AI News, Michael Klare

2020 Budget Request Reveals Slow Shift Toward Great PowerWar

If there’s been one theme at the Pentagon since Donald Trump became president, it’s a desire to move fast, particularly when it comes to buying new weapons.

But it will take much more time to mature new technologies and shift funding away from today’s expensive weapons projects, which are strongly supported in Congress, to a new portfolio including killer lasers, hypersonic missiles and new generations of ships, combat vehicles and warplanes.

The Army is cutting or canceling 93 weapons, vehicle, aircraft, and other projects over a five-year spending period, know as the Future Years Defense Plan, or FYDP, so that Army officials can shift money into projects deemed critical to winning future wars.

“We’re trying to hone in on the exact number of requirements of vehicles and that’s why the [JLTV] buy will be truncated over time.” Big Tech Items Trump is asking Congress for a bit more money for next-generation weapons of use in a potential war with China and Russia.

The 2020 budget proposes a nearly 9 percent increase in the Pentagon’s research and engineering budget, which came in at $104 billion, or roughly $9 billion more than last year.

That technology gets a bump in investment to $2.6 billion, up from about $2.4 billion enacted last year, said Michael White, assistant director for hypersonics. But the actual ask is some $10 billion over the next five years.

 Meanwhile, the Missile Defense Agency is asking for $157 million to develop satellites to better track and defend against enemy hypersonics (also part of the $2.6 billion request.) One big item that stands out is $3.7 billion for “unmanned autonomous new tech.” That could include everything from next-generation fighter drones that fly alongside aircraft to new robot submarines.

They figure heavily into the Pentagon’s expectations for future wars that will increasingly be fought by robots operating in environments that are thick with electromagnetic interference and missiles, and so will have to operate highly autonomously.

There’s $671 million for “unmanned carrier aviation” — read that to mean the new Tactically Exploited Reconnaissance node, or Tern, drone and others — versus $519 million enacted last year.

But there’s a $1 billion request, versus $430 million enacted last year, for “next-generation air dominance,” which means so-called sixth-generation aircraft not yet in existence, in which pilots are optional.

The military will ask for $235 million in research into directed energy, which will include lasers and novel new technologies like neutral particle beams (energy moving slower than the speed of light,) and “implementing direct energy for base defense,” as well as scaling up high-power lasers and testing new ones.

GDPR and Financial Services – Imperatives and Conflicts

This is where techniques such as ML (machine learning) combined with massive amounts of data are providing useful results in narrow fields.

In these stories this system has spread to millions of computers and seeks to exterminate humanity in order to fulfil the mandates of its original coding.

In the short term, Narrow AI can be expected to evolve into Broad AI where a system will be able to support or perform multiple tasks using what is learnt in one domain applied to another.

Ethics is a set of moral principles that govern behaviour, or the conduct of an activity, ethics is also a branch of philosophy that studies these principles.

Social media provides an example of this kind of amplification where uncontrolled channels provide the means to share beliefs that may be popular but have no foundation in fact - “fake news”.

Allowing systems to train themselves can lead to unexpected outcomes since the systems do not have the common sense to recognize mischievous behaviour.

Explanation may be required to justify a life changing decision to the person that it effects, to provide the confidence needed to invest in a project based on a projection, or to justify after the event why a decision was taken in a court of law.

While rule-based systems can provide a form of explanation based on the logical rules that were fired to arrive at a particular conclusion neural network are much more opaque.

This poses not only a problem to explain to the end user why a conclusion was reached but also to the developer or trainer to understand what needs to be changed to correct the behaviour of the system.

the three laws of robotics that were devised by Isaac Asimov in the 1940’s and subsequently extended to include a zeroth law apply equally to AI systems.

For example, the hacking of an autonomous car could turn it into a weapon, which emphasizes the need for strong inbuilt security controls.

This makes it essential to create protection for those affected by the expected downsides to improve acceptability and to avoid social unrest.

This is where techniques such as ML (machine learning) combined with massive amounts of data are providing useful results in narrow fields.

In these stories this system has spread to millions of computers and seeks to exterminate humanity in order to fulfil the mandates of its original coding.

In the short term, Narrow AI can be expected to evolve into Broad AI where a system will be able to support or perform multiple tasks using what is learnt in one domain applied to another.

Ethics is a set of moral principles that govern behaviour, or the conduct of an activity, ethics is also a branch of philosophy that studies these principles.

Chris Rees identified 5 major ethical issues that need to be addressed in relation to AI: Bias is a very current issue with bias related to gender and race as top concerns.

Social media provides an example of this kind of amplification where uncontrolled channels provide the means to share beliefs that may be popular but have no foundation in fact - “fake news”.

Allowing systems to train themselves can lead to unexpected outcomes since the systems do not have the common sense to recognize mischievous behaviour.

Explanation may be required to justify a life changing decision to the person that it effects, to provide the confidence needed to invest in a project based on a projection, or to justify after the event why a decision was taken in a court of law.

While rule-based systems can provide a form of explanation based on the logical rules that were fired to arrive at a particular conclusion neural network are much more opaque.

This poses not only a problem to explain to the end user why a conclusion was reached but also to the developer or trainer to understand what needs to be changed to correct the behaviour of the system.

the three laws of robotics that were devised by Isaac Asimov in the 1940’s and subsequently extended to include a zeroth law apply equally to AI systems.

This makes it essential to create protection for those affected by the expected downsides to improve acceptability and to avoid social unrest.

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