AI Image Prompts for Sari
Explore AI generated designs, images, art and prompts by top community artists and designers.
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Here’s a comprehensive description of Hercule Poirot as Agatha Christie wrote him — with precise references to the novels , and comparisons to key screen portrayals (Finney , Suchet , Ustinov , Branagh , etc.). --- 📖 Hercule Poirot — Literary Description (with Source Quotes) --- 🧍♂️ 1. Physical Appearance 🔹 “A little man with an egg-shaped head” — The Murder of Roger Ackroyd (1926) Short stature Plump and compact build Head described as egg-shaped , often tilted slightly to one side > 🎥 Closest portrayals: 🔸 David Suchet – nails the “little man” shape and tilting head 🔸 Finney – correct manner but taller 🔸 Branagh – too tall and lean 🔸 Ustinov – too broad and casual in posture --- 🥸 2. Moustache 🔹 “The finest moustache in all England — and perhaps in all Europe.” — Death in the Clouds (1935) Immense , curled , waxed , perfectly symmetrical Poirot is extremely vain about it Wears a moustache net at night > “He had a moustache guard to keep it neat in his sleep.” — The Mysterious Affair at Styles (1920) > 🎥 Closest portrayals: 🔸 David Suchet – accurate size and grooming 🔸 Kenneth Branagh – large but overly stylized (double-layered) 🔸 Peter Ustinov – too understated 🔸 Finney – neat , but not extravagant enough --- 👔 3. Dress & Grooming 🔹 “Always immaculate. His clothes were faultless. His boots shone.” — The Mystery of the Blue Train (1928) Fussy and obsessive about cleanliness Well-tailored suits , gloves , polished shoes Takes pride in his appearance , symmetry , and neatness > 🎥 Closest portrayals: 🔸 Suchet – perfect suits , shoe polish , gloves 🔸 Finney – clean but not as fussy 🔸 Branagh – a bit too dramatic in grooming --- 🧠 4. Intelligence & Method 🔹 “I am not one to rely upon physical evidence. I use the little grey cells.” — The Big Four (1927) Psychology-based deductions Avoids fingerprint obsession or brute force Dismisses red herrings and goes after motive and psychology > 🎥 Closest portrayals: 🔸 Suchet – pure psychological method 🔸 Finney – sharp intellect , but less emphasized 🔸 Ustinov – more jovial , less “grey cell” driven 🔸 Branagh – mixes emotion and action unnecessarily --- 🗣️ 5. Speech & Accent 🔹 “His English was precise , but with a foreign accent.” — Peril at End House (1932) Belgian French accent , not French or British Always speaks in precise , formal English Often corrects others politely > 🎥 Closest portrayals: 🔸 Suchet – perfect subtle Belgian accent 🔸 Finney – formal , slight accent 🔸 Branagh – inconsistent Belgian-French tone 🔸 Ustinov – more laid-back , not authentic Belgian --- 🧼 6. Personality & Mannerisms 🔹 “Everything must be tidy and symmetrical.” — The ABC Murders (1936) Fastidious , orderly Polite but proud Prone to mild arrogance , but never mean Occasionally flustered by disorder > 🎥 Closest portrayals: 🔸 Suchet – obsessive , neat , respectful 🔸 Ustinov – polite but too casual 🔸 Finney – more reserved , dignified 🔸 Branagh – too emotional at times (e.g. crying in Death on the Nile) --- 💬 7. Humor & Warmth 🔹 “Poirot smiled — that slow smile that came rarely , but lighted up his whole face.” — Five Little Pigs (1942) Not comedic , but dryly witty Charming in a subtle way , especially with women or children Rarely emotional , but has empathy > 🎥 Closest portrayals: 🔸 Suchet – subtle warmth and charm 🔸 Ustinov – more humorous , sometimes too light 🔸 Branagh – goes for modern emotion --- 🏁 Summary: Who Comes Closest? Trait Best Portrayal Physical Build David Suchet Moustache Our Composite (Suchet + Branagh shape) Accent & Speech Suchet (with Finney’s formality) Intelligence Suchet Mannerisms Suchet Humor Suchet with a dash of Ustinov Visual Style Suchet + Finney blend --- 🏆 Verdict: David Suchet remains the gold standard overall. But a Finney base with Suchet’s mannerisms and moustache enhancements (as we created earlier) gives you a 100% faithful visual and behavioral Poirot. Would you like me to turn this into a printable profile or dossier for Poirot fans? ,
crea una historia tipo plantilla de comics donde los personajes están muy felices , una mujer que tiene flores en sus manos salta de alegría y tira las flores hacia el cielo lleva en su camisa Azul \"12 Ligis\" , una niña que tiene un globo en forma de corazon baila de alegría en sus manos que lleva en su camisa rosada \"23 Sarita\" , un hombre que tiene una taza de café en sus manos la lleva hasta sus labios y toma cafe que lleva en su camisa roja \"24 Angelito\" , un hombre que tiene una pizza en su manos parte una porción y la comparte con un perrito que lleva en su camisa roja \"05 carlini\" , y un hombre que tiene una crispetas en su manos se estallan las crispetas en su manos haciendo mas crispeta que lleva en su camisa verde \"09 El Juli\" , los fuegos pirotécnicos estallan en el cielo , los letreros que dicen \"Mayo , ya esta aquí\" , estilo comic ,
crea una historia tipo plantilla de comics donde los personajes están muy felices , una mujer que tiene flores en sus manos salta de alegría y tira las flores hacia el cielo lleva en su camisa Azul \"12 Ligis\" , una niña que tiene un globo en forma de corazon baila de alegría en sus manos que lleva en su camisa rosada \"23 Sarita\" , un hombre que tiene una taza de café en sus manos la lleva hasta sus labios y toma cafe que lleva en su camisa roja \"24 Angelito\" , un hombre que tiene una pizza en su manos parte una porción y la comparte con un perrito que lleva en su camisa roja \"05 carlini\" , y un hombre que tiene una crispetas en su manos se estallan las crispetas en su manos haciendo mas crispeta que lleva en su camisa verde \"09 El Juli\" , los fuegos pirotécnicos estallan en el cielo , los letreros que dicen \"Mayo , ya esta aquí\" , estilo comic ,
Si me pongo en el lugar de un humano en 2025 imaginando el año 2050 con un estilo retrofuturista , pensaría en un celular que mezcle lo antiguo con lo futurista de una forma nostálgica pero avanzada. Este celular del 2050 tendría una carcasa metálica con detalles cromados y esquinas redondeadas , como los dispositivos de los años 80 y 90 , pero su tecnología sería ultramoderna. En lugar de una pantalla táctil convencional , usaría una proyección holográfica en 3D que se despliega sobre el dispositivo , permitiendo interactuar con gestos en el aire. Tendría botones físicos , pero en realidad serían capacitivos y personalizables según la función que el usuario necesite. Además , incluiría una antena extensible , no porque sea necesaria , sino como un homenaje al diseño clásico de los primeros celulares. La inteligencia artificial del celular sería completamente integrada en la vida del usuario , funcionando casi como un asistente personal avanzado que anticipa necesidades sin invadir la privacidad. Para la energía , ya no dependería de baterías convencionales , sino de una tecnología de carga ambiental que absorbe energía del entorno , como ondas de radio o luz solar. En cuanto a la conectividad , podría comunicarse a través de redes cuánticas , eliminando la latencia y haciendo que las llamadas y transferencias de datos sean instantáneas sin riesgo de hackeo. Y , como detalle estético , sus colores serían vibrantes , con opciones de iluminación neón personalizable para darle ese toque ochentero pero con la elegancia del futuro. ,
Fairness means ensuring your analysis doesn't create or reinforce bias. This can be challenging , but if the analysis is not objective , the conclusions can be misleading and even harmful. In this reading , you’re going to explore some best practices you can use to guide your work toward a more fair analysis! Consider fairness Following are some strategies that support fair analysis: Best practice Explanation Example Consider all of the available data Part of your job as a data analyst is to determine what data is going to be useful for your analysis. Often there will be data that isn’t relevant to what you’re focusing on or doesn’t seem to align with your expectations. But you can’t just ignore it; it’s critical to consider all of the available data so that your analysis reflects the truth and not just your own expectations. A state’s Department of Transportation is interested in measuring traffic patterns on holidays. At first , they only include metrics related to traffic volumes and the fact that the days are holidays. But the data team realizes they failed to consider how weather on these holidays might also affect traffic volumes. Considering this additional data helps them gain more complete insights. Identify surrounding factors As you’ll learn throughout these courses , context is key for you and your stakeholders to understand the final conclusions of any analysis. Similar to considering all of the data , you also must understand surrounding factors that could influence the insights you’re gaining. A human resources department wants to better plan for employee vacation time in order to anticipate staffing needs. HR uses a list of national bank holidays as a key part of the data-gathering process. But they fail to consider important holidays that aren’t on the bank calendar , which introduces bias against employees who celebrate them. It also gives HR less useful results because bank holidays may not necessarily apply to their actual employee population. Include self-reported data Self-reporting is a data collection technique where participants provide information about themselves. Self-reported data can be a great way to introduce fairness in your data collection process. People bring conscious and unconscious bias to their observations about the world , including about other people. Using self-reporting methods to collect data can help avoid these observer biases. Additionally , separating self-reported data from other data you collect provides important context to your conclusions! A data analyst is working on a project for a brick-and-mortar retailer. Their goal is to learn more about their customer base. This data analyst knows they need to consider fairness when they collect data; they decide to create a survey so that customers can self-report information about themselves. By doing that , they avoid bias that might be introduced with other demographic data collection methods. For example , if they had sales associates report their observations about customers , they might introduce any unconscious bias the employees had to the data. Use oversampling effectively When collecting data about a population , it’s important to be aware of the actual makeup of that population. Sometimes , oversampling can help you represent groups in that population that otherwise wouldn’t be represented fairly. Oversampling is the process of increasing the sample size of nondominant groups in a population. This can help you better represent them and address imbalanced datasets. A fitness company is releasing new digital content for users of their equipment. They are interested in designing content that appeals to different users , knowing that different people may interact with their equipment in different ways. For example , part of their user-base is age 70 or older. In order to represent these users , they oversample them in their data. That way , decisions they make about their fitness content will be more inclusive. Think about fairness from beginning to end To ensure that your analysis and final conclusions are fair , be sure to consider fairness from the earliest stages of a project to when you act on the data insights. This means that data collection , cleaning , processing , and analysis are all performed with fairness in mind. A data team kicks off a project by including fairness measures in their data-collection process. These measures include oversampling their population and using self-reported data. However , they fail to inform stakeholders about these measures during the presentation. As a result , stakeholders leave with skewed understandings of the data. Learning from this experience , they add key information about fairness considerations to future stakeholder presentations. ,
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