Author - Edgar Perez

Anthony Bourdain hanged himself in his hotel room in Kaysersberg, France, while in town shooting Parts Unknown

Artificial Intelligence and Anthony Bourdain: “I’ve had a good run – why not just do this stupid thing, this selfish thing… jump off a cliff into water of indeterminate depth”

“It is with extraordinary sadness we can confirm the death of our friend and colleague, Anthony Bourdain,” CNN said in a statement Friday morning. Christian De Rocquigny du Fayel, a prosecutor in the town of Colmar, confirmed Bourdain’s death and said local law enforcement is investigating. ‘At this stage nothing suggests the involvement of a third party,’ the prosecutor said, adding that ‘a doctor at the scene’ had confirmed Bourdin’s death by hanging.

Bourdain’s death, coming days after the suicide of designer Kate Spade, brings to the forefront the complex issue of depression and how Artificial Intelligence can prevent these tragic decisions. A few years ago, a team of Harvard researchers developed the Beiwe platform, which attempted to leverage mobile phone technology and data science to offer medicine a wealth of additional information on disease digital phenotypes, including those of depression.

“Digital phenotyping” is a method of quantifying individual characteristics by analyzing cognitive data generated from an individual’s use of smartphones and other personal digital devices. Mindstrong, a California-based startup, has trained its machine learning algorithms on an equivalent of 200 person-years of cognitive data from three clinical studies. Through analytics, researchers interpret the data and suggest correlations between specific digital activities and brain activity.

A clinical trial managed by Mindstrong in partnership with Stanford University aims to define signals correlated with cognition, brain imaging and mood in patients with depression. Now that the majority of Americans, 77%, own a smartphone, it wouldn’t be too long before these applications come preinstalled and potentially help identify people with the most need for support. Nobody expected the famous chef and TV presenter to be one of them; he did have a good run and did the selfish thing, yet we can’t judge. Rest if peace Anthony Bourdain.

Can Artificial Intelligence’s facial-recognition techniques help end school shootings?

Rapid advances and decreasing prices for facial-recognition artificial intelligence technology, fueled by an arms race of surveillance firms eager to dominate the educational market, have made systems that promise to end school shootings faster, cheaper and more available than ever.

For schools with high-resolution digital cameras activating face recognition can be easy as installing new software. Trevor Matz, the chief executive of video system BriefCam, said there is increased interest in cutting-edge surveillance technology, including from schools. His company makes software that can recognize faces and filter video with search terms like “girl in pink” or “man with mustache,” shrinking hours of footage into seconds.

“Everybody we demo the product to immediately goes, ‘Wow’ and says, ‘I want it.’ There’s not a lot of selling that needs to be done.” The city of Springfield, Mass., for example, is beefing up its school security with an additional 1,000 cameras at its roughly 60 public schools in the coming months, all of which will work with BriefCam.

Yet the most advanced facial-recognition systems on the market provide imperfect matches that have been shown to be less accurate for women and people of color, raising concerns that students could be wrongly blocked from campus or misidentified as violent criminals — even from an early age. Furthermore, innocent lives could be put at risk.

Will these systems deliver on their promises at the time of the next attack? Let’s discuss this and more at my upcoming programs on Artificial Intelligence with Terrapinn Training, GLC Europe and GLDNAcademy.


Thinking twice before dozing off in class at China’s Hangzhou No. 11 Middle School

Hikvision Digital Technology, one of the world’s biggest suppliers of security cameras and which is developing its own AI technology, has developed a “smart classroom behavior management system”, which captures students’ expressions and movements, analyzing them with artificial intelligence to make sure they’re paying attention.

The “Big Brother” strategy underscores how AI and facial recognition tools are increasingly being used in China for a host of tasks, from verifying payments and catching criminals to checking the audience at big entertainment events and customers at fast-food joints.

The system will be able to tell if students are reading or listening – or napping at their desks. It can detect expressions like happiness, repulsion, fear, anger and befuddlement. Students will get a real-time attentiveness score, which will be shown to their teacher on a screen.

How can these technologies be translated into the workplace? Will workers accept this extreme case of monitoring? I am looking forward to discussing these themes at my upcoming Deep Learning programs with GLC Europe, Terrapinn Training and GLDNAcademy.

With a little help from my friends Google and D-Wave, Volkswagen is on the path to simulate and optimize the chemical structure of high-performance electric vehicle batteries on a quantum computer

Cooperating with technology partners Google and D-Wave, who provide the Volkswagen experts with access to their systems, the firm has succeeded in simulating industrially relevant molecules using a quantum computer. They have successfully simulated molecules such as lithium-hydrogen and carbon chains. Now they are working on more complex chemical compounds.

Using newly developed algorithms, the Volkswagen experts have laid the foundation for simulating and optimizing the chemical structure of high-performance electric vehicle batteries on a quantum computer. In the long term, such algorithms could simulate the chemical composition of a battery on the basis of different criteria such as weight reduction, maximum power density or cell assembly and provide a design which could be used directly for production. This would significantly accelerate the battery development process, which has always been time-consuming and resource-intensive to date.

Florian Neukart, Volkswagen’s CODE Lab, said: “We are working hard to develop the potential of quantum computers for Volkswagen. The simulation of electrochemical materials is an important project in this context. In this field, we are performing genuine pioneering work. We are convinced that commercially available quantum computers will open up previously unimaginable opportunities. We intend to acquire the specialist knowledge we need for this purpose now.”

Highly specialized IT experts from Volkswagen, including data scientists, computer linguists and software engineers, are working together at the IT labs in San Francisco and Munich to develop the potential of quantum computers for applications which will be beneficial for the company. For information about applications in other industries, I will review them at my upcoming quantum computing workshops with GLDNAcademy.

Getting our hands “dirty” in the “playground” with GLDNAcademy’s Quantum Computing programs

Jaya Baloo, KPN’s CISO, said recently that quantum computing offers organizations a potentially exponential scalability when it comes to speed and computing power. This “quantum speed-up” poses serious risks to traditional cryptography, in that a current problem that would take “the lifetime of the universe” to solve could end up taking just a few seconds.

With commercial quantum computers potentially emerging in the next 10-20 years, information security professionals must act now. She said, “You need to ask yourself which threat model do you have and how long do you have to keep it safe? I need us all as an information security community to get our hands dirty now.”

That is what attendees to my GLDNAcademy‘s Quantum Computing programs are expected to do. What else would you expect going to the Quantum Computing Playground?

Will Apple succeed in the AI battle against Facebook, Amazon, Microsoft, and Google?

WIRED recently described an iPad app for basketball coaches called HomeCourt. You don’t have to be a pro to use it; is as easy as pointing an iPad’s camera at action on the court. Then the tricky stuff happens automatically. HomeCourt uses the support for machine learning added Apple’s mobile operating system last year to analyze the video. The app tracks each time a player shoots, scores, or misses, and logs the shooter’s location on the court. Each event is indexed so a particular play can later be viewed with a single tap.

HomeCourt is built on tools announced by Apple last summer, when they launched their bid to become a preferred playground for AI-curious developers. Known as Core ML, those tools help developers who’ve trained machine learning algorithms deploy them on Apple’s mobile devices and PCs.

Apple is far from the first tech company to release software to help developers build machine learning models. Facebook, Amazon, Microsoft, and Google have all done so, with TensorFlow the most popular. Apple claims none easily fit into an app developer’s regular workflow, limiting machine learning’s potential. I will review these different approached at my upcoming artificial intelligence and deep learning programs by Terrapinn Training, GLDNAcademy and GLC Europe.


For the UK’s Home Department, quantum computing has the potential to dramatically change and enhance counter-terror operational capabilities

CONTEST, the recently published United Kingdom’s strategy for Countering Terrorism states that new technology creates new challenges, risks and opportunities in fighting terrorism. Terrorists are using new technologies, like digital communications and unmanned aerial vehicles, to plan and execute attacks, and tend to adopt them at the same pace as society as a whole. For terror groups, the internet is now firmly established as a key medium for the distribution of propaganda, radicalisation of sympathisers and preparation of attacks.

This evolving technology, including more widespread use of the internet and ever-more internet-connected devices, stronger encryption and cryptocurrencies, will continue to create challenges in fighting terrorism. Data will be more dispersed, localised and anonymised, and increasingly accessible from anywhere globally. But there will be as great opportunities too.

Developments in artificial intelligence will allow authorities to filter and identify crucial information faster than ever. Virtual or augmented reality gives counter-terrorism teams the opportunity to plan for a wide variety of scenarios in a safe environment. Governments will have new technologies that enhance detection and screening capabilities, for example at borders, airports and crowded places.

Quantum computing has indeed the potential to dramatically change and enhance counter-terror operational capabilities. For example, the power of quantum computing can be combined with artificial intelligence to improve the speed at which large datasets can be sorted and mined for key information that would be of benefit to law enforcement and intelligence agencies. This is just one the applications I will be reviewing at my upcoming seminars on Quantum Computing put together by GLDNAcademy.

One third of global businesses would pay malware ransoms rather than develop stronger cyber defenses. Why?

A recent NTT Security’s report showed that one third of business decision makers globally said that they would prefer to pay malware ransoms to hackers than to invest more money over the long term in cyber security. Why would they do that?

By taking this path, business leaders are showing an unprecedented confidence that their businesses will not be impacted by data breaches and other cyber threats. They might not see cyber risks as one of the most important ones for their firms’ survival. Unfortunately, this approach guarantees trouble once a cyber attack comes their way; no preparation means the adoption of a short-term, reactive approach to security that will instead drive up costs.

Part of the problem is certainly awareness; business leaders have not been informed of proactive steps they can direct their IT organization (and beyond) to take, and the impact of their non action in the bottom line (in case of for profit enterprises). These are areas I will speak about at my upcoming cybersecurity seminars with Terrapinn Training, Marcep and GLDNAcademy.

Pentagon’s AI program to find hidden nuclear missiles can be fooled by China and Russia

Reuters just reported that the U.S. military is increasing spending on a secret research effort to use artificial intelligence to help anticipate the launch of a nuclear-capable missile, as well as track and target mobile launchers in North Korea and elsewhere.

There are multiple classified programs now under way to explore how to develop AI-driven systems to better protect the United States against a potential nuclear missile strike. If the research is successful, such computer systems would be able to think for themselves, scouring huge amounts of data, including satellite imagery, with a speed and accuracy beyond the capability of humans, to look for signs of preparations for a missile launch, according to more than half a dozen sources.

However, there is also a high probability that countries like China and Russia could try to trick an AI missile-hunting system, learning to hide their missiles from identification. Just last week, an experiment by M.I.T. students showed how easy it was to dupe an advanced Google image classifier, in which a computer identifies objects. In that case, students fooled the system into concluding a plastic turtle was actually a rifle. That is the reason why the Pentagon still needs humans to review AI systems’ conclusions.

Military applications of AI and Deep Learning are just one area of the many potential uses of these technologies I will review with attendees to my seminars with Terrapinn Training, GLDNAcademy and GLC.

Yes, the age of quantum computing has arrived

A pioneering article in mainstream media from The Guardian opened the doors of Quantum computing as the technology that many scientists, entrepreneurs and big businesses expected to provide a, well, quantum leap into the future. What was true two years ago, it is even truer now.

The concept of quantum computing is relatively new, dating back to ideas put forward in the early 1980s by the late Richard Feynman, the brilliant American theoretical physicist and Nobel laureate. He conceptualized the possible improvements in speed that might be achieved with a quantum computer. But theoretical physics, while a necessary first step, leaves the real brainwork to practical application.

With normal computers, or classical  computers as they’re now called, there are only two options – on and off – for processing information. A computer “bit”, the smallest unit into which all information is broken down, is either a “1” or a “0”. In the mysterious subatomic realm of quantum physics, particles can act like waves, so that they can be particle or wave or particle and wave. This is what’s known in quantum mechanics as superposition. As a result of superposition a qubit can be a 0 or 1 or 0 and 1. That means it can perform two equations at the same time. Two qubits can perform four equations. And three qubits can perform eight, and so on in an exponential expansion. That leads to some inconceivably large numbers, not to mention some mind-boggling working concepts.

In areas such as artificial intelligence and cryptography, quantum computing will transform the landscape, perhaps bringing about the breakthrough that will enable machines to “think” with the nuance and interpretative skill of humans. I will review these applications at my upcoming seminars on Quantum Computing put together by GLDNAcademy.