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Author: Manahel Thabet

08 Jul 2020

What is Blockchain Technology?

Its been almost ten years since Satoshi Nakamoto first introduced Blockchain technology to the world in his 2008 Bitcoin Whitepaper. Since that time, these revolutionary networks have gained popularity in both the corporate and governmental sectors. This growth is easily explained when you consider that blockchain technology provides the world with some unique advantages that were previously unimaginable. Consequently, today, you can find blockchain technology in nearly every sector of the global economy.

What is Blockchain Technology?
A blockchain is a network of computers that share a distributed ledger across all network participants (nodes). This strategy is far different than say, fiat currencies that originate from a centralized authority figure. Importantly, this ledger keeps an unbroken chain of transactions since the birth of the network. This “chain” of transactions grows larger as new “blocks” of transactions are approved and added to it.

Bitcoin Whitepaper

In order to approve new transactions, each node works together with others to validate new blocks. Additionally, the nodes also validate the current state of the entire blockchain. In order for a new block of transactions to be added to the blockchain, they must receive approval from 51% of the network’s nodes. Nodes are also referred to as miners. In this manner, blockchain networks are decentralized networks that provide unmatched security to the world of digital assets.

Security via Decentralization

Decentralization is an important aspect of blockchain technology because it makes these revolutionary ledgers immutable and unalterable. In fact, since there is no centralized attack vector, hacking a blockchain is nearly impossible. The larger the blockchain network, the more secure the data on it remains.

For example, let’s look at the world’s largest blockchain, Bitcoin. Currently, the Bitcoin blockchain has over 10,000 active nodes located across the globe. This distribution means that in order for an attacker to alter even just one tiny piece of information on the blockchain, they would need to successfully hack 5,000+ computers at once.

While this task may not be impossible for the quantum computers of the future, it’s so unprofitable that it makes no sense to even attempt such a monumental task. Additionally, on top of successfully hacking 5000+ computers at once, an attacker would also need a supercomputer to recalculate the new blockchain transactions in time to introduce them into the network. It would literally be more affordable to create a new cryptocurrency from scratch.

Consensus Mechanisms

One of the reasons why blockchain networks are so secure is the integration of consensus mechanisms. Consensus mechanisms are cryptographic protocols that leverage the participants of a blockchain network in securing its data. In the case of Bitcoin, the Proof-of-Work (PoW) consensus mechanism is used.

Proof-of-Work (PoW)

The Proof-of-Work consensus mechanism was revolutionary to the world of cryptography when it was first introduced years prior by Adam Back in his Hashcash whitepaper. In the concept, Back describes the integration of a mathematical equation to the network’s security protocols. In this way, every computer can show “proof” of their work securing the network.

Miner Rewards

It’s important to understand that nodes receive a reward for their mining efforts. These rewards adjust automatically depending on the network’s difficulty and value. In the case of Bitcoin, miners originally received 50 Bitcoin for their efforts. Today, this seems like fortune, but back in 2009, Bitcoin was only worth pennies. As the value of the token rises and the network goes, the mining rewards shrink. Today, Bitcoin miners receive 6.5 BTC if they add the next block to the chain.


Notably, every node validates and secures the blockchain, but only one gets to add the next block of transactions to the network. To determine who the next miner is that gets to add this block, every computer competes in a mathematical race to figure out the PoW equation. In the case of Bitcoin, the equation is known as SHA-256. Importantly, the first SHA algorithm dates back to Hashcash. This early version of the equation was known as SHA-1.

Bitcoin Consensus Mechanism - SHA-256 - Blockchain Technology

Bitcoin Consensus Mechanism – SHA-256 – Blockchain Technology

Notably, the SHA-256 equation is so difficult that it’s easier and more efficient for your computer to just make random guesses rather than attempting to figure out the equation directly. The answer to the equation must begin with a predetermined amount of 0s. In the Bitcoin blockchain, the equation’s answer must start with four zeros. However, if the network’s congestion rises, so does the difficulty of these equations. This difficulty adjusts by the addition of another zero at the beginning of the required SHA-256 answer.

Similarly to traditional commodities such as gold, there are costs that are associated with the creation and introduction of these digital assets into the market. These random guesses utilize intense computational power. This power equates to real-world costs such as electricity bills. Studies have shown that securing the Bitcoin network can use more electricity than required by entire countries. Luckily, over 80% of Bitcoin’s power consumption comes from renewable sources such as solar or hydroelectric.  This cost of mining also adds measurable value to each Bitcoin.


As Bitcoin began to gain in profitability,  its network’s computing power expanded significantly. In the beginning, nodes, also known as miners, could mine for Bitcoin using nothing more than your home PC. Eventually, miners realized that graphic cards were far better at the repetitive guessing required to figure out the SHA-256 algorithm. This led to a computational race in the market.


Eventually, large blockchain firms such as Bitmain introduced Application Specific Integrated Circuit (ASIC) miners into the equation. These purpose-built miners were thousands of times more efficient at guessing the SHA-256 algorithm than the GPUs and CPUs before them. Consequently, their introduction created a scenario in which the average miner now needed to invest thousands in mining equipment to stay relevant.

Mining Pools

Luckily, some creative minds in the field began to think of ways to level the playing field out again. They developed “mining pools.” A mining pool is a network of miners that all share computational power for the common goal of mining blockchain transactions. Importantly, mining pool participants receive a percentage of the reward based on their contributions to the network’s overall hash (computational power).

Importantly, over the last three years, there has been a push to move away from power-hungry consensus mechanisms such as PoW. This desire to secure blockchains in a more efficient manner has led to the development of some truly unique consensus mechanisms in the sector.

Proof-of-Stake (PoS)

The Proof-of-Stake mechanism does away with the difficult mathematical algorithms and instead utilizes a more psychological approach to securing the network. In a PoS blockchain, users don’t need to compete mathematically to add the next block to the blockchain. Instead, PoS users “stake” their coins via network wallets to secure the network. The way staking works is simple.

Keeping a certain amount of coins in your wallet allows you to participate in transaction validations. The more coins you stake, the more likely the chances are you get to add the next block of transactions to the network. In most PoS systems, a miner from those with the most tokens staked at the time receives the chance to add the blocks.

The advantages of a PoS consensus mechanism are immediately evident. For one, you don’t need to pour tons of resources into your network to keep it safe. Additionally, since nodes are chosen based on their amount of staked coins, there is never a scenario in which a node gains anything from validating incorrect transactions. Basically, a hacker would have to fully invest in the cryptocurrency prior to attacking the network. In this way, PoS systems create a huge deterrent to attackers.

The Future of Blockchain Technology

Blockchain technology has come a long way from its early days as a means to secure cryptocurrency networks. Today, blockchain technology has numerous uses across every type of industry imaginable. Specifically, blockchain programs have impacted the logistical, financial, and data security sectors in a major way.

Blockchain Technology Logistics

Blockchain logistical systems are more efficient and cost-effective to operate than traditional paper-based models. In fact, the immutable and unalterable nature of blockchain tech makes it ideally suited to logistical tasks. Soon, you may be able to ascertain much more information regarding the creation and delivery of your products thanks to these new-age systems emerging.

Blockchain Logistics

Blockchain Logistics via GlobalTranz


Blockchain technology has also altered the way in which businesses raise funds. In a traditional corporate crowdfunding strategy such as an IPO, companies must balance between cost-effectiveness and participation. The inability to process smaller transactions meant that for the longest time, companies had to turn away potential investors. Nowadays, blockchain technology enables businesses to easily automate these procedures via smart contracts.

Smart Contracts

Smart Contracts feature preprogrammed protocols that execute when they receive a certain amount of cryptocurrency sent to their address. These contracts live on the blockchain and enable remarkable functionality. For example, in the case of fundraising, a smart contract can automate processes such as the approval of investors and the distribution of funds.

Blockchain Technology Today

You can expect to see further expansion of the blockchain sector in the coming months as more governments and institutions explore its benefits. For now, the blockchain revolution is well underway.

Source: https://www.securities.io/what-is-blockchain-technology/

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

26 May 2020

Reality Check: The Benefits of Artificial Intelligence

Gartner believes Artificial Intelligence (AI) security will be a top strategic technology trend in 2020, and that enterprises must gain awareness of AI’s impact on the security space. However, many enterprise IT leaders still lack a comprehensive understanding of the technology and what the technology can realistically achieve today. It is important for leaders to question exasperated Marketing claims and over-hyped promises associated with AI so that there is no confusion as to the technology’s defining capabilities.

IT leaders should take a step back and consider if their company and team is at a high enough level of security maturity to adopt advanced technology such as AI successfully. The organization’s business goals and current focuses should align with the capabilities that AI can provide.

A study conducted by Widmeyer revealed that IT executives in the U.S. believe that AI will significantly change security over the next several years, enabling IT teams to evolve their capabilities as quickly as their adversaries.

Of course, AI can enhance cybersecurity and increase effectiveness, but it cannot solve every threat and cannot replace live security analysts yet. Today, security teams use modern Machine Learning (ML) in conjunction with automation, to minimize false positives and increase productivity.

As adoption of AI in security continues to increase, it is critical that enterprise IT leaders face the current realities and misconceptions of AI, such as:

Artificial Intelligence as a Silver Bullet
AI is not a solution; it is an enhancement. Many IT decision leaders mistakenly consider AI a silver bullet that can solve all their current IT security challenges without fully understanding how to use the technology and what its limitations are. We have seen AI reduce the complexity of the security analyst’s job by enabling automation, triggering the delivery of cyber incident context, and prioritizing fixes. Yet, security vendors continue to tout further, exasperated AI-enabled capabilities of their solution without being able to point to AI’s specific outcomes.

If Artificial Intelligence is identified as the key, standalone method for protecting an organization from cyberthreats, the overpromise of AI coupled with the inability to clearly identify its accomplishments, can have a very negative impact on the strength of an organization’s security program and on the reputation of the security leader. In this situation, Chief Information Security Officers (CISO) will, unfortunately, realize that AI has limitations and the technology alone is unable to deliver aspired results.

This is especially concerning given that 48% of enterprises say their budgets for AI in cybersecurity will increase by 29 percent this year, according to Capgemini.

Automation Versus Artificial Intelligence
We have seen progress surrounding AI in the security industry, such as the enhanced use of ML technology to recognize behaviors and find security anomalies. In most cases, security technology can now correlate the irregular behavior with threat intelligence and contextual data from other systems. It can also use automated investigative actions to provide an analyst with a strong picture of something being bad or not with minimal human intervention.

A security leader should consider the types of ML models in use, the biases of those models, the capabilities possible through automation, and if their solution is intelligent enough to build integrations or collect necessary data from non-AI assets.

AI can handle a bulk of the work of a Security Analyst but not all of it. As a society, we still do not have enough trust in AI to take it to the next level — which would be fully trusting AI to take corrective actions towards those anomalies it identified. Those actions still require human intervention and judgment.

Biased Decisions and Human Error
It is important to consider that AI can make bad or wrong decisions. Given that humans themselves create and train the models that achieve AI, it can make biased decisions based on the information it receives.

Models can produce a desired outcome for an attacker, and security teams should prepare for malicious insiders to try to exploit AI biases. Such destructive intent to influence AI’s bias can prove to be extremely damaging, especially in the legal sector.

By feeding AI false information, bad actors can trick AI to implicate someone of a crime more directly. As an example, just last year, a judge ordered Amazon to turn over Echo recordings in a double murder case. In instances such as these, a hacker has the potential to wrongfully influence ML models and manipulate AI to put an innocent person in prison. In making AI more human, the likelihood of mistakes will increase.

What’s more, IT decision-makers must take into consideration that attackers are utilizing AI and ML as an offensive capability. AI has become an important tool for attackers, and according to Forrester’s Using AI for Evil report, mainstream AI-powered hacking is just a matter of time.

AI can be leveraged for good and for evil, and it is important to understand the technology’s shortcomings and adversarial potential.

The Future of AI in Cybersecurity
Though it is critical to acknowledge AI’s realistic capabilities and its current limitations, it is also important to consider how far AI can take us. Applying AI throughout the threat lifecycle will eventually automate and enhance entire categories of Security Operations Center (SOC) activity. AI has the potential to provide clear visibility into user-based threats and enable increasingly effective detection of real threats.

There are many challenges IT decision-makers face when over-estimating what Artificial Intelligence alone can realistically achieve and how it impacts their security strategies right now. Security leaders must acknowledge these challenges and truths if organizations wish to reap the benefits of AI today and for years to come.

Source: https://www.aithority.com/guest-authors/reality-check-the-benefits-of-artificial-intelligence/

14 May 2020

Neuralink Will Do Human Brain Implant in “Less Than a Year”

For the second time in two years, entrepreneur and billionaire Elon Musk sat down with podcaster Joe Rogan to chat about the future of AI and its role in the symbiosis of man and machine.

In their conversation, Musk revealed that the secretive brain stimulation link startup Neuralink, which he co-founded, is close to starting testing in actual humans.

“We’re not testing people yet, but I think it won’t be too long,” Musk told Rogan. “We may be able to implant a neural link in less than a year in a person I think.”

The news comes after Musk teased in February that the brain-computer interface startup was working on an “awesome” new version.

In their conversation, Musk revealed that the secretive brain stimulation link startup Neuralink, which he co-founded, is close to starting testing in actual humans.

“We’re not testing people yet, but I think it won’t be too long,” Musk told Rogan. “We may be able to implant a neural link in less than a year in a person I think.”

The news comes after Musk teased in February that the brain-computer interface startup was working on an “awesome” new version.

Musk likened the process of his neural stimulation device zapping the brain to “kicking a TV.”

While that sounds violent, the goal is to restore brain functionality. For instance, those with Alzheimer’s could have their memories restored.

“It’s like a bunch of circuits and those circuits are broken,” Musk explained.

But the technology is still in its early stages.

“There’s still a lot of work to do,” Musk said. Referring back to his timeline of testing within a year, he noted that “we have a chance of putting a link in someone and having them be healthy and restoring some functionality that they’ve lost.”

Eventually, as Rogan mused about becoming one with machines in the distant future, Musk countered that we have to keep up.

“Even in a benign [AI] scenario we are being left behind,” Musk said. “So how do you go along for the ride? If you can’t beat ’em, join ’em.”

“We are already a cyborg to some degree,” Musk told Rogan. “You got your phone, you got your laptop… If you’re missing your phone, it feels like missing limb syndrome.”

Source: https://futurism.com/elon-musk-neuralink-human-brain-implant

04 May 2020



When the next generation of observatories are deployed, Cornell University astronomers hope to use them to scan distant exoplanets orbiting dead stars for signs of life.

When a rocky, Earth-like exoplanet passes in front of the white dwarf star it orbits, astronomers plan to search them for fingerprints of life, past or present. And to get a head start, the Cornell scientists published research in The Astrophysical Journal Letters on Thursday that offers a reference to help astronomers make sense of what they find.

Second Life

This particular brand of exoplanet would have survived the death of its host star: white dwarves are the remnant cores of stars that exhausted all of their fuel and collapsed. It stands to reason that anything living on those worlds wouldn’t survive such a devastating event, but new life could have theoretically emerged afterward.

“If we would find signs of life on planets orbiting under the light of long-dead stars,” Cornell astronomer Lisa Kaltenegger said in a press release, “the next intriguing question would be whether life survived the star’s death or started all over again — a second genesis, if you will.”

Cosmic Fingerprint

That’s where the new research comes in. It essentially serves as a catalog of what astronomers might come across as they study those exoplanets.

“If we observe a transit of that kind of planet, scientists can find out what is in its atmosphere, refer back to this paper, match it to spectral fingerprints and look for signs of life,” Cornell astronomy grad student Thea Kozakis said in the release. “Publishing this kind of guide allows observers to know what to look for.”

Source: https://futurism.com/the-byte/scientists-hunt-life-long-dead-worlds

04 May 2020
Dr Manahel Thabet in NewsWire

مناهل ثابت | Dr. Manahel Thabet Ph.D Scientist, Economist Biography BRAIN OF THE YEAR – 2015 in Yemen | about.me

Dr. Manahel Thabet is anEconomist in Essence and a Scientist driven by deep passion. Coming from the ancient lands of Yemen, the proud land of great civilizations and immense treasures of knowledge, Dr. Thabet is the youngest and only Arab with a degree of PhD in Financial Engineering with magna cum laude “honor. Dr. Thabet’s thesis has been also involved in the Financial Engineering society research. The thesis has made contributions to finance research studies including the theory of interest rate behavior and empirical testing of arbitrage pricing theory in the financial markets.

As George Bernard Shaw once stated that, “There are passions far more exciting than the physical ones…’intellectual passion, mathematical passion, passion for discovery and exploration: the all mightiest of all passions”. Dr. Manahel confirms this status, she possess a deep passion for science and quantum physics, which she has explored and studied thoroughly, resulting in mind blowing theories, which adds value to modern science. She is one of the rare Arab women to have entered the field of Quantum Mathematics, and currently her research has been adopted by several universities for development purposes. Her thesis in the field of quantum mathematics is to develop new mathematical equations to calculate distances of universe and micro elements. She is the only Arab woman and one of the few in the world to enter into the discipline of science complex numbers theories. The thesis has been accepted by the boards of several Universities as an exception due to the genuineness of the subject. In case of success, it will be a revolution expansion of the science of mathematics together with quantum physics. This gives Dr. Manahel Thabether second Doctorate degree.

In the year 2010 and until this date, Dr. Thabet is assigned as the President of “Iquestion”, the High IQ society 98% Percentile Rarity Intelligence Rate and the Vice President of “WIN” (World Intelligence Network), undertaking more than 45,000 members from all over the world.

Dr. Thabet is also an active member of several organizations such as Mensa International, Young Arab Leaders and the International Association of Financial Engineers. She is also a Columnist and an Economic Researcher in many leading financial publications.

Source: https://about.me/dthabet

03 May 2020
Dr Manahel Thabet in NewsWire

مناهل ثابت | Manahel Thabet, One of the Smartest People Alive! by Newswire


Dr. Manahel Thabet is a very successful name who has created a niche for herself in the Arab countries, as well as in the world. She has given a new face to the small- and medium-scale enterprises in the GCC countries. With a clear vision and great perseverance, she has introduced herself to a new height. She has been ranked among the 30 smartest people alive.

Dr. Thabet flaunts many feathers in her hat. She is the Founder and the President of SmartTips Consultants, President of Would IQ Foundation, President of the Brain Trust Foundation (MENA/ Middle East and North Africa), Vice President of WIN (World Intelligence Network), Vice Chancellor of The Gifted Academy, and Deputy Director of the Institute for Brain Chemistry. 

She is the curator of the Economic Think-Tank group of well-qualified economics advisors. It would not be wrong to say that Dr. Thabet is the flag-bearer for the women in the field of Science, Technology, Engineering, and Mathematics in Arab.

In the year 2012, she was elected as the Chairperson of the Scientific Committee, Recommendation Committee, and the Senior Adviser from amongst numerous participants from around 42 countries, at the International Asia Pacific Giftedness Conference. The Conference took place in Dubai and it was hosted by Hamdan Bin Rashid Awards for Distinguished Academic Performance.

Dr. Manahel Thabet has been ranked among 30 smartest people alive by Super Scholar. In the year 2013, she was named the Genius of the Year by the World Genius Directory delineating ASIA. After introducing the world to her great expertise and immense knowledge in the field of science, in the year 2014, Dr. Thabet was named the AVICENNA Award Laureate. She was next-in-line after Professor Tony Buzan. Continuing her success stories, she also registered her name in the new Guinness World Records in the year 2015, in one of the most arduous teaching methodologies. She also received Brain of the Year award in 2015-2016.

She has also had a successful stint as a GoodWill Ambassador for Eco International of Prince Albert II De Monaco Foundation. She is the president of IQuestion and a member of the Young Arab Leaders. She has judged the Drones for Good Awards UAE (2015-2016). She is the member of the International Association of Quantitative Finance, member of advisory board for In-Sight: Independent Interview-Based Journal, Arabian Intelligence Network supervisor, and editor of Synapsia’s IQ section.

Dr. Thabet is the Royal Grand Cross Officer of Companionate of White Swan. She is also a Fellow of the Royal Society of Medicine, London, UK. In the year 2016, she was given away the honor of Freedom of the City of London.

She is a member of many aristocratic high IQ societies like HELLIQ High IQ Society, QIQ High IQ Society, CIVIQ High IQ Society, GRIQ High IQ Society, 4GHigh IQ Society, HighIQWorld, Mensa International, etc.

Dr. Mahanel Thabet has influenced the lives of many. With her work, she has managed to create an impact not just in her native nation but across the globe.

She has been awarded the Middle East Achievement Award in Science. She was listed among the most powerful 500 Arabs in the world and the 100 most powerful women in the Middle East. She was also listed among the BBC’s 100 most inspirational women across the world.

With so many laurels, she is indeed one of the smartest and the most intelligent economist, scientist, and consultant.