I never took a tour of an actual castle, sounds fun actually.

Withstood the toils of history, impressive!

I don’t remember much from reading Hamlet in high school, but it’s interesting to know that Castle is inspired by a real location.

The article talks about the potential AI has in healthcare. Especially since it is evolving quickly, it now has the power to provide patients with resources and their health status. The use of AI has also enabled virtual consultations and remote monitoring which is very convenient and supports patients at any time outside of the hospital.

The purpose of this article is to provide a detailed analysis of how AI has impacted the field of healthcare and education. It specifically delves into the use of AI in medical and dental education to show how students are learning. It also discusses the advantages and disadvantages of how AI has transformed learning.

This sentence is very important because it describes the ethical problems with using AI tools. The more you use AI, the better it understands you and therefore can generate information to fit your biases better. This can lead to unqualified information. Privacy issues can arise since AI can collect data. Human jobs are being replaced with AI, so morals start to play a role in the justification of AI tools.

Annotation: This is exciting because AI could make education more efficient and allow instructors to focus more on teaching and student interaction rather than paperwork.

Explanation: AI has the potential to transform education by automating repetitive tasks such as exam preparation and grading. This allows educators to devote more time to teaching and fostering critical thinking skills. According to Weiner et al. (2025), AI can streamline workflows in healthcare education, reducing costs and administrative burdens while improving efficiency. However, ethical considerations remain, including maintaining fairness in grading and ensuring transparency in automated decisions. Balancing efficiency with fairness will be essential for responsible implementation.

References Weiner, E. B., Dankwa-Mullan, I., Nelson, W. A., & Hassanpour, S. (2025). Ethical challenges and evolving strategies in the integration of artificial intelligence into clinical practice. PLOS Digital Health, 4(4), e0000810–e0000810. https://doi.org/10.1371/journal.pdig.0000810

Annotation: This is interesting because AI can personalize learning and improve diagnostic training, but it may also reduce critical thinking if over-relied upon.

Explanation: AI in medical education offers opportunities for personalized learning and enhanced diagnostic training, but it also raises important ethical questions about trust and accountability. Weiner et al. (2025) highlight that while AI improves clinical efficiency, its use must be balanced with transparency and oversight to ensure that medical professionals retain critical thinking skills. Over-reliance on AI risks reducing independent judgment, which could compromise the quality of care in the long term.

References Weiner, E. B., Dankwa-Mullan, I., Nelson, W. A., & Hassanpour, S. (2025). Ethical challenges and evolving strategies in the integration of artificial intelligence into clinical practice. PLOS Digital Health, 4(4), e0000810–e0000810. https://doi.org/10.1371/journal.pdig.0000810

AI does have an great ability in being able to look at images and being able to identify the image. It would be able to reduce any sort of human errors if the doctors are not to sure on how to diagnose the problem. AI should only be used to assist and not actually give a diagnoses.

Annotation: AI’s role in diagnosis could speed up care and reduce errors, but it also raises questions about trust and accountability in medicine.

Explanation: AI has the potential to transform healthcare by analyzing large datasets quickly and accurately, helping clinicians make better decisions. Surdu et al. (2024) explain that AI enhances diagnostic precision by identifying patterns in medical records and images that might be missed by humans. While this can improve efficiency and patient outcomes, it also creates ethical questions around trust, accountability, and the role of human oversight in treatment decisions. Ensuring responsible AI use will be key to its success in medical practice.

Reference Surdu, A., Budala, D. G., Ionut Luchian, Foia, L. G., Botnariu, G. E., & Scutariu, M. M. (2024). Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review. Diagnostics, 14(24), 2804–2804. https://doi.org/10.3390/diagnostics14242804

Cloud networks integrated with AI and ML are another great benefit to the medical field. Especially to doctors, allowing them to easily access patient information whenever they wish. Giving doctors and medical workers faster and easier workflow.

Annotation: This could completely transform preventative dental care, especially for people who can’t make it to the dentist often.

Explanation: AI devices can improve oral health by continuously monitoring a patient’s hygiene and giving tailored advice, potentially preventing problems before they worsen. According to Surdu et al. (2024), AI in dentistry enhances diagnostic precision and treatment planning by analyzing patient data to identify early signs of issues like cavities and gum disease. This kind of early detection could save patients time, money, and discomfort, especially those with limited access to dental care.

Reference Surdu, A., Budala, D. G., Ionut Luchian, Foia, L. G., Botnariu, G. E., & Scutariu, M. M. (2024). Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review. Diagnostics, 14(24), 2804–2804. https://doi.org/10.3390/diagnostics14242804

This sentence is important to understand. The more people rely on AI tools, the less they take the time to find and research on their own. This can lower their ability to find information and change the way they process information.

Addressing the moral ramifications of utilizing AI in tests, you raise a crucial concern. If algorithms are not properly developed and evaluated, they could end up in unjust grading or an inaccurate assessment of the skills of learners. Concerns about privacy also appear since AI systems often collect private student data which needs to be strictly regulated. Furthermore, if AI is utilized excessively, it may eliminate the need for human educators for certain jobs, which would have an effect on jobs. Ethical AI integration into instruction calls for striking the right chord between innovation and equity, transparency, and transparency.

While yes I do agree that this would be helpful to reduce any sort of mistakes, but it can't always be reliable. It would be easier to check for patients vitals, but if the power goes out this wouldn't work. It is very important for healthcare works to actually know how take vitals if any sort of complication were to happen. If they are to reliant on AI they can hurt them.

This use of AI could become a great tool for the medical field if it becomes efficient. Having AI become a preventative tool, instead of one that corrects mistakes, is a role that could save more lives than before. Having the potential to help people from a medical need that could seem "stable" but will only get worse over time. Or even perhaps a case where the patient has not even developed any symptoms, but will in the future.

This claim highlights the growing use of neural networks for enhancing the accessibility and adaptability of oral care. Tools powered by machine learning may assess brushing routines, diagnose any dental health problems early, and deliver comprehensive guidance on improving oral hygiene. Especially those those who live in rural or underdeveloped regions, online arguments mediated by computers offer access to credible oral advice.Technology encourages preventive care, lowers the need for visits in person, and enables patients with greater responsibility in conserving the condition of their teeth.

From the many ways AI can be used for, it can be used for educational purpose's like creating practical's through VR and simulations, allowing for the learning to be in a controlled and safe environment.

This reason I would agree is the most powerful factor of entailing AI into healthcare. Mostly all patients and family members of patients are willing to learn about their sickness and are overlooked/not given the full description of their sickness. This might be due to doctors/nurses not having the time to explain in depth and make sure patient fully deciphers information. AI can change this, with personalized information that is taken from patient data analysis, could be programmed to create an entire file on patient, so anyone with acess could learn and ask questions from.

Dave, M., & Patel, N. (2023). Artificial intelligence in healthcare and education. British Dental Journal, 234(10), 761–764. https://doi.org/10.1038/s41415-023-5845-2

Dave and Patel (2023) point out that AI tools like ChatGPT often generate information without reliable or verifiable sources, creating challenges for proper referencing and academic integrity. Because these systems draw from a huge amount of online data, they may produce inaccurate or defective citations, as the authors found when ChatGPT provided outdated or invalid references. This raises concerns about unintentional plagiarism and misinformation in academic writing. To address this, educators and researchers should verify all AI-generated content, use credible databases for citations, and teach students critical evaluation skills to ensure accuracy and ethical use of AI in scholarly work.

The authors caution that AI tools like ChatGPT make it easier for students to complete assignments without genuine understanding, especially in open-book or online exams. To address this, educators should redesign assessments to emphasize critical thinking, problem-solving, and clinical reasoning, as these are skills that AI cannot replicate. For example, analyzing patient cases or interpreting radiographs encourages original thought and applied knowledge. If students rely too heavily on AI, they may lose essential abilities like research, synthesis, and independent judgment. Therefore, integrating AI responsibly while reinforcing ethical use and reflective learning is key to maintaining academic integrity in healthcare education.

From the many ways AI can be useful; it can be used in a healthcare setting by using it to extract important and valuable intel from patients feedback, which can of course in return manage patient complaints.

Yes, these are powerful benefits to having AI as advanced as it is in medical care. Remote monitoring is the future of healthcare, when used correctly, it is proactive, personalized care that allows the patient have control in their health and can make them feel as the healthcare system is "on their side".

Dave, M., & Patel, N. (2023). Artificial intelligence in healthcare and education. British Dental Journal, 234(10), 761–764. https://doi.org/10.1038/s41415-023-5845-2

Dave and Patel (2023) acknowledge that while AI tools like ChatGPT can efficiently generate clear, factual text, their writing often lacks creativity, nuance, and emotional depth. This limitation becomes significant in healthcare education, where reflective and critical thinking are essential for clinical reasoning and empathy. Overreliance on AI-generated content may lead students to engage less deeply with material, weakening their ability to analyze, question, and synthesize ideas. Additionally, the absence of human tone or storytelling can make complex medical concepts less engaging or relatable, reducing motivation and long-term retention. Therefore, AI should complement—not replace—human creativity in learning.

AI could significantly reshape how scientific research is published and shared. AI tools can enhance efficiency by automating tasks such as plagiarism detection, reviewer matching, and data validation. These systems can also improve the accuracy and clarity of manuscripts by identifying errors or inconsistencies before publication. Beyond editing, AI can support reproducibility and transparency, helping ensure that published findings are trustworthy. Overall, the authors emphasize that, when used responsibly, AI can improve both the speed and quality of scientific communication in academic publishing.

Advances in artificial intelligence are beginning to transform the way scientific articles are published. AI can help streamline the peer-review process by automatically checking for plagiarism, detecting data errors, and suggesting qualified reviewers. These tools can also enhance the quality and consistency of reviews by identifying operational weaknesses and supporting data reproducibility. Additionally, AI presents opportunities for innovative publication formats, including automatically generated summaries and visual content. Overall, the authors suggest that AI has great potential to make academic publishing more efficient, transparent, and reliable.

Ethical issues in using AI for exams include bias in algorithms, privacy concerns, and the risk of reducing human involvement in evaluation. If the data used to train AI are biased, some students may be graded unfairly, and weak data protection could expose personal information. Experts recommend that schools weigh AI’s benefits against these risks and create clear rules to keep assessments fair. Universities should also teach students about responsible AI use and honesty in academics to ensure technology supports fairness and trust in medical education.

The use of AI can be used for education but also to an extent. It's important to still keep in mind about academic integrity. Students must still be responsible and have ethics when it comes to using AI for school. Making sure they're not plagiarizing information and knowing that what they need to learn is for their future career.

AI in dental education increasingly uses adaptive quizzes and serious games to enhance engagement and long-term retention. These tools apply machine learning to tailor question difficulty, provide instant feedback, and simulate clinical decision-making in a safe environment. Studies show that game-based and AI-assisted learning improves students’ diagnostic accuracy and motivation compared to traditional formats. Reviews further suggest that gamified, retrieval-based learning supports better knowledge retention when paired with timely feedback. Overall, AI-driven quizzes and educational games make dental education more interactive and personalized, strengthening learning outcomes.

This paragraph explains that hospitals can deploy AI technology to anticipate when their machines will most likely fail. The technology analyzes data from medical devices to proactively identify indications of potential failure. This is similar to how your phone or computer reminds you when to charge your device or update to the latest operating system. Maintenance can occur prior to a failure which allows hospitals to avoid equipment breakdowns that delay patient care. Even when equipment does the fail, patients and staff feel more confident about the equipment being properly maintained. This proactive approach makes everything run more smoothly and makes the patient feel better about their care.

The use of AI in medical care would be a great benefit for healthcare workers. As it is stated in the paragraph, it helps doctors identify where there are issues that need improvement and provides general feedback that can help improve their skills. This helps ensure that the doctors are providing care for the patient to the best of their abilities, improving their skills to fit with new improvements in their field of care. With AI identifying where improvement is needed, it helps ensure that the patients are getting the best care, accurate diagnosis, and treatment.

As such, hospitals can implement artificial intelligence to maintain their equipment. AI evaluates data from medical devices and forecasts when there might be an interruptive failure, similar to how your phone suggests it’s time for a software upgrade or when the battery needs replacing. Hospitals can now repair or service equipment prior to a failure, preventing a breakdown, treatment delays, and improving patient satisfaction; even if the equipment fails, the prognosis that everything was okay until it failed brings more satisfaction for patient care.

The use of AI in diagnostic histopathology using image analysis is a great benefit because it can help speed up the process of analyzing the microscopic image and find abnormalities a lot faster than a human can. The use of AI in histopathology can also compare a normal tissue sample to the one that is being analyzed, and if any abnormalities are present, it can analyze what the abnormality is and make an accurate diagnosis of the abnormality and how it can be treated.

Being able to easily pinpoint areas that need improvement can allow for hospitals to take their patient’s feedback seriously and in a timely manner .

Just as AI can transform the medical education scene with increased efficiency and individualized help, AI comes with its own set of problems. It’s not perfect and just like any piece of technology, it can fail. This paragraph highlights the importance of having review processes and guidelines to ensure that the AI is being more helpful than not.

This line focuses on AI’s role in medication safety and management, analyzing structured data like prescriptions and vital signs enables AI to detect potential harmful drug interactions. This is useful for preventing medical errors, especially in cases involving multiple medications, and ones that support personalized treatment adjustments.

This sentence highlight applications of AI medical imaging, by allowing algorithms to analyze diagnostic scans, it may help in detection and the reduction of errors. It should be noted the term assist is used, AI is a tool that should be used in collaboration with clinicians and not as a replacement.

AI is very valuable in the ways that it can help caregivers do their job better. The potential AI has can help support improvement and growth in our doctors, but is not limited to this.

These two sentences show the support of AI in health care. AI has the ability to help with patient care by handling complaints efficiently, this means this could help the staff with their workload and also cater to patients faster than staff can from being busy.

The following paragraph demonstrates how AI technology has the ability to revolutionize medical radiology which serves as a vital diagnostic and treatment planning tool. AI helps doctors interpret medical images which leads to better diagnostic accuracy and reduced errors and improved patient results. The system provides efficient management of large imaging data which enables radiologists to make fast and precise diagnostic decisions (Dave & Patel, 2023). AI implementation in radiology needs complete analysis of operational changes and monetary implications and human specialist involvement to achieve the substantial benefits of this technology.

Dave, M., Patel, N. Artificial intelligence in healthcare and education. Br Dent J 234, 761–764 (2023). https://doi.org/10.1038/s41415-023-5845-2

This sentence underscores how AI is rapidly reshaping the landscapes of both healthcare and education. AI technology in healthcare systems provides accurate medical diagnosis and fast data processing and personalized treatment plans. The technology supports adaptive learning systems which provide automated feedback and customized curricula that adapt to individual student requirements (Dave & Patel, 2023). The implementation of AI systems creates two main challenges because it leads to human relationship loss and generates problems with algorithmic bias and data protection and system transparency. The author needs to present both positive and negative aspects in order to create an objective evaluation.

Dave, M., Patel, N. Artificial intelligence in healthcare and education. Br Dent J 234, 761–764 (2023). https://doi.org/10.1038/s41415-023-5845-2

The use of AI in dental and medical education shows how technology may improve learning effectiveness and security. Virtual simulations provide a safe yet realistic setting for skill development by enabling students to rehearse difficult operations without endangering patients. But these advancements also bring with them new difficulties, like less human connection and a reliance on robots to solve problems. No algorithm can completely replace empathy, flexibility, and ethical thinking, which are still necessary for true competency in the healthcare industry. Thus, rather than taking the role of human instruction, AI should be seen as a supplement to it.

Medical and dentistry students can safely rehearse complex procedures using AI-powered virtual simulations, which fosters skill development prior to actual patient interactions. This experiential learning is one of AI's most potent educational benefits. However, the worry about fewer human connections is legitimate; students could grow overly reliant on technology and lose their confidence in actual clinical situations. Thus, traditional therapeutic practice should be complemented by AI rather than replaced.

The authors speak of how AI in the field of radiology the potential has to provide more accurate diagnostic imaging by detecting abnormalities on X-rays and CT scans. This can save time and avoid human mistakes, especially in large hospitals. However, I think human experience is still required to interpret ambiguous results and provide empathy to patients. AI should be viewed as an auxiliary tool, but not a replacement for the radiologist's experience.

AI’s ability to analyze medical histories and lifestyle factors to offer personalized health recommendations represents a major step forward in preventive care. However, this personalization depends heavily on the accuracy and fairness of the datasets used. If the data contain biases or missing variables, the AI’s suggestions might mislead patients rather than help them. This paragraph made me think about how much responsibility healthcare professionals have when interpreting AI-generated advice.

This paragraph discusses the potential drawbacks of using artificial intelligence (AI) to generate exams or assignments. It points out that AI generated questions lack quality and creativity. Due to the questions generated by AI they might be too easy, difficult or not at all engaging for learners. This raises concerns about AI's effectiveness and its assessments in learning outcomes.

This paragraph explains how artificial intelligence (AI) contributes to the reproducibility of scientific research. And it also highlights that AI algorithms can analyze and validate scientific data to ensure that research findings are accurate and reliable. Having improvements in data verification and having a reduction of errors can help AI increase the quality of scientific publications and help decrease the number of retractions.

AI is being used throughout the university teaching. Professors can use AI to create plans that will help students be more engaged helping them learn at their own pace. AI can be used to see students data and seeing how they learn best. Having AI come up with ways that accommodate to each certain student. Once they have AI grade homework or any assignments. This can help student learn and even using AI as a tutor. Once they get any feedback they can use AI to help create plans and tutors for them.

This section explains the role of cloud networks in healthcare, showing how they make patient data storage and access more efficient and secure. By allowing providers to run AI and machine learning algorithms on remote servers, doctors can quickly access important information and use it to make better clinical decisions. It also highlights how cloud networks support remote access, meaning physicians can deliver care even outside traditional hospital settings, which improves timeliness and quality of care for patients

This sentence highlights how AI can strengthen the patient-provider relationship by making healthcare more transparent. When patients have access to their own health information and treatment details, they are not left in the dark and can actively participate in decision-making. This shift not only empowers patients to take more control over their health but also builds trust, since providers are seen as open and collaborative rather than withholding information. It shows AI’s role not just in clinical accuracy, but also in promoting equity and shared decision-making in healthcare.

The task environment includes four key components: consumers, suppliers, competitors and regulators.

Task environment consists of elements outside an organization that enable it to operate and that set the basic contact for these operations.

Mission statements involve problems, needs and or populations the agency serves, along with client outcomes to be expected.

What is the history of this organization? (mission statement, when was it founded, by who was founded, etc.) How would you describe the organizations identity, and is it congruent with its image? determine the organizations mission statements and values then from there look at it from an outsiders perspective.

The lakeside family service agency was orginally founded by the methdolist church. In the 40s and 30s it was the recipient of generous contributions from united way. in the 70s united way took prizitizng the service.

The organization became more focused on adherence to policies and procedures rather then achievement of appropriate case outcomes. ALL decisions about cases had to pass through and be signed by a supervisor.

1) growing population of the county 2) retirement of current management staff Brought in a professional in insurance, things quickly drifted from its original form. Noticeable changes in its structure, with defined work units, and reporting lines from entry level all the way to the director.

The digital age has permitted the public to exercise self-expression (via writing) in a way unimaginable in prior generations.

interesting dichotomy between a writers attitude in writing for an intended, intellectual audience vs an unintended audience; while writing for the blog, okolloh is focused on capturing her feelings/emotions however, she claims to be introverted when a book opportunity is presented

I feel like this is so important in the modern age of social media. anonymity allows individuals to be evil online without repercussions.

our thinking comes from the world, not just single thoughts conjured up by the individual

The idea that an audience sharpens thought brings up ideas of Thompson’s example with children solving puzzles

writing forces you to dig deeper into your thoughts

People post writing on the internet as a way to garner feedback through individuals who don't know them. The easier and most blunt way to polish your writing.

people write on the internet to get their voices out there, even if the writing isn't perfect, atleast they're expressing themselves.

An example of the "audience effect"

good examples as to why people in this generation get the "audience effect" we are in a era where opinions are normalized through the media and critiqued.

Description of what measures are used in such a research article is very helpful as the graphs used are helpful in knowing what is changing.

I find it interesting that we get a full description of the idea of involvement in such a different way than of what the technical parts of the article such as what AI, Augmented Reality, or Virtual Reality are presented.

More use of past tense. should also is used as a qualifier here to promote.

Passive voice was used through the entire article.

Small description of something that it shortened for the most of this article. Bolded however to encourage reading.

Passive voice use here.

Use of model to show the causes of our stimuli to response

Three different citations here but no attribution.

No attribution here just a link to the citations page

Description of the formatting of this article,

Example of passive voice as well as qualifier.

Past tense in the introduction section.

Article is from this academic journal, and is catered to all within the IT and CIS fields.

Easy to understand description of atmospherics.

I have not come across that. I have only come across an allergy to GPLv3 in particular. And all those companies are seemingly happy to continue shipping GPLv2(+), as the next sentence indicates re Apple.

I dunno. "Is this licensed as GPLv2-or-later (or compatible)?" still works (and is really the same question that was being asked all along)—nothing really has changed (except for the proliferation of projects that are a GPL for which the relevant answer is "no"—but, still, the question didn't change).

comment Music is part of every one culture .Music helps each culture to express their emotions as well as relax at times. Music is relatable to everyones culture. Music helps you to release emotions with dancing and singing and relating to the music that is playing .

comment... In the U.S. Americans are taught to be independent and to accomplish things on your own and also to use your own judgment of thought . Generally speaking i believe americans worker harder than other cultures believe.

question.. How do the passengers get on a public bus that never stops moving?

question .How do you learn to love some one you were forced to be with who is also allowed to have more than one wife?

the voice, tone and content of your work should be authentically yours and also at the same time reflect the same internal voice inside the mind of your target audience, down to what they tell themselves about your topic, and maybe even touching on the same exact thoughts and phrases that keep them up late at night

tone is usually reflected in the language that you choose to send your message with. In this case, you should be able to deliver your message using the words of the audience that you are targeting.

the best content for your audience is data and research that is uniquely relevant to your target audience. the longer you research your audience, the clearer your messaging becomes.

Introduction: AI is now recently everywhere but we still need humans

I didn't know that there are four collection data types in the python programming language. The four types are list, tuple, set, and dictionary. I also learned how important it is that you know the different types of lists because they all effect the outcome of the code differently.

It is hard to break something that already formed as 'norm' or usual thing in people's mind. The first reason is that people often ignore something they think that is normal or usual, so the true problem could not be seen by the society. Another reason is that people usually don't want to admit their mistakes even they knew they were wrong. Therefore, we need articles like this to drag the entire society's attention, and then could influence the 'rule makers' to change the current situation.

Hoffmann's concept of "data violence" resonates strongly with this chapter's discussion of how data practices encode social power. She argues that when engineers treat datasets as neutral, they overlook how design decisions--such as labeling conventions or exclusion of marginalized voices--can reproduce harm. I found this perspective particularly striking after reading the earlier part of chapter 4 on data collection and bias: it reframes technical errors not just as mistakes, but as moral and structural failures. It makes me think that ethical data work requires both tecinical literacy and historical awareness of inequality.

I am very new to programming and computer all this computer stuff. I had no idea that images are pixels with three different numbers. I wonder how many possible images you can change and manipulate with numbers.

This is definitely necessary to understanding because without perseverance we would get stuck at some point. perseverance is the only way to thrive in something.

I feel like this is totally me. I have a desire to understand and learn things that I don't understand. I seek to know and to find answers which motivates me.

personally it made the poem feel a little difficult to follow along with

the imagery is striking, it helps to create a scene in your mind.

the speaker is someone who lost their love, and can only look at a portrait.

the speaker doesn't have to be the writer, the writer can write from the perspective of a different speaker.

it makes you feel nervous and on edge, like something is waiting to get you

Tired, Sweating, Overworked the glass syrup container, sits on the edge of the counter, it falls, tumbles down, all over, my new shoes

needs carrier protein to work

I totally agreed with this idea. Sometimes people only want to hear what they want or come up an outcome that only benefit to them. In this case, people will try to find a reasonable explanation for their planned outcomes, which usually cause biases. The process and the solution are actually up side down in logistical procedure. To avoid this, we have to place our view in third person and sometimes need the peer-review process.

for the third girlfriend? or third poem for the same girlfriend?

an old memory of a childhood fishing trip with dads, uncles, cousins, and brothers

this feels beautiful, sad, and cold

* **What's the deal big? ** = que importancia tiene / que pasa

The annotation associated with this line references the Buddha’s Fire Sermon, and is where the line itself, and the idea of burning, is drawn from. Within the Fire Sermon, The Blessed One says, “All things are on fire. With the fire of passion, with the fire of hatred, with the fire of infatuation; with birth, old age, death, sorrow, lamentation, misery, grief, and despair are they on fire.” Fire and burning, within the sermon, are associated with feeling and sensation. “All things,” claims Buddha, “are on fire,” meaning all things, which are listed extensively throughout the sermon, are full of sensations and feelings. The passage claims further that “the learned and noble disciple conceives an aversion” for all sensation, and that said disciple must separate themselves, detach themselves, from sensation. Within the context of The Waste Land, the line “Burning, burning, burning, burning” comes at a point where the form of the poem is breaking down, and where references are becoming so intertwined it's difficult to know where you are. In that sense, sensations are everywhere yet nowhere. The sensations of the poem, which are so potent earlier in the section, become mixed up and muddled so that the reader, like the disciples of the Fire Sermon, have an aversion to those very same sensations. The Fire Sermon portion of The Waste Land follows the pattern of The Fire Sermon: attachment to sensation and sensation in everything, transformed into an extreme aversion to sensation. The chapter ends with the word “burning” sitting alone, uncapitalized. The single word ties back to the title, bookending the chapter with the teaching of the Buddha as the poem detaches from sensation.

This line immediately stood out to me as adding to the conversation on voice. I wonder if in general the Thames has been referred to with a female identity or with a male identity (I am finding conflicting things online). I am leaning towards a female identity—not only would this follow the pattern thus far of silencing female voices/stories/identities, it also seems to make sense to me in the way that London was founded on the Thames and here has a kind of mother role (like a part of mother nature, almost). Cities were often started around rivers because a river is navigable, and provides a defensive advantage and fresh water.

The speaker repeats this line three times. If the Thames is thought of as above, the speaker is silencing a primal force of nature, a silencing that far outdoes and at the same time solidifies those prior. It is also to be noted that the silencing taking place here is in direct relation to the rising up/over of the speaker’s voice—there is an apparent trade. The repetition seems to point to some resistance on part of the river. What is also interesting is the part in the third repetition “for I speak not loud.” This is not taken from Prothalamion. So if the speaker were just to speak louder then the river would not need to “run softly”?

Coming out a bit, it doesn’t make much sense to me that the river Thames runs so loudly. Wouldn’t all the noise be coming from the surrounding city, especially by the time Eliot is writing? So perhaps, then, this line functions as a kind of longing call, to a time prior, a happier time, a time when this would really be the case—when/what Spenser is writing about (fleeting even as he describes it). But this is an impossible reality. Perhaps this extends to the reference to Carpenter’s work—a fruitless reaching to his call for the land’s “own people to come and take possession of it,” and perhaps also to his more general detailing of the river/bodies of water as uniting and foundational in that way. This relates to an idea explored a while back with waste lands being communal lands. Or, alternatively, it is possible that, in the case of silencing the river, this role of the river is being erased completely.

Upon reading these two stanzas, it appeared to me that they both might be spoken by the same narrator. Specifically, the same voice appeared to be maintained throughout the stanzas: the same clipped rhythm, and habit of geographically tracing the events of the person's life indicates to me that the lines recounted the events of a particular female individual in TWL. From there, I began to unpack the narrative the speaker was describing. Two moments stood out to me in particular.

1a) Eliot’s phrase "Highbury bore me. Richmond and Kew / Undid me" mimics the lines spoken by the noblewoman La Pia in Dante's Purgatorio, in which she says: "'Siena made me, in Maremma I was undone" (Aligieri, line 134). She attributes her cause of death to her husband, saying “He knows how [I died], the one who, to marry me, / first gave the ring that held his stone’ (Aligieri, lines 135-6). Her “undoing” is the result of marital violence and betrayal, placing her among the many wronged women in The Waste Land—Philomela, Baudelaire’s unnamed sex worker, Ophelia—each undone by male lust, violence, or moral failure. However, in the waste land, the woman is undone not by violence in particular, but by the emotional futility of intimacy in the modern world.

1b) I discovered a painting by Dante Rossetti entitled “Pia de’Tolomei” while researching more on La Pia. In the painting, La Pia is captured as she fiddles with her wedding ring, surrounded by a lush scenery of ivy overgrowth and a fig tree, as well as a sundial, letters, a prayer book, and the rosary lying beside her. The religious objects no doubt serve as testaments to her devout faith, whereas the sundial likely indicates the passage of time, and perhaps in reference to the time passing during her suffocating and unfulfilling marriage with her husband. The surrounding botany also forms a striking contrast to the barrenness of Eliot’s waste land. As a fruit-bearing tree, the fig tree reflects the physical vigor and health of La Pia, as well as her fertility. By contrast, the ivy—often associated with climbing and clinging—suggests the confinement and isolation of her unhappy marriage.

2a) The speaker continues the same pattern of geographical mapping in the second stanza. It is here that the reader comes to most certainly understand that the voice belongs to a female speaker. She recalls an unfulfilling sexual encounter, dismissively calling it “the event,” followed by her partner’s promise of “a new start” (Eliot, lines 297–98). However, her partner only weeps afterwards. While La Pia is undone by betrayal and violence, the speaker is undone by the recurring disappointment in sex, and by the emotional sterility of her relationships. In both cases, women appear as passive victims of the shortcomings of intimacy and romantic relationships.

2b) The reference of “a new start” also echoes the poem’s larger preoccupation with fertility and regeneration, recalling the Fisher King myth. Yet the failure of this promise nods back to the spiritual barrenness of the modern world, in which intimacy is hollow, not sacred.

While reading a poem about thorn bushes, I realized that Hirsch is right, poems are like a sort of virtual reality. Something that you have never experienced first hand feels like a movie scene while being read just due to the language and imagery in the poem

The way you phrase your poetry means more than the words that you use

Mellet v. ireland was a milestone where the UN Human Rights Committee declared that banning abortion violates international law. It marks a shift towards viewing abortion not as an exception, but as a core human right.

This critiques the "limited grounds" approach, when abortion is allowed only in cases like rape or health risk. The authors argue that this still denies women full autonomy and treats reproductive freedom as conditional rather than inherent.

This case is a turning point that shows how international human rights principles directly influenced national law. It connects global norms to real world policy, showing how human rights language can redefine legal frameworks

I agree with this point. It's not enough to just pass a law saying abortion is legal if people still can't get it safely or afford it. I think this shows how human rights don't really mean much unless theyre actually put into action

This shows how international human rights can actually change real laws in different countries. I thinks its interesting how global agreements can pressure local governments to update outdated laws. It makes me realize how connected the world is when it comes to human rights.

Decision simplifies access to legal abortion for women and girls who became pregnant due to rape by removing the need for proof or judicial approval by relying international rights standards it holds the state accountable for ensuring timely and unimpeded access to abortion service.

I agree because it shows that international human rights groups are clear about how harmful absolute abortion bans are. They push laws that protect women's rights and health, especially in serious situation like rape or health risk. The fact that CEDAW has directly told the country to change its law highlights how important these protections are and.Human rights can drive real legal progress.

It shows how international human rights laws like CEDW really influence countries to help improve our abortion access. Spain's law is a good example of how the following global standards can lead to more freedom and better production for rights for women. Recognizing the special challenges. It also shows how important these agreements are pushing for a positive change.

I wonder who came up with the idea of annotating, and how they thought of it.

Because this is an online class, this can take the place of in classroom discussions between students. On top of students sharing their thoughts with each other, it also allows students to learn from each other.

Most organisms have the characteristic of living in groups, but only Homo sapiens live in groups to form a society.

The role or position of a species in its environment.

Our full name is now Homo sapiens sapiens, which means "wiser Homo sapiens," a subspecies of Homo sapiens used to distinguish it from earlier Homo sapiens (Homo sapiens neanderthalensis, the Neanderthals).(from internet)

Using Sumac as an example to tell us the conditions for living in communities

The study examined how humans live and emphasized that humans live in groups.

I am excited to make a lesson plan based on the class content.

I noticed we are given a grace period for some assignments.

I like that we are focusing more on how people from other cultures interact rather than reading maps.

Streaming services are more dominant than cable television today. Almost every show that you want to watch is now on a streaming platform.

这也有讲究啊

I feel like with tv and shows today there are so many shows of different genres chose from. But I do believe that cinema have strayed away from nonfiction.

This is where I think atmosphere has to play a big part when it comes to watching tv and cinema. When you’re watching tv at home you are more susceptible to distraction or even falling asleep. The comfort if your home is a big contrast compared to a theatre.

I feel like there is an assumption that people who watch tv are multitasking or distracted while watching. That’s the big difference between cinema. When at a theatre all of your attention is on the movie, causing you to be more immersed in the film.

The difference between TV and Cinema is the repetition that is developed throughout each media. Films being “closed system” is referring to how most films are portrayed. Often being predictable before the movie is over. This is due to the amount of time that the film is. The problem is introduced, characters go through some type of adversity, the climax happens, and then there is closure. With a TV show the problem can be extended through various episodes, adding depth and new doorways for other material to be introduced.

The difference between TV and Cinema is the repetition that is developed throughout each media. Films being “closed system” is referring to how most films are portrayed. Often being predictable before the movie is over. This is due to the amount of time that the film is. The problem is introduced, characters go through some type of adversity, the climax happens, and then there is closure. With a TV show the problem can be extended through various episodes, adding depth and new doorways for other material to be introduced.

News programs and soap operas have similar structure and effectiveness on their respective viewers. Both programs similarly display ongoing crises that may lead to cliffhangers. The only thing that separates them is how the information is being portrayed. The news is straight forward because it’s informational and soap operas use characters to relay the information.

!!!

I found this section particularly thought-provoking because it shows how neutral design decisions can quietly define who belongs in a system. As someone who has filled out many online forms as an international student, I've often experienced exactly what this paragraph describes--forms that assume every user lives in the U.S. or has a "first" and "last" name that fits English conventions. It reminds me that "fitting into the data" isn't just about usability but also about representation and identity. The example of address fields illustrates how technical defaults can privilege one group's reality while making others invisible. It makes me wonder how many times I've unconsciously adapted myself to technology, rather than technology adapting to me.

In the quiet woods, the bird captures the essence of Romanticism. Away from society, it finds its own voice in wild nature. Its lonely song reflects the speaker's deep sadness. Whitman turns the bird into a symbol of grief, showing how nature can share in human emotion.

In the opening lines, Whitman connects nature with a human emotion, which is an integral charactersitc of romanticism. The lilac, star, and spring season aren't just imagery, but reflections upon the poet's mourning for the death of Abraham Lincoln.

With this take I don't necessarily agree with the idea of the way they worded it .However i can say from the beginning of the internet it has gotten more advance to the point where it might seem as if it very hard to understand I can say It has also had impact on social norms and a influence in our communities.

Most of the data we see on the surface is provided by the users. Such as videos, profile pictures, what they captioned with, etc. Most data collected automatically isn't shown, such as your scrolling patterns.

Research what you are writing about to make a stronger argument in your favor.

makor take-away

why we need ot study the entire chain, with an emphasis on beneficiaries

yes! must lok at the intersections! holistic approaches!

omg that's shocking

მოცემული ბლოგი განხილავს და მაქსიმალური სიზუსტით აღწერს მაღალმთიან რეგიონებში არსებულ ყველაზე რთულ და აქტუალურ პრობლემას-ტერიტორიის მოსახლებისგან დაცლას. ბლოგის ავტორები გვაცნობენ შვეიცარიის ალპურ ზონაში არსებულ პატარა სოფელ ალბინენს. მოსახლეოობის სიმწირის პრობლემის აღმოსაფხვრელად სახელმწიფო იძულებული გახდა შეემუშავებინა ახალი ფინანსური დახმარების პროექტი, რომელსაც მათი აზრით უნდა გაეზარდა მოსახლეობის დაინტერესება და მოტივაცია ეცხოვრათ და კვლავ შეეტანათ ახალი სიცოცხლე მაღალმთიან რეგიონში. ინიციატივის შედეგებმა (სოფლის მოსახლეობა შემცირდა 273დან 262მდე) ცხადყო, რომ მხოლოდ ფინანსური წახალისება არაა საკმარისი ისეთ პირობებში საცხოვრებლად სადაც მწირია ინფრასტრუქტურული, სოციალური, კულტურული განვითარებისა და უზრუნველყოფის შანსები. ბლოგი პარალელეს ავლებს საქართველოს მაღალმთიან რეგიონებთან-სვანეთთან და თუშეთთან, სადაც ანალოგიური პრობლემები დიდი ხანია არსებობს. სოფლები იცლება ეკონომიკური განვითარების არარსებობის გამო. საქართველოც ანალოგიურად ცდილობს რეგიონის გაძლიერებას ფინანსური დახმარებებით, ეკოტურიზმის განვითარებით, თუმცა პროცესი შეუქცევადია, საქართველოს მთიანი რეგიონები ნელ-ნელა იცლება მოსახლეობისგან. ბლოგზე დაყრდნობით შეგვიძლია დავასკვნათ რომ მსგავსი პრობლემების აღმოფხვრა შეუძლებელია მხოლოდ ფინანსური სტიმულებით. აუცილებელია ინფრასტრუქტურის განვითარება, სოციალური ცხოვრების გაუმჯობესება, თუნდაც იმისთვის, რომ ახალი მოსახლეობა მარტივად ინტეგრირდეს გარემოსთან, ისეთი პროცესების უზრუნველყოფა, რაც გაზრდის კულტურულად და სოციალურად აქტიური ცხოვრების არსებობის შესაძლებლობას.

this stood out to me due to religion to this day is talked about when it comes to abortion. Some using religion to go against abortions. This intriguing due to the fact many religious people don't follow the rules of their religion to a tea, but when it comes to certain topics they pick and choose.

oop. that's a problem!

local = better without logging national = better with logging (more $$) international = better without logging

this is a great example of how it is much easier for people to see "value" in terms of $$. Even though there are numerous ecossytem services provided by the forests existing AND it hosts a biodiverse ecosystem, policymakers would STILL quickly turn to logging instead because it is more "profitable"

i wonder why they chose these cutoff dates in their model?

economic loss if converted to logging practices

[costs]

[benefits]

considering factors outside of just the obvious, direct impacts of logging

importance of larger-scale incentives

ვენეციის ფესტივალმა ოსკარის სეზონის ფავორიტები გამოკვეთა. მთავარი ყურადღება დუეინ ჯონსონმა მიიპყრო ფილმით The Smashing Machine, ასევე გამოირჩნენ ემა სტოუნი და ჯესი პლემონსი ლანთიმოსის Bugonia-ში, ჯულია რობერტსი After the Hunt-ში და ამანდა სეიფრიდი The Testament of Ann Lee-ში. ჩემთვის ვენეციის ფესტივალი წელს განსაკუთრებით ძლიერი იყო, დუეინ ჯონსონის გარდასახვა გამორჩეული მომენტი იყო, ხოლო ემა სტოუნი მის უნიკალურობას კვლავ ამტკიცებს. ვფიქრობ, ოსკარების სეზონი ამჯერად ძალიან საინტერესო იქნება.

making the argument that native America should be brought into the international society.

TLDR: Use Annotated

Cet extrait m'intérèsse!

Are golf courses and datacentres in the same place, and the same water basin though?

.

The data sample of Soulier et al. (36) was limited, in that it included only appellate cases and therefore did not include verdicts in state trial courts that are not appealed or cases settled before trial.

"Ultimately, we conclude that the courts converge on three themes of the duty to warn or protect: hold therapists liable only in obvious cases of negligence that result in harm to a victim; recognize when a state has a permissive statute, rather than an obligatory one; and do not hold therapists liable for violence that occurs well after the termination of therapy (37). We note that these narrow interpretations of therapist liability stand in contrast to earlier rulings that ignored the language of the statutes and interpreted broad liability, such as cases in which therapists were held liable for motor vehicle accidents that occurred months after termination of therapy"

"Mental health professionals were exonerated on the following bases: no imminent threat was communicated to a therapist about an identifiable victim; the victim was already aware of the danger; or the therapist warned the victim, but the victim took actions that went against the warning."

having the same boundaries or extent in space, time, or meaning.

coexistance

Tamara Lich’s imprisonment highlights how stakeholder power and legitimacy can shift when activism crosses into perceived disruption, challenging governance boundaries between civil liberty and public order. Her case underscores the need for leaders to manage high-salience stakeholders through dialogue and transparency before conflict escalates into legal or ethical crises.

This event illustrates how a single stakeholder group, when feeling unheard, can evolve into a powerful collective actor influencing national policy and public perception. It reminds leaders that in stakeholder management, silenced voices don’t disappear; they organize, and effective governance must engage early, transparently, and empathetically to prevent polarization.

This passage reveals how stakeholder influence can lead to bias when power and visibility overshadow ethical responsibility. The media, an essential stakeholder in any governance ecosystem, holds the power to shape narratives and public opinion; however, with that power comes a duty to uphold fairness, empathy, and transparency. When media discourse becomes punitive or moralizing, it silences legitimate concerns and narrows the scope of democratic dialogue. In stakeholder management, a balanced approach recognizes that even dissenting groups deserve representation and respect. Excluding or shaming them undermines both legitimacy and trust: two pillars of ethical governance. From my perspective, governance must never frame disagreement as defiance. Instead, it should protect freedom of choice and expression as part of the stakeholder landscape, ensuring that communication, even when tense, remains grounded in dignity and respect.

This passage touched me deeply because it reminds us that behind every policy are individuals with unique needs that can easily be overlooked. In stakeholder management, we often focus on groups with high power or urgency; however, this scenario reminds us that legitimacy and vulnerability also demand attention. Students with special needs are stakeholders whose voices are seldom heard directly; yet, the consequences of decisions profoundly affect them. Mitchell et al.’s salience theory encourages managers and leaders to evaluate who matters, and this must include those who may lack voice but not value. In governance, sensitivity toward small or marginalized groups is not an act of charity; it’s a matter of justice and ethical accountability. When decisions involve health, accessibility, or education, equity necessitates more nuanced solutions than one-size-fits-all approaches. Effective governance notices the quiet stakeholders, those whose well-being depends on thoughtful exemptions, flexibility, and empathy.

Reading this moment, I felt both the weight and vulnerability of leadership. When emotions take over reason, leaders must carry not only the decision but also the temperature of the room. Chair Evans’s calm firmness demonstrates how emotional intelligence can become a governance tool. It’s not about silencing opposition but protecting the integrity of the process. In any stakeholder environment, whether a public board or a community meeting, trust grows when leaders manage disagreement with empathy and restraint. I’ve seen how a composed tone, a deep breath, or even a respectful pause can shift an entire discussion. In crisis moments, the most effective authority is not control; it’s a steady presence.

From experience, I’ve learned that the goal of governance isn’t perfect agreement; it is a shared understanding. When people feel their perspective has been heard, they become more open to compromise. Even during polarized moments, creating structured space for every stakeholder builds trust that lasts long after the vote is done.

This small detail says a great deal about inclusion. Student voices were heard but not counted. In stakeholder terms, they had legitimacy but no power. I’ve seen similar imbalances, with younger or less experienced members being invited for diversity optics rather than genuine influence. Meaningful participation means ensuring that every voice has weight in shaping outcomes, not just being present in the room.

When governance collapses into shouting, it’s a sign that the process has lost legitimacy. I recall that, in our school’s committee, before reaching a consensus on the mask policy, we first agreed on the rules of discussion: respect, turn-taking, and focusing on shared goals (protecting students). Once stakeholders feel respected, they are more likely to listen. It’s never just about the decision; it’s about how it is made.

This passage captures a deep clash of epistemic worlds: lived experience versus data. As someone who worked on decisions where evidence confronted beliefs, I’ve learned that truth doesn’t speak for itself; it must be translated. Stakeholder management here means listening with empathy, not superiority. It’s not about who is right, but about how to rebuild trust across different forms of “knowing.”

Promises that stretch beyond their limits create long-term distrust. In any governance structure, whether a school, a regulatory body, or a government, credibility is fragile. Once people feel deceived, they stop listening, even when the science is solid. In stakeholder terms, legitimacy erodes faster than it can be rebuilt. I’ve seen how transparency, even about uncertainty, is the only way to maintain engagement in times of crisis.

It's striking how a simple public health tool turned into a symbol of identity. During the COVID-19 pandemic, I observed the same polarization within my kids' Catholic French school committee in Lebanon. Masks weren't just medical; they represented belief, trust, and even belonging. In moments like this, stakeholder management becomes emotional negotiation. It is crucial to understand that each position is rooted in fairness, religious beliefs, and personal values. I learned that leadership in polarized spaces isn't about convincing; it's about creating space for dialogue without judgment.

high-rank LoRA and FullFT have identical curves. Medium/low rank fall off when they hit capacity limits. This is the visual proof of the main claim.

contradicts common practice of attention-only LoRA!

Key practical finding, multiply by 10 when switching, at least until a better method is identified...

Rank 1 is enough for LoRA when doing RL! Huge computational benefit!

Not just matching metrics - behaviors match too further strengthening the claim that LoRA is as robust as Full

For 2. The fact that training efficiency is worse seems to indicate that we somehow keep on refining the combination of components that we encode to better fit the dataset, but still have the fundamental limitation of not enough directions. For 3, this is not quite understood or explained well, only the throwaway line regarding the product of matrices with no explanation

Rather than focusing on specific samples, this paper looks for generalizable patterns

The LR may be a product of the initialization more so than the inherent properties of the two methods.

Here remember the "bits" argument for before O(1) for RL, O(tokens) for SFT

This is the way to estimate information content of your dataset. ~1 bit/token for typical LLM data

The capacity predictions are still rough , would want a way to estimate the rank needed given dataaset and model sizes. Would want to better understand the LR to choose more than "10x the one for SFT" + How do you even find the one for SFT in the first place?

Even beyond the memory and adapter benefits, we have also computational benefits in training

This is the core of the paper, we have a mismatch between dataset size and model size whenever we do post training

@Valentin These forest plots are really hard to read, it's so dense without spacing. Let's work together on some ways of making it more informative.

I'm also puzzled as to why so many papers are shown only one type of rating and not the other. I know that some of our evaluators did not give ratings like this, and in some cases, we didn't even encourage it. But why is it missing for some of the llms? Did it just not have time to finish processing it?

Maybe it's a display issue? It seems that the papers that were rated highest in terms of these tiers by the human raters did not get rated by the LLMs. Or maybe it just didn't show up in the graph?

Richard Sutton page, lists more articles than the folder I found.