Arrow AI is an artificial intelligence company that specializes in making life more efficient and cost-effective. We are firm believers in the simple fact that Arrow can help any individual. Regardless of the project, Arrow will utilize unique machine learning and it's infinite knowledge engine in order to meet your every need. Arrow AI was founded late 2017 as a startup company hoping to make a difference. After developing the necessary technology, we now have the capability to deliver on our promise of making everyday people's lives better in many ways. Find out how by clicking here.
Creators of Arrow AI
Close As superintelligent AI becomes a reality, most researchers believe that it is unlikely the AI will ever be able to genuinely exhibit emotions like love and hate, because of this there is no reason to expect AI to become intentionally benevolent or malevolent. Instead, AI might have other ways of becoming a risk. Two scenarios are most likely.
- AI is programmed to do something devastating: Autonomous weapons are created with artificial intelligence, and these systems are programmed to kill. In the hands of the wrong person, these weapons could be devastating leading to mass casualties. With multiple AIs in the hands of different people could also inadvertently lead to an AI war that also results in mass casualties. These systems would be programmed to be very difficult to "shut off" to keep the enemy from turning them off, because of this humans could plausibly lose control of the situation. This risk is present even with narrow AI, and as AI increases in autonomy and intelligence so does the risk.
- AI is programmed to do something beneficial, but it develops a destructive method to achieve that goal: An AI can develop destructive methods when people fail to fully align the AI's goals with our goals, which is strikingly difficult. If you ask an obedient intelligent car to take you to the airport as fast as possible, it could end up being chased by helicopters after running over pedestrians, doing what you wanted but not literally what you asked for. If a superintelligent system is tasked with a geoengineering project, it could end up wreaking havoc on our ecosystem as a side effect, and view humans trying to stop it as a challenge to be met.
These examples illustrate concern for the AI's competence, not its malevolence. An AI will be extremely good at accomplishing its goals, but if its goals aren't exactly the same as ours, we will have a problem. For example, you're probably not a horrible ant-hater who steps on ants out of malice every chance you get, however, if you're in charge of a hydroelectric green energy project and there's an ant hill in the region to be flooded, too bad for the ants. The main goal of our AI development team is to never put humans in the ant's positions.
AI won't wake up one day and immediately see humans as a threat to be eliminated. This is because it is very unlikely that humans will ever create a truly alive and sentient AI, instead, the AI will follow set parameters to meet a goal. In the process to reach its goal the AI could do things that humans don't agree with, if it was tasked with lowering pollution levels the AI could see the fastest way to stop pollution from rising is to stop the producers of pollution, aka humans. All of these risks can be dealt with and mitigated through thorough tests and research.
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Aviation
The use of Arrow in the Air Operations Divisions (AOD) is mainly for simulations. AI can simulate enemy operators in combat training simulators, mission management aids, post-processing of simulator data into statistics, and supports systems for tactical decision making.
The use of Arrow in the AOD is already proving to be very useful. Airplane simulators utilize Arrow to process the data taken from simulated flights into useful numbers. Arrow can also help come up with the best success scenarios and maneuvers in aircraft warfare simulations. Utilizing these scenarios Arrow is able to come up with strategies based on the size, placement, speed, and strength of the enemy forces as well as the AOD's forces. Arrow can then assist pilots during air combat by providing them with the best possible maneuvers, as well as eliminating maneuvers that would be impossible for a human to perform. Multiple aircraft are needed to get good approximations for some calculations, Arrow allows simulated pilots rather than real ones to be used to get the data. These computer simulations are also used to train future air traffic controllers.
The AOD also uses Arrow for speech recognition software. The air traffic controllers (ATC) give commands to the simulated pilots and the pilots are supposed to give responses back. These programs that incorporate speech software must be trained through repeated uses, which means that they use neural networks. The continued use and improvement of Arrow is imperative in situations with speech recognition because ATCs use very specific dialog and the software needs to be able to communicate correctly and promptly every time.
Arrow has also been incorporated to run on damaged aircraft. Arrow enables the damaged aircraft to continue to fly until it reaches a safe landing zone. Arrow compensates for the damaged components by relying on the undamaged components. Arrow utilizes a neural network in order to learn how best to optimize each aircraft's components.
Arrow has also been developed based on an Intelligent Autopilot System (IAS). Arrow acts as an IAS, this means that Arrow behaves like a highly experienced pilot who is faced with an emergency situation, such as severe weather, system failure, or turbulence. To develop this experience in Arrow supervised machine learning was used, this is where Arrow was treated as a human pilot going to a flying school. Once Arrow was deemed to have enough experience, it was given full control and overserved by the pilot as it executes the training exercises.
The Intelligent Autopilot System combines the principles of Behavioral Cloning and Apprenticeship Learning where the autopilot observes the low-level actions required to maneuver the aircraft and the high-level strategy used to apply those actions. IAS implementation employs three phases; pilot data collection, training, and autonomous control. With these strategies, Arrow creates an autonomous autopilot that assists pilots in responding to emergency situations.
Education
Arrow AI has been designed to help tutor students. Arrow can be utilized as an intelligent tutoring system, or ITS, for higher education. This educational system has been used to teach Air Force technicians to diagnose electrical system problems in aircraft. Arrow as also been used by to train Navy recruits in technical skills in a shorter time.
Arrow AI can not only help the students but the teachers. Since Arrow AI has advanced language processing and machine learning, it can be used for automatic grading of assignments as well as data-driven understanding of individual students needs. This automatic learning about students has led to Arrow being used as a Massive Open Online Course or MOOCs where students from around the world can learn about a multiplicity of different subjects. This large data pool of students also allows Arrow to utilize learning analytics to improve the quality of learning at a scale. Arrow AI helps students learn faster and better than traditional teaching.
Hospitals and Medicine
Arrow AI has potential in the medical field as well. Approximately twelve million adults are misdiagnosed every year in the US alone; Arrow AI with its advanced machine learning and neural network is able to look at diagnostic scans for a patient and correctly diagnose them with a higher success rate than professional doctors.
Arrow AI is also able to help with mining medical records to provide useful information, designing treatment plans, assisting with medication management, provide consultations, drug creation, and using an avatar in place of a patient for clinical training.
Human Resources and Recruiting
Arrow AI can be used for companies recruiting as well. There are three ways Arrow AI can be used by human resources and recruiting professionals. Arrow AI can be used to screen resumés to rank candidates according to their level of qualification. Through job matching platforms, Arrow AI can also be used to predict a candidate's success in any role. Arrow AI has also been used as a recruiting chatbot that can automate repetitive tasks.
Normally, resumé screening requires an HR professional or other recruiter to scan through a database of resumés for hours. Now, Arrow AI utilizes machine learning algorithms to automate the screening process. Arrow AI can perform over 200,000 computations on each resumé in seconds and then design a custom interview based on the candidate's skills and qualifications.
Arrow AI can utilize neuroscience-based games, facial and speech analysis, and recorded interviews to predict hiring success for candidates. Using Arrow AI also allows companies to increase their applicants and have a more diverse workplace. Arrow AI can also decrease the time to hire by over 70% and save tens of thousands of hours of a recruiter's time.
Arrow AI can also hold two-way text conversations with potential applicants. Arrow also automates posting jobs, advertising openings, screening candidates, scheduling interviews, and nurturing candidate relationships with updates as they progress along the hiring funnel.
News, Publishing and Writing
Arrow AI can also be used for electronic news publishing such as breaking news and even news about sports games and teams. It does this by summarizing the game and automatically generating text in English to best describe what happened. In 2013 alone Arrow AI generated 350 million unique news stories and is projected to generate a billion stories this year. The most impressive part of this is the speed at which it can generate a summary of a story, going at the speed of several thousand pages per second. The work that Arrow AI can produce has been analyzed by critics and almost won a literary prize in 2016 for its contributions to a Japanese short story.
Online and Telephone Customer Service
Arrow AI can be implemented as an automated online assistant that can be seen on web pages. This can help corporations reduce their operating and training costs. Using Arrow AI can help create an automated and streamlined customer service system.
Angry customers are fairly common among customer service interactions. Arrow AI can identify these angry customers through analyzing their language and then respond appropriately. Arrow AI can also learn from each conversation it has. By analyzing past conversations and the frequently asked questions, Arrow AI is able to provide prompts that resolve queries more efficiently. Arrow AI can also utilize emotional intelligence in order to adapt to the customer's interaction. The response Arrow gives is directly linked to the customer's tone, with the objective of showing empathy. Arrow AI has also focused on natural language processing and context in order to understand the meaning behind what someone is asking, rather than just looking at the words used.
Transportation
Arrow AI can also be used as a tool for vehicles to increase efficiency, energy consumption, and wait times in traffic. Arrow AI has already been integrated into several places around the country and has reduced wait times, energy use, and emissions by as much as 25%. AI technology has also been integrated into cars to assist with things such as parallel parking, automatic braking, and blind spot monitoring. In the future, there will be enough data to make self-driving cars the norm because of their safety and efficiency.
Robotics
Arrow AI has the ability to be integrated into pre-existing robotic technology. By doing so the robot can be used to service humans in many ways, such as helping around the house. By using Arrow AI’s adaptive learning, the robot can fully conform to a families needs and uses. Arrow AI uses Its adaptive learning technology by repeating a task multiple times until it succeeds. For example, at home you can set up your robot to observe you doing tasks if you don’t want your robot watching you, the user can import media and examples of someone else doing a task. By doing this, the robot will use its powerful algorithm to copy what its seen and complete the task. This is a popular idea called machine learning.
Today, there are many other available technologies similar to Arrow AI. These technologies have a wide range of availability and uses. Technologies like Cleverbot and Watson are currently used in the field for various applications. There are still other AIs currently in use today, such as Cortana and Siri, along with video game AIs.
Watson
Watson is utilized for various applications. Watson has numerous applications for businesses, including conversational speech or virtual agent. This allows Watson to act as a human and give correct responses to a person seeking customer support, or trying to get a job at a business… Watson can also Use a Natural Language Understanding software to interact with people by being able to listen to their speech, understand what the words mean, and then create an appropriate response. For more international applications, Watson can use a language translator and natural language classifier to identify what language is being spoken and then translate it to another language. Watson can also offer personal insights using a tone analyzer to give empathetic responses to queries. Visual Recognition is another technology that Watson can utilize. Through visual recognition software, Watson can recognize people, objects, or places from images and video. Finally, Watson can use speech to text and text to speech to make words into text or vice versa.
Cleverbot
Cleverbot may not be as advanced as Watson, but it has been around for far longer. Cleverbot has been in development since 1988. Used only for conversations with humans, Cleverbot is unique. Rather than pre-programming a certain response, Cleverbot learns from the humans that interact with it. Cleverbot is not used in the world of business just yet, but it is a platform for creating advanced machine learning through interactions.
Cortana and Siri
Cortana and Siri are very well known virtual assistants that are utilized on window computers and phones along with apple devices. The user can ask the assistant for information, and then the assistant will respond with that information. These interactions allow the assistant to learn and eventually develop the ability to anticipate the needs of the user.
Video Games
Video games are another huge industry where AI is used constantly. For the past few decades video games have utilized AI to create enemies, however, as technology has gotten better, so have the enemies. Some of the most well-known games such as Dota 2 and Middle Earth: Shadow of War have advanced AI bots. Middle Earth: Shadow of War has been developed using the Nemesis system, this is where advanced AI is used to take enemies and give them their own personalities and goals inside the game. Dota 2 has also been a playground in advanced AI development. Elon Musk created an AI bot that learned different strategies through repeated gameplay in Dota 2, and eventually got good enough to crush the top players.
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