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Exploring Artificial Intelligence in Education: The Three Paradigms

AI Education
Kashmir Observer

Today’s digital world has merged artificial intelligence (AI) with education, changing the era in how learning is perceived, delivered, and experienced. Around the world, education systems have strived to adapt to technological development. However, the arrival of AI dispensed an unmatched shift. The main reason for this transformation is to re-envision the educational environment and digitize traditional teaching methods. AI potential intelligent tutoring systems, teaching robots, adaptive learning systems, and human-computer interaction create room for personal learning and provide insight into student learning patterns, which pave the way for a more efficient and adaptive educational system. The proposition of AI in education is not just about using new devices. It’s about reconsidering the educational paradigm itself.

Understanding and utilizing AI within educational settings is widely categorized into three paradigms: AI-directed learner-as-recipient, AI-supported learner-as-collaborator, and AI-empowered learner-as-leader. In Paradigm One AI-directed, learner-as-recipient, AI represents and directs cognitive learning while learners are recipients of AI services. In Paradigm Two, AI-supported, learner-as-collaborator, AI supports learning while learners collaborate with AI. In Paradigm Three, AI-empowered, learner-as-leader, AI empowers learning, and learners take agency of their learning. Each paradigm offers a distinctive spectacle through which AI’s potential and challenges can be investigated.

Artificial Intelligence in Education: The Three Paradigms

The investigation of Artificial Intelligence in Higher Education and Artificial Intelligence in Academic Writing discloses an advanced impact that redesign the educational realm. Interaction between AI and the learner is the impact that falls into three distinct paradigms. This paradigm gives the perception that AI is not just a tool for orderliness but a progressive element in educational approach and learner engagement.

  1. Paradigm One: AI-directed, Learner-as-recipient

This paradigm characterizes AI as the domain of knowledge and directs the learning processes, while the learner acts as the recipient of the AI service to follow the specific learning pathways. AI is in charge here; it uses algorithms to modify educational content, evaluate learners’ performance, and give customized feedback. In Paradigm One, although some systems collect the learner’s information to diagnose the learning state, the system defines learning content, procedure, and goal. In contrast, the learner is coerced along a particular learning path provided by the AI system. The goal is to modify the learning process and ensure learners access content matching their learning pace and style.

  1. Paradigm Two: AI-supported, Learner-as-collaborator

This paradigm constitutes a more interactive and cooperative relationship between AI and learners. AI acts as a support system in this fixture. It moves towards learner-centered human learning through mutual interaction and sustains collaboration between the learner and the AI system. AI-enabled collaborative platforms and tools like intelligent tutoring fall under this category. They help in collaborative problem-solving and cultivate group discussion and peer learning. Here, AI is created to increase human intelligence rather than replace it.

  1. Paradigm Three: AI-empowered, Learner-as-leader

In the most advanced paradigm, AI is viewed as a tool to augment human intelligence and holds the learner’s agency as the core of artificial intelligence in education. Essentially, this paradigm has learner agency as the core of AI in education and views AI as a tool to augment human intelligence. It reflects a perspective from complexity theory that views education as a complex adaptive system. The synergetic collaboration between multiple entities in the system, such as the learner, the instructor, information, and technology, is essential to ensure the learner’s augmented intelligence. In this complex system, AI applications are designed and applied with the awareness that AI techniques are parts of a larger system consisting of learners, instructors, and other humans.

Thus far, it’s clear that integrating AI technologies has redefined educational methodologies and made learning more adaptive and personalized. Parallel to this, professional writing services like CustomWritings have become a vital tool for students that complements AI’s advancements. These services help students understand complex concepts and refine their writing skills. They help students grasp intricate topics more effectively by providing expert guidance and high-quality examples. This aspect is emphasized in the AI-empowered, learner-as-leader paradigm.

Application of Artificial Intelligence in Higher Education

AI’s role in academia is extensive. It ranges from amplifying how papers and essays are written to reshaping educational paradigms. AI applications organize administrative and academic processes and explore and carry out advanced learning theories. Consequently, it leads to a more personalized, effective learning environment. The following are some of the key applications of AI in higher education.

  1. Learning and instruction: Artificial intelligence in education is used in the education system in grading. In this process, teachers mechanize the grading of students for certain fixed sets of questions. Further, AI can also be applied in adaptive and individualized learning to fulfill students’ requirements, and it also assists instructors in accessing the understanding capacity of the students in their lectures and empowers them to give the appropriate clues for students.
  2. Personalized learning experiences: This technology delivers personalized degree planning and intervention with struggling students. Its algorithms can analyze individual learning patterns, preferences, and performance. This application guarantees that students receive modified content and resources that align with their unique learning style and areas for improvement. Simply put, it makes learning more enjoyable with its significant shift from a one-size-fits-all approach.
  3. Adaptive courseware: At its most direct, AI is integrated into courseware as a direct instructional tool. This application can either help students practice and guide them through learning activities or enable them to walk through more realistic simulations and applications. Some AI applications are targeted and content-specific. For instance, ShadowHealth simulates patient cases for nursing students who would typically have to schedule time with live actors (a common practice in medicine) to practice skills they need for patients.
  4. Automated essay scoring and feedback: AI-powered tools are increasingly being used to evaluate essays and provide immediate feedback on papers. They use simple language processing and machine learning to acquire quality writing, grammatical accuracy, and content relevance. This usage is beneficial since it offers students immediate feedback and speeds up the grading process.
  5. Research and content development: As if that’s not enough, AI is also transforming academic research and content development by offering improved tools for data analysis, simulation, and literature review. For example, AI algorithms can predict outcomes, analyze large amounts of data, and propose new research areas.

What is the Impact of Artificial Intelligence on Writing

AI has presented a new era. Take the case of ChatGPT, an AI technology that has transformed the way text is generated, edited, and refined. AI tools are now indispensable assistants for professional writers since they suggest correct phrases, grammar corrections, and style improvement. Grammarly is another impactful AI tool that has transformed the writing process. It is an automated tool that eliminates grammatical errors and other writing issues. Millions of writers, students, and instructors trust Grammarly’s AI writing assistance to confidently communicate and make writing faster and more delightful. So, using AI in writing is not just about correcting errors. These tools enhance the quality of writing, making it more engaging and accessible. Besides, they help writers continuously improve their skills by providing real-time feedback to promote learning processes.

And as if that’s not enough, AI has created a new forum for creativity. It generates ideas for plots and settings and assists writers in overcoming writer’s block. With the existing genre and themes, this technology can suggest original and reasonable content since it can examine large quantities of text. This advantage benefits professional writers looking to explore new genres or add additional information to their narratives. However, ethical questions regarding the impact of AI in writing revolve around consequences in terms of different groups and subgroups, educational values, and how AI systems might alter those values. There’s an ongoing debate about how these AI tools aid in writing processes and should be relied upon.

Embrace the AI Revolution

While current AI developments for instructional support are emerging, it’s easy to see how their short-term trajectory could empower faculty in the classroom. As assessment aggregation AI proliferates, faculty teaching loads and administrative responsibilities may stabilize, and faculty will have more time to interact with students individually. This situation will likely lead to increased standardization of curriculum. As for students, AI helps them improve their writing quality, increase their understanding of course concepts, and appreciate the adoption of learning aids that facilitate their learning experiences.

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Imran Khan used AI-Generated Audio Clip to Address a Virtual Rally from Prison

Imran Khan AI-Generated Voice

Former Pakistan Prime Minister Imran Khan, currently jailed, used an AI-generated audio clip to deliver a speech during a virtual rally, making a pioneering event in South Asia. 

Khan spoke for four minutes on Sunday, incorporating the AI-generated audio over a video featuring his computer-generated image, along with images from Pakistan Tehreek-e-Insaf (PTI) rallies and his earlier speeches. 

The AI-generated voice mimicking Khan stated, “Our party is not allowed to hold public rallies. Our people are being kidnapped, and their families are being harassed.” The AI-generated further added that the speech was taken from notes written by Imran Khan in Prison. 

Read More: Introducing Fal.Ai, A Tool that Can Create Deep Fake Videos in Real-Time

“History will remember your sacrifices,” the AI voice added, referencing the crackdown on PTI, which led to the arrest and resignation of numerous party leaders. 

The PTI claimed that its virtual rally got more than five million views across social media platforms such as YouTube, Facebook, and Twitter, despite reported internet disruptions in different regions of the country. The party arranged this online event to sidestep a government prohibition on public rallies. 

It is quite fascinating to see that AI is being widely used as a political weapon to justify narratives. In this case, the intangible nature of AI was used efficiently for a political speech to mitigate/compensate for the absence of a tangible presence of a leader. With AI growing rapidly, it is to be seen how the coming decade will harness the capabilities of AI for good and for bad. 

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MusicFX by Google will allow you to Create your Own Music with AI

Google MusicFX

Google has announced MusicFX, an innovative experimental tool empowering users to create their own music using artificial intelligence. 

This cutting-edge creation leverages Google’s MusicLM and Deepmind’s SynthID watermarking technology to embed distinct digital watermarks into the generated outputs, guaranteeing their authenticity and source. 

As part of Google’s AI Test Kitchen initiative, the service offers an early glimpse into the company’s latest AI innovations. Its primary aim is to foster collaboration by inviting public engagement, allowing early feedback crucial for responsible and inclusive advancements in AI technology. 

Read More: Google’s NotebookLM Helps You Take Online Notes

Regarding privacy, Google guarantees that the information gathered during interactions with MusicFX remains unassociated with users’ Google accounts and is stored anonymously. Human reviewers may analyze this data to enhance models. 

While using the tool, users have the option to delete the data. However, once the session concludes, the data becomes non-identifiable and non-erasable, kept for a maximum of 18 months. 

Residents in the USA, Kenya, New Zealand, and Australia now have access to MusicFX and TextFX. TextFX enables users to transform text inputs into music or textual outputs, showcasing the capabilities of generative AI.

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Meet OpenHathi by Sarvam AI, First Ever LLM Model Proficient in Indic Languages

SarvamAI OpenHathi
Source: Sarvam AI

Indian AI startup Sarvam AI has introduced OpenHathi-Hi-vo.1, representing the inaugural release within the OpenHathi series of large language models. The model expands upon the powerful Llama2-7B and boats performance similar to GPT-3.5 (sometimes even surpassing), specifically tailored for Indic languages. 

OpenHathi notably expanded the Llama2-7B tokenizer by adding 48,000 more tokens. This is possible as a result of a meticulous two-phase training process. Initially, the focus lies on embedding alignment, a method that strategically aligns the initial random Hindi embeddings. Following this is the bilingual language modeling phase, which educates the model on how to handle different languages attentively across tokens. 

Sarvam AI’s rigorous assessments cover not just standard Natural Language Generation tasks but also practical, real-world challenges. These evaluations, comparing OpenHathi against GPT-3.5 with GPT-4 as the referee, consistently highlight OpenHathi’s superior performance in Hindi, both in its native script and Romanized versions. 

Read More: Mistral AI’s New LLM Model Outperforms GPT-3 Model

This collaboration saw Sarvam AI teaming up with academic partners from AI4Bharat, bringing in crucial language resources and benchmarking knowledge. Moreover, the model’s refinement was a result of collaboration with KissanAI, utilizing conversational data derived from a bot engaging with farmers in diverse languages. 

Pratyush Kumar and Vivek Raghavan, the founders of Sarvam AI, initiated this venture in July 2023. They received $41 million in Series A funding. Lightspeed spearheaded the investment round, and Peak XV Partners and Khosla Ventures contributed significantly.

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Introducing Fal.Ai, A Tool that Can Create Deep Fake Videos in Real-Time

Deepfake Fal.ai
Source: Fal.ai

DeepFake hasn’t busted onto the scene quite yet. However, the anxiety related to it is already kicking in. Fake news and cyber crimes have infiltrated our lives, and we know the dangers associated with it. As a result of the rapid evolution of AI, which is intertwined with the sophistication of deepfake, an air of uncertainty is felt, as the negative connotation attached to it isn’t just a distant dystopian hypothesis. 

Fal.ai is a new tool that utilizes your webcam to morph your appearance into the character you script. Operating in real-time at over 40 frames per second, it is presently available at no cost. 

Fal presents a freely accessible public demo. Upon entry, it requests permission to access the webcam. Users need to input a prompt specifying the character they wish to embody. The outcome is a real-time video reflecting the chosen character’s appearance. The deepfake rendition also mirrors our clothing accessories and replicates our movements, such as hand gestures, smiles, etc. 

Read More: Kerala Man Loses ₹40,000 to AI-based Deepfake Scam 

Currently, the demo is restricted to a 15-second runtime to prevent server overload and curb excessive resource consumption. You can find the code for Fal on GitHub. 

Fal.ai is backed by a team comprising seven engineers. Beyond their deep fake creation, they specialize in developing real-time AI applications.

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Krutrim: Ola’s Answer to ChatGPT, Revolutionizing AI with India’s Linguistic Diversity

Bhavish Kumar's Image
Image Credit: Analytics Drift

Ola, led by CEO Bhavish Aggarwal, has recently unveiled Krutrim, a significant addition to the LLM landscape. Krutrim, a multi-lingual AI model, is notable for its extensive training on a vast array of Indian data, making it particularly adept at understanding and speaking multiple Indian languages. Ola’s Krutrim represents a critical step in making AI more accessible and relevant to India’s diverse linguistic landscape.

Krutrim LLM is composed of two versions: the base model and the more advanced Krutrim Pro. These models are not only proficient in language but also in understanding cultural nuances, indicating a significant advancement in AI’s ability to engage with and reflect diverse cultural contexts.

This initiative also underlines Ola’s commitment to developing indigenous technology solutions. The company is working on AI infrastructure, planning to develop data centers, server-computing, edge-computing, and super-computers, with a focus on efficiency and sustainability.

Krutrim’s launch is a part of a broader movement in India towards developing native AI solutions, exemplified by Sarvam AI’s recent unveiling of OpenHathi, a Hindi language model. These developments reflect a growing recognition of the importance of AI in India’s future, both as a technological leader and as a society increasingly shaped by digital innovation.

Aggarwal’s vision for Krutrim is not just about technological advancement but also about connecting India’s future to its roots, recognizing the unique cultural and linguistic diversity of the country, and the role AI can play in enhancing and preserving it. This vision positions Krutrim as a tool for not just economic efficiency but also cultural expression and preservation.

In summary, Krutrim represents a significant stride in AI development, particularly in the context of linguistic and cultural diversity. It’s a move towards making AI more inclusive and reflective of global diversity, especially in a country as linguistically rich as India.

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What is GPAI and the New Delhi Declaration?

New Delhi Declaration GPAI AI
Source: PGurus

After seven hours of extensive discussions, delegates from 28 nations and the European Union have officially ratified the “New Delhi Declaration” within the Global Partnership on Artificial Intelligence (GPAI). GPAI brings countries from North and South America, Europe, and East Asia, all dedicated to advancing the “trustworthy development, deployment, and use of AI.”

The ministerial declaration highlights how these nations are dedicated to following principles that guide the responsible handling of reliable AI. These principles are deeply rooted in democratic values and human rights. The goal is to push forward the development of AI in a way that’s ethical, responsible, and focused on benefiting humanity. 

Rajeev Chandrasekhar, Minister of State for Electronics and Information, said that the declaration aimed to establish GPAI as a pivotal force in steering the trajectory of AI, focusing on fostering innovation and cultivating collaborative AI initiatives among partner nations. 

He also said that the consensus among countries involved commitments to explore AI applications in crucial sectors such as healthcare, agriculture, and other areas of shared interest, demonstrating a collective goal to address global challenges through technological advancements. 

Read More: Global Leaders Agree on AI Safety Principles at UK Summit

Some of the most important delegates at GPAI were Jean-Noel Barrot, representing France as the minister of digital affairs; Hiroshi Yoshida, serving as the vice-minister of internal affairs for Japan; and Viscount Jonathan Camrose, the minister overseeing AI and intellectual property matters for the UK. 

Yoshida and Camrose emphasized the integral role of inclusivity within GPAI’s global AI development efforts. Yoshida specifically expressed the body’s aspiration to “encourage increased participation from developing nations within GPAI.” 

Upon the GPAI Summits’s closure on Thursday, the Centre is set to reveal its official AI policy through the India AI Program on January 10. Additionally, discussions concerning global AI regulation advancement will continue during the Korea Safety Summit scheduled for mid-2024. 

Prime Minister Narendra Modi said that AI must embrace inclusivity, incorporating a diverse array of Ideas. The more inclusive its evolution, the more favorable the outcomes. The trajectory of AI’s development will hinge on human and democratic values, said Modi. 

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Optimus Gen-2, Second Generation Humanoid Robot Unveiled by Tesla

Tesla Optimus
Source: X

Elon Musk, CEO of Tesla, unveiled the second generation of the company’s humanoid robot, Optimus, in a video posted on X. Tesla’s accompanying statement highlighted that Optimus Gen-2 boasts a 30% increase in speed compared to the May prototype and weighs 10 kg less without any compromises. 

Tesla also asserted that Optimus had undergone several technical enhancements, including refined torque sensing, articulated toe sections, and improved human geometry. 

In the later segment of the video, Optimus Gen-2 demonstrates its capabilities by performing squats in a gym, attributed by Tesla to the humanoid’s enhanced balance and full-body control. 

Read More: Is Grok the First-Ever Politically Incorrect AI Chatbot?

Additionally, the footage shows Optimus Gen-2 delicately transferring eggs from a carton to an egg boiler, made feasible by the humanoid’s new hands equipped with “tactile sensing on all fingers.” 

It was back in 2022, during Tesla’s AI Day when Elon Musk first unveiled two prototypes of Optimus. He was confident that the robots would serve humanity in a good way and likely change the socio-economical structures. With an advanced version of Optimus has been unveiled, it is likely to be seen if his predictions come true. 

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Microsoft Unveils Phi-2, a Small Language Model Which Can Operate on Mobile Devices

Microsoft Phi-2

Microsoft has launched its Phi-2 small language model (SML), an AI program specialized in text-to-text tasks. Microsoft’s official account on X states that this model is compact enough to operate seamlessly on laptops or mobile devices. 

Phi-2, equipped with 2.7 billion parameters (connections between artificial neurons), showcases performance akin to significantly larger models such as Meta’s Llama 2-7B, which contains 7 billion parameters, and Mistral-7B, another model boasting 7 billion parameters. 

Figure 1

In Microsoft’s official blog post, Phi-2 is seen as a pursuit of smaller-scale language models to match the capabilities of larger ones. The key strategies of researchers include prioritizing high-quality training data focusing on textbook-quality content and synthetic datasets for common sense reasoning and general knowledge. They also enrich their dataset with meticulously selected web content emphasizing educational value. 

Read More: Ranjani Mani is Microsoft’s New AI Director

Moreover, Microsoft innovatively leveraged knowledge transfer from Phi-1.5, a 1.3 billion parameter model, embedding its insight into the 2.7 billion parameter Phi-2. This technique not only expedites training but also substantially elevates Phi-2’s benchmark performance. 

Going more into the model’s technicality, Phi-2 operates on a next-word prediction objective and underwent training on a massive 1.4 trillion tokens sourced from web datasets focusing on NLP and coding. Its training spanned 14 days, utilizing 96 A100 GPUs. 

Fig 2: Safety scores computed on 13 demographics from ToxiGen. A subset of 6541 sentences are selected and scored between 0 to 1 based on scaled perplexity and sentence toxicity. A higher score indicates the model is less likely to produce toxic sentences compared to benign ones. (Source: Microsoft) 

This model, notably a base version, did not undergo alignment through reinforcement learning from human feedback or instruct fine-tuning. Despite this absence of additional refinement, researchers observed Phi-2 displaying improved behavior regarding toxicity and bias compared to existing open-source models that underwent alignment processes. (See Figure 2)

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Mistral AI’s New LLM Model Outperforms GPT-3 Model

Mistral Mixtral 8x7B
Source: MISTRAL AI

Mistral released its latest model, the Mixtral 8x7B, last week. Named after its “mixture of experts” technique, this model combines various specialized models, each focusing on different task categories. 

Surprisingly, Mistral made it available online as a torrent link without accompanying it with explanations, blog posts, or demo videos showcasing its capabilities. 

Mistral later published a blog post that delved deeper into the model. They showcased benchmarks where Mixtral 8x7B matched or even surpassed the performance of OpenAI’s GPT-3.5 and Meta’s Llama 2

Read More: Datasaur Launches LLM LAB Through Which Enterprises can Create their Own Generative AI Application

Acknowledging collaboration with CoreWeave and Scaleway for technical support during training, Mistral also confirmed that the Mixtral 8x7B model is open for commercial use under the Apache 2.0 license

Ethan Mollick, an AI influencer and professor at the University of Pennsylvania Wharton School of Business, pointed out on X that Mixtral 8x7B appears to lack “safety guardrails.” This means users who are dissatisfied with OpenAI’s stricter content policies have access to a model with similar performance that can generate content considered unsafe. On the flip side, this absence of safety measures could pose a challenge for policymakers and regulators.

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