US 2017 Defense Budget Proposal to Include Billions for Next-Generation Weapons Research

[F-22Raptor]

The Obama administration's 2017 budget proposal will include up to $15 billion to advance the Defense Department's “third offset strategy,” Deputy Secretary of Defense Robert Work said Dec. 14 in Washington, D.C.

The Pentagon’s new strategy, unveiled last year, is focused on developing new technologies and operating concepts that will offset the growing conventional military capabilities of potential adversaries such as Russia and China.

“It’s going to rely initially on wargaming, experimentation and demonstrations,” Work said at a conference hosted by the Center for a New American Security. The Defense Department will likely spend $12 billion to $15 billion in fiscal year 2017 on these activities, he said.

The administration is set to release its fiscal year 2017 budget proposal the first week of February.

Defense Department leaders are hoping to lay the groundwork for future advances in the third offset strategy so it will survive after Obama administration officials leave office, Work said.

“A successful offset strategy will go from administration to administration, so for the next year we are focused on doing the intellectual underpinning and doing as much of the demonstration work as we possibly can so that Congress will help us keep this going,” Work said. “I will argue that when you look back between ’16 and ’17, there were a lot of technological bets that allow us” to push it forward.

A key focus of the work will be proving out the five “building blocks” of human-machine collaboration that the Pentagon hopes to exploit as the autonomy and artificial intelligence fields advance, he said.

One of those building blocks is autonomous “deep learning systems” that can analyze large amounts of data, improve indications and warning, and deal with incoming threats. For example, “You cannot have a human operator operating at human speed fighting back a determined cyber attack,” Work said. “You’re going to have to have a learning machine that does that.”

A second pillar is “human-machine collaboration” to improve decisionmaking. The cutting edge helmet for the F-35 joint strike fighter is an example of such teaming, because it provides “360 degrees of information” to pilots by piping images outside the plane to their advanced helmet displays, Work said.

A third area of interest is “assisted human operations.” One such tool could be exoskeletons similar to the “Iron Man suit” that U.S. Special Operations Command is developing to improve the physical capabilities of its commandos, Work said.

A fourth component being looked at is “human-machine combat teaming,” such as having a commander direct a swarm of unmanned aerial vehicles against enemy forces, he said.

A fifth area of investment is “network enabled semi-autonomous weapons” that could continue to operate in the face of cyber and electronic warfare attacks on communication systems and technologies such as GPS, he said.

The Defense Department is preparing to flesh out these high tech concepts in fiscal year 2017, he said.

“What you’re probably going to see is closer to the order of [$12 billion to $15 billion spent] on wargaming, experimentation and demonstrations to verify that our hypothesis on these five components is sound,” Work said.

2017 Budget Proposal to Include Billions for Next-Generation Weapons Research - Blog

 

[F-22Raptor]

These Are the Decisions the Pentagon Wants to Leave to Robots

It’s a “wonderful time” to be a military scientist, where the next big leaps will depend on rapid advances in machine learning, artificial intelligence, and computer science — but the Pentagon needs to catch up to private industry, says deputy defense secretary Robert Work.

“The commercial world has already made this leap. The Department of Defense is a follower,” Work told the audience at a national security forum co-hosted by the Center for a New American Security and Defense One.

Yet the the development of new artificial intelligence and autonomy capabilities is key to the Pentagon’s third offset strategy, a research effort intended to endow the United States with strategic advantage over her adversaries. In his talk, Work cleared up several of the mysteries surrounding the third offset strategy, including: Just what does the military want robots to take over for humans? Here are a few areas Work highlighted.

Cuing intelligence analysts about what to pay attention to. Machine learning systems looking through volumes of data to find weak signals of social change could provide early indicators of danger or unrest, deserving analyst attention. “The AI guys say that what’s happening in the grey zone with the little green men is nothing more than a big data analytics problem,” Work said. He spoke of a National Geospatial Intelligence program called Coherence Out of Chaos, which could “cue human analysts” to take a look at different situations as those situations evolve on the ground. “It will do so in situations that require faster than human reaction,” he said.

Conducting cyber defensive operations, electronic warfare, and over-the-horizon targeting. “You cannot have a human operator operating at human speed fighting back at determined cyber tech,” Work said. “You are going to need have a learning machine that does that.” He did not say whether the Pentagon is pursuing the autonomous or automatic deployment of offensive cyber capabilities, a controversial idea to be sure. He also highlighted a number of ways that artificial intelligence could help identify new waveforms to improve electronic warfare.

Semi-autonomous weapons could act when humans might be too slow, such as aerial defense, or when communications were degraded. “We believe strongly that humans should be the only ones to decide to when use lethal force. But when you’re under attack, especially at machine speeds, we want to have a machine that can protect us.” He cited the Israeli Iron Dome air-defense system as an example.

Telling F-35 pilots what to point and shoot at… “Human-machine collaboration and decision-making” is another one of the core components of the offset strategy, as exemplified by the Rockwell Collins F-35 helmet, which provides a dynamic display to the pilot in real time. “360 degrees of information is being crunched by the machine and being displayed in an advanced way,” he said.”It can simplify the speed of operations by allowing the humans to make better decisions faster.”

…and how to fly and land. Assisted human operations is another key component of the AI-heavy offset strategy. Work cited the Aircrew Labor In-Cockpit Automation System, or ALIAS, which takes some of the decision-making away from the pilot. It was, he said, “A system designed to reduce the number of crew in the cockpit at any time.”

Flying drones and driving boats. Work defined human-machine combat teaming as a human working with an unmanned aerial vehicle, or UAV, to conduct operations. “The Army’s Apache and Gray Eagle UAV are designed to operate together. The P-8 [Poseidon] and [MQ-4C] Triton UAV work together,” he noted. “We are looking at a large number of very, very advanced things.” He cited recent programs that would deploy cascades of small drones from larger drone “motherships,” (a DARPA program called Gremlins), swarming boats (an Office of Naval Research program), and efforts to allow a single human operator to direct a wide number of drones (as opposed to several crewmembers operating one drone, which is the state today, part of an Air Force effort called the Vigilant Spirit Control Station).

Many of these AI aids and capabilities would be backed by a fast-learning system that collects, processes, and disseminates information to help commanders make better decisions. He described it as a “learning network.” It would not replace humans but vastly accelerate the collection and dissemination of relevant data and commands to more machines and humans on the battlefield.

“If we launch seven missiles at a surface action group and one missile goes high, and is looking at all the different things that the battle group is doing to defend itself and it sees something new that’s not in its library, it will immediately report back on the learning network, which will go back to a learning machine, which will create ‘here’s something you should do’ which will pass it over to human machine collaboration—so the mission commander can make an adjustment on the next salvo and then make a command change inside the software of the missile so that the next seven missiles launch will be that much more effective,” he said.

There’s “a lot of skepticism right now inside the department of defense that we will be able to perfect and protect such a network,” Work said. “But if you do the smart design up front, coupled with learning defenses. It is not only possible but it is a requirement.”

These Are the Decisions the Pentagon Wants to Leave to Robots - Defense One

 

[C130]

electronic warfare R&D should have the highest priority

slashing or canceling spending on ABM research should happen.

would free up a lot of money for things we actually need to get.

 

[GR!FF!N]

One of those building blocks is autonomous “deep learning systems” that can analyze large amounts of data, improve indications and warning, and deal with incoming threats. For example, “You cannot have a human operator operating at human speed fighting back a determined cyber attack,” Work said. “You’re going to have to have a learning machine that does that.”

 

[raktaka]

They are building "Terminator" AND "Skynet".

This is the first generation "Terminator". The subsequent generations will have a life of its own.

“assisted human operations.” One such tool could be exoskeletons similar to the “Iron Man suit” that U.S. Special Operations Command is developing to improve the physical capabilities of its commandos.

AND Skynet,

“deep learning systems” that can analyze large amounts of data, improve indications and warning, and deal with incoming threats.

“You cannot have a human operator operating at human speed fighting back a determined cyber attack,” Work said. “You’re going to have to have a learning machine that does that.”

“network enabled semi-autonomous weapons” that could continue to operate in the face of cyber and electronic warfare attacks on communication systems and technologies such as GPS



The Beginning of the End.