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Monthly Archives: February 2022
Who was Nostradamus, could he see the future and did he ever predict a third World War? – Portsmouth News
Posted: February 28, 2022 at 7:58 pm
His many prophecies are still referenced and he continues to appear in popular culture.
And did he have any predictions about future world wars?
Heres what you need to know:
Born Michel de Nostredame in the 16th century.
He was an astrologer, physician and reputed seer.
His name is usually Latinised as Nostradamus.
He is most famous for his book Les Prophties, which was a collection of 942 poetic quatrains that were said to predict future events.
Could Nostradamus see the future?
The answer to this is heavily contested.
His supporters claim that he predicted such events as the Great Fire of London, the French Revolution, the rises of Napoleon and Adolf Hitler, both world wars, and the nuclear destruction of Hiroshima and Nagasaki.
But academic research from the 1980s unearthed a lot of personal correspondence and other artifacts that cast doubt on the prophetic nature of his predictions.
They found that not one of Nostradamuss contemporary prophesies listed was backed up by any known contemporary documentary evidence.
Many of his prophecies have also been misinterpreted and wrongly applied to current disasters such as 9/11.
Did Nostradamus predict there would be a WW3?
His supporters claim that the Frenchman foresaw both of the world wars in the 20th century.
'Nostradamus believes it will be a great protracted war, 25 to 29 years, followed by lesser battles,' he stated last year.
But once again it needs stating that academics have long poured cold water on the so-called prophetic nature of Nostradamus writings.
A message from the Editor, Mark Waldron
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Biden says alternative to sanctions is WW3, Lukashenko slams west for pushing Russia – The Business Standard
Posted: at 7:58 pm
US President Joe Biden on Saturday said an alternative to sanctions that Washington has slapped on Russia would be the Third World War.
"You have two options. Start a Third World War, go to war with Russia, physically. Or two, make sure that the country that acts so contrary to international law ends up paying a price for having done it," Biden said in an interview with blogger Brian Tyler Cohen. The video was posted on his YouTube page on Saturday (26 February).
Meanwhile, Belarusian President Alexander Lukashenko has said that the policy of sanctions is aimed at eliminating Russia as a competitor and is leading to another world war.
Russia is being pushed towards a third world war. We should be very reserved and steer clear of it. Because nuclear war is the end of everything," Lukashenko said Sunday, reports TASS.
He noted that the rigid sanctions imposed bythe western countries are worse than war.
"In a situation like this, we should be aware that there are such sanctions. A great deal is being said about the banking sector. Gas, oil, SWIFT. It's worse than war."
"This is the problem they are addressing. They have gone as far as war," the Belarusian leader said.
The US President said that no sanctions are immediate. "But I think these sanctions, I know these sanctions are the broadest sanctions in history, and economic sanctions and political sanctions," Biden said.
"Russia will pay a serious price for this short term and long term, particularly long term," the US leader stressed.
Countersanctions for the West
Lukashenko warned that Minsk and Moscow would take very panful sanctions against the West.
"Our sanctions, to be taken by Russia and Belarus, will be very panful These mechanisms have already started working. If need be, we will be building up these measures, but not to our own detriment," the Belarusian leader said.
He warned that another iron curtain was about to fall.
On 24 February, Russian President Vladimir Putin said in a televised address that in response to a request by the heads of the Donbass republics he had made a decision to carry out a special military operation in order to protect people "who have been suffering from abuse and genocide by the Kiev regime for eight years." The Russian leader stressed that Moscow had no plans of occupying Ukrainian territories. Its objective is demilitarization and denazification of the country.
When clarifying the unfolding developments, the Russian Defense Ministry reassured that Russian troops are not targeting Ukrainian cities, but are limited to surgically striking and incapacitating Ukrainian military infrastructure. There are no threats whatsoever to the civilian population.
A number of countries, including the US, have declared tough sanctions against Russia. The US Department of Treasury has announced sanctions against Russian President Vladimir Putin, Foreign Minister Sergey Lavrov, Defense Minister Sergey Shoigu and Chief of General Staff Valery Gerasimov.
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Albert Einsteins WW3 quote is more relevant than ever, authenticity aside – HITC – Football, Gaming, Movies, TV, Music
Posted: at 7:58 pm
Albert Einstein is known for introducing the theory that E=mc2, but people all around the world are focusing on one of his more poignant quotes this week.
Einstein was well aware of the damaging effects of nuclear warfare and described his role in the development of the atom bomb as indirect.
However, his quote about what atrocities could come with World War Three remains a harrowing reminder of mankinds own scientific developments.
Einstein is often quoted as having said:
I know not with what weapons World War III will be fought, but World War IV will be fought with sticks and stones.
While the origin of the quote is often debated, the point still rings clear. The impact that nuclear war could have on the world is devastating, and this quote conveys that in such a short sentence.
If humans are around for a World War Four following a potential WW3, it is unlikely there will be anything left to fight with due to the magnitude and brutality of nuclear weapons.
In the 1920s, Einstein collaborated with Leo Szilrd to develop and patentan energy-efficient fridge. The pair eventually ended their partnership but stayed in touch.
In 1933, Szilrd discoveredthe nuclear chain reaction (the process that unleashes the energy locked in atoms to create explosions) and according to National Geographic became convinced that German scientists might be using current scientific developments to develop an atomic weapon.
He approached Einstein and asked him to help contact US President Franklin D. Roosevelt. So, Einstein drafted a letter to Roosevelt that warned of what might happen if the Nazis developed an atomic bomb before the United States.
In the letter Einstein advised that Roosevelt should fund an initiative to research atomic energy and wrote: It appears almost certain that [a nuclear chain reaction] could be achieved in the immediate future.
Two months after receiving Einsteins letter, the Roosevelt-appointedAdvisory Committee on Uraniummet for the first time. It was the predecessor of the Manhattan Project, the top-secret government project that eventually invented a working atom bomb.
When writing about the bombs development in a Japanese magazine in 1952, Einstein said: I was well aware of the dreadful danger for all mankind, if these experiments would succeed. I did not see any other way out.
The American Museum of Natural History explains that while Einsteins equation E=mc2 explains the energy released in an atomic bomb it did not explain how to build one.
The scientist often reminded people: I do not consider myself the father of the release of atomic energy. My part in it was quite indirect.
When asked by a Japanese magazine editor why he cooperated in the production of atomic bombs, Einstein reaffirmed that his only act had been to write to Roosevelt.
However, in an interview withNewsweekmagazine, Einstein said: Had I known that the Germans would not succeed in developing an atomic bomb, I would have done nothing.
In other news, Explained: Who are Chechen people and where is Chechnya
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How to cope with threat of WW3? Hopefully these memes will helpa bit – The London Economic
Posted: at 7:58 pm
Britain will hit five Russian banks and three wealthy individuals with sanctions, Boris Johnson announced under a first barrage of punitive measures ahead of a feared full-scale invasion of Ukraine. But
The Prime Minister described on Tuesday the troops being sent by Vladimir Putin into the Donbas region under the guise of being peacekeepers as a renewed invasion of Ukraine.
He said the Russian President is establishing the pretext for a full-scale offensive as he warned this could include the capture of the capitol Kyiv by the nearly 200,000 troops amassed on Ukraines borders.
Mr Johnson told the Commons immediate sanctions would be deployed against the Russian banks Rossiya, IS Bank, General Bank, Promsvyazbank and the Black Sea Bank, as well as three very high net wealth individuals.
Any assets they hold in the UK will be frozen, the individuals concerned will be banned from travelling here and we will prohibit all UK individuals and entities from having any dealings with them, he told MPs.
This the first tranche, the first barrage, of what we are prepared to do and we hold further sanctions at readiness to be deployed.
Only one man knows the answer to that question: Vladimir Putin. He isnt exactly an open book.
He has made it clear he does not accept Ukraines right to independence and considers its land to be part of Russias imperial birthright.
Well will these sanctions be enough to stop Putin in his tracks? Id say its doubtful.
So are we facing WW3? Nobody wants it but it is a possibility.
Please dont panic, look at these memes, then maybe have a stiff drink. Thats what Im doing!
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Related: Watch: Reactions as Nigel Farage defends Russia & blames EU for invasion of Ukraine
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How to cope with threat of WW3? Hopefully these memes will helpa bit - The London Economic
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World War 3: Here is what would happen if a nuclear bomb dropped on Los Angeles during WW3 – Portsmouth News
Posted: at 7:58 pm
It was announced that it would be remaining at 100 seconds to midnight for 2022.
This is the closest to midnight the clock has ever been.
The countdown - a metaphor for global collapse - took into account dangerous threats posed by nuclear weapons, climate change, disruptive technologies and COVID-19.
While nuclear war remains extremely unlikely it could have a devastating impact.
Previously The News revealed that Portsmouth was one of the key Russian targets during the cold war along with many other cities across this country.
But what about targets in America could WW3 see Washington D.C. and other major cities targeted by missiles.
Russia continues to amass troops on the border with Ukraine, while President Biden announced that U.S troops were on standby to be sent to Eastern Europe in the case of an invasion.
NUKEMAP calculates the predicted number of fatalities and injuries that would be caused - based on the size of the bomb dropped on a city for this story we have selected the option of the bomb exploding as an airblast.
So if the Little Boy 15 kiloton bomb, which was dropped by the US on the Japanese city of Hiroshima in WW2, fell on Los Angeles which is the second largest city in the United States - it is estimated that 100,040 people would die and another 150,700 would be injured.
The fireball would have a radius of 180m, the air blast radius - which would severely damage buildings would be 340m and the radiation radius where death rates would be between 50% and 90% - would be 1.2km.
However the Little Boy' hasnt been used since WW2, so if a 800kt Topol nuke currently the largest in the Russian arsenal was used on L.A. it would be much more devastating.
With an estimated 582,880 fatalities and an estimated 1,454,320 people injured.
A message from the Editor, Mark Waldron
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World War 3: Here’s what would happen if a North Korean nuclear bomb dropped on Seoul in South Korea in WW3 – Portsmouth News
Posted: at 7:58 pm
It was announced that it would be remaining at 100 seconds to midnight for 2022.
This is the closest to midnight the clock has ever been.
The countdown - a metaphor for global collapse - took into account dangerous threats posed by nuclear weapons, climate change, disruptive technologies and COVID-19.
North Korea confirmed over the weekend that it had tested its biggest ballistic missile in years.
The launch of the Hwasong-12 intermediate-range ballistic missile (IRBM) was first reported by South Korean and Japanese authorities.
It is the seventh missile test carried out by the North Koreans this month.
Sky News reported that North Korea has previously said the Hwasong-12 can carry a large-size heavy nuclear warhead, and analysts estimate it has a range of 2,800 miles (4,500km).
But what if North Korea fired the missile at its regional rival South Korea?
NUKEMAP calculates the predicted number of fatalities and injuries that would be caused - based on the size of the bomb dropped on a city for this story we have selected the option of the bomb exploding as an airblast.
In this case Seoul, the capital and largest city in South Korea.
So if the North Korean weapon tested in 2013 which is 10kt it is estimated that 77,670 would die and 268,590 would be injured.
A message from the Editor, Mark Waldron
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What is the Doomsday Clock and what does it predict? Here’s all you need to know – Portsmouth News
Posted: at 7:58 pm
From appearing in the likes of Watchmen to inspiring a Linkin Park album in the mid-00s.
However you might be wondering what it actually is.
But what is the Doomsday Clock and can it predict World War Three?
Here's all you need to know:
What is the Doomsday Clock?
The Doomsday Clock is a symbol which represents the likelihood of a man-made global catastrophe.
It has existed since 1947 and is maintained by the members of the Bulletin of the Atomic Scientists' Science and Security Board.
During the cold war it was used as an analogy for the chances of global nuclear holocaust.
With midnight representing a global catastrophe and the minutes to midnight representing how close the world is to it.
While originally referring to a nuclear apocalypse - the Doomsday clock also now includes climate change as part of the global catastrophe.
What is the current minutes to midnight?
In January 2020, the clock was moved to 100 seconds to midnight and it remains at that level.
It was announced this week that it would be remaining at this level due to the dangerous threats posed by nuclear weapons, climate change, disruptive technologies and COVID-19
This is the closest the Doomsday Clock has been to midnight since 1953 - when the hands were also at 2.
The furthest it has been from midnight was 17 - following the fall of the Soviet Union and the end of the Cold War.
However the closest the world came to a Nuclear War was the Cuban Missile Crisis in 1962 - but that climax and resolved before the minutes could be changed.
Does the Doomsday Clock predict WW3?
No the clock isnt a predictor of the chances of World War Three just the Bulletin of the Atomic Scientists' Science and Security Boards belief of how close the world is to a global man-made catastrophe.
When deciding on the minutes to midnight for any given year they consider a wide range of factors which might include Politics, Energy, Weapons, Diplomacy, and Climate science.
With potential threats including nuclear threats, climate change, bio-terrorism, and artificial intelligence.
A message from the Editor, Mark Waldron
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What is the Doomsday Clock and what does it predict? Here's all you need to know - Portsmouth News
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Portsmouth named on hit list of Russia’s potential nuclear targets in the UK in World War 3 – Portsmouth News
Posted: at 7:58 pm
Explosions have been reported across the country through the night.
It comes days after Russia recognised two separatist regions in the east of Ukraine.
The invasion of the country by Russia could flare tensions between the nation and the west.
However of course despite this the chances of WW3 remain extremely slim although the Doomsday Clock, which tracks the possibility of the end of the World, is at two minutes to midnight, the closest approach to midnight, matching that of 1953.
The News previously revealed a hit list of Russian targets in the UK in the event of a nuclear attack from the Soviet Union during Cold War.
Cold War predictions drawn up in secret by the British government reveal the extent of a Russian nuclear strike on the UK.
Portsmouth's Naval Base was on the list of target.
At the height of nuclear tensions in the 1970s and 80s, at least 38 towns and cities were feared to be at risk from a strike from the Soviet Union and Portsmouth was one of the key targets.
Dozens of army, navy and air force bases were also earmarked for destruction, with Portsmouth Naval Base topping the list of strategic targets.
The city is home to a majority of the Royal Navys fleet, as well as the Senior Services HQ where much of its top brass are located.
Bases in nearby Gosport and Fareham also house thousands sailors.
Russian President Vladimir Putin has previously made no secret of the fact he is willing to use nukes and relations between the UK and Russia have reached new lows over the poisoning of Sergei Skripal as fears of a new Cold War grow.
UK defence officials drew up a list of 106 locations they believed were a target for Russia marking them as probable nuclear targets.
Alongside these major population centres were 23 RAF bases, 14 USAF bases, 10 radar stations, eight military command centres, and 13 Royal Navy bases.
It is not known if the list of probable targets has changed since the Cold War.
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Responsible Artificial Intelligence Is Still Out Of Reach For Many Organizations – Forbes
Posted: at 7:57 pm
Time for AI proponents to step up..
Theres strong support for analytics and data science and the capabilities it offers organizations. However, the people charged with developing analytics and artificial intelligence feel resistance from business executives in getting fully on board with data-driven practices. In addition, efforts to ensure fairness in AI are lagging.
Thats the word from a recent study of 277 data managers and scientists out of SAS, which finds that overall, more than two-thirds were satisfied with the outcomes from their analytical projects. At the same time, 42% say data science results are not used by business decision makers, making it one of the main barriers faced.
A lack of support from above is cited as the leading challenge to getting data analytics initiatives off the ground, the survey shows. Data quality issues ranked second, followed by lack of adoption of the results by decision-makers. Its interesting that explaining data science to others is also seen as a challenge, suggesting that a big part of managers jobs needs to be evangelizing and educating their business counterparts on the benefits data analytics can deliver to their organizations, and how to do it right.
Here are the leading challenges to becoming more data-driven in todays environments:
Managers are generally more satisfied with the companys use of analytics compared to individuals; however, individuals seem more satisfied with the outcome of analytics projects, the studys authors state. That difference echoes the possible difference between satisfaction with their own projects outcomes versus how theyre deployed, and that data science as a whole is more than siloed, individual efforts.
The study also tackled the question of delivery of ethical and unbiased AI. A substantial segment of companies in the survey, 43% do not conduct specific reviews of their analytical processes with respect to bias and discrimination. And only 26% of respondents indicated that unfair bias is used as a measure of model success in their organization. The top two roadblocks were a lack of communication between those who collect the data and those who analyze it, and difficulty in collecting data about groups that may be unfairly targeted.
The studys authors recommend working to make data science a team sport in organizations, and to make an effort to provide data managers and scientists a more active role in the organization. They also urge managers and executives to get more proactive about responsible AI. Get started with your own project and find ways to add in the means to detect and measure bias, they advise. Document your work and present it to management. Sometimes a working example of success is whats needed to get started theres no reason it cant be your work that sparks the beginning.
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Responsible Artificial Intelligence Is Still Out Of Reach For Many Organizations - Forbes
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Using artificial intelligence to find anomalies hiding in massive datasets – MIT News
Posted: at 7:57 pm
Identifying a malfunction in the nations power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated sensors spread across the U.S. capture data on electric current, voltage, and other critical information in real time, often taking multiple recordings per second.
Researchers at the MIT-IBM Watson AI Lab have devised a computationally efficient method that can automatically pinpoint anomalies in those data streams in real time. They demonstrated that their artificial intelligence method, which learns to model the interconnectedness of the power grid, is much better at detecting these glitches than some other popular techniques.
Because the machine-learning model they developed does not require annotated data on power grid anomalies for training, it would be easier to apply in real-world situations where high-quality, labeled datasets are often hard to come by. The model is also flexible and can be applied to other situations where a vast number of interconnected sensors collect and report data, like traffic monitoring systems. It could, for example, identify traffic bottlenecks or reveal how traffic jams cascade.
In the case of a power grid, people have tried to capture the data using statistics and then define detection rules with domain knowledge to say that, for example, if the voltage surges by a certain percentage, then the grid operator should be alerted. Such rule-based systems, even empowered by statistical data analysis, require a lot of labor and expertise. We show that we can automate this process and also learn patterns from the data using advanced machine-learning techniques, says senior author Jie Chen, a research staff member and manager of the MIT-IBM Watson AI Lab.
The co-author is Enyan Dai, an MIT-IBM Watson AI Lab intern and graduate student at the Pennsylvania State University. This research will be presented at the International Conference on Learning Representations.
Probing probabilities
The researchers began by defining an anomaly as an event that has a low probability of occurring, like a sudden spike in voltage. They treat the power grid data as a probability distribution, so if they can estimate the probability densities, they can identify the low-density values in the dataset. Those data points which are least likely to occur correspond to anomalies.
Estimating those probabilities is no easy task, especially since each sample captures multiple time series, and each time series is a set of multidimensional data points recorded over time. Plus, the sensors that capture all that data are conditional on one another, meaning they are connected in a certain configuration and one sensor can sometimes impact others.
To learn the complex conditional probability distribution of the data, the researchers used a special type of deep-learning model called a normalizing flow, which is particularly effective at estimating the probability density of a sample.
They augmented that normalizing flow model using a type of graph, known as a Bayesian network, which can learn the complex, causal relationship structure between different sensors. This graph structure enables the researchers to see patterns in the data and estimate anomalies more accurately, Chen explains.
The sensors are interacting with each other, and they have causal relationships and depend on each other. So, we have to be able to inject this dependency information into the way that we compute the probabilities, he says.
This Bayesian network factorizes, or breaks down, the joint probability of the multiple time series data into less complex, conditional probabilities that are much easier to parameterize, learn, and evaluate. This allows the researchers to estimate the likelihood of observing certain sensor readings, and to identify those readings that have a low probability of occurring, meaning they are anomalies.
Their method is especially powerful because this complex graph structure does not need to be defined in advance the model can learn the graph on its own, in an unsupervised manner.
A powerful technique
They tested this framework by seeing how well it could identify anomalies in power grid data, traffic data, and water system data. The datasets they used for testing contained anomalies that had been identified by humans, so the researchers were able to compare the anomalies their model identified with real glitches in each system.
Their model outperformed all the baselines by detecting a higher percentage of true anomalies in each dataset.
For the baselines, a lot of them dont incorporate graph structure. That perfectly corroborates our hypothesis. Figuring out the dependency relationships between the different nodes in the graph is definitely helping us, Chen says.
Their methodology is also flexible. Armed with a large, unlabeled dataset, they can tune the model to make effective anomaly predictions in other situations, like traffic patterns.
Once the model is deployed, it would continue to learn from a steady stream of new sensor data, adapting to possible drift of the data distribution and maintaining accuracy over time, says Chen.
Though this particular project is close to its end, he looks forward to applying the lessons he learned to other areas of deep-learning research, particularly on graphs.
Chen and his colleagues could use this approach to develop models that map other complex, conditional relationships. They also want to explore how they can efficiently learn these models when the graphs become enormous, perhaps with millions or billions of interconnected nodes. And rather than finding anomalies, they could also use this approach to improve the accuracy of forecasts based on datasets or streamline other classification techniques.
This work was funded by the MIT-IBM Watson AI Lab and the U.S. Department of Energy.
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