AI News, Questionable Conferences artificial intelligence

AI, Showbiz, and Cause for Concern (x2)

Omnipresent AI themes like “applications for deep learning”, “algorithmic fairness”, and “the future of work” are set aside in preference for rather more dazzling conversations on topics like “digital humans”, “AI and creativity”, and “our augmented intelligence digital future.” It’s not that there’s anything wrong with the big reoccurring AI themes.

In the near future, he promised, more AR-enabled smart glasses will ship than smart phones and with this shift, “brand new real estate will open up for advertisers and merchandisers.” And the preparations are already underway… Indeed, the questionable practice of tracking and monitoring internet users is about to take steroids, as AR and VR solutions allow retailers and other interested parties pack-out their already overflowing databanks with granular biometric information from surveillance like eye-tracking.

The incredibly talented (and refreshingly candid) John Canning of Digital Domain, the visual effects and digital production company responsible for this tool, openly admitted that problems could well arise from the abuse of the technology responsible for so-called “digital humans” — particularly when these AI imposters are based on real people.

It is simply left to us concerned makers and citizens to anticipate and block any malicious use — like the impersonation of world leaders before their populations, parents before their unsuspecting children, and authority figures before anyone who might reveal important personal information to a recognizable figure, like law enforcement.


In recent years machine learning (ML) and Artificial Intelligence (AI) methods have begun to play a more and more enabling role in the sciences and in industry.

Specifically I will first introduce XAI methods (such as LRP) that are now readily available and allow for an understanding of the inner workings of nonlinear ML methods ranging from kernel methods to deep learning methods including LSTMs.

Then, ML for Quantum Chemistry is discussed, showing that ML methods can lead to highly useful predictors of quantum mechanical properties of molecules (and materials) reaching quantum chemical accuracies both across chemical compound space and in molecular dynamics simulations.

His research interest is in the field of machine learning, deep learning and data analysis covering a wide range of theory and numerous scientific (Physics, Chemistry, Neuroscience and Biomedical Engineering) and industrial applications.

How tech is transforming the intelligence industry

At a conference on the future challenges of intelligence organizations held in 2018, former Director of National Intelligence Dan Coats argued that he transformation of the American intelligence community must be a revolution rather than an evolution.

The hierarchical, compartmentalized, industrial structure of these organizations is now changing, revolving primarily around the integration of new technologies with traditional intelligence work and the redefinition of the role of the humans in the intelligence process.

They argue that artificial intelligence will never be capable of comprehending the full spectrum of considerations in strategic decision-making, and that it cannot evaluate abstract issues in the interpretation of human behavior.

From 1995 to 2016, the amount of reading required of an average US intelligence researcher, covering a low-priority country, grew from 20,000 to 200,000 words per day.

Billionaires, chief executive officers, and leaders from the technology, media, and finance industries gather this week at the Idaho mountain resort conference hosted by investment banking firm Allen &

Photographer: David Paul Morris/Bloomberg via Getty Images Private services and national intelligence In the United States there is dynamic cooperation between these bodies and the security community, including venture capital funds jointly owned by the government and private companies.

a venture capital fund established 20 years ago to identify and invest in companies that develop innovative technology which serves the national security of the United States, thus positioning the American intelligence community at the forefront of technological development.

Companies like Hexagon, Nice, Splunk, Cisco and NEC offer intelligence and law enforcement agencies a full suite of platforms and services, including various analytical solutions such as video analytics, identity analytics, and social media analytics .

Established in 2006, IARPA finances advanced research relevant to the American intelligence community, with a focus on cooperation between academic institutions and the private sector, in a broad range of technological and social sciences fields.

Some of the tools can be purchased and quickly implemented – for example, data and knowledge sharing and management platforms – while others are developed by the organizations themselves to meet their specific needs.

In the past, the collection of information about a given target required a specific decision to do so and dedicated resources to be allocated for that purpose, generally at the expense of allocation of resources to a different target.

But in this era of infinite quantities of information, almost unlimited access to information, advanced data storage capabilities and the ability to manipulate data, intelligence organizations can now collect and store information on a massive scale, without the need to immediately process it – rather, it may be processed as required.

It is therefore not surprising that most of the technological advancements in the intelligence field respond to these challenges, bringing together technologies such as big data with artificial intelligence, advanced information storage capabilities and advanced graphical presentation of information, usually in real time.

This is not another attempt to carry out structural reforms: there is a sense of epistemological rupture which requires a redefinition of the discipline, the relationships that intelligence organizations have with their environments – from decision makers to the general public – and the development of new structures and conceptions.

legislators need to create a legal framework that accurately incorporates the assessments based on data in a way that takes the predictive aspects of these technologies into account and still protects the privacy and security rights of individual citizens in nation states that have a respect for those concepts.

In a sense, intelligence organizations have not internalized the complexity that characterizes the present time – a complexity which requires abandoning the dichotomous (within and outside) perception of the intelligence establishment, as well as the understanding of the intelligence enterprise and government bodies as having a monopoly on knowledge;

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