Argumentative essay generation (AEG) aims to generate complete texts on specific controversial topics or debates. Although current AEG methods can generate individual opinions, they often overlook the high-level connections between these opinions. This often leads to the generated results being mired in logical confusion, unable to proof their own arguments effectively. The generated essay may present evidence that contradicts the claims or they may fail to assemble the claims into logical flow. In this paper, we present a unified two-stage framework: Proof-Enhancement and Self-Annotation (PESA) for AEG with a focus on logical enhancement. Specifically, we first construct pseudo-labels for logical information,claims and grounds, using a large language Figure 1: Two examples of proof and logical disorganization model. We then propose a tree planning leading to impaired persuasiveness. Obviously, approach that introduces proof principles and the upper example gives self-contradiction claim and ensures logical consistency. Extensive experimental ground, the lower example gives correct and persuasive results show that, benefiting from proof proof.

The dominant paradigm for instruction tuning is the random-shuffled training of maximally diverse instruction-response pairs. This paper explores the potential benefits of applying a structured cognitive learning approach to instruction tuning in contemporary large language models like ChatGPT and GPT-4. Unlike the previous conventional randomized instruction dataset, we propose a highly structured synthetic dataset that mimics the progressive and organized nature of human education. We curate our dataset by aligning it with educational frameworks, incorporating meta information including its topic and cognitive rigor level for each sample. Our dataset covers comprehensive fine-grained topics spanning diverse educational stages (from middle school to graduate school) with various questions for each topic to enhance conceptual depth using Bloom's taxonomy-a classification framework distinguishing various levels of human cognition for each concept. The results demonstrate that this cognitive rigorous training approach yields significant performance enhancements - +3.06 on the MMLU benchmark and an additional +1.28 on AI2 Reasoning Challenge (hard set) - compared to conventional randomized training, all while avoiding additional computational costs. This research highlights the potential of leveraging human learning principles to enhance the capabilities of language models in comprehending and responding to complex instructions and tasks.

Closely linked to the topic of ML is data science, which is of particular interest for approaches in machine learning and As a consequence of the increasing influence of thus also reflected in multiple AI curricula. Corresponding machine learning on our lives, everyone needs methods are also used to gain knowledge in a wide variety competencies to understand corresponding phenomena, of scientific disciplines. Data analysis and artificial intelligence but also to get involved in shaping our are often referred to as the fourth pillar of science world and making informed decisions regarding (Riedel et al., 2008; Tolle et al., 2011). This is becoming the influences on our society. Therefore, in K-increasingly relevant for K-12 education as well, as this shift 12 education, students need to learn about core in the scientific disciplines is also reflected in corresponding ideas and principles of machine learning.

Are you a scientist with a keen interest in education, research and intelligent technologies? At the National Education Lab for Artificial Intelligence (NOLAI in Dutch), we develop innovative and intelligent technologies aimed at improving the quality of primary and secondary education. Over the next ten years, NOLAI teams up with schools, universities and companies to create new innovative examples of AI in education. As a postdoctoral researcher on ethical aspects of AI in education, you can contribute to NOLAI's goals in our scientific programme. The new National Education Lab AI (NOLAI), located at Radboud University in the Netherlands, is looking for a postdoctoral researcher to study the ethical and social implications of AI in education.

Knowledge and skills from different fields are required for this. The fields in which you need to have knowledge to program artificial intelligence and some additional concepts about artificial intelligence are shown in this post. It is possible that you can program artificial intelligence without any knowledge, but the ideal is to have a minimum of them. This will make it possible for you to fix any issues that arise in your project. The very term of "programming" artificial intelligence tells us that it is necessary to know some programming languages to carry out this type of project.

What's New: Intel in collaboration with the Central Board of Secondary Education (CBSE), Ministry of Education today announced the launch of the AI For All initiative with the purpose of creating a basic understanding of artificial intelligence (AI) for everyone in India. Based on Intel's AI For Citizens program, AI For All is a 4-hour, self-paced learning program that demystifies AI in an inclusive manner. It is as applicable to a student, a stay-at-home parent as it is to a professional in any field or even a senior citizen. The program aims to introduce AI to 1 million citizens in its first year. "AI has the power to drive faster economic growth, address population-scale challenges and benefit the lives and livelihoods of people. The AI For All initiative based on Intel's AI For Citizens program aims to make India AI-ready by building awareness and appreciation of AI among everyone. The program further strengthens Intel's commitment to collaborating with the Government of India to reach the full potential of AI and further the vision of a digitally-empowered India."

Such work may be protected once the creation becomes an expression of the author and not merely an idea. It refers to the right to enjoy the subject matter and use the same for economic purposes. On the other hand, the artworks based on Artificial Intelligence are relied heavily on the programmer who gives the input for creation of the work. However, with technological advancement, AI has developed a capability of understanding and creating outputs without any human interference.[7] The main issue raised, is regarding the protection of work created by AI.

Perhaps you remember the iconic theme of the globally popular Kung Fu Panda movies, "You are the secret ingredient!" This meant that self-belief is important and with it great things can be achieved--Po, for example, became the Dragon Warrior. My meaning here is that computer science is both a powerful enabler of rapid advances in all intellectual fields and a disruptor driving furious revolutions in commerce and society worldwide. Computer science is more important and potent than ever! Computing is driving unprecedented rapid change.

The report anticipates economic effects across several fronts. AI, like any new technology, is key to growth because it increases output without requiring increases in labor or capital. "In the last decade, despite technology's positive push, measured productivity growth has slowed in 30 of the 31 advanced economies, slowing in the United States from an average annual growth rate of 2.5% in the decade after 1995 to only 1.0% growth in the decade after 2005," the report states. Any increase in aggregate productivity from adopting artificial intelligence would be a welcomed change. But the resultant job automation is causing alarm.

Nearly 50 million students are now returning to classrooms--from kindergarten through 12th grade. They will spend approximately eight hours a day at school and additional hours doing homework. They will be educated, in public schools alone, by the equivalent of over 3 million full-time teachers. And they will, with rare exception, learn a dismal fraction of what they ought to be learning to be creative, confident and critical thinkers about themselves and the world around them. As a parent myself, I literally apologized to each of my children--and not just once--for the fact that so much of their time as grade school and junior high school and high school students (even at private school) was being spent on memorization, regurgitation and rote learning that amounted to busy work and the warehousing of them, physically and mentally.