AI Engineering
AI engineering involves the application of engineering principles to the development and deployment of artificial intelligence systems. It encompasses the design, construction, and optimization of AI solutions, including machine learning models, algorithms, and data pipelines. AI engineers work to ensure the reliability, scalability, and efficiency of AI technologies in various applications.
7 Key excerpts on "AI Engineering"
eBook - ePubRegulating Artificial Intelligence
Binary Ethics and the Law
- Dominika Harasimiuk, Tomasz Braun(Authors)
- 2021(Publication Date)
- Routledge(Publisher)
...AI systems can either use symbolic rules or learn a numeric model, and they can also adapt their behaviour by analysing how the environment is affected by their previous actions. As a scientific discipline, AI includes several approaches and techniques, such as machine learning (of which deep learning and reinforcement learning are specific examples), machine reasoning (which includes planning, scheduling, knowledge representation and reasoning, search, and optimisation), and robotics (which includes control, perception, sensors and actuators, as well as the integration of all other techniques into cyber-physical systems)’. 34 The HLEG’s AI definition is a very broad one, covering robotics, software-based systems, encompassing all sorts of techniques presently used in the AI industry. For the purpose of our book, we will also be using term AI in its broadest scope. 34 Ibid. A more detailed definition, in terms of distinction made, is the one proposed by the European Parliament in its motion for a new EU regulation on ethical aspects of artificial intelligence. 35 The proposed legal definitions separate three notions—artificial intelligence, robotics and related technologies. 36 Artificial intelligence shall be understood as ‘software systems that, inter alia, collect, process and interpret structured or unstructured data, identify patterns and establish models to reach conclusions or take actions in the physical or virtual dimension based on such conclusions’. Robotics are ‘technologies that enable machines to perform tasks traditionally performed by human beings including by way of AI or related technologies’...
eBook - ePubDigital Disruption in Teaching and Testing
Assessments, Big Data, and the Transformation of Schooling
- Claire Wyatt-Smith, Bob Lingard, Elizabeth Heck, Claire Wyatt-Smith, Bob Lingard, Elizabeth Heck(Authors)
- 2021(Publication Date)
- Routledge(Publisher)
...AI systems are designed to operate with varying levels of autonomy” (para. 12). AI are computer systems that can undertake tasks or activities that require features of human intelligence, such as planning, problem solving, pattern recognition, prediction, learning from experience, and logical action. AI researchers focus on developing machines that can think and behave in a rational manner according to mathematical assumptions and rules encapsulated in algorithms (these are instructions that tell the computer or machine how to accomplish a task or operation), with an increasing emphasis on building capacity for automated decision-making. The field of AI is decades old, with the term first coined in the 1950s. Over time, there has been definitional tension within computer science about what constitutes AI. Maini and Sabri (2017) note that standards for what AI is remain open to interpretation and continue to change. They suggest as well that AI refers to how computers “figure out” and can perform tasks usually done by humans. When this occurs, there is a tendency for humans to reject that this is indicative of machine intelligence. This is known as the AI effect… Perhaps there is a certain je ne sais quoi inherent to what people will reliably accept as “artificial intelligence”: So, does a calculator count as AI? Maybe by some interpretation. What about a self-driving car? Today, yes. In the future, perhaps not. (Maini & Sabri, 2017, p. 10) Krafft et al. (2020) suggest there are differences between the way technologists and non-technologists use the term AI. They argue that AI researchers support definitions that accentuate technical functionality, while policymakers prefer more anthropomorphic explanations that relate to aspects of human thinking and behavior...
- Adedeji B. Badiru(Author)
- 2021(Publication Date)
- CRC Press(Publisher)
...1 Understanding AI DOI: 10.1201/9781003089643-1 Introduction Artificial intelligence (AI) is not just one single thing. It is a conglomerate of various elements, involving software, hardware, data platform, policy, procedures, specifications, rules, and people intuition. How we leverage such a multifaceted system to do seemingly intelligent things, typical of how humans think and work, is a matter of systems implementation. This is why the premise of this book centers on a systems methodology. In spite of the recent boost in the visibility and hype of artificial intelligence, it has actually been around and toyed with for decades. What has brought AI more to the forefront nowadays is the availability and prevalence of high-powered computing tools that have enabled the data-intensive processing required by AI systems. The resurgence of AI has been driven by the following developments: Emergence of new computational techniques and more powerful computers Machine learning techniques Autonomous systems New/innovative applications Specialized techniques: Intelligent Computational Search Technique Using Cantor Set Sectioning Human-in-the-loop requirements Systems integration aspects As long ago as the mid-1980s, the author has led many research and development projects that embedded AI software and hardware into conventional human decision processes. AI has revolutionized and will continue to revolutionize many things we see and use around us. So, we need to pay attention to the emerging developments. Historical Background The background of Al has been characterized by controversial opinions and diverse approaches. The controversies have ranged from the basic definition of intelligence to questions about the moral and ethical aspects of pursuing AI. However, despite the unsettled controversies, the technology continues to generate practical results. With increasing efforts in AI research, many of the prevailing arguments are being resolved with proven technical approaches...
eBook - ePubArtificial Intelligence
Evolution, Ethics and Public Policy
- Saswat Sarangi, Pankaj Sharma(Authors)
- 2018(Publication Date)
- Routledge India(Publisher)
...It is natural that as a science, it draws from many academic disciplines and calls for expertise in disciplines such as computer science, medicine, biology, psychology, linguistics, mathematics, and engineering. AI is focusing on the development of computer functions that mirror human intelligence, such as cognition, compliance with socially acceptable practices, reasoning, persuasion, learning, knowledge transfer and problem solving. So, multiple areas can contribute to build an intelligent system: mathematics, biology, philosophy, computer science, sociology and neurology. This list is certainly not exhaustive and it is not unusual for other, less obvious, disciplines to also contribute towards AI development. This is one of the important reasons why AI is unique and different to other technologies and why, at times, progress in AI is dependent on advancements in several disciplines. AI is for decision-making; other technology is about better execution Throughout human history, the focus of science has been on developing an understanding of natural phenomena and then identifying the laws of nature associated with them. For simple processes, this was done one by one and for complex ones, in conjunction with many others. Prehistoric man, through trial and error, figured out causal relations: that if X happens, Y will follow. These lessons were later on used to make predictive models for things around them. This predictive model could be used to develop useful technologies to make things that reduced human effort and improved the quality of life for humans. Most of the focus of science and technology effort throughout human history has been on making the lives of human beings easier. The common thread in various technological endeavors has been that humans knew what they wanted and what they wanted to achieve. They were deciding the direction and were trying to figure out “how”...
- Liza Ireni-Saban, Maya Sherman(Authors)
- 2021(Publication Date)
- Routledge(Publisher)
...For instance, the 2019 US National Defense Authorization Act offers a valuable starting point. It defines AI as including (1) any artificial system that performs tasks under varying and unpredictable circumstances without significant human oversight, or that can learn from experience and improve performance when exposed to data sets; (2) artificial systems developed in computer software, physical hardware, or other context that solves tasks requiring human-like perception, cognition, planning, learning, communication, or physical action; (3) artificial systems designed to think or act like a human, including cognitive architectures and neural networks; (4) a set of techniques, including machine learning, that is designed to approximate a cognitive task; and (5) artificial systems designed to act rationally, including an intelligent software agent or embodied robot that achieves goals using perception, planning, reasoning, learning, communicating, decision making, and acting. (Congress, US, 2018, p. 330) In addition, the US Army Sciences Board highlighted the decision making aspect of AI, that it ‘can incorporate abstraction and interpretation into information processing and make decisions at a level of sophistication that would be considered intelligent in humans’ (Brownstein and et al., 1984), or as articulated by the US Defense Science Board, which depicts AI as ‘[t]he capability of computer systems to perform tasks that normally require human intelligence (e.g., perception, conversation, decision-making)’ (Fields, 2016). The more streamlined definition offered by the European Commission’s Communication on AI refers to AI as ‘[s]ystems that display intelligent behaviour by analysing their environment and taking actions—with some degree of autonomy—to achieve specific goals’. It posits that AI-based systems ‘can be purely software-based, acting in the virtual world (e.g...
eBook - ePubArtificial Intelligence
Fundamentals and Applications
- Cherry Bhargava, Pradeep Kumar Sharma, Cherry Bhargava, Pradeep Kumar Sharma(Authors)
- 2021(Publication Date)
- CRC Press(Publisher)
...AI is a focused area of science and technology to make machine knowledgeable, which basically means generalized learning, reasoning, analyzing, and understanding of natural languages. These days, the term “AI” envelops the entire concept of a machine that astute in wording of both operational and social results. When the AI is incorporated with robots, there comes a concept of automated bots, and we need to understand that it’s not necessary that robotics always mean to have the physical robots; these can be application bots that work on human instructions and are made to mimic human work and automate the process and from here, the “automation” term is coined, which basically means the replicating human task and integrating these automated bots with AI to make decisions. On the one hand, automation leads to business benefits like cost, time, and a rapid production rate; on the other hand, the automated technologies lead to “technological unemployment.” These technologies have not only suppressed the physical strength of human but also suppressed the human cognitive ability to work and process the huge amount of data and decision-making power. The development of AI and automated technologies can lead a world to better off, but as these technologies are growing, they can lead to a negative impact on society if not handled accordingly. This chapter will discuss the features of automated bots, difference between bots and robots, features and scope of automation, and the technologies that support their implementation, and some of the vulnerabilities. 5.2 History The term “automation” was coined in 1946 by D.S. Harder of Ford Motor industries, and it was used to describe the enhancement in the production line, which basically means replacing human workers with machinery...
eBook - ePubArtificial Knowing
Gender and the Thinking Machine
- Alison Adam(Author)
- 2006(Publication Date)
- Routledge(Publisher)
...2. AI IN CONTEXT Marvin Minsky (1968:v) defines AI in these terms: ‘Artificial Intelligence is the science of making machines do things that would require intelligence if done by men.’ However, in describing what AI is about, I doubt whether it is ultimately useful to offer an immutable definition, and certainly not one which defines it in terms of men’s intelligence! The ‘artificial mind’ myth has contributed to a view of AI which, as well as being too mystical, may well be some distance from the intentions of those working in the field. This is especially problematic if, as I have suggested, AI researchers tend to view their discipline in terms of engineering, of designing and building computing artefacts; this does not tie in neatly with an ‘artificial mind’ view. It is hard to know why such a position has proved so persistent. It may be that for many, at least outside the confines of computing, their introduction to the subject comes from one of the widely known philosophical critiques, such as that of Dreyfus (1979; 1992) or Searle (1987). In such a case it would be easy to fix on the idea that the aim of AI is primarily to create an artificial mind, and that the success or failure of the whole AI project should be judged against this one goal. GENERAL PROBLEM-SOLVING—THE EARLY DAYS OF AI A researcher entering the field of AI at the end of the twentieth century enters a mature discipline with clear boundaries and a set of problems which are deemed to be appropriate for the subject, what Thomas Kuhn (1970) would have termed a ‘paradigm’, or Imre Lakatos (1970), a ‘research programme’. Forty or more years earlier, in an entirely new subject area, the choice of appropriate problem was not so clear...
