Algorithms are increasingly affecting our lives . But most of the time it works, we don't notice , Only when the algorithm goes wrong can we notice its existence . Only then did we think back to the world of algorithms — The ones that dominate all the computers around us , Rules that are increasingly difficult to understand for humans , How dependent is it . Once the algorithm goes wrong , We will remember how fragile we are ( Think Skynet ).

Pedro Domingos It took a lot of time to think about algorithms . His new book ,《The Master Algorithm: How the Quest for the
Ultimate Learning Machine Will Remake Our
World》 It's an introduction to that world , And report on the latest situation . He thinks that , We live in an age of algorithms , We're seeing them reshape our world in an unprecedented way .

What is the impact of algorithm on human beings ? What is the difference between human thinking and computer thinking ? What happens when the machine finally learns to learn everything ?Jesse Hicks Interview on these issues


Why are so many people not aware of algorithms in your so-called algorithmic era ? What is the machine learning mechanism behind it ?

Computer can't do anything without algorithm . Your cell phone , notebook , automobile , There are algorithms everywhere in houses and appliances . But the algorithm is invisible , You can only see the bright appearance , I can't see what's going on inside .Siri
Use algorithms to understand what you say ,Yelp Use algorithms to select restaurants for you , vehicle GPS
Use algorithms to find the best route for you , The reader uses algorithms to pay for you . Companies use algorithms to screen job seekers , Mutual funds use algorithms to trade stocks , Mobile phones use algorithms to mark suspicious calls .

“ normal ”
The difference between algorithm and learning algorithm is that , The former relies on manual programming by software engineers , Step by step, tell the computer what to do , The latter relies on reading the data : Na , Here is the input , Here is the output we want , How can I turn one into another ? What's striking is that , From chess to medical analysis , The same machine algorithm can learn almost unlimited things — Just give it the right data .

In the title of the book “ Main algorithm master algorithm” What is it? ? It follows Ray Kurzweil What's the difference between the singularity of ? What progress can the main algorithm bring ?

The main algorithm is an algorithm that can learn anything from data . Give it the movement of the planet , Inclined plane , Pendulum data , It will discover Newton's law . Give it DNA
Crystal structure data, it can find the double helix . With the data on your smartphone, it can predict what you're going to do next and how to help you . You can even find a cure for cancer by learning a large database of cancer patients' medical records .

Algorithms may also bring us home robots ; use WWB(World Wide Brain, Vincristine ) replace WWW( web ), Answer your questions directly instead of showing you the web page ; as well as
360° Recommendation system for , Know not only you but also your best friend , Not only can I recommend books to you , film , And the date , work , Houses and tourist destinations are everything in your life .

Kurzweil The singularity of artificial intelligence is that artificial intelligence surpasses human intelligence , The moment that we couldn't understand . Or more precisely , It's singular “ Horizon event horizon
”, Just like the horizon of a black hole is the point where even light cannot escape . If there is no main algorithm , We won't get to the singularity so soon . With the main algorithm ,AI
Of course, it will speed up , But we can still understand a lot about the world , Because under our leadership AI
Still able to serve us . We may not know how they produce results , But we can know what these outputs will do for us , Or they won't be . in addition , There are things in the world that we can't understand . The difference is that , This incomprehensible part of the world today is made by ourselves , This is, of course, an improvement .

You said this field is currently “ tribe ”
The situation of separatism , Some machine learning algorithms perform better in solving specific problems , But no algorithm can beat any other algorithm : There is a lack of a unified theory that can be applied to everything we know so far , A theory that can lay the foundation for the development of the next few decades or even hundreds of years . The assertion itself is grand . What is the rationality of the main algorithm ? Why now
“ tribe ” We can't unite yet ?

It can be proved mathematically , Even the simplest learning algorithm , Just give enough data , You can learn anything . therefore , There is no doubt that the main algorithm exists , And the researchers of each algorithmic tribe confirm that they have discovered it . But the key is that the algorithm must be able to use reasonable data and computation to learn what you want it to learn . We can give two empirical examples : Nature offers at least two examples of how algorithms can learn anything : Evolution and the brain . So the main algorithm exists , The question is whether we can find out exactly , Write it down in its entirety , Just as physicists express the laws of physics by formula ( It is also an algorithm in itself ).

Unfortunately , Machine learning 5
A tribe is like a blind man and an elephant : He who touches his nose thinks it's a snake , He who touches his foot thinks it's a tree , The one who touched the tooth thought it was a cow . We need to step back and look at the panorama , See how all these parts come together . Ironically , It may be easier for people who don't know what to do .

His book begins with a quotation Alfred North Whitehead The words of :“ The progress of human civilization is achieved by increasing the number of important operations that can be performed without thinking .”
Whether this conclusion holds or not , but “ reflection ” Undoubtedly, it is closely related to civilization and human nature . Thinking is unique , Even decisive human activities . therefore Nicholas Carr
Others are against outsourcing thinking , Because it reduces our humanity — The fear is that the lack of thinking will lead us to be more robotic ( In a broad sense ). meanwhile , We are worried again “ reflection ”
machine : You mentioned the apocalyptic AI like Skynet . Does the computer have the ability
“ reflection ”? Or is it a unique human activity — If so , What are the differences between future human thinkers and machine learners ?

Famous computer scientist Edsger Dijkstra
Yes , Whether a computer can think about this is as important as whether a submarine can swim . The important thing is that computers can solve problems that human beings solve through thinking — And the scope of these problems is expanding . Through machine learning, computers have even solved problems that we don't know how to program them to solve — They came up with it on their own . So the line is very vague , And it's changing all the time .

I disagree Nicholas Carr The argument that outsourcing thinking will destroy human nature — contrary , It also enhances humanity , Because it allows us to think about better things . And that's exactly what it is Whitehead
What's the point . Socrates doesn't like writing , Because it makes people forget things . Fortunately Plato wrote down his ideas , So now humans can remember them . Writing enhances our memory ,Google
It has raised it to a higher level . It doesn't make us any more stupid , It's getting smarter .

The book ends with ,“ People worry that computers will become too smart to take over the world , But the real problem is that they are stupid and have taken over the world .” Can you explain what it means ?

Hawking and Elon Musk These celebrities expressed concerns about AI , It's a threat to human existence . but “ Skynet ” Such evil AI
The idea of taking over the world is far fetched . The problem is , People confuse intelligence with people . In Hollywood movies AI
And robots are always humanoid , But in reality, they are very different . Computers have no will of their own , Emotional or conscious . They're just an extension of us . As long as they solve the problems we set , As long as we set the boundary of the problem and examine the solution , Computers can be infinitely intelligent without threatening us .

But that's not to say you don't have to worry at all . Just like any other technology , People also use them for evil purposes AI. But the most important thing is ,AI
Will provide what we ask for, not what we really want , And that could lead to injury . Computers have made important decisions today — Who should get the job , Who should get credit , Who should be labeled as a potential terrorist . And they tend to make mistakes , Because they lack common sense . But the solution should be to make them smarter , Not more stupid . So what we should worry about is not
AI Too much , It's too little .