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”Edgar Perez
“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.
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.
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 computerEdgar Perez
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.
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.”
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 capabilitiesEdgar Perez
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.
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.
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.
According to Jeff Dean, Senior Fellow at Google, no more than a few thousand companies today have the right talent for building Artificial Intelligence, but many more have the necessary data. Based on the feedback I receive in my presentations across all continents, I am persuaded the urgent goal today is to take A.I. from thousands of organizations solving deep learning problems to millions, as soon as possible.
The impact of Artificial Intelligence cannot be underestimated. Millions of jobs will be radically transformed across hundreds of thousands companies around the world. Tasks that still require a heavy human component will be automated, leaving former employees with few options: upgrade your skills or go unemployed. For those who decide to acquire new skills, the sudden increase in productivity will bring a new wave of opportunities that will create jobs we can’t even imagine as of today. (more…)
Cybersecurity is top of mind for management. That same cannot be said of all your employees, who need to be appropriately trained and evaluated on a consistent basis. Is your cybersecurity team up to the challenge? (more…)
Edgar Perez, the author of “The Speed Traders: An Insider’s Look at the New High-Frequency Trading Phenomenon That Is Transforming the Investing World” and the forthcoming “Knightmare on Wall Street: Do Facebook’s Botched IPO and Knight Capital’s Technology Error Mark the Beginning of the End of Equities Investing?,” leads The Speed Traders Workshop 2012. He is on Twitter and Weibo. (more…)
Open Letter to SEC Chairman Mary Jo White: Maintaining the Standing of the U.S. as the World’s Most Sophisticated Financial and Trading MarketEdgarAdmin
NASDAQ suffered a trading freeze on August 22, when price quotes were not being disseminated by the Securities Information Processor (SIP) for three hours. While NASDAQ has promised to work with other exchanges that are members of the SIP to come up with permanent fixes, their time to self-police has passed.
Dear chairman Mary Jo White. (more…)
美国纽约大学金融系教授、高频交易专家埃德加-佩雷兹所著《华尔街噩梦：骑士资本兴亡与金融市场最大风险》(Knightmare on Wall Street: The Rise and Fall of Knight Capital and the Biggest Risk for Financial Markets)一书对骑士资本公司的兴亡进行幕后审视。本书全面叙述了骑士资本如何成为20世纪90年代末投资革命中的弄潮儿，如何奋力度过繁荣与萧条，以及公司衰落、最终被竞争对手收购的不光彩命运。 (more…)
THE combined forces of speed and technology are turning the stock market into a different animal from the days of our fathers and mothers with small retail players being the casualties of the sweeping changes, particularly in the West. This is the dark side of technology which cannot be ignored but which must be managed by regulators. (more…)