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Killexams : AAFM Examination answers - BingNews https://killexams.com/pass4sure/exam-detail/GLO_CWM_LEVEL_I Search results Killexams : AAFM Examination answers - BingNews https://killexams.com/pass4sure/exam-detail/GLO_CWM_LEVEL_I https://killexams.com/exam_list/AAFM Killexams : Interview with Director of the Department of the Airforce-Artificial Intelligence

Colonel Tucker "Cinco" Hamilton is an Experimental Fighter Test Pilot and currently the Director of the Department of the Air Force – MIT Artificial Intelligence Accelerator. He has served his nation as an operational F-15C pilot, Air Liaison Officer, initial cadre of the MC-12 Intelligence gathering aircraft, F-35 program manager, F-35 test pilot/ commander, and Director of the only dedicated Artificial Intelligence unit in the Department of the Air Force. He has more than 2,000 flying hours in the F-35A/B/C, F-15C/D/E, MC-12W, F-18, F-16, A-10, T-38A/C, T-34, T-6, and 20 additional aircraft. In addition to his military service he is the founder and CEO of a 501(c)3 non-profit that runs a national high-school robotics competition called the Aerospace Robotics Competition. He currently lives near Cambridge, MA with his wife and four children.

What would be your definition of AI in this context, and how does it differ from machine learning? 

The DoD defines Artificial Intelligence as the ability of machines to perform tasks that normally require human intelligence. I think we can all agree that the DoD definition is vague and does not get to the heart of the discussion. In the same breath, I think we often spend too much time arguing over definitions. My personal opinion is that when AI is being discussed I treat it as if we are just speaking about Machine Learning. If it's an expert system, a rule-based system, a deterministic system, I think of it differently than Machine Learning. What most folks are speaking of when discussing AI is truly Machine Learning -- so I just make AI and ML synonymous. As for defining ML, I prefer to think of it as software code that rewrites itself based on data...that is it, simple and to the point.  

Where are we now in terms of AI (what is fact and. what is still fiction)? 

The fact is that AI/ML is already an integral part of our society. It is in the apps we use and numerous other systems we interact with. It is ubiquitous and here to stay. Every aspect of our culture has and will be influenced by software code that rewrites itself based on data. What else is fact, developing (i.e., training) an AI system is energy intensive and has a tremendous impact on our carbon emissions. Additionally, though most do not realize it, data are pouring off our systems and individuals yet most of that data are completely useless for ML purposes. Machine-ready data is what we need but going from data that are available to that data being useful can take years in data preparation.    

Here are some facts that counter certain fictional characterizations. AI is not self-aware, it is terribly narrow in how it can be applied, and it is brittle. For the first comment (which the second comment feeds into), it is mathematically impossible for AI to become self-aware anytime soon. We waste precious time drumming up concerns for a future that is highly unlikely and distant. I will confess that we may tap into currently unknown mathematical solutions when we combine bio-computing, quantum, and AI; but in the current state we must face a world where AI is already here and transforming our society. AI is also very brittle, i.e., it is easy to trick and/or manipulate. We need to develop ways to make AI more robust and to have more awareness on why the software code is making certain decisions – what we call AI-explainability. I also feel that we are too often hoping for and wanting exquisite AI solutions for grand problems. Rather, we should focus on narrow applications to tackle repeatable processes with measurable outcomes. 

What has enabled the greater interest in AI in the fighter domain? Why now? 

AI/ML in the fighter domain can be an impactful tool if it is used to power-systems that ultimately team with an operator. Standing on the shoulders of autonomous systems like Automatic Ground Collision Avoidance and Automatic Air Collision Avoidance, operators have developed trust in autonomy. While AI is not autonomy, it can be an exquisite expression of autonomy. AI can provide an operator the needed awareness of the world around them. I think of AI being useful in three distinct increasingly complex ways: descriptive, predictive, and prescriptive. All three are aspects of the fighter domain. We want to understand the data and allow AI to help paint the picture of what happened. We want to be able to use the data to predict what will happen. Finally, we want AI to provide recommendations on what we should do about it. And now to get to your question, there is greater interest because the operators have trust in autonomy, and we have the data and compute power to do something beyond simple autonomy and can now provide AI-powered capability into the cockpit.  

How does AI fit into the Fighter Generation transformations, from 4th to 5th to possibly 6th? 

Fighter aircraft need AI-powered systems to help accomplish tasks. Those tasks vary widely with certain tasks being most important for 4th generation while other tasks best for 6th generation. What it comes down to is that each platform could possibly adopt AI-powered capability. The most compelling will come in the form of human-machine teaming; AI-powered systems providing prescriptive input to targeting, maneuvering, task management, and unmanned partnerships. This could be coupled with autonomous maneuvers as well. Though we are still a way from each of these aspirations, the potential is ready to be developed. 

How does applying AI to fighters help in achieving multidomain superiority?   

Multi-domain superiority is a great way to frame the conversation. Air superiority no longer holds sway when discussing the multi-faceted and intertwined battlefronts. Getting AI into our fighters will, without a doubt, increase capability for our fighter aircraft, however and more importantly, the real-time data coming off our fighter aircraft will inform and shape our land, sea, air, and space systems. The digital ecosystem will be the difference between success and failure.  

Generally speaking, what would an AI-infused air force look like? How would it operate, train, and be maintained? 

It may not sound as alluring as our pop-culture would lead us to believe. An AI-infused air force is first and foremost an interconnected force founded on a strong digital and data architecture. We need systems that can gather data in a machine-readable format and seamlessly share that data. This includes training our operators, maintainers, logisticians, industry partners, etc. on the basics of AI/ML. Since AI is best used in narrow applications, I foresee the initial use cases focused on low-risk tasks with measured outcomes. Operating a system like this requires understanding limitations. Training a system like this requires appreciating and mitigating for biased data in concert with ensuring the right subject matter experts are a part of the development. Maintaining an AI-powered system requires an iterative cycle of evaluation and updates. As data “rewrites” the code we need to ensure that the code does not adopt sub-optimal behavior. 

What would this mean for the fighter maintenance industry? 

I sense that this question is coming from a traditional maintenance mindset. Maintaining AI is different than AI impacting maintenance. Addressing the latter, AI has already proven a remarkable differentiator for preventative maintenance. This will continue to be true and expand further to allow our maintainers and logisticians to primarily conduct routine preventative measures vice troubleshooting discovered faults. The challenge for military maintainers is not allowing their responsive maintenance skills to atrophy. For the military this type of skill is essential because of the likelihood of combat damage undermining the best preventative maintenance software. 

How will AI change the mission envelope of fighters? 

It is well agreed to that the limiting factor in a fighter aircraft is the human. There is nothing stopping an aircraft from pulling 20 Gs except the “meat-servo” (human) not being able to. With the adoption of autonomy and unmanned systems the flight envelopes will change to maximize performance. As for AI shaping that change, I think it will play hand-in-hand with autonomy. I.e., I do not think AI will be the driver but rather autonomy. Now the mission envelope is a different story. Fighter aircraft may be more capable all-around, but I am not sure that is the best way to think about it. Our future fighters, think beyond 6th generation, will probably not be robust masters-of-all type vehicles. I think unmanned systems that are simpler may prove more beneficial. The way military aviation unfolds in the next decade will really redefine what this looks like.  

Is putting AI on a combat jet a progression or revolution? 

Getting AI into the combat will simply be a progression…for now. As mentioned earlier, we cannot focus on grand AI solutions. AI simply does not work that way. We need baby-step AI-powered capability and grow from there. We simply do not have the digital foundation and/or data architecture to do anything but small, focused, narrow AI applications. In the end AI will prove to be the game changer for our society, but we need the foundational stuff first to make that a reality.  

How do you envision Manned-Unmanned Teaming for upcoming fighter programs? 

Manned-Unmanned teaming is very exciting. It is exactly what we need to be focused on, but it is also very challenging. Humans are not good at multi-tasking, yes, I am also talking to fighter pilots. We may think we are but trying to maintain overall situational awareness is nearly impossible. Finding the sweet spot of providing the right information at the right time with easily discernable decisions is key. The user interface is what we should be focused on. This type of teaming is a force multiplier, but it will require a lot of thoughtful conversations. When you begin discussing this type of effort you need to understand that lethal autonomy is an aspect of this future. How will we manage the moral implications and the technical backdrop powering and coding those moralities? It needs to begin with understanding our systems and their limitations. Starting small and building trust while ensuring our democratically elected leaders help shape a battlespace that is forced to deal with this future. We may never want to address this type of lethality, but I ensure you that our adversaries are already preparing to exploit lethal autonomy.   

 In brief terms, how will this change the way we fight? 

  Just look at how it is changing tactics on the front in Ukraine. Unmanned systems have such an important role to play, and our tactics and strategy must address this transformative step in military capability.   

Where do you feel the industry has been lacking in terms of AI for fighters? What would you suggest? 

Industry is leading the government in many ways regarding AI. Ultimately though, our industry partners need to deliver machine-ready data. That is step one. We can no longer afford the time or money to cleaning data for use by AI. If our governments placed more emphasis on industry delivering machine-ready data we would all benefit. With this change we need to address the legal and proprietary aspect of data. Some business models are based on the data being collected. The government garnering full government-purpose rights on that data could pose a threat to those companies unless we devise ways to protect their IP. It requires our lawyers, contracting and acquisition professions to understand AI/ML and then define and implement best practices. I have long said that our key for an AI-powered military must go through acquisition, contracting, and legal. 

If you could deliver one message to governments concerning AI, what would it be? 

AI is not a nice to have, AI is not a fad, AI is forever changing our society and our military. We must act with urgency to address this future. The threats we face are not just at our door, they are inside our house. AI is a tool we must wield to transform our nations…or, if addressed improperly, it will be our downfall.  

Sun, 07 Aug 2022 12:00:00 -0500 en text/html https://www.defenceiq.com/air-forces-military-aircraft/reports/interview-with-director-of-the-department-of-the-airforce-artificial-intelligence
Killexams : WBJEEB ANM GNM Final Answer Key 2022 Out on wbjeeb.nic.in; Result Expected Soon

WBJEEB ANM GNM Answer Key 2022: The West Bengal Joint Entrance Examinations Board(WBJEEB) has released the final Answer key for the West Bengal Auxiliary Nursing and Midwifery (ANM) course and General Auxiliary Nursing and Midwifery(GNM)course on July 25, 2022. Registered candidates can download the WBJEEB ANN GNM Answer Key 2022 through the official website of the Board at wbjeeb.nic.in. Now the final answer key has been released, the Board will soon release the WBJEEB ANM GNM Result 2022.Also Read - MPSOS Result 2022: MP 10th 12th Results Declared For Ruk Jana Nahi Yojana; Here's Direct Link

WBJEE in its official statement said, “The final answer keys, after thorough post-examination internal review and review of candidates’ challenges received are given below. Scoring and ranking of all candidates will be done based on these final answer keys, ” WBJEEB in an official notification said. Also Read - Odisha OJEE Result Declared at orissaresults.nic.in, Steps to download Rank Card Here

How to download WBJEEB ANM, GN, Answer Key 2022?

  • Visit the official website of the West Bengal Joint Entrance Examinations Board at wbjeeb.nic.in.
  • On the homepage, click on the link that reads, “Final Answer Keys of GNN and ANM.”
  • To check your rank, click on “View/Download Rank Card For ANM(R) & GNM 2022.
  • A new PDF document will open on the screen.
  • Download the WBJEEB ANM GNM Answer Key 2022 and take a printout of it for future reference.

Why is ANM(R) & GNM-2022 Conducted?

WBJEEB will conduct OMR-based Common Entrance Test ANM(R) & GNM-2022 for admission in various Colleges/ Institutes in the State of West Bengal for the academic session 2022-23 into two (2) years’ Auxiliary Nursing & Midwifery (Revised) course and three (3) years’ General Nursing & Midwifery course. Also Read - CHSE Odisha Plus 2 Science, Commerce Results Declared; Check Pass Percentage, Alternate Ways to download Marksheet

Tue, 26 Jul 2022 22:58:00 -0500 en text/html https://www.india.com/education/wbjeeb-anm-gnm-answer-key-2022-out-west-bengal-auxiliary-nursing-and-midwifery-anm-gnm-result-expected-soon-at-wbjeeb-nic-in-5538220/
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