping us from a massive shift to self-driving vehicles. Our current options allow you to control the vehicle at any time, all well and good until we have people who start sleeping in their cars as they drive.

There are also a plethora of issues that plagues the primitive AI. This article discusses ways self-driving cars lag behind humans in driving skill. For example, if a ball comes bouncing onto a road, a human driver might slow down in anticipation of a child. A computer needs to be explicitly taught this scenario to react in the same way. Because of the magnitude of scenarios that can't be hardcoded into the car's operating system, it needs to drive extremely defensively. As soon as it sees the ball, a self-driving car will likely come to a stop until the obstruction is gone, or attempt to go around it at low speed if the roads are clear. Obviously human drivers can also exploit the naivety of autonomous vehicles, cutting them off and generally driving like assholes around them because they know they will always yield.

The first time a human is killed by a self-driving car is going to be a wake-up call for us to start addressing these problems. This is a technological leap forward that will pervade our lives in the future. We are going to need to face some surreal ethical questions very soon, and it's important we're all on the same page.
What is your point?
Technology has given us this dilemma - it may also be the safest way out of this dilemma. If autonomous, or at the very least 'smart' modules are implemented in all the cars on the road, vehicles can communicate to avoid dangerous scenarios. Swerving to avoid a child that's run onto the road only to crash head-on into a van is not a scenario that can happen if your car can 'tell' the van to brake as soon as your car sees the child. Cars in traffic could interact with each other 250m from each other. Yes, this has terrifying implications regarding the security of these modules and what a malicious person with access to them could do. But we've solved one problem, and with cars communicating and operating in tandem we'd help reduce both accidents and gridlock.

Then there are mistakes. Bugs. Glitches. Even in the perfect world of sensor-laden, radio-communicating vehicles, there are going to be errors. We know that the programmers of these vehicles are going to take their job seriously. There will be failsafes and redundancies, they'll put in some high-level chips and code to deal with rare events. Most problems with your car are going to default to it pulling over and turning off, not veering wildly around the interstate. If it does have to turn off, it can alert all smart cars within a certain area before it shuts down so they can avoid it.

However, even with perfect programmers in a perfect world, we're still dealing with millions of tons of steel flying around the country under all sorts of weather conditions, on all sorts of roads, in all sorts of scenarios. Safer than human vehicles, sure, but autonomous vehicles are going to lead to people dying or being serious injured. That is guaranteed. That is statistics. How we react to this is the real question. In the end, this is fundamentally an ethical and philosophical problem. The technology will advance in whatever direction we pull it in, but our values and morals are not as flexible and must be hashed out.

If we as a society decide that we can't stand behind cars killing their occupants for the greater good - there will be no self-driving cars with ethical algorithms. There will be selfish self-driving cars. It's a hurdle we need to jump, a barrier we need to break through to introduce this technology. The benefits are mind-boggling and stand to change the way we live our lives. Imagine sleeping in your car while it drives you to your next destination. Hostels or hotels are suddenly irrelevant to the frugal traveler. A single family car spends the day driving around, picking up and dropping off family members to work and school, and collecting them at the end of their day. Why fly when your destination is an 8 hour night drive away, in a car that looks more like a mini hotel room than your current car? Instead of truck drivers working ridiculous shifts, we have automated conveys rolling through highways, slashing the price of distribution. Drunk driving is virtually eliminated, just take a nap in the back of your car as it drives you home from the bar. Tell your car to bring you a pizza before picking you up. Why not? It's the future, and pizza tastes damn good in the future.

There is a lot to take in - and it's coming soon. Sooner than you think, and we shouldn't leave these decisions up to the manufacturers or government. We need to discuss and decide what we want out of this technology, we will be the end-users of these cars. This technology will cater to us - if we can make up our minds.

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We've reached a defining moment in our collective human history. It's time to decide whether we should give machines the option of purposefully killing us - if the alternative results in more human casualties.

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Why links are still the core authority signal in Google’s algorithm

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Why links are still the core authority signal in Google’s algorithm

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It's almost impossible to see any meaningful search engine optimization (SEO) results without spending some time building and honing your inbound link profile.

Of the two main deciding factors for site rankings (relevance and authority), one (authority) is largely dependent on the quantity and quality of links pointing to a given page or domain.

As most people know, Google's undergone some major overhauls in the past decade, changing its SERP layout, offering advanced voice-search functionality and significantly revising its ranking processes. But even though its evaluation of link quality has changed, links have been the main point of authority determination for most of Google's existence.

Why is Google so dependent on link metrics for its ranking calculations, and how much longer will links be so important?

The concept of PageRank

To understand the motivation here, we have to look back at the first iteration of PageRank, the signature algorithm of Google Search named after co-founder Larry Page. It uses the presence and quality of links pointing to a site to determine how to gauge a site's authoritativeness.

Let's say there are 10 sites, labeled A through J. Every site links to site A, and most sites link to site B, but the other sites don't have any links pointing to them. In this simple model, site A would be far likelier to rank for a relevant query than any other site, with site B as a runner-up.

But let's say there are two more sites that enter the fray, sites K and L. Site L is linked to from sites C, D and E, which don't have much authority, but site K is linked to from site A, which has lots of authority. Even though site K has fewer links, the higher authority link matters more - and might propel site K to a similar position as site A or B.

The big flaw

PageRank was designed to be a natural way to gauge authority based on what neutral third parties think of various sites; over time, in a closed system, the most authoritative and trustworthy sites would rise to the top.

The big flaw is that this isn't a closed system; as soon as webmasters learned about PageRank, they began cooking up schemes to manipulate their own site authority, such as creating link wheels and developing software that could automatically acquire links on hundreds or thousands of unsuspecting websites at the push of a button. This undermined Google's intentions and forced them to develop a series of checks and balances.

Increasing phases of sophistication

Over the years, Google has cracked down hard on such rank manipulators, first punishing the most egregious offenders by blacklisting or penalizing anyone participating in a known link scheme. From there, they moved on to more subtle developments that simply refined the processes Google used to evaluate link-based authority in the first place.

One of the most significant developments was Google Penguin, which overhauled the quality standards Google set for links. Using more advanced judgments, Google could now determine whether a link appeared "natural" or "manipulative," forcing link-building tactics to shift while not really overhauling the fundamental idea behind PageRank.

Other indications of authority

Of course, links aren't the only factor responsible for determining a domain or page's overall authority. Google also takes the quality of on-site content into consideration, thanks in part to the sophisticated Panda update that rewards sites with "high-quality" (well-researched, articulate, valuable) content.

The functionality of your site, including its mobile-friendliness and the availability of content to different devices and browsers, can also affect your rankings. But it's all these factors together that determine your authority, and links are still a big part of the overall mix.

Modern link building and the state of the web

Today, link building must prioritize the perception of "naturalness" and value to the users encountering those links. That's why link building largely exists in two forms: link attraction and manual link building.

Link attraction is the process of creating and promoting valuable content in the hope that readers will naturally link to it on their own, while manual link building is the process of placing links on high-authority sources. Even though marketers are, by definition, manipulating their rankings whenever they do anything known to improve their rankings, there are still checks and balances in place that keep these tactics in line with Google's Webmaster Guidelines.

Link attraction tactics won't attract any links unless the content is worthy of those links, and manual link-building tactics won't result in any links unless the content is good enough to pass a third-party editorial review.

The only sustainable, ongoing manual link-building strategy I recommend is guest blogging, the process by which marketers develop relationships with editors of external publications, pitch stories to them, and then submit those stories in the hope of having them published. Once published, these stories achieve myriad benefits for the marketer, along with (usually) a link.

Could something (such as social signals) replace links?

Link significance and PageRank have been the foundation for Google's evaluation of authority for most of Google's existence, so the big question is: could anything ever replace these evaluation metrics?

More user-centric factors could be a hypothetical replacement, such as traffic numbers or engagement rates, but user behavior is too variable and may be a poor indication of true authority. It also eliminates the relative authority of each action that's currently present in link evaluation (i.e., some users wouldn't be more authoritative than others).

Peripheral factors like content quality and site performance could also grow in their significance to overtake links as a primary indicator. The challenge here is determining algorithmically whether content is high-quality or not without using links as a factor in that calculation.

Four years ago, Matt Cutts squelched that notion, stating at SMX Advanced 2012, "I wouldn't write the epitaph for links just yet." Years later, in a Google Webmaster Video from February 2014, a user asked if there was a version of Google that excludes backlinks as a ranking factor. Cutts responded:

We have run experiments like that internally, and the quality looks much, much worse. It turns out backlinks, even though there's some noise and certainly a lot of spam, for the most part, are still a really, really big win in terms of quality of our search results. So we've played around with the idea of turning off backlink relevance, and at least for now, backlink relevance still really helps in terms of making sure that we return the best, most relevant, most topical set of search results.

The safe bet is that links aren't going anywhere anytime soon. They're too integrated as a part of the web and too important to Google's current ranking algorithm to be the basis of a major overhaul. They may evolve over the next several years, but if so, it'll certainly be gradual, so keep link building as a central component of your SEO and content marketing strategy.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
About The Author

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Why links are still the core authority signal in Google's algorithm - Search Engine Land

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It's almost impossible to see any meaningful search engine optimization (SEO) results without spending some time building and honing your inbound link profile. Of the two main deciding factors for site rankings (relevance and authority), one (authority) is largely dependent on the quantity and quality of links pointing to a given page or domain.

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What Are Google Algorithms and Why Do They Matter?

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What Are Google Algorithms and Why Do They Matter?

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Have you ever wondered how Google ranks websites? Do you know how they exactly determine which web site to position on the first page results? The truth is that Google uses a formula in determining a websites that will include on their results page. This formula is known as algorithm.

If you are really concerned about the status of your website, then you have to have some knowledge of the algorithm being used. This infographic shows how the Google Algorithm works and some major algorithm updates that have occurred over the years..

[Click image for full size version]

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What Are Google Algorithms and Why Do They Matter? [Infographic]

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Have you ever wondered how Google ranks websites? Do you know how they exactly determine which web site to position on the first page results? The truth is that Google uses a formula in determining a websites that will include on their results page. This formula is known as algorithm.

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ALGORITHM MAPS THE MOST BEAUTIFUL ROUTE TO WHERE YOU'RE GOING

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ALGORITHM MAPS THE MOST BEAUTIFUL ROUTE TO WHERE YOU'RE GOING

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If you want to find the most scenic route to get somewhere, there may soon be an app for that. Daniele Quercia and colleagues at Yahoo Labs in Barcelona have come up with a way to create a crowd-sourced measure of a city's beauty, and made an algorithm to find the prettiest way to get from one point to another. "The goal of this work is to automatically suggest routes that are not only short but also emotionally pleasant," the scientists told Technology Review:

Quercia and co begin by creating a database of images of various parts of the center of London taken from Google Street View and Geograph, both of which have reasonably consistent standards of images. They then crowd-sourced opinions about the beauty of each location using a website called UrbanGems.org. Each visitor to UrbanGems sees two photographs and chooses the one which shows the more beautiful location. That gives the team a crowd-sourced opinion about the beauty of each location. They then plot each of these locations and their beauty score on a map which they use to provide directions.

Quercia et al then got 30 actual human beings in London and another 54 in Boston to test out this internet-collected data, and the subjects agreed that the more beautiful areas--according to the program--were indeed more beautiful.

To add power to the algorithm, the team mined data from photos with GPS tags posted to Flickr, taking into account "positive emotions" ascribed to different locations, and also computing how many photos were taken in different places (not many people take photos of really drab or mediocre sites, as you might expect). They are currently working on a mobile app, to test in different cities in Europe and the U.S. Until then, you could just ask a real breathing resident what route they would suggest--but that would involve human interaction.

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Algorithm Maps The Most Beautiful Route To Where You're Going

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If you want to find the most scenic route to get somewhere, there may soon be an app for that. Daniele Quercia and colleagues at Yahoo Labs in Barcelona have come up with a way to create a crowd-sourced measure of a city's beauty, and made an algorithm to find the prettiest way to get from one point to another.

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melihat contoh penyelesaian masalah menggunakan algoritma berdasarkan kegunaan lif di pejabat-pejabat.

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http://futurism.com/images/what-are-algorithms/

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Youtube : Kevin Slavin: How algorithms shape our world

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Youtube : Kevin Slavin: How algorithms shape our world

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How algorithms shape our world | Kevin Slavin

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http://www.ted.com Kevin Slavin argues that we're living in a world designed for -- and increasingly controlled by -- algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture. And he warns that we are writing code we can't understand, with implications we can't control.