Web Summit is the world's largest technology conference, taking place November 6-9 in Lisbon, Portugal. Today, VMware CEO Pat Gelsinger will participate in a debate about the belief that technology should be available and accessible to the entire global population; he'll also give a fireside chat on how legacy brands can stay innovative in a startup-focused world. This essay is a version of his speech; Web Summit presentations are being livestreamed here. There's an ongoing debate about whether or not technology will benefit everyone. As tech breaks out and reshapes so many aspects of business and society, will breakthrough innovation deliver value to everyone on the planet, regardless of geography, background or culture?

In this image taken from video, a sheep indicates recognition of former US president Barack Obama, right, displayed on a computer screen during research carried out by scientists at Cambridge University with their results published Wednesday Nov. 8, 2017, in Royal Society: Open Science. The new study shows that sheep have advanced face-recognition abilities comparable to those of humans and monkeys, according to Professor Jenny Morton, and the university hope their research assists research into Huntington's disease and other human brain disorders that affect mental processing.(Cambridge

Last week, a student asked me whether our new MSc module "Big Data Epidemiology" would be covering "machine learning" techniques and enthusiastically told me all about how they intend to apply such techniques to their own research. The short answer to the student's question was "Yes, but only briefly". The long answer requires some exploration into what we mean by "big data epidemiology" and consideration of what machine learning can (and perhaps more importantly, cannot) do for researchers. Data is often considered "big data" if it can be described in terms of the "four V's": volume (there's a lot of it), variety (the data takes lots of different forms), velocity (the data changes or is updated frequently) and veracity (the data may be of poor/ unknown quality).1 On our module we use electronic healthcare records databases that can contain information about millions of patients, collected over several years (volume).

If you are a data scientist, a software developer, or in the social and human sciences with interest in digital humanities, then you're no stranger to the ongoing discussions on how algorithms embed biases, and discrimination and the call for critical and ethical engagement. I have keenly been following such discussion for a while and this post is an attempt to put together the articles, books, book reviews, videos, interviews, twitter threads and so on., that I've come across in one place so it can be used as a resource. This list is by no means exhaustive and as more and more awareness is being raised, there are more pieces/articles/journal papers being written on a daily basis. I plan to update these lists regularly. Also, if you think there are relevant material that I have not included, please leave them as a comment and I will add them.

When people talk about artificial intelligence (AI) and machine learning (ML), they tend to make them sound like technologies of a distant future – smarter and more customized versions of everything we use every day. What they may not realize is that early applications of these technologies are already part of today's reality. This week on STACK That, we sit down with Airbnb, a company that is making great strides in their AI journey in one of the most exciting applications for machine learning -- the travel industry. "Airbnb has been using machine learning in our products for years," says Mike Curtis, VP of Engineering at Airbnb. "…everything from how we recommend prices to our hosts, understanding the value of their space, to how we do search ranking, and that really comes down to matching between our guest and hosts, as well as all the things we do to detect fraud and keep our communities safe."

Post offices are often at the forefront of new technology, as developing efficient systems for delivering mail is essential for keeping costs down for users. Computer systems, in particular, hold tremendous potential for scanning and routing mail, allowing post offices to lower costs. Accenture has released a report, entitled "The New Delivery Paradigm," that examines 25 post offices through Europe, the Americas, and Asia-Pacific. For an average post and parcel industry, the analysis reveals that $500 million per year in value is possible through investment in advanced digital technologies. Increased competition and lower demand for mail is placing pressure on many post offices, but new investment could help cut costs, particularly when it comes to handling the so-called "last mile" of delivery.

Sheep have been notoriously associated with the "herd mentality" insult. In fact, the Miriam-Webster dictionary, included into its list of recognized words this April, the word "sheeple," -- which is a derogatory term directed at "people who are docile, compliant, or easily influenced," or just plain simple-minded. But a major study published in the journal Royal Society Open Science, has now debunked the stupidity that we have come to associate with sheep. Researchers from the University of Cambridge have trained sheep to identify the pictures of celebrities including Emma Watson, Jake Gyllenhaal, journalist Fiona Bruce and Barack Obama. The team was astonished to find that the animals are able to recognize familiar faces from just 2-D images.

A large and necessary step in achieving the Paris Agreement requires a transition to a highly efficient building stock in terms of real energy performance. This is perhaps nowhere more true than in Europe, where it is often stated that "all buildings built before 1990 are inefficient" and that up to 75% need renovating in order to reach a higher energy efficiency standard. In order to decarbonise EU building stock by 2050, a vision laid out in the Clean Energy for All Europeans communication (2016), the majority of buildings must be highly energy efficient, meaning they should comply with an Energy Performance Certificate (EPC) label A. Unfortunately, this might prove more difficult than expected. New research from the BPIE shows that although building performance is constantly improving in the EU, only after 2010 was the average building was built to an efficient standard (0.49 W/m2 K for the building envelope) in the European Union. That means only 3% of building stock in the EU does actually qualifies for the A-label, so 97% (not 75% as typically stated) should therefore be upgraded.

As an entrepreneur and AI guru, Trevor O'Brien is deeply engrained in the digital start-up community. He is founder at the innovative design and prototyping studio, theexperiment.io, and has been crucial in a number of ground-breaking start-up initiatives, including thegrid.ai Throughout his career, Trevor has lead sprawling multidisciplinary teams, created award-winning digital campaigns, and proven that technology paves endless paths for communicating and doing business, through the success of his clients. We caught up with our latest scholar to find out more about his thoughts on the role of AI in our future – from minimizing food-waste, to terrible self-creating music! Julie Hough: Contagious are global supporters of brave creative thinking and innovation, especially in the face of daunting new technologies.

PARIS – Sheep learned to recognize Barack Obama after seeing his photo a few dozen times, says a study that suggested our four-legged friends may be smarter than we think. The former U.S. president was one of four celebrities used in a test of the woolly creatures' face-recognition skills, along with Harry Potter actress Emma Watson, British TV host Fiona Bruce and American actor Jake Gyllenhaal, the research team said. "We chose these people because there were lots of images of each person available online, both front-on and taken at different angles," said study co-author Jennifer Morton of the University of Cambridge. "We also chose them because we were sure that our sheep had never met them in person." Morton and a team trained eight sheep to recognize the faces from a frontal photo of each of them.