Please queue here: UK parliament votes on ending special #Coronavirus measures

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British lawmakers will form a long queue snaking through parliament today (2 June) to decide whether to ditch the system of remote voting and parliament-by-videoconference that has allowed scrutiny of the government’s coronavirus response, writes William James in London.

In April, the House of Commons announced changes that allowed its 650 lawmakers to question ministers by video link, and in May the house held its first remote vote – casting aside centuries of tradition in a building known worldwide for adversarial debates and arcane procedures.

The system was temporary, and despite functioning as planned, ministers said it should be scrapped when parliament returned on June 2 from a scheduled break, because it did not allow enough scrutiny and was slow at processing legislation.

On Tuesday lawmakers will decide on the new system of voting – by holding a vote in which they will line up, two metres apart, in a queue expected to snake out of the debating chamber, down ornate hallways and into an 11th century hall where kings and queens have lain in state.

“It is not perfect, it will take time, and members will need to be patient. But it is the safest method I can think of,” Commons Speaker Lindsay Hoyle said.

Political rivals have decried the end of the hybrid parliament, saying it will disenfranchise those who cannot attend for medical reasons and could spread the infection as lawmakers travel in and out of London.

Tuesday’s vote could spark a rebellion within Prime Minister Boris Johnson’s Conservative Party among those who want to keep some elements of the hybrid parliament. Lawmakers will vote on rebel plans which could allow remote voting or videoconferencing to continue.

The government, however, is pushing for an end to the special arrangements.

“Westminster has been the seat of our democracy for centuries. It will take more than the coronavirus to change that,” Jacob Rees-Mogg, the government’s leader in the House of Commons, said in The House magazine.

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Ex-RNC Chair: Trump ‘Does Not Believe In The Ideals Of This Country’

Michael Steele, the former chair of the Republican National Committee, on Monday hammered President Donald Trump’s lack of leadership amid the national crises of the coronavirus pandemic and the protests that have erupted following the death of George Floyd.

Steele, appearing on MSNBC’s “Deadline White House,” suggested that “for some reason, there’s still this expectation that Donald Trump in a moment like this is going to respond” like his predecessors, such as Barack Obama.

Instead, Steele noted, “you have is a president who retreats to his bunker out of fear of what? I don’t know.” (Trump was reportedly rushed to an underground bunker on Friday as anti-racist protests took place in Washington, D.C.)

“He doesn’t step into that leadership, he repels from it and yet we still expect him to behave differently,” said Steele, who was chair of the RNC from 2009 to 2011.

“This president has shown us who he is,” he added. “He has told us over and over again what he believes. He does not believe in the ideals of this country.”

Check out Steele’s comments below:

A HuffPost Guide To Coronavirus



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All you need to know about symbolic artificial intelligence

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Today, artificial intelligence is mostly about artificial neural networks and deep learning. But this is not how it always was. In fact, for most of its six-decade history, the field was dominated by symbolic artificial intelligence, also known as “classical AI,” “rule-based AI,” and “good old-fashioned AI.”

Symbolic AI involves the explicit embedding of human knowledge and behavior rules into computer programs. The practice showed a lot of promise in the early decades of AI research. But in recent years, as neural networks, also known as connectionist AI, gained traction, symbolic AI has fallen by the wayside.

The role of symbols in artificial intelligence

Symbols are things we use to represent other things. Symbols play a vital role in the human thought and reasoning process. If I tell you that I saw a cat up in a tree, your mind will quickly conjure an image.

We use symbols all the time to define things (cat, car, airplane, etc.) and people (teacher, police, salesperson). Symbols can represent abstract concepts (bank transaction) or things that don’t physically exist (web page, blog post, etc.). They can also describe actions (running) or states (inactive). Symbols can be organized into hierarchies (a car is made of doors, windows, tires, seats, etc.). They can also be used to describe other symbols (a cat with fluffy ears, a red carpet, etc.).

Being able to communicate in symbols is one of the main things that make us intelligent. Therefore, symbols have also played a crucial role in the creation of artificial intelligence.

The early pioneers of AI believed that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” Therefore, symbolic AI took center stage and became the focus of research projects. Scientists developed tools to define and manipulate symbols.

Many of the concepts and tools you find in computer science are the results of these efforts. Symbolic AI programs are based on creating explicit structures and behavior rules.

An example of symbolic AI tools is object-oriented programming. OOP languages allow you to define classes, specify their properties, and organize them in hierarchies. You can create instances of these classes (called objects) and manipulate their properties. Class instances can also perform actions, also known as functions, methods, or procedures. Each method executes a series of rule-based instructions that might read and change the properties of the current and other objects.

Using OOP, you can create extensive and complex symbolic AI programs that perform various tasks.

The benefits and limits of symbolic AI

Symbolic artificial intelligence showed early progress at the dawn of AI and computing. You can easily visualize the logic of rule-based programs, communicate them, and troubleshoot them.