go to site As this new technological framework is applied to more fields of activity it remains to be seen whether this is an artificial intelligence for the good, capable of communicating in an efficient way with human beings and increasing our capabilities, or a control mechanism that, as it substitutes us in specialised tasks, captures our attention converting us into passive consumers.
At the start of the year, Mark Zuckerberg published the post Building Global Community addressing all users of the social network Facebook. These promises stem from a change in the algorithms governing this platform: if up to now the social network filtered the large quantity of information uploaded to the platform by compiling data on the reactions and contacts of its users, now the development of smart algorithms is enabling the content of such information to be understood and interpreted.
Thus, Facebook has developed the Deep Text tool, which applies machine learning to understand what users say in their posts, and create models of classification of general interests. Artificial intelligence is also used for the identification of images.
DeepFace is a tool that enables the identification of faces in photographs with a level of accuracy close to that of humans. Computerised vision is also applied to generate textual descriptions of images in the service Automatic Alternative Text aimed at blind people being able to know what their contacts are publishing. In its endeavour to administrate connection to the Internet worldwide via drones, this laboratory has analysed satellite images the world over in search of constructions that reveal human presence. These data in combination with the already existing demographic databases offer exact information on where potential users of the connectivity offered by drones are located.
How Does Facial Recognition Work? Brit Lab. These apps and many others, which the company regularly tests and applies, are on the FBLearner Flow , the structure that facilitates the application and development of artificial intelligence to the entire platform. Flow is an automated learning machine that enables the training of up to , models each month, assisted by AutoML, another smart app that cleans the data to be used in neural networks. These tools automate the production of smart algorithms that are applied to hierarchize and personalise user walls, filter offensive contents, highlight tendencies, order search results and many other things that are changing our experience on the platform.
What is new about these tools is that not only do they model the medium in line with our actions but when accessing the interpretation of the contents that we publish, they allow the company to extract patterns of our conduct, predict our reactions and influence them. In the case of the tools made available for suicide prevention , this actually consists of a drop-down menu that allows possible cases to be reported with access to useful information such as contact numbers and vocabulary suitable for addressing the person at risk.
However, these reported cases form a database that when analysed gives rise to identifiable patterns of conduct that in the near future would enable the platform to foresee a possible incident and react in an automated way. For its part, Google is the company behind the latest major achievement in artificial intelligence. Alpha Go is considered to be the first general intelligence program. The program developed by Deep Mind , the artificial intelligence company acquired by Google in , not only uses machine learning that allows it to learn by analysing a register of moves, but integrates reinforced learning that allows it to devise strategies learned by playing against oneself and in other games.
Last year this program beat Lee Sedol, the greatest master of Go, a game considered to be the most complex ever created by human intelligence. This fact has not only contributed to the publicity hype that surrounds artificial intelligence but it has put the company at the head of this new technological framework. Google, which has led the changes that have marked the evolution of web search engines, is now proposing an AI first world that would change the paradigm that governs our relationship with this medium.
Google applies machine learning to its search engine to auto-complete and correct the search terms that we enter. For this purpose it uses natural language processing, a technology that has also allowed it to develop or its translator and voice recognition and to create Allo , a conversational interface.
Moreover, the computerised vision has given rise to the image search service , and is what allows the new Google Photos app to classify our images without the need to tag them beforehand. Other artificial intelligence apps allow Perspective to analyse and report toxic comments to reduce online harassment and abuse, and even to reduce the energy cost of its data server farms. The Google assistant will represent a new way of obtaining information on the platform, substituting the page of search results for a conversational interface.
In this, a smart agent will access all the services to understand our context, situation and needs and produce not just a list of options but an action as a response to our questions. In this way, Google would no longer provide access to information on a show, the times and place of broadcast and the sale of tickets, but rather an integrated service that would buy the admission tickets and programme the show into our calendar.
This assistant will be able to organise our diary, administer our payments and budgets and many other things that would contribute to converting our mobile phones into the remote controls of our entire lives. Machine learning is based on the analysis of data producing autonomous systems that evolve with use.
These systems are generating their own innovation ecosystem in a rapid advance that is conquering the entire Internet medium. Smart algorithms govern the recommendations system of Spotify, are what allow the app Shazam to listen to and recognise songs and are behind the success of Netflix which not only uses them to recommend and distribute its products but also to plan its production and offer series and films suited to the taste of its users.
As the number of connected devices that generate data increases, artificial intelligence is being infiltrated everywhere. Amazon not only uses it in its recommendation algorithms but also in the management of its logistics and in the creation of autonomous vehicles that can transport and deliver its products. The transport-sharing app Uber uses them to profile the reputation of drivers and users, to match them, to propose routes and calculate prices within its variable system. These interactions produce a database that the company is using in the production of its autonomous vehicle.
Autonomous vehicles are another of the AI landmarks. Since the GPS system was implemented in vehicles in , a major navigation database has been produced together with the development of new sensors, which has made it possible for Google to create an autonomous vehicle that has now travelled over , km without any accidents and it has announced its commercialisation under the name Waymo. AI is also implemented in assistants for our households such as Google Home and Amazon Echo and in wearable devices that collect data on our vital signs and that together with digitalisation of the diagnostic images and medical case histories, is giving rise to an application based on prediction algorithms and robots designed for health.
In addition, the multiplication of surveillance cameras and police records is taking the application of smart algorithms to crime prediction and the taking of judicial decisions. Automatic Learning, the new paradigm for Artificial Intelligence The algorithmic medium where our social interactions were taking place has become smart and autonomous, increasing its capacity for prediction and control of our behaviour at the same time that it has migrated from the social networks to expand to our entire environment.
The new boom in artificial intelligence is due to a change of paradigm that has led this technological fabric from the logical definition of intellectual processes sustained by data that allows algorithms to learn from the environment. Nils J. Nilson defines artificial intelligence as an activity devoted to making machines smart, and intelligence as the quality that allows an entity to function appropriately and with knowledge of its environment. This founding event was destined to bring together a group of specialists who would investigate ways in which machines simulate aspects of human intelligence.
This study was based on the conjecture that any aspect of learning or any other characteristic of human intelligence could be sufficiently described to be simulated by a machine. The same conjecture led Alain Turing to propose the formal model of the computer in his article Computer Machinery and Intelligence , together with other precedents such as Boolean logic, Bayesian probability and the development of statistics, with progress made in what Minksy defined as the advance of artificial intelligence: the development of computers and the mechanisation of problem-solving.
This situation changed with the dissemination of the Internet and its major capacity to collect data. Data is what has enabled the connection between solving problems and reality, with a more pragmatic and biology-inspired focus. Here, instead of there being a programmer who writes the orders that will lead to the solution of a problem, the program generates its own algorithm based on example data and the desired result. In Machine Learning the machine programs itself. He has coauthored numerous formal academic journal and conference publications, and his book publications include the Springer title "Complexity and Approximation" published in His main research interests include on-line algorithms, approximation algorithms, dynamic graph algorithms, optimization problems in vehicle routing and logistics, and streaming algorithms; he has also researched and published on programming theorys, computational complexity, and database theory.
She cofounded the International Conference on Algorithms and Complexity CIAC , and she coauthored many formal academic journal and conference publications. Many of her former students occupy key positions in industry and research. It is a good source for teachers giving algorithm course to students majoring in fields other than computer science or mathematics.
Its language, style and outlook is appealing also for any non-academic person who want to obtain some inspiration for the age of computers.
Passar bra ihop. Collaboration of finance industry and artificial intelligence is a perfect match. Konrad Hinsen. The second chapter shows how the design of algorithms requires appropriate techniques and sophisticated organization of data. Buy eBook. Computer Science.
Buy eBook. Buy Hardcover. Buy Softcover. FAQ Policy. About this Textbook To examine, analyze, and manipulate a problem to the point of designing an algorithm for solving it is an exercise of fundamental value in many fields.