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New York, NY, September 10, 2019―ACM, the Association for Computing Machinery, today announced that Yoshua Bengio, co-recipient of the 2018 ACM A.M. Turing Award, will present his Turing Award Lecture, "Deep Learning for AI," at the Heidelberg Laureate Forum on September 23 in Heidelberg, Germany. Bengio’s Turing Lecture will be live streamed via the Heidelberg Laureate Forum’s website.

 

Bengio is a professor at the University of Montreal and Scientific Director at Mila, Quebec’s Artificial Intelligence Institute. He received the 2018 ACM A.M. Turing Award with Geoffrey Hinton, VP and Engineering Fellow of Google, and Yann LeCun, VP and Chief AI Scientist at Facebook. Bengio, Hinton and LeCun were recognized for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing.  In recent years, deep learning methods have been responsible for astonishing breakthroughs in computer vision, speech recognition, natural language processing, and robotics—among other applications.

 

In his Turing Lecture, “Deep Learning for AI,” Bengio will look back at some of the principles behind the recent successes of deep learning as well as acknowledge current limitations and propose research directions to build on this progress and towards human-level AI. Among the promising new research directions Bengio will discuss are deep learning from the agent perspective, with grounded language learning, discovering causal variables and causal structure, and the ability for machines to explore their surroundings in an unsupervised way to understand the world and quickly adapt to changes in it.

 

Livestream Details: 

Date:  Monday, September 23, 2019

Time:  9:00 - 9:45 am (Central European Summer Time)

Livestream Link:  https://www.heidelberg-laureate-forum.org/

 

The ACM A.M. Turing Award, often referred to as the “Nobel Prize of Computing,” carries a $1 million prize, with financial support provided by Google, Inc. It is named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing. In receiving the award, each Turing Laureate agrees to give a Turing Lecture within one year of being selected. 

 

The Heidelberg Laureate Forum (HLF), scheduled this year from September 22-27, is an annual one-week event that brings together 200 of the world’s most promising young researchers in mathematics and computer science with the recipients of the disciplines’ most prestigious awards: the Abel Prize, the ACM A.M. Turing Award, the ACM Prize in Computing, the Fields Medal and the Nevanlinna Prize. With scientific, social and outreach activities, the HLF is a networking event meant to inspire the next generation of scientists.

About the ACM A.M. Turing Award

The A.M. Turing Award was named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing, and who was a key contributor to the Allied cryptanalysis of the Enigma cipher during World War II. Since its inception in 1966, the Turing Award has honored the computer scientists and engineers who created the systems and underlying theoretical foundations that have propelled the information technology industry.

 

About ACM

ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.

CONTACT:          
Jim Ormond

212-626-0505

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ASSOCIATION FOR COMPUTING MACHINERY’S 2019 RECSYS CONFERENCE  
SHOWCASES LATEST RESEARCH AND ADVANCES IN RECOMMENDER SYSTEMS

RecSys 2019 Workshops Examine Challenges and Opportunities in Healthcare, 
Fashion, News, Among Other Industries  

New York, NY August 29, 201– The latest research and advancements in recommender systems―those useful but somewhat mysterious software systems that suggest what books, songs, and products consumers might like―will be presented at RecSys 2019, the most important annual conference for this growing area of computing.

The conference, hosted by the Association for Computing Machinery’s Special Interest Group on Computer-Human Interaction (ACM SIGCHI), takes place in Copenhagen, Denmark, from Sept. 16-20, 2019. RecSys 2019 brings together academia-based research groups and many of the world’s leading e-commerce and media companies.

A “recommender” system is a particular form of information filtering that leverages past behaviors and user similarities to generate a list of items personally tailored to an end-user’s preferences. For consumers, future purchase recommendations can be based on shopping patterns and other data, while in an industry such as healthcare, recommendations on treatment plans can be made based on previous outcomes.

“Recommender systems are perhaps the most commonly used computing technology by consumers, even if they don’t realize the technology behind the suggestions,” said conference General Co-Chair Toine Bogers, Aalborg University Copenhagen, Denmark. “The Recommender Systems conference is the premier international forum for the advancement of this industry - providing opportunities for the sharing of new research and the discussion of new systems and techniques in the field.”

In addition to the main technical track, RecSys 2019 will feature keynote and invited talks, tutorials covering state-of-the-art in this domain, a workshop program, an industrial track and a doctoral symposium. As a pre-program to the conference, the ACM Summer School on Recommender Systems will take place in Gothenburg, Sweden, the week before the conference.

“Recommender systems wield the potential for tremendous economic and societal impact,” added General Co-chair Alan Said, University of Gothenburg, Sweden. “These systems encompass a range of computing technologies, from AI and algorithms, to knowledge-based reasoning and deep learning.”

This year’s RecSys, will be the largest to date, with 850 registrations. Now in its 13th year, RecSys long has been characterized by strong industry participation. In 2018, for example, industry practitioners represented the majority of the 820 attendees who attended the conference.

Aside from the technology itself, RecSys 2019 will include presentations and research that addresses the conscientious use of these technologies. A “Responsible Recommendation” panel will examine what it means to build, deploy, and study recommender systems in a socially responsible manner, which is crucial to ensure that the systems promote human welfare. The panel will cover many topics, including fairness, accountability, transparency, privacy, and social impact, and will offer a variety of perspectives from industry, academia, and the public sector.

 

RECSYS 2019 HIGHLIGHTS

KEYNOTE ADDRESSES
Rude Awakenings from Behaviourist Dreams. Methodological Integrity and the GDPR” 
Mireille Hildebrandt, Vrije Universiteit Brussels, Belgium
Recommendations are meant to increase sales or ad revenue, since this is the first priority of those who pay for them. As recommender systems match their recommendations with inferred preferences, it should not come as a surprise if the algorithm optimizes for lucrative preferences and thus co-produces the preferences they mine. This talk will explain how the GDPR will help to break through this vicious circle, by constraining how people may be targeted.

“Whose Data Traces, Whose Voices? Inequality in Online Participation and Why it Matters for Recommendation Systems Research” 
Eszter Hargittai, University of Zurich, Switzerland
This talk will discuss online participation from a digital-inequality perspective, highlighting how differences in online behavior vary by socio-demographic characteristics and the user’s Internet prowess. It will explore whose traces are most likely to show up on various systems and what this means for potential biases in what researchers draw from analyzing digital trace data. Hargittai states that as research relies on data traces about people’s online behavior, it is important to take a step back and ask: who uses the systems where these traces appear? The presentation breaks down the various steps necessary for engagement—the pipeline of online participation—and shows that different factors explain different parts of the pipeline with skills mattering at all stages.

RESEARCH PAPERS (Partial List) 
for a complete list of papers visit here

User-Centered Evaluation of Strategies for Recommending Sequences of Points of Interest to Groups
Daniel Herzog, Wolfgang Wörndl, Technical University of Munich 
Most recommender systems (RSs) predict the preferences of individual users; however, in certain scenarios, recommendations need to be made for a group of users. Tourism is a popular domain for group recommendations because people often travel in groups and look for point of interest (POI) sequences for their visits during a trip. In this study, the authors present different strategies that can be used to recommend POI sequences for groups. In addition, they introduce novel approaches, including a strategy called Split Group, which allows groups to split into smaller groups during a trip.

 

Recommending What Video to Watch Next: A Multitask Ranking System
Zhe Zhao, Google Brain; Lichan Hong, Google Brain; Li Wei, Google; Jilin Chen, Google; Aniruddh Nath, Google; Shawn Andrews, Google; Aditee Kumthekar, Maheswaran Sathiamoorthy, Google; Xinyang Yi, Google; Ed Chi, Google
In this paper, the authors introduce a large scale multi-objective ranking system for recommending what video to watch next on an industrial video sharing platform. Their system faces many real-world challenges, including the presence of multiple competing ranking objectives, as well as implicit selection biases in user feedback. To tackle these challenges, they explored a variety of soft-parameter sharing techniques such as Multi-gate Mixture-of-Experts so as to efficiently optimize for multiple ranking objectives. They demonstrated that their proposed techniques can lead to substantial improvements on recommendation quality on one of the world’s largest video sharing platforms.

 

Uplift-based Evaluation and Optimization of Recommenders 
Masahiro Sato, Janmajay Singh, Sho Takemori, Takashi Sonoda, Qian Zhang, Tomoko Ohkuma, Fuji Xerox, Co. 
Recommender systems aim to increase user actions such as clicks and purchases. Typical evaluations of recommenders regard the purchase of a recommended item as a success. However, the item may have been purchased even without the recommendation. An uplift is defined as an increase in user actions caused by recommendations. Situations with and without a recommendation cannot both be observed for a specific user-item pair at a given time instance, making uplift-based evaluation and optimization challenging. This paper proposes new evaluation metrics and optimization methods for the uplift in a recommender system.

 

WORKSHOPS (Partial List)

For a full list of RecSys 2019 workshops visit here
Recommender Systems in Fashion
While online fashion retailers have significantly increased in popularity over the last decade, customers still face several hurdles with current online shopping solutions. This new workshop aims to bring together researchers and practitioners in the fashion, recommendations and machine learning domains to discuss open problems in the area of fashion e-commerce and retail.

Health Recommender Systems
Recommendations are becoming ever more important in health settings with the aim being to assist people live healthier lives, but they come with a number of challenges, including privacy issues and multiple and diverse stakeholders in health systems. The Health Recommender Systems Workshop will deepen the discussions started at the three prior workshops and will work towards further development of the research topics in Health Recommender Systems.

News Recommendation and Analytics
This workshop primarily addresses news recommender systems and analytics with a focus on three main categories: News recommendation, news analytics and ethical aspects of news recommendation. The news domain is characterized by a constant flow of unstructured, fragmentary and unreliable news stories from numerous sources and different perspectives, posing challenges unlike those in music, movies and books. The spread of increasing concerns about disinformation coupled with privacy violations necessitates improving news recommender systems.

ADDITIONAL HIGHLIGHTS 
Women’s Breakfast 
Since 2014, RecSys has offered a platform where all conference attendees who identify as female can celebrate and connect with other women in the RecSys community. The event provides an opportunity for female attendees to share the challenges and successes of women working within the community and to exchange experiences with one another.

Doctoral Symposium 
The Doctoral Symposium provides an opportunity for doctoral students working in recommender systems research to receive critical feedback about their work and further develop their research under the guidance of distinguished and established researchers in recommender systems.

RecSys Challenge 2019 
The RecSys Challenge 2019 presents a real-world task in the travel metasearch domain. Users that are planning a business or leisure trip can use trivago’s website to compare accommodations and prices from various booking sites. The goal of this challenge is to develop a session-based and context-aware recommender system using various input data to provide a list of accommodations that will match the needs of the user. In the challenge, participants will be tasked with predicting which accommodations (items) have been clicked in the search result during the last part of a user session in an offline evaluation setup.


About SIGCHI 
SIGCHI, the ACM Special Interest Group on Computer-Human Interaction, is the premier international society for professionals, academics and students who are interested in human-technology and human-computer interaction (HCI). SIGCHI serves as a forum for ideas on how people communicate and interact with computer systems. This interdisciplinary group of computer scientists, software engineers, psychologists, interaction designers, graphic designers, sociologists, and anthropologists is committed to designing useful, usable technology which has the potential to transform individual lives.

About ACM 
ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.  

CONTACT:  
Jim Ormond
212-626-0505
This email address is being protected from spambots. You need JavaScript enabled to view it. 

ACM FEDERATED COMPUTING RESEARCH CONFERENCE COMBINES 13

COMPUTING CONFERENCES INTO ONE MAJOR EVENT

 

2018 Turing Award Laureates to Present Lecture on the State of Machine Learning

 

New York, NY, June 12, 2019 – ACM, the Association for Computing Machinery, will hold the Federated Computing Research Conference (FCRC), June 22-28 in Phoenix, Arizona. FCRC assembles a spectrum of affiliated research conferences and workshops into a week-long coordinated meeting. The FCRC model allows both a strong research focus within each represented subdiscipline of computing while also facilitating communication among researchers in different fields of computer science and engineering.

 

The FCRC is held only once every four years. Each morning, FCRC features a joint plenary talk on topics of broad appeal to the computing research community. To the extent facilities allow, attendees are free to attend technical sessions of other affiliated conferences being held at the same time as their "home" conference.

 

Turing Lecture

Two of this year’s recipients of the ACM A.M. Turing Award—Geoffrey Hinton of Google, and Yann LeCun of Facebook—will present their Turing Lecture at FCRC. Hinton and LeCun, along with Yoshua Bengio of the University of Montreal, received the 2018 A.M. Turing Award for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing. Working independently and together, they developed conceptual foundations for the field, identified surprising phenomena through experiments, and contributed engineering advances that demonstrated the practical advantages of deep neural networks. 

 

Hinton and LeCun will present their Turing Lecture as part of FCRC on June 23 at 5:15 p.m. at Symphony Hall of the Phoenix Convention Center. The titles of their presentations are:

Geoffrey Hinton: “The Deep Learning Revolution”

Yann LeCun: “The Deep Learning Revolution: The Sequel”

 

FCRC Plenary Speakers

 

“A Roadmap for Reverse-Architecting the Brain’s Neocortex”

James E. Smith, University of Wisconsin-Madison

Understanding, and then replicating, the computing paradigm(s) used in the brain’s neocortex is a computer architecture research problem that is of unquestionable practical and scientific importance, but one that will require an unconventional approach. Smith’s talk lays out a potential roadmap, based on several years of study and experimentation, in a methodical, bottom-up manner.  According to Smith, the first important milestone along the road is the development of feedforward biologically plausible neural networks capable of unsupervised, continual learning, and implementable with high energy efficiency. After the first milestone is reached and the roadmap going forward becomes a little clearer, reverse-architecting the higher level cognitive functions promises to be at the leading edge of computer architecture research for decades to come. 

 

“Differential Privacy and the US Census”

Cynthia Dwork, Harvard University

Differential privacy is a mathematically rigorous definition of privacy tailored to statistical analysis of large datasets. Differentially private systems simultaneously provide useful statistics to the well-intentioned data analyst and strong protection against arbitrarily powerful adversarial system users –without needing to distinguish between the two. Differentially private systems "don't care" what the adversary knows, now or in the future. Finally, differentially private systems can rigorously bound and control the cumulative privacy loss that accrues over many interactions with the confidential data. These unique properties, together with the abundance of auxiliary data sources and the ease with which they can be deployed by a privacy adversary, led the US Census Bureau to adopt differential privacy as the disclosure avoidance methodology of the 2020 decennial census. Dwork’s talk will motivate the definition of differential privacy, reflect on the theory-meets-practice experiences of the decennial census, and highlight a few pressing challenges in the field.

 

“The Role of Computer Science in Computer Science Education”

Shriram Krishnamurthi, Brown University

Computer science education is a difficult and fascinating problem, sitting at the intersection of the technical and human. It is also an increasingly urgent problem as countries around the world are rushing to add computing to their curricula and wrestling with broadening access to it. The needs are not limited to schoolchildren: working adults and the elderly use computers in ever more sophisticated ways. What role can computer scientists play in this movement? In this talk, Krishnamurthi will provide a look at some of those questions, and identify a few of the numerous challenges the field has barely begun to address.

 

“Data for Good: Data Science at Columbia”

Jeannette M. Wing, Columbia University

Every field has data. We use data to discover new knowledge, to interpret the world, to make decisions, and even to predict the future. The recent convergence of big data, cloud computing, and novel machine learning algorithms and statistical methods is causing an explosive interest in data science and its applicability to all fields. Jeannette Wing is the Director of the Data Science Institute at Columbia University. The Data Science Institute promotes “Data for Good”: using data to address societal challenges and bringing humanistic perspectives as—not after—new science and technology is invented. In this talk, Wing will present examples of research and education projects to illustrate how data science is transforming every field, profession, and sector. 

 

“Heterogeneous Acceleration and Challenges for Scientific Computing on the Exascale”

Erik Lindahl, Stockholm University

Modern computer hardware has become tremendously powerful in terms of FLOPS, memory bandwidth, multithreading and accelerators—but while codes could get close to the theoretical peak performance 20 years ago, many of today’s applications struggle to reach 10% due to the complexity of hardware. In this talk, Lindahl will showcase the challenges faced by real-world scientific applications that primarily focus on improving time-to-solution on increasingly powerful supercomputers rather than FLOP-counts, scaling, or relative acceleration. Among other topics, Lindahl will also discuss the strategies needed for all these applications to be able to turn Exascale computing investments into scientific discoveries and impactful industrial innovations.

 

Participating Conferences Include:

COLT: The 32nd Annual Conference on Learning Theory 
e-Energy: The Tenth ACM International Conference on Future Energy Systems

EC: 20th ACM Conference on Economics and Computation 
HPDC: The 28th International Symposium on High Performance Parallel and Distributed Computing

ICS: International Conference on Supercomputing

ISCA: The 46th International Symposium on Computer Architecture 
ISMM: International Symposium on Memory Management

IWQoS: IEEE/ACM International Symposium on Quality of Service

LCTES: Languages, Compilers, Tools, and Theory of Embedded Systems

PLDI: Programming Languages and Programming Systems Research

SIGMETRICS/IFIP Performance 2019: Measurement-Based Performance Evaluation Techniques

SPAA: 31st ACM Symposium on Parallelism in Algorithms and Architectures 
STOC: 51st ACM Symposium on the Theory of Computing

 About ACM

ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence.  ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.

Contact:           
Jim Ormond

212-626-0505

This email address is being protected from spambots. You need JavaScript enabled to view it.

Wigderson Receives Knuth Prize for Revolutionizing Our Understanding 
of Randomness in Computation 

 

Gödel Prize Awarded to Irit Dinur for Foundational Work on the PCP Theorem

 

New York, NY, June 13, 2019--SIGACT, the Association for Computing Machinery’s Special Interest Group on Algorithms and Computation Theory, has announced that the Donald E. Knuth Prize will be awarded to Avi Wigderson and the Gödel Prize will be awarded to Irit Dinur. Wigderson and Dinur will be formally recognized at the 51st Annual Symposium on the Theory of Computing (STOC 2019) in Phoenix, Arizona, June 23-26.

 

Donald E. Knuth Prize

Avi Wigderson of the Institute for Advanced Study  is recognized with the 2019 Donald E. Knuth Prize for fundamental and lasting contributions to the foundations of computer science in areas including randomized computation, cryptography, circuit complexity, proof complexity, parallel computation, and our understanding of fundamental graph properties. 

 

In a series of results, Wigderson showed, under widely-believed computational assumptions, that every probabilistic polynomial time algorithm can be fully derandomized. In other words, randomness is not necessary for polynomial-time computation. In cryptography, Wigderson co-authored two landmark papers that showed how one could compute any function securely in the presence of dishonest parties. He was also part of a team that showed that all problems with short proofs (i.e., all problems in NP) in fact have zero-knowledge proofs: that is, proofs that yield nothing but their validity, a central cryptographic construct.  

 

Wigderson received his PhD from Princeton University in 1983. He then served as a Visiting Assistant Professor at the University of California, Berkeley, a Visiting Scientist at IBM, and a Fellow at the Mathematical Sciences Research Institute (MSRI) in Berkeley before joining the Hebrew University as a faculty member in 1986. Since 1999, Wigderson has been a Professor in the School of Mathematics at the Institute for Advanced Study. Wigderson also received the Gödel Prize in 2009, for work with Omer Reingold and Salil Vadhan, and received the Nevanlinna Prize in 1994.

 

The Donald E. Knuth Prize recognizes outstanding contributions to the foundations of computer science by individuals for their overall impact in the field over an extended period. It is named in honor of Donald Knuth of Stanford University who has been called the “father of the analysis of algorithms.” The prize is jointly bestowed by the ACM Special Interest Group on Algorithms and Computation Theory (SIGACT) and the IEEE Computer Society Technical Committee on the Mathematical Foundations of Computing (TCMF).

 

Gödel Prize

The 2019 Gödel Prize is awarded to Irit Dinur of Hebrew University for her proof of the PCP Theorem in the paper “The PCP Theorem by Gap Amplification.”

 

The PCP theorem is one of the most influential and impressive results of the theory of computation, having fundamental implication both to the study of the inherent difficulty of approximation problems and to the study of probabilistic proof systems. Dinur’s paper provides an alternative proof of the PCP Theorem, which is fundamentally different from the original proof. Her new proof is significantly simpler than the original, making its presentation in complexity courses a feasible task. In addition, it significantly improves on important parameters of the resulting PCP, yields the same improvements for locally testable codes, and has inspired much research including practical applications. Providing an alternative proof for a result of such importance is a significant achievement, especially for a proof which addresses issues that have been puzzling many researchers and resolving a central open problem in the field.


Dinur received her PhD from Tel Aviv University. She later held appointments at the Institute of Advanced Study (Princeton, NJ), NEC, and the University of California, Berkeley before joining the Weizmann Institute of Science (Israel) as a Professor of Computer Science. Dinur won the Anna and Lajos Erdős Prize in Mathematics (2012) and a Michael Bruno Memorial Award (2007).

 

The Gödel Prize  recognizes major contributions to mathematical logic and the foundations of computer science. The prize is named in honor of Kurt Gödel, who was born in Austria-Hungary (now the Czech Republic) in 1906. Gödel's work has had immense impact upon scientific and philosophical thinking in the 20th century. The Gödel Prize is awarded jointly by ACM SIGACT and the European Association for Theoretical Computer Science (EATCS).

 

About SIGACT

The ACM Special Interest Group on Algorithms and Computation Theory fosters and promotes the discovery and dissemination of high quality research in the domain of theoretical computer science.  The field includes algorithms, data structures, complexity theory, distributed computation, parallel computation, VLSI, machine learning, computational biology, computational geometry, information theory, cryptography, quantum computation, computational number theory and algebra, program semantics and verification, automata theory, and the study of randomness. Work in this field is often distinguished by its emphasis on mathematical technique and rigor.

 

 

About ACM

ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.


Contacts:  

Samir Khuller, ACM SIGACT Chair, 301-405-6765, This email address is being protected from spambots. You need JavaScript enabled to view it.   
Jim Ormond, ACM, 212-626-0505, This email address is being protected from spambots. You need JavaScript enabled to view it.

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Dr Jose Cordeiro helping with a genuine grassroots campaign to get the first ever futurist/transhumanist elected to the European Parliament. Dr Jose Cordeiro has written books on how we can use artificial intelligence and other technologies to improve the world. He has a good shot at getting elected as the EU elections use proportional representation. This is a campaign reliant on supporters who share these beliefs - helping human civilisation through technology

This week will see the first transhumanist running to become elected to the European Parliament. Dr Jose Cordeiro has written several books about how technology can transform society, including the best-selling “La Muerte de la Muerte” -- the Death of Death -- and has had many television appearances promoting how we can use artificial intelligence, nanotechnology and other emerging technologies to radically improve the human condition and create a new form of society. Below is an animation which goes through how these ideas are different to much of mainstream political discourse, which tends to focus on short-term fixes to problems which affect politicians’ electability.

 

https://www.youtube.com/watch?v=5LJqETyNE2k

 

If we are to build a better civilisation using technology like artificial intelligence then we must put these ideas first rather than bickering about sales taxes, political shenanigans and the like. The total funding from the European Union on artificial intelligence -- even after its recent focus on this technology -- comes to less than one percent of the agricultural subsidies in the EU, which total 40 billion Euros per year. What do you think will benefit human civilisation more over the next generation, artificial intelligence or agricultural subsidies?

 

Please do what you can to promote Dr Cordeiro this week, forward this to as many people as possible and make any Spanish friends you have aware of his campaign. From the European Parliament he will have far more influence than in a national parliament.

 

You can find infographics in Spanish and English here: https://drive.google.com/drive/folders/1g4sn5t5OauRAFPMdoL9WY9JDZfUPD-6Q?usp=sharing  

 

Campaign website (in Spanish): www.somosmiel.es

Facebook page (in Spanish): https://www.facebook.com/SomosMiel2019

 

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