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Month: June 2020

22 Jun 2020


A team of researchers claim to have achieved quantum teleportation using individual electrons.

Quantum teleportation, or quantum entanglement, allows particles to affect each other even if they aren’t physically connected — a phenomenon predicted by famed physicist Albert Einstein.

Rather than a teleportation chamber out of a sci-fi movie, quantum teleportation transports information rather than matter.

Scientists have recently shown that pairs of photons — massless elementary particles — could form entangled qubits, the basic unit of quantum information. The discovery suggested that these qubits could transmit information via quantum teleportation.

Electron Qubits
The new research, however, marks the first time the same has been demonstrated using individuals electrons to form qubits.

“We provide evidence for ‘entanglement swapping,’ in which we create entanglement between two electrons even though the particles never interact, and ‘quantum gate teleportation,’ a potentially useful technique for quantum computing using teleportation,” John Nichol, an assistant professor of physics at the University of Rochester, co-author of the new paper published in Nature Communications this week, said in a statement. “Our work shows that this can be done even without photons.”

Info Dump
Allowing electrons to use quantum-mechanical interactions over a distance without touching could revolutionize the development of quantum computers. After all, semiconductors inside conventional computers use electrons to transmit information.

“Individual electrons are promising qubits because they interact very easily with each other, and individual electron qubits in semiconductors are also scalable,” Nichol said.

But passing this information over longer distances remains to be a big hurdle. “Reliably creating long-distance interactions between electrons is essential for quantum computing,” Nichol added.

Source: https://futurism.com/the-byte/scientists-demonstrate-quantum-teleportation-using-electrons

20 Jun 2020

Why Disciplined Innovation Matters Most Now

VP of manufacturing, technology and Innovation at Jabil. Over 20 years of experience helping global teams create cutting-edge manufacturing.

A double dose of disciplined innovation will go a long way in helping the world right now. Think about all the benefits that could come from innovations such as wearable patches embedded with biosensor technology to monitor a patient’s vital signs remotely, along with patches equipped with acoustic and audio sensors to interpret cough patterns and respiratory rates, as well as heart and lung sounds.

Expect to see an influx of sensor-based wearable devices, which will give overworked health care workers a much-needed break by enabling remote and low- or no-touch patient monitoring. Emerging advances in electrochemical biosensors for pathogen detection also promise big benefits in more rapidly detecting and combatting viral and bacterial pathogens.

Innovations are popping up everywhere, many leveraging advances in flexible hybrid electronics (FHE). For instance, integrating capacitive touch capabilities with FHE enables functionality to be embedded directly onto plastic or glass surfaces without the need for knobs, buttons or crevices. For hospitals, the opportunity to have device and appliance surfaces that are easy to clean and disinfect is hugely helpful.

In my last column, I explained how innovation goes into overdrive in times of crisis as a shared sense of urgency and purpose propel projects forward. Equally important is infusing each new product with proven principles and processes to maximize results.

A New Take On Innovative Thinking

I have long been a Clayton Christensen fan, ever since he coined the term “disruptive innovation” to describe how a product or service can take root in simple applications at the bottom of a market and then move upmarket to displace established competitors. I’ve also followed Professor Christensen’s fellow Harvard professor and strategy guru Michael Porter.

For many, being a disruptor means thinking “outside the box” to challenge conventional wisdom. As an engineer, I favor applying discipline and rigor to build a better box. It is a more practical spin on the theories espoused by the aforementioned professors because discipline helps you adapt more readily to new situations and constraints.

You may be faced with limited time, lack of materials, financial restrictions or constrained people resources. There is always something that necessitates a modification to the initial plan. The recent health crisis underscores this point, especially when you realize what innovators have managed to accomplish despite facing every limitation on the list.

In The Innovator’s Solution, Professor Christensen describes how disruptive innovators rely on discovery-driven planning to make decisions based on pattern recognition. Conversely, organizations seeking to sustain innovation plan deliberately and make project decisions based on numbers and rules. In the world of manufacturing, we have to balance both sides of the innovation equation, despite the obvious conflicts between them.

Unlimited Is Not In My Lexicon

In supporting any new product development, I look closely at the constraints, as the word “unlimited” is not in my lexicon. Industrialization dictates that we constantly review and leverage the best processes, technologies and people. We continually monitor outcomes to yield the best results at the “lowest landed cost,” which is the total price of a product once it has reached the buyer’s doorstep.

Each product brainstorm is framed by the core fundamentals of advanced manufacturing: design, materials, process, quality and test. We adhere to these tenets without exception and innovate within these foundational pillars.

This approach ensures the right investments are made at the right time without stifling innovation. Early entrants tend to address an urgent need, such as the emergence of infrared sensors in retail, which take shoppers’ temperatures as they enter the store. Interest in developing devices activated by voice control and gesture recognition also are on the rise, along with sanitizing and disinfecting robots and accelerated research and development for autonomous system innovations.

Through structured manufacturing and industrialization initiatives, companies can apply disciplined innovation to build upon these early product advancements, reallocate their own product development investments or become hyperfocused on solutions to help society.

Robust, Repeatable Rigor

Each new product comes with its own set of constraints. Clearly, autonomous systems for situation awareness applications carry significant operational risk, but they will get smarter and safer, thanks to additional sensors and actuators as well as cross-discipline expertise and arduous testing.

Today, an overriding sense of urgency is condensing industrialization phases without compromising the robust, repeatable processes and manufacturing rigor required to ensure the highest levels of quality possible. Disciplined innovation matters most when time is of the essence. That is why, right now, it is going to catalyze unbelievable product breakthroughs that will make us stronger, safer and better prepared for whatever the future holds.

Source: https://www.forbes.com/sites/forbestechcouncil/2020/06/19/why-disciplined-innovation-matters-most-now/#6de3f9801c20

16 Jun 2020

How using neuroscience can help capture customer sentiment and predict future behavior

As you integrate data to create a complete picture of your customers, you must always place an added emphasis on the brain.

Do you want to predict the future? The ability to foretell how customers might respond to a new product or service can translate into millions. But it’s difficult to do. The Coca-Cola Company tried to do it and failed miserably. The introduction of New Coke in 1985 was an epic failure, despite pouring millions of dollars into market research. Success isn’t always easy. And according to the Harvard Business Review, 90% of product launches fail every year.

Do you think your customers will respond positively to your next offering? You can turn to focus groups and try to get an idea of what people might like. Surveys can provide decent insights at times. And if you have a robust predictive analytics platform, you can assess behavioral data to identify patterns that might indicate future behavior among larger groups. But if you really want to understand how customers might respond to future offerings, you need to take a look at the brain.

Sharpen your focus: Inside group dynamics
Focus groups provide value, but they can be remarkably flawed. Do certain participants bend the truth to look good in the eyes of an attractive person in the group? Certainly. Do participants change their tune to dance to the trumpeting of a more dominant person? Naturally. Perhaps most surprisingly, however, group dynamics affect what people say – whether they believe what they’re saying or not.

In 1951, psychologist Solomon Asch conducted a series of experiments to assess the influence of group behavior on individuals. During each experiment, a volunteer joined a group of several peers in a room. Unknown to the volunteer, everyone else in the group was part of the experiment. Each person viewed two cards – one card with a single straight line and a second card with three lines of different lengths.

The task was simple. The volunteer simply had to say which two lines were the same length. There were no visual illusions. No tricks. The task was straightforward. Interestingly, 75% of real participants intentionally gave the wrong answer. Why? As each fake participant provided an incorrect answer, the real participant felt pressure to fit in with the group – and eventually gave way.

Market researchers are aware of the biases associated with group dynamics. But even with the best safeguards in place, group responses don’t always reflect real-world experiences. As you explore different approaches to capturing customer sentiment to estimate behavior in the future, you might want to consider how your offering – or the creative work associated with your offering – will activate certain parts of the brain.

Using the brain to predict future behavior
Researchers at Stanford University and the University of Michigan evaluated the brain’s response to different types of Kickstarter projects. The participants also rated the projects in terms of likability and the likelihood of success. Did brain activity predict behavior more accurately than self-reports?

Even during individual tasks, people tend to make faulty predictions—but the brain doesn’t. As the researchers predicted, brain behavior “outperformed models that included self-reported ratings of liking…and individual choices of the laboratory sample.” In fact, activity in two areas of the brain associated with reward (nucleus accumbens) and value integration (medial orbitofrontal cortex), respectively, “predicted individual choices to fund on a trial-to-trial basis.”

But does this translate to a larger population? In other words, is it possible to take individual brain activity and predict behavior in the broader marketplace? Interestingly, the answer is yes. Brain activity from the study was predictive of behavior from a larger group of people outside the study. In fact, it was activity in the nucleus accumbens that “generalized to forecast market funding outcomes weeks later on the Internet.”

Music downloads beat to the rhythm of the brain
What happens when you try to predict the success of a product or service several years into the future? Researchers at the Department of Economics and Center for Neuropolicy at Emory University conducted a study to predict the future success of music sales. Is it possible for brain activity to predict song popularity years (instead of weeks) in advance?

In the study, participants listened to music from unknown artists in a scanner that measured brain activity. The participants also rated each song. The songs that generated activation in the nucleus accumbens turned into big hits a few years later (as measured in downloads and overall sales). While the brain predicted the popularity of songs, “subjective likability of the songs was not predictive of sales.” In other words, activation in a key area of the brain predicted the success of future sales better than direct feedback from participants.

Source: https://marketingland.com/how-using-neuroscience-can-help-capture-customer-sentiment-and-predict-future-behavior-279918

08 Jun 2020

Researchers: This AI Can Judge Personality Based on Selfies Alone

A team of researchers from the Higher School of Economics University and Open University in Moscow, Russia claim they have demonstrated that an artificial intelligence can make accurate personality judgments based on selfies alone — more accurately than some humans.

The researchers suggest the technology could be used to help match people up in online dating services or help companies sell products that are tailored to individual personalities.

That’s apropos, because two co-authors listed on a paper about the research published today in Scientific Reports — a journal run by Nature — are affiliated with a Russian AI psychological profiling company called BestFitMe, which helps companies hire the right employees.

As detailed in the paper, the team asked 12,000 volunteers to complete a questionnaire that they used to build a database of personality traits. To go along with that data, the volunteers also uploaded a total of 31,000 selfies.

The questionnaire was based around the “Big Five” personality traits, five core traits that psychological researchers often use to describe subjects’ personalities, including openness to experience, conscientiousness, extroversion, agreeableness, and neuroticism.

After training a neural network on the dataset, the researchers found that it could accurately predict personality traits based on “real-life photographs taken in uncontrolled conditions,” as they write in their paper.

While accurate, the precision of their AI leaves something to be desired. They found that their AI “can can make a correct guess about the relative standing of two randomly chosen individuals on a personality dimension in 58% of cases.”

That result isn’t exactly groundbreaking — but it’s a little better than just guessing, which is vaguely impressive.

Strikingly, the researchers claim their AI is better at predicting the traits than humans. While rating personality traits by human “close relatives or colleagues” was far more accurate than when rated by strangers, they found that the AI “outperforms an average human rater who meets the target in person without any prior acquaintance,” according to the paper.

Considering the woeful accuracy, and the fact that some of the authors listed on the study are working on commercializing similar tech, these results should be taken with a hefty grain of salt.

Neural networks have generated some impressive results, but any research that draws self-serving conclusions — especially when they require some statistical gymnastics — should be treated with scrutiny.

Source: https://futurism.com/researchers-ai-judge-personality-selfies