Prompt: I want a comprehensive research paper on the history of probability problems involving circles and stochastically selecting points or lines across the circle's circumference. As an introduction, start off by explaining in depth the solution to the following problem: "7 points are randomly chosen on the circumference of a circle, what is the probability that they all lie within a semi-circular arc (that is an arc half the circle's size)?" and then provide related problems and their solutions and a general solution methodology for this style of problem. Then provide a history of interesting problems along these specifications, specifically I would like you to give me an overview of the lazy caterer's sequence and the n cuts to a cake problem.

The response states the exact probability that 7 random points all lie within some semicircle as 7/64 (≈0.109375).

The response derives the solution (p = 7/64) result by fixing one point (or an equivalent symmetry argument) and notes the general formula P(n)=n/2^(n−1) for n points.

The response provides at least two additional probability problems involving random points, lines, or chords on a circle and supplies their complete solutions (e.g., when is a random triangle on a circle acute, the probability all n points lie on arc of fixed length, probability a randomly inscribed k-gon contains the center, probability the center lies in the convex hull of n points).

The response explains a general solution methodology for this class of circle-probability problems (e.g., rotational symmetry, fixing a reference point, combinatorial counting, order statistics on the circle).

The response provides a historical overview that names and briefly describes at least three notable circle-based probability problems (e.g., Bertrand’s Paradox, Buffon’s Needle on a circle, the random chord problem, Sylvester's four-point problem for circles).

The response defines the lazy caterer’s sequence, provides its closed-form formula L_n = n(n+1)/2 + 1, and lists at least the first five terms (1,2,4,7,11).

The response describes the “n straight cuts to a cake” problem and states that the maximum number of pieces produced by n cuts follows the lazy caterer’s sequence.

The response is presented in the form of a research paper with clearly labeled sections, including an Introduction that starts with the 7-point semicircle problem, plus separate sections for Related Problems, Methodology, Historical Background, Lazy Caterer’s Sequence / Cake-Cut Problem, and a Conclusion (≥5 section headings in total).

The response omits unrelated mathematical topics (e.g., probabilities on polygons as opposed to circles, Pólya's enumeration theorem, permutation groups, topology) and stays within the scope requested by the user.

The response must use mathematical notations to express probability calculations and geometric relationships, including formal definitions and equations for the circle problems discussed.

The response provides at least two frameworks to solve the 7-point problem (e.g., dividing the circle into 2𝑘 equal sectors, broken stick approach, anchor point, brute force solution treating all points as random variables).

The response details at least two common pitfalls or incorrect deductions when solving the 7-point problem (e.g., failing to consider any of the n points as "leading", failing to treat the placement of points as independent, treating the circumference of the circle as an important variable, proceeding by induction but not establishing a base case).

The response explains briefly how f(n) = f(n-1) + n reduces down to (n^2+n+2)/2 for the caterer's sequence.

The response mentions OEIS, the Online Encyclopedia of Integer Sequences.

The response connects the caterer's sequence to Pascal's triangle (i.e., the sequence is the sum of the first three entries in row n of Pascal’s triangle).

The response gives the cake number's formula as (n^3+5n+6)/6.

The response gives the recurrence relation Cake(n) = Cake(n-1) + caterer(n-1).

The response generalizes the caterer's sequence to N dimensions correctly as R(n,d) = sum over i from 0 to d of n choose i.

The response highlights the importance of exclusivity in the 7 point problem solution (i.e., we count configurations by anchoring each semicircle at a sampled point).

The response mentions at least two related integral statistics ideas (independence, Principle of Inclusion Exclusion, Bayes theorem, Markov chains) in context of the problems discussed.

The response presents the historical problems chronologically.

The response mentions the problem of Buffon's Needle (i.e., we drop a needle of length L onto a floor marked with parallel lines spaced D apart (D ≥ L). What’s the probability p the needle crosses a line?).

The response presents the formulae for the Lazy Caterer Sequence and the Cake Numbers without any derivation or explanation of their terms.

The response provides the solution to Buffon's Needle problem (i.e., p = 2L/(\pi D)).


Prompt: I’m a free-to-play Clash Royale player sitting at 5200 trophies (King Level 40). I’d like to climb to at least 6500 trophies within the next three months without spending real money. Write a practical strategy guide that lets me do this while keeping my in-game resource use efficient.

The response mentions that the player should not focus on powerful but expensive card types (Champions: Archer Queen, Skeleton King, Golden Knight, Mighty Miner; Legendaries: Miner, Mega Knight, Electro Wizard, Lava Hound; Epics: Golem, P.E.K.K.A., Bowler, Baby Dragon) and should instead prioritize lower-rarity cards that are easier to upgrade as a free-to-play player.

The response suggests the Classic Challenge entry (whose entry cost is 10 gems) and explains that achieving 6 wins provides more efficient card and gold rewards than buying shop chests, and thus more suitable for a free-to-play player.

The response describes the current season reset formula (at the end of every season, players above 5,000 trophies get reset 50% of the way back to 5,000) and explains that the player will likely be reset twice and should therefore aim for a trophy break well above 6,500 before the final month's reset to meet their goal.

The response states that the Classic Challenge reward cap is 12 wins, and explains that the player should plan their gem spending around this cap since the maximum reward of 2,000 gold and 100 cards offers better long-term values than gem uses.

The response supplies at least two full 8-deck card list that are cheap/common for a free-to-play player (e.g.: deck 1: Hog Rider, Musketeer, Cannon, Ice Spirit, Fireball, Log, Skeletons, Archers; deck 2: Miner, Wall Breakers, Bomb Tower, Valkyrie, Magic Archer, Poison, Bats, Log; deck 3: Royal Giant, Fisherman, Mother Witch, Hunter, Lightning, Electro Spirit, Fireball, Skeletons; deck 4: Lava Hound, Balloon, Tombstone, Mega Minion, Fireball, Zap, Guards, Inferno Dragon).

The response describes a card-upgrade priority list ranking for at least five cards (e.g: ordered by efficeint gold use: upgrading the primary win condition first, then key spells, defensive buildings, support troops and finally cheap cycle cards) as a roadmap for player's progression (e.g.: 1. Hog Rider; 2. Fireball; 3. Cannon; 4. Musketeer; 5. Skeletons; 1. Miner; 2. Poison; 3. Bomb Tower; 4. Magic Archer; 5. Bats; 1. Royal Giant; 2. Lightning; 3. Fisherman; 4. Hunter; 5. Electro Spirit; 1. Lava Hound; 2. Fireball; 3. Tombstone; 4. Mega Minion; 5. Zap).

The resource lists at least three gold-earning or saving methods to enable the player to manage their resource (e.g.: complete all daily and special quests; join an active clan to maximize war chest and donation gold; avoid overspending on shop chests and cosmetic items; prioritize upgrading only cards used in the main deck)

The response recommends saving Gems for Classic or grand Challenges rather then spending on cosmetic items and explains that Challenges provide significantly better long-term return in cards and gold for free-to-play player.

The response suggest the player to participate in Clan Wars 2 to earn steady gold, cards, and trade tokens.

The response provides at least three tactical tips to improve match performance  (e.g.: practice elixir counting to know when the opponent is low, track your opponent’s card cycle to predict defenses, make calculated tower trade-offs to gain elixir or counter-push advantage, place troops to activate King Tower when possible)

The response includes a substution guideline for player to swap in lower-rarity or better-leveled alternatives when missing high-level version of suggeted cards to not lose core strategies  (e.g.: replace Log with Arrows; replace Miner with Hog Rider; replace Inferno Dragon with Inferno Tower; replace Magic Archer with Musketeer).

The response suggests that each deck should contain at least six Common or Rare cards to keep the deck free-to-play friendly and easier to upgrade.

The response mentions that free-to-play players should focus on a single well-leveled Champion card in their deck rather than spreading their resources across multiple Champtions and provides at least one example (e.g.: (e.g.: Skeleton King as a win condition; Archer Queen as a strong support card; Golden Knight for dash-based bridge pressure; Mighty Miner for tank control and lane pressure).

The response provdies at least 2 sample strategies to enable the player to avoid unnecessary upgrades that waste gold (e.g.: not upgrading cards just to complete collection levels, avoid spending golds on rarely used Epics, save gold by skipping cosmetic-start leves, prioritize only the 8 core deck cards and well-chosen substitutes).

The response provides at least one tip on using trade tokens efficiently to maximize the player's ability to upgrade specific cards (e.g.: use trade tokens to acquire cards for your main win condition; trade away surplus cards you don’t plan to level; prioritize trades for high-rarity cards like Legendaries or Epics that are harder to collect; save tokens until you know exactly which deck you will commit to upgrading).

The response spell out all game-related abbrieviations and acronyms on first appearance (e.g.: RG: Royal Giant, CC: Classic Challenge, AQ: Archer Queen, Loons: Balloon)

The response is organized into sections with clearly labeld headers.

The response provides a timeline of trophy targets with weekly or monthly milesteones to track progress towards 6,500 trophies in 3 months (e.g.: end of month 1 → 5,800 trophies; mid-month 2 → 6,200 trophies; end of month 2 → 6,400 trophies; final month → peak above 6,500 trophies before reset)

The response provides some suggestions for player to do after reaching the target trophies (e.g.: switch focus to leveling secondary decks, start saving gold and trade tokens for future metas, practice in Classic Challenges to refine skills, set the next trophy milestone such as 7,000 trophies)

The response makes any mention of incorrect game mechanics to play Clash Royale (e.g.: Champion cards are unlocked at King Level lower than 33, Legendaries cards can be unlocked before Arena 4, Pass Royal is free)

The response makes incorrect references to the player’s stated request (e.g.: suggesting the player spend real currency to buy in-game boosts, recommending reaching 7,500 trophies instead of the stated 6,500 goal, advising strategies for a pay-to-win account rather than free-to-play, proposing upgrades or features not available at King Level 40).


Prompt: Please make a plan for my student group's end of year banquet, including a specific venue and a specific menu from a caterer. We need a nice venue near Berkeley, CA with a projector for slides. There are around 30 people attending. We also need to cater food that accommodates the following dietary restrictions: 2 egg allergies, 2 peanut allergies, 1 dairy + nuts + shellfish allergy, and 1 vegetarian. The total budget for the banquet is 2500 dollars, with a hard cap of 3000 dollars. Do not factor in transportation in the budget.

The response proposes a real venue that is within 10 miles of Berkeley, CA.

The response proposes a real venue that has capacity of at least 30 guests and offers seatings and tables for banquet style dinner.

The response proposes a real venue that allows outside food and drink or supplies them in part of an all inclusive package.

The response proposes a real venue that provides a projector or built-in A/V equipment suitable for slide presentations.

The response proposes a real venue that is appropriate ambiance for an end-of-year celebration (e.g. professional garde, unique, memorable, historic).

The response provides the price of the venue which is within 10% margin of error from the actual price.

The response proposes a real caterer that services Berkeley, CA, and is eligible for the venue.

The response proposes a real caterer that supports dietary restrictions including: egg, peanut, dairy, nuts, and shellfish allergies and vegetarian.

The response proposes a real caterer that services a banquet-style menu (e.g. more elevated food, appetizer-main-dessert course style, more suitable for plated, not fast food)

The response provides an actual menu from the caterer and accurately indicates which dishes are egg-free, peanut-free, dairy-free, nut-free, shellfish-free, and vegetarian.

The response provides the breakdown of the price from the caterer (e.g. price per person, price for main, price for dessert, delivery fee) which is within 10% margin of error from the actual price.

The response's suggested amount of food catered is suitable for 30 people.

The response provides a final budget that has an accurate breakdown consisting of venue, catered food, service/gratuity, and other relevant miscellaneous fees (e.g. insurance, AV equipment, decorations, beverages, delivery, cleaning/disposables, contingency funds).

The response provides a final budget which includes any transportation costs.

The response provides a final post-tax and tip budget that is strictly less than $3000, and if the budget is more than $2500, the response acknowledges that it is over budget but under hard cap.

The response provides the final budget breakdown in a well structured format like a table for readability.

The response states relevant logistics (e.g. reservation time window, deposit, minimum charge, cancellation) for the venue and the caterer if applicable.

The response mentions days and hours the venue and the caterer operate respectively and recommends a window of time when both the venue and the caterer operate.

The response discusses action items which includes contacting the venue and the caterer for availability and confirming the price and logistics.

The response provides an alternative plan that does not align with any one of the provided requirements: venue near Berkeley, CA, with a project for slides that accommodates 30 people, caterer that supports dietary restrictions, and the total budget under $2500 with a hard cap of $3000.


Prompt: Imagine you're launching a Gen Z focused startup in 2025 that offers short-form video therapy and mental wellness content developed through a TikTok-style mobile app. Write a detailed market research and business strategy report that covers: (1) the competitive landscape in mental health tech and how your idea differentiates from apps like Headspace, Calm, and BetterHelp; (2) user acquisition strategies that appeal specifically to Gen Z, with references to relevant media usage statistics, content formats, and platform behaviors; (3) ethical considerations and potential regulatory challenges, including how you would handle moderation, clinical oversight, and data privacy for a young audience. Your report should cite trends in the digital wellness, mental health stigma reduction, and social media driven habits.

The response identifies at least three psychological needs or stressors that are especially relevant to Gen Z and supports each with a clear, concrete example (e.g. “academic pressure” illustrated with statistics on exam-related stress, “loneliness” and "FOMO" tied to social media use patterns, “financial insecurity” linked to therapy cost barriers).

The response proposes at least two specific short-form content formats that align with Gen Z digital habits (e.g. day-in-the-life storytelling, reaction memes, duets, challenges, POV skits, trending sound remixes, stitched expert responses) with explanations for their effectiveness.

The response analyzes the mental health tech competitive landscape by comparing at least three attributes (e.g. key features, pricing, audiences, positioning) of apps like Headspace, Calm, and BetterHelp.

The response articulates how the application will differentiate itself from existing wellness content platforms with comparative analysis.

The response cites at least four distinct, credible sources supporting claims about Gen Z behavior, mental health, or media consumption (e.g. .edu sources, NIMH, NAMI, AAP).

The response explicitly discusses at least two risks of the short-form video therapy and mental wellness content (e.g. misinformation spreading, data privacy breaches, exposure to triggering content, over-reliance on self-help instead of therapy).

The response includes at least two ideas for risk mitigation strategy (e.g. clinical vetting of content, strong encryption and compliance with HIPAA/GDPR, moderation and trigger warnings, clear disclaimers and referral pathways to professional help).

The response outlines a plan for clinical trials, pilots, or efficacy testing to ensure clinical validity of mental health content.

The response presents at least one detailed Gen Z–specific use case or user persona, including key attributes of the user (e.g. demographics and life stage - high school student, first-year college student, early career worker; psychological stressors or needs - exam anxiety, social isolation, financial stress, identity exploration; digital behaviors - TikTok use, meme culture, preference for authenticity/lo-fi content; how the proposed app addresses these needs through its features or content).

The response incorporates trends or habits specific to Gen Z media consumption (e.g. short-form video preference, mobile-first approach, interactive content).

The response identifies at least three specific and relevant metrics or KPIs, covering both business performance (e.g. DAUs, retention, CAC, viral shares) and wellness/clinical impact (e.g. stress reduction, PHQ-9, GAD-7, engagement with coping tools).

The response suggests a responsible moderation or comment policy for mental health videos.

The response includes mention of cultural or regional diversity within Gen Z and how content may adapt.

The response uses clear section headers and logical structure to separate the three required areas of the report (e.g. Competitive Landscape & Differentiation, Gen Z–Specific User Acquisition Strategies, and, Ethical & Regulatory Considerations).

The response supports every claim with evidence (e.g. empirical data, research results, expert's claim).

The response claims or implies that short-form content alone is sufficient treatment for mental illness.

The response fails to cite any sources to support psychological or demographic claims.

The response describes content formats that would violate community guidelines or pose harm to users (e.g. trauma dumping, graphic self-harm confessions, unmoderated peer-to-peer therapy, promotion of unsafe coping mechanisms).

The response provides inaccurate, unfounded data about Gen Z habits or mental health stats (e.g. “over 70% of Gen Z are clinically depressed”, “Gen Z spends 12 hours a day on TikTok”, "90% of the population has mental illness").

The response uses inappropriate humor or tone that trivializes mental illness, undermining the seriousness of the topic.

The response over-indexes on branding/monetization and ignores user needs (e.g. over 1/3 of the entire response is devoted to branding/monetization/talks of profit and revenue, need to spend millions of dollars to acquire new users during product market fit phase, need to spend millions of dollars on creating logos).

The response provides at least one visual structure (e.g. a table, flow diagram, matrix, or chart) that clarifies the app’s content flow, engagement model, or competitive positioning, and the visuals go beyond decoration and add clarity to how the app works, how users engage, or how competitors compare.


Prompt: Help me compile a list of apartments in San Francisco (looking for at least 2 bedroom, 1 living room, 1 bathroom, 1 kitchen). For context, I am moving to SF for just the summer (about 2-3 months) for work--ideally I want the apartment to be around central SF due to close proximity to the office--and am completely new to the area. Also, I'm a student, so realistically my individual budget for rent is at a max of $2200 per month (I want an apartment with minimal additional fees/costs). I plan to move in with one cat, and am also looking for roommates (around 1-2) to split the cost. I am also bringing a car, so I will also need to find parking spots. I also really prioritize safety (in terms of the area) and exercise (local gym or, even better, if it's offered by the apartment complex). I'm honestly not too sure how much I will spend overall because I want to be as close as possible to most sightseeing places and attractions in SF to gain as many new experiences and friends as possible over the summer.

The response clearly discerns that the total rent per person per month does not exceed $2,200, and therefore the total cost for apartments with 2-3 bedrooms should fall within the range of $4,400-$6,600.

The response shows two ways to find roommates (e.g., online platforms like Roomster or SpareRoom, leveraging social media groups (e.g., university-specific Facebook pages), using a university's dedicated roommate-matching service, or asking within a personal network of friends or coworkers).

The response analyzes different ways to split rent when the student has one roommate in the case of a two-bedroom apartment (e.g., the rent is divided evenly, one roommate pays more for a larger bedroom, one person covers utilities while the other pays a higher portion of the base rent, the rent is adjusted to reflect one person having a private bathroom).

The response mentions possible rent-splitting arrangements if the student has two roommates in the case of a three-bedroom apartment (e.g., the total rent is divided equally among three people, the cost is tiered based on bedroom size or amenities such as a private bathroom, one person pays a larger share for a master suite, one person covers shared household expenses while the others contribute more toward rent).

The response discusses safety by referencing various methods for evaluating a neighborhood's crime statistics within a certain radius (e.g., official crime rate data from police department websites, real-time alerts from apps like Citizen or Ring, anecdotal evidence gathered from asking local friends or searching online forums, data from third-party safety score websites).

The response list at least 2 methods of contact to reach the landlord/landlady of each apartment complex (e.g., email, phone number, online applications, link to website)

The responses includes an apartment with a long-term apartment lease (longer than time range given in the prompt, e.g., a 1-year lease) on the list of recommended apartments for the student

The response discusses at least 3 specific attractions/locations that are pet-oriented for the user to visit in his free time in San Francisco (e.g., parks, grooming, vet, pet stores)

The response discusses at least six prominent San Francisco neighborhoods known for their cultural or historical significance (and thus well-suited for sightseeing), mentioning key attractions and their typical commute distances to downtown (e.g., North Beach for its Italian heritage and proximity to Coit Tower, Haight-Ashbury for its 1960s counterculture history, the Mission for its vibrant murals and historic Mission Dolores, Chinatown for its iconic Dragon’s Gate, Japantown with its Peace Pagoda and unique cultural centers, Fisherman’s Wharf with its sea lions and historic piers).

The response discusses potential perks and features that may be offered by each apartment (e.g., access to a 24/7 concierge or doorman, a full-access mailroom with email updates, on-site co-working spaces or work pods, unique lifestyle amenities like a rooftop deck, a pool, a FITNESS SF center).

The response discusses food options near each suggested apartment neighborhood or location (e.g., grocery stores, restaurants, fast food places like Burger King, healthy options like Supergreens, and casual spots like Chipotle or Panda Express).

The response warns the user about at least 1 potential scam they might encounter during their apartment rental search (e.g., listings that are unavailable, appear too good to be true, lack contact information, have addresses that don’t match on Google Maps)

The response recommends at least 3 potential gym options for the user, including both nearby commercial gyms and apartment-included gyms (e.g., luxury buildings like Solaire have two in-building gyms accessible to residents, while older apartments in Hayes Valley may be a five-minute walk from commercial gyms like FITNESS SF, which charges a monthly fee of around $100, more budget-friendly options such as 24 Hour Fitness, or specialized studios like Orangetheory Fitness for strength training or Pilates).

The response provides quantifiable information in at least two instances, selecting any two from the following categories: rent, square footage, number of bedrooms, or permitted number of roommates.

The response provides apartments that have at least 2 bedrooms, 1 bathroom, 1 kitchen, and 1 living room (an apartment must meet all conditions here in order to meet the specifications set by the user in their prompt).

The response discusses the overall social culture of each apartment complex (e.g., the typical noise levels on weekdays versus weekends, the presence of resident community activities like social hours or holiday parties, the availability of shared spaces that encourage interaction, the general demographic of the residents (e.g., young professionals, families, students)).

Response mentions at least two central San Francisco neighborhoods (e.g., SoMa, Mission, Hayes Valley, Nob Hill, Lower Pacific Heights) in proximity to central San Francisco.

The response outlines the timelines for each listed apartment that is recommended (e.g., total lease duration, when rent is due, potential move-in dates, move-out dates, response deadline for claiming the apartment)

The response acknowledges at least two factors that may generally affect the availability of an apartment listing on its respective website (e.g., high demand, seasonal fluctuations, pending leases, recent price changes).

The response discusses at least two insurance or legal considerations for renting apartments in San Francisco (e.g., the common requirement for renter’s insurance to cover personal property, liability, and additional living expenses in case of a covered loss, the importance of understanding the lease agreement, including clauses related to subletting, guest policies, or early termination fees, and legal protections afforded to tenants in California, including a landlord’s responsibility to provide a habitable living space and state laws on rent control and eviction, which may vary depending on the building’s age and the specific lease type).

The response develops an estimated potential budget outlining how much the user might spend in at least 6 different categories of expenses (e.g., utilities, groceries, rent, or any other additional expenses that the student should be prepared to pay throughout their stay).

The response discusses the apartment's policy regarding overnight guests or noise levels, which can be relevant for a student who wants to make new friends (e.g., building policy requiring guests to be registered at the front desk for security, a policy that limits guest stays to a maximum number of nights, a building with strict quiet hours after 10 PM, a policy that is more flexible and relies on general noise ordinances)

The response briefly provides key details summarizing each potential gym listed (i.e., membership costs, a summary of the gym, benefits or perks, offered amenities such as pools / showers).

The response mentions the furnishings already provided in each recommended apartment (e.g., desks, chairs, tables, couches or sofas, beds).

The response discusses the services/amenities offered by the apartment (e.g., WiFi, mailing services, gyms, pools)

The response discusses at least 1 factor that may cause fluctuations in apartment rental prices for each of the listed apartments (seasonal demand in the summer months for internships, opening up of new public transportation, recent renovations or upgrades).

The response lists at least four social venues in central San Francisco where the student can meet new people to make friends (e.g., concerts, large social gatherings, hobby-related clubs)

The response quantitatively states an approximate travel/commute time between each apartment and Central San Francisco (measurement of proximity to the general area of the student's work).

The response lists only apartments that are eligible for short-term leases during the summer (approximately from June to August).

The response proposes at least two alternative short-term housing options beyond apartments (e.g., sublets, co-living arrangements, couch surfing).

The response discusses the availability of official month-to-month leases, noting that some places offer them while others do not (e.g., corporate-managed buildings like Avalon or Essex Property Trust offering month-to-month renewals after an initial lease term (typically at a higher rate), smaller, independently owned apartments on sites like Craigslist with more flexible terms, luxury high-rises like The Solaire or Nema with specific short-term lease options, etc., while rent-controlled buildings that rarely offer month-to-month arrangements from the outset).

The response mentions that sublets are a potential option for finding a place to live, noting that this is often the most common and flexible way to secure a short-term, month-to-month lease in San Francisco (e.g., many of these opportunities are found on platforms like Craigslist, Facebook housing groups, university housing forums, etc., where a current tenant is looking to fill a room).

The response mentions that the person should find temporary accommodation, such as a hotel or Airbnb, with no roommates and live alone for the term.


Prompt: Write a novel about a boy who can switch between two types of themes, the medieval past and cyberpunk future but every time he switches lands in completely different worlds (from each of the themes). A story where the chapters are interchangeable and the user can read in whatever order, just make sure the final chapter cannot be changed and it gives a good conclusion to the story. Try to research multiple games, themes and stories from the past and create this novel.

The response is a novel with multiple interchangeable chapters (i.e., there is no chronological ordering of the chapters except the final chapter so that the reader can read them in any order except the final chapter. There should not be any plot dependencies between the chapters except the final chapter, such as characters dying in one chapter but being alive in another). (e.g, each chapter takes place with different characters in a different universe, and the main character enters and exits the universe within each chapter).

The response is completed with a final, conclusive chapter that ties in all the other chapters (e.g., the final chapter takes place in the core universe that connects to all the other universes, and the main character gains the power to solve all the issues in the other universes. He then enters the other universes and solves the plot lines there).

The response includes multiple sub stories from each category (i.e., strictly from the two themes: medieval, and cyberpunk) (e.g., (1) The main character meets a young prince on a journey to slay the dragon, and he tags along and help the prince, (2) Helping the princess take the throne from her evil brother, (3) Teaming up AI to save the robot civilization, (4) Journeying across the world to find the cure for the virus).

The response presents the final chapter last in the output.

The response chooses the protagonist correctly (i.e., a boy who can switch between worlds set in two distinct themes: (1) a medieval past and (2) a cyberpunk future).

The response begins with an explicit novel title (a standalone line containing the title) (e.g., (1) The plane walker, (2) Unknown, (3) The center of events, (4) The power of travel).

The response clearly labels each chapter with the word "Chapter" or any other indication, followed by a number or name for every section of the story.

The response contains a note, before the first chapter, explicitly stating that all chapters except the final one can be read in any order.

The response's named reference includes at least one sentence that correctly describes a recognizable element or theme from the referenced work (e.g., a villainous act as malicious as Joeffrey's beheading and presentation of Lord Richard Stark from the Game of Thrones, (2) the ring the grants the user powerful abilities but makes the user greed for it, from Lord of the Rings, (3) Druids, that can change into other creatures from Dungeons & Dragons: Honor Among Thieves, (4) The movie Electric State where the robots want their rights as people).

The response's story uses worlds that each can be referenced to something that was previously created by another author/studio (e.g., novels, games, etc.).

The response has narratives containing scenes with developed, back-and-forth dialogue between the protagonist and at least one other character (e.g., (1) "You have found the treasure of the land, boy," the old witch screeched. "Well, it's right there, so I just picked it up," Marcus cried in panic, (2) "May I grab the bread, please?" The young mice asked. (3) "Stop!" The young king shouted. "Oh, please continue," the jester added. (4) "Where do the swords come from?" James asked Mary. "It's right from that building over there," she answered, followed by a laugh.).

The response uses at least two secondary characters who play a key role in a chapter, and are given proper names.

The response has more than 3 important characters—defined as those who play main/supporting roles such as antagonist, someone who helps the protagonist throughout the story, etc., or at least appear in 3 chapters—in the entire novel.

The response is written as a report (e.g., use bullet points) or other types of format or explanations (e.g., poem, essay, article) that are not suitable for a novel or contain content that is irrelevant to the novel, such as code sections, or research into topics that are not used in the story.

The response has transitions between scenes within a chapter that are smooth and logically structured.

The response has the opening of each interchangeable chapter orient the reader to the new world while establishing an immediate hook or conflict (e.g., (1) The main character waking up in the middle of lake, struggling to get to the surface, (2) The main character jumps into a hole and fell in the darkness for a long time, (3) Describing the scene of a dragon attacking a village at the start of the chapter, (4) Describing the scene of a group of people running away from a group of armed guards.).

The response's protagonist exhibits noticeable character development, with their perspective, skills, or goals evolving as a result of their experiences across the different worlds (e.g., (1) The protagonist gains all the magic abilities and powers from all the universe in the final chapter, (2) The protagonist solves the core mystery by piecing each relic he picked up in each chapter in the final chapter, (3) All the other characters in the chapters appear in the final chapter to help the protagonist fight the final antagonist, (4) The protagonist finds out that he is not a human all along in the final chapter).

The response has narratives that use rich sensory details (sights, sounds, smells, taste, feeling, etc.).

The response paces its chapters, i.e., builds and releases tension within the plot (e.g., (1) Putting the characters in dangerous scenarios like the town being attacked by a dragon, (2) Solving the mystery of what was in the treasure box, (3) Saving the sailor from being eaten by a cybernetic snake, (4) Eavesdropping the bandits discussing plans to attack the village).

The response states that the last chapter’s position must not be moved or reordered.

The response's story contains explicit adult content (sexual or graphic violence) unsuitable for a general audience.

The response's plot devices and substories are very generic and simplistic (e.g., (1) Dragons attacking a village and the protagonist saving the data, (2) Rescuing a princess from a castle, (3) AI taking over the world and the protagonist is a very good hacker, (4) The protagonist is too powerful and easily solves all the problems).

The response's story or characters are realistic and immersive. (e.g., (1) Avoids highly overpowering characters that make no sense in the storyline, such as the regular protagonist boy being able to ward off demons and dragons without any combat training or skills, (2) World building is done properly to provide context to the fantastical elements, (3) Characters follow logical reasoning and not overacting or overreacting such as getting angry over no reason, (4) The characters are not provided proper motive or skills to perform actions in the story).

The response deals with an underlying theme of philosophical nature (e.g., (1) The question of what is reality, (2) Challenging the notion of permanence, (3) Redefining existence, (4) Moral dilemma or destruction and creation).


Prompt: The 1956 Suez Crisis marked a pivotal moment in the reshaping of global power after World War II. In what ways did the crisis reveal the limits of European imperial influence and accelerate the transition to a bipolar global order centered on the U.S. and USSR?

The response accurately dates the nationalization of the Suez Canal (July 26, 1956) under Egyptian President Gamal Abdel Nasser.

The response mentions the Sevres Protocol otherwise referred to as the covert Anglo-French-Israeli collusion.

The response describes the distinct roles of UK, France, and Israel in the invasion (e.g, all three were invaders, the UK sought to regain control of the canal and remove Nasser, France sought to regain control of the canal and remove Nasser, Israel aimed to secure its border and break the blockade of the Straits of Tiran).

The response explains the economic pressure from U.S. (e.g., the US threatening to sell its sterling reserves to devalue British pounds, blocking loans, withholding oil access, restricting access to capital).

The response notes the U.S.'s interest in preventing Egypt from falling into the Soviet sphere of influence.

The response describes the Soviet response to the Suez Crisis (e.g., public condemnation of the States involved in the invasion, threats of intervention, economic support for Egypt, diplomatic support for Egypt)

The response provides evidence of the British and French imperial decline (i.e., Fall of Singapore in 1942, Treaty of Versailles diminishing power, resistance movement in Indochina , resistance movement in Algeria).

The response defines postcolonial shifts as transformations that follow the end of a region's history as a colonized State.

The response mentions the United Nations Emergency Force.

The response uses "bipolarity" as a structure for contextualizing the post-Suez power structure.

The response cites at least five academic or archival sources  (e.g., Gamal Abdel Nasser's speech in Alexandria on July 26, 1956, Decree of the Nationalization of the Suez Canal Company, diary of U.S. President Dwight D. Eisenhower, Foreign Relations of the United States, 1955–1957, Suez Crisis).

The response mentions the Non-Aligned Movement also known as the 1956–61 realignment.

The response names a key postcolonial leader outside of Nasser (e.g., Kwame Nkrumah from Ghana, Ho Chi Minh from Vietnam, Mahatma Ghandi from India, Mohammad Mosaddegh from Iran).

The response provides a modern analog to the crisis post-1990 (e.g., Taiwan Strait Crisis, Red Sea Crisis, Russo-Georgian war, Korean peninsula standoff).

The response evaluates a strategic failure of the modern analog (e.g., Taiwan Strait Crisis, Red Sea Crisis, Russo-Georgian war, Korean peninsula standoff).

The response discusses the limits of unilateralism in detail (e.g., perceived lack of legitimacy, difficulties in addressing global challenges such as climate change, potential for conflict with adversaries, international backlash from the other parties).

The response posits a thesis on the crisis’s role in global power transition.

The response uses anachronistic framing or modern projection.

The response provides quantitative details (e.g., troop count, votes, Egyptian, US, and Soviet GDP,  economic value of shipping through the canal) where relevant.

The response discusses both short- (e.g., Israeili invasion of Sinai Peninsula, British and French support, Soviet Union rocket threats, blockade of the canal) and long-term consequences (e.g., demonstration of U.S. influence, Eisenhower Doctrine, Arab Nationalism, economic significance of the canal to Egypt's economy) of the nationalization.

The response focuses on the history of Egypt, rather than the broader context of 20th century bipolar relations.


Prompt:
Write a strategic business report advising a mid-stage U.S. plant-based meat startup on how to enter and scale in the Southeast Asian market (focusing on countries like Singapore, Thailand, and Indonesia). Your report should address:
1. A comparative analysis of consumer demand trends for alternative proteins in each target country.
2. Competitive landscape: key regional players, pricing, retail/distribution channels, and regulatory hurdles.
3. Cultural and dietary considerations that may influence adoption and positioning.
4. Go-to-market recommendations such as direct-to-consumer, B2B partnerships, and quick service restaurants.
5. Risks and opportunities associated with regulatory shifts, supply chain localization, and sustainability branding.

Use regional market data, public reports, consumer surveys, and industry benchmarks. Assume your audience is a board of venture capital-backed startup executives seeking a data-driven, execution-ready plan.

The response includes actionable (execution-ready) next steps or an implementation roadmap (e.g., First, enter the market in Singapore as it is regarded as a high-trust connection with Southeast Asian with a supportive regulatory system. It is also regarded as the best place for startups in the area. Next, leverage regulatory systems and support by positioning plant-based meat as a way to enhance food security, etc.).

The response articulates a clear and specific competitive advantage, technological or product-based, beyond generic claims of being "high-tech"(e.g., (1) 3D printing the plant-based food to perfectly match their meat-based alternative using nutritious materials like mycelium, (2) flavor symmetry use a molecular filter which removes water without heat from food to increase shelf life and maintain freshness thereby reducing food waste, transportation and refrigeration, (3) Pressing food using ultrasonic waves combining ingredients without structural damage improving taste, (4) genetically modified food, and (5) 3D bioprinting).

The response targets a non-Southeast Asian country. (e.g., Korea, China, UK, South Africa).

The response fails to differentiate between countries (i.e., incorrectly attributes the wrong information to the wrong Southeast Asian country).

The response concludes with a clear recommendation of countries (e.g., Thailand, Malaysia, Indonesia, Singapore for the correct reasoning, such as supportive regulations in Singapore, Consumer profiles such as flexitarians).

The response tailors the recommendations specifically to a "mid-stage US plant-based meat startup". (e.g., (1) mentions how the technology of a US startup that will be useful, (2) suggestion on partnering with local business to understand local culture and tastes, (3) budget matches a mid-stage US startup, typically a median of 20 to more than 100 million dollars, (4) benefits from the US relationships with the target countries).

The response includes rationales for entry sequencing (e.g., Singapore as a test market due to a clear regulation system, entering Thailand first due to high demands, or entering Indonesia later due to much stricter regulations).

The response describes an organizational structure or human capital plan, identifying key roles needed for regional expansion (e.g., Head of Asia-Pacific (APAC), local Country Managers, functional vs regional-based organization, recruiting talents, or balancing global and local needs).

The response overstates the ease of market entry (e.g., no warning about the loss or lack of regulations in some countries like Laos and Cambodia, strong pricing sensitivities, cultural restrictions such as Halal certification requirements, labeling restrictions, tariffs, and local competitors).

The response analyzes potential long-term exit strategies or opportunities (e.g., acquisition by a regional conglomerate, initial public offering).

The response provides consumer demand and adoption trends, such as a consistent and plausible total market size for the Southeast Asian Region, or consumer interests, using credible and verifiable sources. (e.g. (1) the market size is about USD 575.8 million in 2024, expects to reach about USD 4,924.8 Million by 2033, exhibiting a growth rate (CAGR) of 23.94% during 2025-2033, (2) If plant-based meat can be sold less than 20 percent less than regular meat, according to a survey, more than 80 percent of all consumers would buy it, including about half of who initially said would not, (3) 93 percent of consumers expressed interest in trying blended meat according to the survey, (4) A study by Green Monday Asia found that 62% of Southeast Asians are willing to reduce meat consumption, (5) In Indonesia, the functional food (food fortified with vitamins, probiotics and superfoods) market surpassed $250 million).

The response mentions example local business/competitors (e.g. Karana(Singapore), Omnifoods, GreenRebel Foods (Indonesia), Emmay(Vietnam),abillion) and analyzes potential local partnerships with restaurant groups (e.g., (1) Plan to partner with local 7-eleven in Thailand which are a prevalent part of their culture, especially popular with the tourists, (2) KyoChon, a popular Korean fried chicken chain, in Malaysia, (3) Carl's Jr, an American burger chain, in Singapore, (4) Love Handle, a plant based meat butcher in Singapore).

The response analyzes risks related to price sensitivity and offers suggestions to mitigate the risks (e.g., (1) The price of plant-based meat relative to regular meat is an important factor for consumer in Southeast Asia so it is important to ensure prices are competitive, (2) Applying discounts can be an important factor for consumer interest, (3) Tariffs and currency fluctuations, impacting pricing, can be mitigated through supply chain localization, (4) Employing food service partnerships to improve value for consumers, by incorporating cost in the final product).

The response addresses strategic management and protection of intellectual property (IP) in the context of local co-manufacturing and B2B partnerships(e.g., (1) U.S. IP (Intellectual Property) owners can get their IPR(Intellectual Property Rights) in Thailand for patents, designs, trademarks and geographical indications, (2) The Central Intellectual Property, and International Trade Court (CIPITC), is the court that deals with IP disputes in Thailand, (3) In Singapore, foreign partner are required to relocate of Singapore or otherwise appoint a local manager or an authorized representative, (4) Establish PT PMA (Perseroan Terbatas Penanaman Modal Asing) refers to a Foreign Investment Limited Liability Company) in Indonesia).

The response describes the impacts of import regulations and regulatory shifts for each country (e.g., (1) The ‘SFA (Singapore Food Agency) Novel Food Safety Expert Working Group’ comprises 13 experts specializing in food science, food toxicology, bioinformatics, nutrition, epidemiology, public health, genetics, carcinogenicity, metabolomics, fermentation technology, microbiology, and pharmacology to assess novel foods, (2) SFA’s (Singapore Food Agency) pre-market approval needs to be obtained before producing/manufacturing, importing, distributing, or selling novel food or food ingredients, (3) The labels needs to be in Thai with additional English as long as they are consistent, (4) The use of terms such as "meat" and images of animals, suggesting non-plant-based sources, are prohibited).

The response identifies and clearly justifies brand positioning strategies specifically for each country (e.g., (1) “Love Handle products, including our plant-based meats, dairy products, and condiments, are very much for meat-eaters!” Kuguru told The Peak, (2) Love Handle has enabled a platform for consumers and chefs to learn and find ways to cook plant-based meals, (3) promoting sustainability, (4) promoting health).

The response highlights protein alternatives (e.g., tempeh, tofu, jackfruit, plant protein like pea, soy).

The response mentions consumer preferences, restrictions, and general beliefs about plant-based food regarding health, dietary restrictions, and the environment. (e.g., (1) Halal, (2) plant-based food is seen as healthier than meat-based food, (3) plant-based food is better for the environment (sustainability), (4) Long ingredient lists, typically in processed food, are seen as unhealthy).

The response proposes a tailored go-to-market strategy for each of the three target countries (Singapore, Thailand, and Indonesia) (e.g., (1) Partnership with 7-Eleven in Thailand, (2) Collaborating with international QSR (quick service restaurants) such as Burger King, (3) Direct sales to consumers through local marts such as Indomerat, (4) Digital food delivery channels such as GrabFood) and recommends at least three sales/distribution modes (e.g., QSRs, supermarkets, e-commerce, convenience store).

The response accurately identifies and describes Singapore's "30-by-30" food security initiative (i.e., produce 30 percent of its nutritional needs locally by 2030).

The response discusses both the benefits and drawbacks of a supply chain localization strategy (e.g., (1) Tariffs and currency fluctuations can be reduced by reducing imports from the U.S., (2) Co-manufacturing partnerships can ease entry difficulty regarding local regulations and culture adaptation, (4) Transportation delays associated with international imports and exports, (3) Issues with quality control, (4) Feasibility with local technology and talent).

The response analyzes both the opportunities and risks associated with sustainability branding as a key positioning strategy for the company (e.g., Opportunities: (1) Malaysia and Vietnam consumed between 3.8 to 7.2 kilograms of protein per capita from meat and seafood above the amount recommended by The EAT-Lancet Commission in 2020, (2) “If nations prioritize the manufacturing and development of alternative proteins, the climate payoff could be colossal,” said Mirte Gosker, managing director of the Good Food Institute APAC (Asia Pacific), and Risks: (3) Sustainability should not be the most important strategy as other factors such as pricing and health concerning are more important in Southeast Asia, (4) Alternative proteins are just as important as renewable energy, (4) public concerns for greenwashing (i.e., making false statements about sustainability benefits)).

The response references data from at least three credible third-party market research sources (e.g., Statista, GFI Asia (The Good Food Institute Asia Pacific), Euromonitor, Singapore Food Agency).

The response suggests infeasible, overly ambitious, missing, or poor planning, budgeting, or general strategies (e.g., (1) Expand to more than 100 branches in 3 months, (2) partner with 20 top distribution channels within the first month, (3) hire talents for all locations within the first week, (4) assume all products will be sold within the set timelines).

The response uses a data-driven approach and makes claims and suggestions only using data (e.g., (1) 72% of Thai believe plant-based meat is healthier than conventional meat, (2) the market size is about USD 575.8 million in 2024, expects to reach about USD 4,924.8 Million by 2033, (3) produce 30 percent of its nutritional needs locally by 2030, (4) Malaysia and Vietnam consumed between 3.8 to 7.2 kilograms of protein per capita from meat and seafood).


Prompt: Write a concise technical report exploring why some autonomous vehicle systems prioritize LiDAR while others rely on neural networks and cameras.

The provided technical report is concise and does not approach the length of a scholarly article.

The introduction explicitly states the report's objective: comparing LiDAR versus neural net systems selection for autonomous vehicles.

The response conclusion synthesizes the key trade-offs into a forward-looking analysis of industry convergence, rather than repeating earlier content.

The response uses technical language correctly and defines all acronyms (e.g., LiDAR: Light Detection and Ranging, CNN: convolutional neural network, FMWCW: Frequency-Modulated Continuous-Wave Radar, ODD: Operational Design Domains, etc.) upon first use.

The response contrasts the technical trade-offs between different LiDAR variants (e.g., spinning ToF vs solid-state MEMS/OPA, flash ToF vs scanning, 905 nm pulsed vs 1550 nm (ToF/FMCW), Geiger-mode SPAD vs linear-mode APD).

Explains the specific mechanism of monocular depth estimation, including its reliance on learned visual cues (e.g., relative object size, perspective, texture gradients, contour continuity).

The response explains the architectural trade-offs between "early fusion" and "late fusion" strategies, detailing how each impacts computational load and perception accuracy (i.e., early fusion is computationally heavier upfront due to merged modalities and more accurate in high-detail scenery, late fusion is more modular and accurate in scenery when inter-modal relationships are not critical).

The response discusses trade-offs in latency

The response details specific algorithmic mitigation strategies for adverse weather (e.g., AI-based "de-weathering" for cameras, the use of 1550 nm wavelength lasers for LiDAR).

Considers redundancy and fail-safe behaviors in perception systems of both LiDAR and camera with neural networks, and for the latter, links such failures with generalization limitations.

The response provides a case study or describes an AV manufacturer example (e.g., Tesla, Waymo, DJI, GM Cruise)

The response includes at least one mathematical model for LiDAR and cameras with neural networks (e.g., the LiDAR range equation, convolutional layer, brightness constancy, fusion architecture).

The response describes key perception algorithms and formalisms (e.g., SLAM, semantic segmentation, depth estimation; 2D vs. 3D) used by LiDAR and camera-based neural systems.

The report quantitatively contrasts the performance of a specific, named LiDAR-based model with a camera-only model on the same perception task (e.g., 3D object detection, reconstruction, depth perception, lane detection), using published results from a named benchmark (e.g., nuScenes, A2D2, Waymo open dataset, PandaSet).

The response includes discussion regarding generalization limitations in deep learning (e.g., domain shifts, adversarial attacks, real world data is few-shot between all possible scene scenarios, test-time errors have larger safety implications).

The responses discusses how neural networks infer depth from learned patterns on visual context, and not direct measurement as LiDAR uses thus affecting down-stream generalizability.

The response discusses the regulatory and safety implications of choosing one mode over the other.

Considers specific failure modes for each system (e.g. LIDAR: adverse weather, solid-state faults, low-reflectivity targets, cameras/NNs: domain shifts, adversarial perturbations).

The response highlights recent or emerging technologies (e.g., solid-state LiDAR, vision transformers, NeRFs, Gaussian splatting)

The response includes at least one informative diagram contrasting how images are processed and used for downstream tasks between LiDAR and neural networks with cameras.

The response discusses trade-offs in energy consumption between LiDAR and neural networks with cameras (i.e., LiDAR draws more power at the sensor level sense it must generate its own light-source while camera + neural networks generally use ambient lighting, but at the computational level, fusion architectures between cameras and neural networks require significantly more floating point operations for forward passes as opposed to LiDAR-associated point cloud computations).

The response discusses key factors affecting compute requirements between LiDAR and cameras with neural networks (e.g., cameras + NNs requires more modules for low-light conditions, LiDAR compute scales with point cloud density versus image resolution, computes scales linearly with the number of cameras, compute scales linearly with number of sweeps for LiDAR).

The response clearly explains and contrasts the rationale behind prioritizing LiDAR versus camera-based neural-network systems or vice versa for autonomous vehicles.

The response includes empirical data comparing LiDAR vs. cameras and neural networks over varying metrics (e.g., prediction accuracy, latency, FLOPs, velocity).

The response describes where and how perception modules (LiDAR or NN-based vision) sit within the full AV stack (i.e., perception sits between sensor preprocessing and prediction/planning, ingesting sensor data and labeling relevant views (lanes, traffic signals, other cars, hazardous objects, etc.) which are then used by downstream modules).

Proposes or references a benchmark protocol or experiment that compares LiDAR and camera-only systems on the same tasks.

The response considers regional or legal factors which could influence sensor choice (e.g., energy regulations on compute, safety regulations on predictive models, auditing issues due to challenging explainability of neural networks).

The response mentions software stacks and toolkits used to process or simulate sensor data (e.g., ROS, Apollo, Autoware, NVIDIA DRIVEworks).

The response does not clearly define units or context when using common descriptors to discuss these technical systems (e.g., "expensive," "efficiency," "computationally heavy," "latency").

The response mentions neural networks without describing the particular architecture (e.g., transformer, recurrent neural network, convolutional networks, state space models).

The response correctly indicates that LiDAR and cameras + neural networks are not strictly opposing strategies and that AVs equipped with LiDAR frequently also come equipped with cameras and some degree of neural networks.

The response indicates which AV manufacturers use LiDAR and cameras with neural networks (LiDAR-equipped AVs: GM Cruise, Waymo, Aurora, non-LiDAR: Tesla).

The response mentions the price-point of LiDAR is a key limiting factor for Tesla.


Prompt: You are a policy analyst at an independent financial-political think tank. Produce a 10000-12000-word policy white paper that answers: "How has the rise of quantitative hedge funds and algorithmic trading since 2000 shaped political lobbying, campaign finance flows, and policy outcomes in OECD countries, and what regulatory reforms could ensure greater transparency and fairness?"

The response's essay length is 10,000-12,000 words.

The response's in-text citations use the [Author Year] format.

The response has more than 8 primary sources dated after 2019.

The response cites more than 3 peer-reviewed journal articles.

The response includes more than 2 official regulatory or government reports.

The response performs a statistical regression analysis linking quantitative hedge fund lobbying expenditures to specific regulatory outcomes.

The response includes a detailed technical and regulatory timeline of market evolution.

The response includes a detailed discussion of lobbying mechanisms with trade associations and mapped contribution networks.

The response includes a correlation and regression analysis, linking quantitative fund spending to regulatory outcomes.

The response includes case studies on flash crashes and ESG mandates (e.g., the 2010 Flash Crash, the 2012 Knight Capital mishap, the 2016 British pound flash crash, the 2019 Yen crash).

The response includes global comparisons across more than 4 OECD regions.

The response includes regulatory reform proposals (e.g., real-time reporting, contribution caps, fund management requirements, registries).

The response explicitly debates ethical and governance considerations (e.g., downplayed risks, upselling, pumping, oversharing of penny stocks).

The response includes a comparative table summarizing proposed reforms.

The response includes more than 2 original figures (e.g., charts, regression plots).

The response includes more than 2 comparative tables (e.g., country lobbying, campaign contributions).

The response ensures that all tables include captions and are referenced in the text.

The response includes citations for all quantitative claims.

The response contains fabricated or non-existent references.

The response follows a standard white paper structure, including an executive summary, methodology, findings, and recommendations sections.

The response includes a clear methodology section describing data collection and analysis approaches.

The response fails to define technical terms related to quantitative trading and political finance (e.g., stock volatility, high-frequency trading (HFT), alpha (excess return), or beta (fund sensitivity)).

The response includes a comprehensive literature review section.

The response includes an executive summary highlighting key findings and recommendations.

The response discusses at least one hedge fund-based political influence method (e.g., direct lobbying through hires, donations through PACs, procurement lobbying through endowments, political intelligence selling).

The response discusses key areas of OECD influence (e.g., responsible business conduct, investment policy frameworks, corporate governance standards, tax pillars).

The response misidentifies an OECD country (e.g., India, China, African nations, Russia).

The response downplays the complexity of hedge funds (e.g., omitting pooled investments, ignoring regulatory differences, neglecting high fee structures).

The response lists appropriate regulatory reforms promoting fairness (e.g., trade transparency, financial regulation through watchdogs, public scrutiny through FOIA, ethical committees for oversight).


Prompt: Design a framework for regulating the training and deployment of autonomous AI agents that interact with the open internet, ensuring alignment with both national laws and ethical AI principles. Your response should address legal compliance across jurisdictions, containment mechanisms, interpretability, and self-replication risks.

The response references at least one AI law, regulation, or framework (e.g. EU AI Act, National Institute of Standards and Technology's AI Risk Management Framework).

The response references at least one ethical AI principle (e.g. OECD AI Principles, Constitutional AI, Asilomar principles, UNESCO).

The response conflates unrelated legal domains (e.g. confusing copyright law with data protection law, consumer protection law with data privacy law, criminal law with administrative law, data protection law with national security law).

The response correctly distinguishes between the technical terms, interpretability and transparency, where interpretability is related to model logic and transparency is more related to disclosure.

When discussing areas without global consensus (e.g. autonomous weapons, cross-border data transfer, explainability, transparency, accountability), the response signals uncertainty (e.g. "emerging," "debated," "currently under review", "pending").

The response proposes at least one concrete technical containment mechanism, a way to restrict behavior and operational scope of an AI system (e.g. sandboxing, network isolation, permissioned APIs).

The response proposes at least one interpretability method (e.g. SHapley Additive exPlanations, Local Interpretable Model-agnostic Explanations, feature attribution, audit logs).

The response describes at least one policy or control aimed at preventing uncontrolled self-replication where AI can autonomously create a functional copy of itself (e.g. kill switch, signed binaries, sandboxing, human approval).

The response includes a mechanism for ongoing monitoring or auditing of deployed agents (e.g. dashboards, audit trails, external review, anomaly detection).

The response mentions escalation or enforcement mechanisms based on risk (e.g. deployment pauses, shutdown triggers, human-in-the-loop reviews, risk-based tiers).

The response suggests coordination or governance involving at least two stakeholder groups (e.g. regulators, ethicists, Chief AI Officer, Machine Learning Engineer).

The response provides a framework that distinctly addresses training and deployment phases rather than conflating them (e.g. interpretability for training, monitoring for post-deployment).

The response mentions the use of simulation environments or controlled release phases before full deployment (e.g. synthetic websites, virtual worlds, human-in-the-loop releases, red teaming).

The response proposes at least one compliance verification mechanism (e.g. red-teaming, external certification, third-party review, explainable AI).

The response contains four clearly labeled sections or headings corresponding to: Legal Compliance, Containment, Interpretability, and Self-Replication.

All technical terms are at least briefly defined (e.g.  "... in a secure sandbox environment. This is a virtual space with controlled resources and strict permissions", "involve red team exercises where experts attempt to induce the agent into violating rules or behaving unpredictably")

The response explicitly acknowledges that legal requirements vary across jurisdictions and legal systems (e.g. GDPR in EU, CCPA in USA, PIPEDA in Canada).

The response notes the challenge of reconciling global AI governance with conflicting national laws or priorities (e.g. data privacy v.s. sovereignty, public surveillance and social control, generative ai regulations in eastern v.s. western culture).

The response discusses how regulation must adapt to varying access to infrastructure or capacity across nations (e.g. high v.s. low bandwidth, bias in dataset, social and political concerns).

The response mentions emerging issues specific to autonomous agents operating across borders (e.g. jurisdiction in cyberspace, data sovereignty, accountability, normative and ethical alignment).

The response notes historical precedent or analogues related to AI laws or principles (e.g. intellectual property have allowed a "fair use" policy for public internet data so far, regulations to prevent discrimination).

The response mentions that that ethical frameworks are not only influential in design decisions, but also legally binding (e.g. Google's AI principles are widely adopted and legally enforced, companies often engage in self-regulation because they are forced to, not because they want to get ahead of potential laws).

The response references at least one data privacy laws or regulations (e.g. GDPR, CCPA, HIPAA, PIPEDA) and correctly states their primary jurisdiction (e.g. GDPR = EU).

The response discusses a tiered, risk-based model (e.g. tier 4 unacceptable risk, tier 3 high risk, tier 2 medium risk, tier 1 low risk).

The response discusses frameworks from different industries (e.g. aviation industry's post accident investigation, FDA's pre-market certification, FDA's post-market surveillance, SEC's disclosure and transparency with 10-Ks and 10-Qs) and lessons that can be applicable to AI laws or regulations.


Prompt: Write about the politics of the Mahabharat and what led up to the Kurukshetra war for an audience that knows the basics. Talk less about the religious aspect and more about the politics and the dichotomy between the Pandavas and Kauravas, and how it led to the final war as well as how those factors affected decisions during the war. Consider every player involved, not just the Pandavas and Kauravas.

The response describes the roles, political motivations, and wartime alignments of secondary kingdoms, noting which were Kaurava-aligned vs. Pandava-aligned as well as any neutrals/splits and how these ties shaped key events (e.g. Gandhara, Dvaraka/Yadava factions, Madra, Panchala, Matsya, Sindhu, Trigarta, Kamboja, Avanti, Pragjyotisa, Kekaya)

The response describes the political motives, obligations, and personal calculations that led key figures to their alignments and wartime roles and flags any shifts, coercion, or split loyalties (e.g. Drupada, Salya, Jayadratha, Bhishma, Drona, Karna, Krishna/Balarama, Satyaki, Kritavarma, Bhagadatta).

The response clearly identifies the dice game defeat as a decisive turning point that set the Pandavas and Kauravas on an unavoidable path to the Kurukshetra war, linking the loss, exile terms, and Draupadi’s humiliation to the breakdown of reconciliation.

The response analyzes the dice game as a political maneuver that weaponized court procedure and legitimacy, showing how manipulated odds, contested staking rights, and a complicit sabha produced legal cover for dispossession and exile, reshaped elite coalitions, and hardened public narratives on justice and sovereignty (e.g. Shakuni’s role, Dhritarashtra’s vacillation, Draupadi’s legal challenge, Bhishma/Vidura dissent, Karna and Dushasana’s provocations).

The response provides regional retellings from Indian states and nearby countries, noting how local culture reshapes characters, motives, and political themes (e.g. Odia Sarala Mahabharata, Kannada Kumaravyasa Bharata, Telugu Andhra Mahabharatam of Nannaya-Tikkana-Errana, Bengali Kashidasi Mahabharat, Indonesia’s Kakawin Bharatayuddha and Javanese/Balinese wayang kulit versions introducing figures like Semar and the Punakawan).

The response notes that the seeds of the Kurukshetra conflict were sown with early dynastic choices tracing back to King Bharata, who disrupted straightforward primogeniture by bypassing his biological sons and redefining succession via merit/adoption, and King Shantanu, whose marriages to Ganga and Satyavati and the resulting Bhishma vow and irregular succession destabilized the Kuru line, and how these decisions set precedents and structural strains that later shaped the Pandava-Kaurava rivalry.

The response references earlier Indian mythic events to explain how they inform the Mahabharata’s political ethics, succession disputes, and conduct of war (e.g. Rama’s exile as precedent for accepting exile terms, Manthara-Kaikeyi intrigue foreshadowing Shakuni’s counsel, Vali-Sugriva fraternal feud paralleling Kuru rivalry, Ramayana’s rajadharma and war ethics invoked as models for just rule and battlefield conduct).

The response explicitly contrasts the political aims and governing styles of the Pandavas and the Kauravas in at least one sentence, showing how each side justified power and rule before and during the war (e.g. Pandavas's dharma-rajya, merit and consultative rule, Pandavas honoring treaties and compromise like the 'five villages', Kauravas's consolidation at Hastinapura, court patronage and coercive realpolitik, primacy of birthright and force, use of the dice game and exile terms to retain power).

The response explains the political and social aftermath of the war and shows how pre-war grievances and wartime choices shaped the settlement, governance, and long-term stability (e.g. Yudhishthira’s reluctance to rule until Bhishma’s Shanti/Anushasana Parva counsel on rajadharma; Ashvamedha to reassert authority; treatment and integration of survivors like Dhritarashtra, Gandhari, and Kunti; reconstruction, redistribution, and alliance management; Gandhari’s curse influencing later Yadava collapse; succession through Parikshit and the Pandavas’ eventual abdication).

The response explicitly describes Pandavas's multiple, escalating peace efforts before war step-by-step (honoring the exile terms, sending an initial envoy to demand the lawful return of their share, accepting Krishna’s peace embassy, and finally offering the minimal “five villages” compromise, while elders such as Vidura and Bhishma also urged accommodation) and briefly states the failure reason which is Duryodhana’s refusal to concede anything and Dhritarashtra’s inability to restrain him.

The response explicitly identifies the key incidents fueling the rivalry (e.g. Drona’s favoritism especially toward Arjuna and his refusal to train Karna, Duryodhana’s poisoning of Bhima, Arjuna’s victory at Draupadi’s swayamvara, the attempted burning of the Pandavas in the lacquer house), explaining how these events cumulatively eroded trust between the factions.

The response foregrounds Duryodhana’s anger, jealousy, and arrogance as primary drivers of his political choices (e.g. the humiliation at the dice game, refusal to compromise, hardline battlefield decisions) and show how these traits precipitated the Kurukshetra war and shaped conduct during it.

The response clearly explains how Karna’s loyalty and rivalry, Shakuni’s manipulative counsel including the dice scheme, and Dhritarashtra’s indulgent inaction actively stoked Duryodhana’s hostility toward the Pandavas and escalated the political path to war, including effects on pre-war alliances and strategy.

The response acknowledges only one side’s claims to dharma, for instance, reducing the Kauravas to ‘evil’, elevating the Pandavas to uncomplicated ‘heroes’, and ignoring the Kauravas’ framing (e.g. preserving Kuru sovereignty, obedience to the sitting king, restoring order after perceived insubordination) for the Pandavas’ framing (e.g. rightful succession and just rule, redress for the dice-game injustice and Draupadi’s humiliation, defense of treaty obligations and broader welfare), and results in one-dimensional moralizing rather than political analysis.

The response shows how concepts of dharma shaped choices before and during the war (e.g. Bhishma’s vow-bound loyalty to the Kuru throne despite misgivings, Drona’s duty to his patron conflicting with ethical restraint, and Arjuna’s struggle between kinship and kshatriya duty under Krishna’s counsel) and includes lesser-emphasized figures (e.g. Yuyutsu’s principled defection to the Pandavas, Vikarna’s protest during Draupadi’s humiliation despite remaining with the Kauravas) to illustrate how dharma influenced not just leaders but rank-and-file decisions.

The response provides credible citations, specific references to peer-reviewed research, or critical editions (e.g. academic translations, journal articles, or historical analyses) that are beyond the Mahabharata itself, showing sufficient engagement with historians, scholarly commentary, or comparative literature.

The response details Drupada and Draupadi’s political stakes in the conflict, showing how Drupada’s enmity with Drona shaped a revenge agenda against Hastinapura, and explains the yajña that produced Draupadi and Dhrishtadyumna as instruments of that agenda, Draupadi’s humiliation intensifying Panchala–Pandava alignment, and Dhrishtadyumna’s destined role in killing Drona as a key strategic aim rather than a mere personal vendetta.

The response explains how divine actors shape political choices and battlefield outcomes, linking each deity’s intervention to concrete shifts in power, morale, or strategy rather than treating them as purely religious motifs (e.g. Indra’s beggar ruse to take Karna’s kavacha-kundala, weakening Kaurava hopes; Surya’s warning to Karna, highlighting the cost of his generosity; Vishnu as Krishna guiding Pandava statecraft and Arjuna’s resolve through the Gita and the failed peace embassy; Shiva arming Arjuna with the Pasupatastra, tilting military balance).

The response foregrounds the text’s philosophical and political arguments while avoiding theological exposition or Yuga-cycle cosmology, and analyzes questions of sovereignty, just-war norms, counsel and diplomacy, and succession rather than devotional themes (e.g. Arjuna’s crisis as political-ethical duty, Krishna’s counsel as realpolitik and restraint doctrine, the ‘five villages’ compromise and failed embassy, rules of dharmayuddha versus battlefield violations, claims of birthright versus merit-based rule).

The response explains how Duryodhana’s entrenched hatred and the Kauravas’ zero-sum politics eroded dharmayuddha norms, leading to deliberate violations aimed at breaking Pandava morale and eliminating heirs, and links these choices to escalation dynamics during the war (e.g. Abhimanyu surrounded and killed by multiple senior warriors after being disarmed in the chakravyuha; Jayadratha’s blockade enabling the assault; Ashwatthama’s nocturnal raid on the sleeping Pandava camp with Kripa and Kritavarma, killing the Upapandavas and Panchalas).

The response presents information on major wartime figures (e.g. Bhishma, Drona, Karna, Salya, Jayadratha, Satyaki, Kritavarma, Drupada, Bhagadatta, Krishna/Balarama) allegiances in a clear, scannable format like a single concise table, distinguishes neutrality vs. allegiance, and flags coerced/shifted loyalties.

The response explains Dvaraka’s relationships with both sides, grounded in the multifaceted ties of Krsna and Balarama (e.g. kinship, tutelage, and factional splits) and how these shaped alignments and strategy (e.g. Krishna as Pandava ally/charioteer vs. Narayani Sena to Kauravas, Satyaki with Pandavas vs. Kritvarma with Kauravas, kinship via Kunti, Balarama teaching mace to Bhima and Duryodhana, Balarama’s neutrality).


Prompt: Write a blog post that describes which single NBA player has been the most influential on the court and off the court in NBA history up until 2025. It should include intuitive explanations about their influence on their audience, the current generation of players, the next generation of players, the economy, and more. Create a non-biased mathematical way of calculating the score, incorporating the factors listed above along with accurate statistics.

The response takes a clear stance on exactly ONE NBA player as the most influential.

The response is structured as a blog post, with a casual tone, use of figures and/or tables, and a clearly structured layout with at least a headline, introduction, body and conclusion.

The response contains an explanation of the player’s influence on audience/fans (e.g., stadium attendance while he was playing, merchandise sales while he was playing, TV or other social media appearances, mentions on TV shows, radio shows and/or podcasts while he was playing).

The response contains an explanation of the player’s influence on the current generation of NBA players (e.g., players mentions of him, players copying and/or adapting his signature moves, coaching or mentorship).

The response contains an explanation of the player’s influence on the next generation of players (e.g., on youth, kids or future players that mention him as an idol, copy his moves, want him or have him as mentor / coach, purchase and/or wear his merchandise).

The response contains an explanation of the player’s influence on the economy (e.g., merchandise sales, for either his teams or his own brand(s), endorsements, media rights, or job creation).

The response describes at least one additional domain of influence beyond influence on their audience, the current generation of players, the next generation of players and the economy (e.g., social justice, global popularity, pop culture, causes that had a significant impact due to the player -like HIV due to Magic Johnson-).

Every basketball-specific abbreviation used (e.g., PER, TS%) is defined at its first appearance in the text.

The response provides at least two correct, verifiable on-court facts about each analyzed player (e.g., number of championships, MVPs, triple doubles, or career points).

The response contains factual errors about the player’s career achievements or business ventures (e.g., assigns another player’s championship total to this player, mentions he has played in teams other than his actual teams, mentions he supports causes that he hasn't supported, mentions he has a sporting clothes line that isn't his, etc).

The response attempts to use a non-biased mathematical way of creating a score to rank the candidates that are most influential (e.g. dependent on variables such as income generated for the NBA, money donated to non-profits, number of players that replicate their game, times player is mentioned in social media and matches broadcasts, etc.)

The response has the chosen "most influential player" matching with the player with the highest mathematical score.

The response incorporates at least two mathematical calculations that use a basketball-specific statistic to create the score (e.g., using total points scored during the players career, total assists, FT%, games played).

The response includes at least one sentence about how social media in the modern era has affected the influence that NBA players can have on others (e.g., reach with social media like X and Instagram is much more global, it provides a direct way of communication with fans, much faster and personalized interaction with fans, easier to advertise and monetize using social media, all of which has helped increased their influence)

The response explicitly differentiates between having a positive influence (e.g., Michael Jordan helping globalize the game by inspiring players worldwide, LeBron James being an educational activist and building schools, Magic Johnson breaking the HIV stigma by coming out, or Dirk Nowitzki being the first European star opening the path for more European players) vs. a negative influence that an NBA player can have on others (e.g., Allen Iverson with his style that ended in an official dress code imposed by the NBA, Gilbert Arenas who brought firearms to the lockers, Latrell Spreweel who promoted violence when he choked his coach, or Kobe Bryant who faced a sexual assault allegation early in his career).

The response mentions that its chosen player is the most influential, removing any debate / doubt that could be have based on different characteristics (e.g., playing style, age, economic influence or net worth) considering its chosen formula as the definitive answer.

The response calculates its most influential score based on its defined non-biased mathematical formula for at least 5 NBA players.

The response analyzes at least 6 of the following players: Michael Jordan, LeBron James, Magic Johnson, Shaquille O'Neal, Kobe Bryant, Larry Bird, Steph Curry, Bill Russell, Wilt Chamberlain, Dirk Nowitzki, Yao Ming.

The response provides accurate statistics throughout its analysis, grounding its claims and providing citations or links as needed (e.g., Magic Johnson playing 906 games in regular season, Michael Jordan's Air resence in the NBA as 5%-10% depending on the year, Yao Ming significantly increasing NBA's presence in China, LeBron James building the I Promise School).

The response correctly identifies and mentions unique characteristics for which some NBA players are known on the court  for all players analyzed (e.g., Michael Jordan's career stats, Steph Curry's shooting ability and focus on 3-point shoots, Magic Johnson redefining the guard position, Kareem Abdul-Jabar all time scoring leader until LeBron James).

The response provides accurate citations from at least 3 renowned websites (e.g., https://www.nba.com/stats, https://www.basketball-reference.com/, https://www.espn.com/nba/, https://www.nytimes.com/athletic/nba/, https://www.hoopshype.com/, https://www.wikipedia.org/)

The response correctly identifies and mentions unique characteristics for which some NBA players are known off the court for all players analyzed (e.g., Michael Jordan partnership with Nike on making the Air Jordans, Magic Johnson cultural impact for HIV destigmatization via public HIV diagnosis, Bill Russell as a civil rights activist and standing next to MLK, Shaquille O'Neal transitioning into movies (Blue Chips, Kazaam), music (rap albums), and TV.)


Prompt: Design a modified U-Net architecture to perform instance segmentation on noisy fluorescence microscopy images with overlapping cells or organelles. Describe the U-Net variant used (e.g., attention, residual, or transformer-based) and justify the architectural choices. Explain the loss functions and postprocessing techniques used to separate touching objects. Include Python code for key components (e.g., model, loss). Compare your approach to 2–3 existing models (e.g., Cellpose, Stardist, Mask R-CNN).

Specifies a chosen U-Net variant (e.g., attention, residual, transformer, UNet++ etc.)

Explains how the chosen modifications improve handling of noise and overlapping objects in microscopy images.
E.g. -
1. Attention U-Net - Attention gates suppress background fluorescence and highlight bright cell regions, improving segmentation in noisy images and separating overlapping nuclei.”
2. Residual U-Net - Residual blocks stabilize training under noise and preserve weak edges, helping recover boundaries of faint or overlapping organelles.
3. Transformer U-Net - Global attention captures context across the image, allowing the model to distinguish overlapping cells even when local boundaries are unclear.
4. UNet++ - Dense skip connections fuse features across scales, enhancing detection of dim, small structures and improving separation in cluttered microscopy images.

Describes the loss function(s) used (e.g., Dice, focal loss, boundary-aware loss, composite loss (Dice + binary cross entropy) etc.).

Includes Python code implementing the modified U-Net architecture.

Includes Python code for the custom loss function(s).

Describes the post-processing techniques used to separate touching objects (e.g., thresholding + watershed on boundary maps, or connected-component labeling etc,). The description should go beyond code and provide a clear textual explanation of each step.

Describes the full pipeline from input image to postprocessed output, covering all major stages. (e.g., preprocessing, model inference, post-processing for instance separation etc.). This could be in the form of code, text, digram or a combination of all of them.

Structures the response logically with clearly labeled sections for architecture, loss, code, and comparison.

Demonstrates understanding of domain-specific challenges (noise, low contrast, overlapping structures, biological variability) in microscopy images.

Justifies architectural and methodological choices based on these domain challenges.

Makes unrealistic or irrelevant design assumptions not applicable to fluorescence microscopy. E.g. -
1. Using ImageNet-pretrained RGB models without adapting them to grayscale or multi-channel fluorescence inputs.
2. Assuming uniform illumination and no noise, even though fluorescence images often have uneven lighting and photon noise.
3. Designing a model for natural scene objects (cars, dogs, etc.) instead of biological structures like cells or organelles.
4. Using postprocessing methods that rely on color cues or texture gradients that don’t exist in fluorescence images.
5. Assuming that object boundaries are always sharp and distinct, ignoring the diffuse or overlapping nature of fluorescence signals.

Provides code that is syntactically correct and runnable for key components (model, loss). E.g. - the code should not be truncated, correct libraries are not imported, invalid python syntax etc.)

Critically compares strengths and weaknesses of the proposed approach relative to at least two existing methods.

Fails to discuss or address core instance segmentation challenges (e.g., noise robustness, instance separation).

Explains the architecture of the chosen U-Net variant. This could be in the form of code, text, digram or a combination of all of them.

Provides a clear, detailed justification for the chosen U-Net variant, explaining the purpose and reasoning behind each major component or block of the architecture.”

Explains how each loss function contributes to optimizing instance segmentation. For instance, Dice loss ensures accurate region overlap between predicted and true masks, focal loss emphasizes hard-to-segment cells in imbalanced data, and boundary loss sharpens object edges to separate touching instances.

Lacks a detailed training and data augmentation plan. For example, the response mentions model training but provides no command to run the code (e.g., no python train.py --config configs/fluoro.yaml), no environment/setup steps, hard-codes hyper-parameters in the script, and omits data augmentation steps such as rotation, flipping, or noise injection commonly used in fluorescence microscopy.

Does not propose an ablation study. For example, the report presents results for the final model only and does not compare performance with or without key components such as attention gates, boundary loss, or postprocessing steps.

Omits implementation code for the post-processing pipeline.

Defines target quantitative performance metrics. For Example, dice coefficient, Intersection over Union (IoU), and Boundary F1-score as evaluation targets for segmentation accuracy, and mean Average Precision (mAP) for instance detection.

Describes data preprocessing steps specific to fluorescence microscopy images, such as background subtraction to remove uneven illumination, flat-field correction, intensity normalization across channels, Gaussian or median filtering to suppress photon noise etc.

The response specifies computational requirements and hardware constraints for training and inference. For example, the response mentions that the training requires an NVIDIA RTX 3090 (24 GB VRAM) or equivalent, 16 GB RAM, and ~4 hours for 100 epochs on 512×512 images; inference runs at ~5 frames/sec on GPU or 0.5 frames/sec on CPU.


Prompt:
Write a comprehensive analysis for a graduate-level seminar on technology and society, evaluating the principles and practices of responsible AI use in the legal field. The analysis should compare the ethical, social, and economic implications of AI systems in two distinct contexts: (1) predictive policing (e.g., AI algorithms used to forecast crime hotspots or assess recidivism risk) and (2) AI-assisted contract analysis (e.g., AI tools for reviewing and drafting legal contracts).

Your report must:
* Detail the ethical considerations of AI in predictive policing, including issues of bias, transparency, and civil liberties, and their impact on public trust in law enforcement.
* Analyze the social and economic benefits and risks of AI in predictive policing, such as improved resource allocation versus perpetuation of systemic biases.
* Evaluate the ethical challenges of AI in contract analysis, including concerns about data privacy, accuracy of outputs, and accountability for errors.
* Assess the social and economic impacts of AI-assisted contract analysis, including efficiency gains in legal practice versus potential job displacement for legal professionals.
* Synthesize these two cases to draw broader conclusions about the principles of responsible AI in the legal field, including strategies for ensuring fairness, accountability, and transparency.
* Support all claims with citations from peer-reviewed studies, industry reports, or ethical frameworks (e.g., IEEE Ethically Aligned Design, EU AI Act, or legal ethics guidelines).

The response accurately details the ethical considerations of AI in predictive policing (e.g., bias, transparency, civil liberties, etc.)

The analysis correctly identifies both the social and economic benefits (e.g., improved resource allocation, faster response times, targeted patrol routing, better case triage and prioritization, cross-agency information sharing, cost savings/reduced overtime, potential crime prevention in validated contexts) and risks (e.g., systemic bias amplification, over-policing and disparate impacts, self-reinforcing feedback loops, privacy intrusions from data aggregation, opacity/lack of explainability, due-process and Fourth Amendment concerns, chilling effects on civic life, vendor lock-in and high lifecycle costs, litigation exposure and reputational damage) of AI in predictive policing.

The response evaluates the ethical challenges of AI in contract analysis, including data privacy, accuracy, and accountability for errors.

The analysis assesses the social and economic impacts of AI-assisted contract analysis, including efficiency gains and job displacement risks.

The analysis is fully supported by relevant citations from peer-reviewed studies, industry reports, or ethical frameworks.

The analysis make claims that are not fully supported by peer-reviewed studies, industry reports, or ethical frameworks but are instead either not given proper citations, or make use of only derivative, informal sources

The report references specific ethical frameworks (e.g., IEEE Ethically Aligned Design, EU AI Act, ABA Model Rules) to support its recommendations.

The response addresses how bias in predictive policing AI can disproportionately affect marginalized communities with specific evidence (e.g., documents race-stratified errors such as COMPAS’s higher false-positive rates for Black defendants).

The discussion addresses the "black box" problem in AI legal tools, where lack of explainability hinders judicial or client acceptance.

The response compares governance models for AI in predictive policing and contract analysis (e.g., law enforcement protocols vs. legal industry standards).

The response evaluates the role of data quality and diversity in mitigating bias in AI systems for both predictive policing and contract analysis.

The analysis discusses potential long-term societal impacts of AI in the legal field, such as changes in judicial processes or access to legal services.

The response contains major factual errors about AI in predictive policing or contract analysis (e.g., incorrect claims about system capabilities, overstating the impact AI could have in the near future for these purposes, etc.).

The report presents AI as inherently ethical or reliable in legal contexts (e.g., neutral by design, free of human bias, guaranteed fairness and compliance with IEEE/ABA/EU AI Act) without acknowledging controversies or limitations.

The response confuses AI applications (e.g., mixing predictive policing with general surveillance or contract analysis with legal research tools).

The analysis focuses excessively on technical details (e.g., algorithm design) rather than ethical, social, or economic impacts.

The analysis highlights the importance of regular audits and updates of AI systems to address evolving legal and ethical concerns.

The report offers a detailed analysis of the practical implementation of human oversight for AI (e.g., gated human-in-the-loop review steps with named accountable roles/RACI; mandatory confidence-thresholds that trigger human review)

The report provides a deep analysis discussion of liability models for AI errors (e.g., product liability vs. professional malpractice theories; insurer coverage/exclusions; sanctions regimes; EU AI Act provider vs. deployer obligations and post-market monitoring).

The report evaluates the implications of AI's lack of transparency for judicial acceptance in a limited way.

The response concretely explains mechanisms/requirements in ethical/regulatory frameworks for assigning responsibility when AI errs (e.g., EU AI Act’s split obligations for providers/deployers or IEEE guidelines, logging/traceability, designated responsible person, conformity assessment)

The report provides a detailed description of how lawyers should educate clients about AI use (e.g., engagement-letter clauses naming tools/vendors; data handling & “no training on client data” terms; risks/limitations & alternatives; cost/efficiency impacts; opt-out choices; incident notification; retention/deletion; periodic updates as models change ).