#rinard

[elwynten]

Haruhime

[middleland]

Little Muskingum River & Hune Covered Bridge (2) (3) (4) by Tim Hoeflich

Via Flickr:

Hune is a beautiful old covered bridge just off of Ohio Rt 26 near Dart, Ohio. It is now closed to traffic due to land slippage around one of its piers. Thankfully there is a plan to stabilize the pier and possibly even eventually move the bridge to a safer location. Hune covered bridge spans the Little Muskingum River a few miles beyond Dart but before Rinard Mills Ohio. It was built in 1879 by Rolla Merydith and rehabilitated in 1998, but is once again in need of some repair.         

[driftingqueer]

entropy by andrea rinard is mafuyu coded and shows the intensity of mafuyu's identity suppression and her mother's overbearing presence

"I need to make myself smaller. I need to not take up so much room."

mafuyu's self suppressing and drowning deeper down the lake, is shrinking in presence, she couldn't let it take much room inside her when the room, her intrinsic feelings were crumbling and crafted into ones that she could let on surface.

"I suck the oxygen out of the house, this family. I'm busy shrinking myself when she comes into the only room in the house with empty hinges."

mafuyu felt like her self expression was a burden and bother and something that made others worrisome, she apologizes to her mother anytime she puts forward a piece of her mind. the 'she', the mother who barges in, in a room with empty hinges,it's mafuyu's mother's invasion of privacy and obsessive control over her without a regard to provide mafuyu true and free choice

"Mom has those eyes, and I know she's about to say again (and again, and again) "Did you take your meds?"

Yes. It's always yes. I swallow the pills every morning, round like a buoy. I do what I'm supposed to do even though nothing keeps me afloat."

the question about medication, while radiates as concerned and caring facade, something mafuyu's mother also implements for more effective manipulation, she too brings up the question about (studying) medicine, the answer is always in accordance to obedience, mafuyu does everything she could to fit into the illusion of her mother's image of the daughter she thinks she has, while mafuyu's identity sinks deeper and deeper down the lake

"Those eyes walk away, but they've rent my skin, and I seep, the blood rising. I try to unfurl my wings to fly away because the window still works, but my wings are sticky, and I can't rise. A single feather falls. More will follow unless I'm very still, so I fold in on myself and try not to look up."

even when the mother is not physical present and her surveillance is not actually there, the mother's huge presence lingers over mafuyu from the skin that looks like hers to the same blood that runs in both of their veins, she can't extend her wings when they're tied by the marionette strings, her wings are sticky, just like the mother's huge presence sticky into her way of being, the falling feathers, is how mafuyu's self falls deeper down the abyss, there's nothing visible, it's an empty world down below, with each feather falling her wings are dying and mafuyu's descending closer and closer to never being able to hope to fly, she'd disappear..

"I need to make myself smaller. I need to not take up so much room. There's not enough space, enough air for me in this house, in this family. Mom walks through the doorway to the open portal to where I live, the only room without a door.

Her eyes swallow me, and she digests me at a glance; I'm getting better at being small.

"Did you take your meds?" she asks. I nod because I need to take away the sadness, a darkness over the hope and the love. If I'm smaller. I won't cast a shadow.

Besides, it's always yes. I swallow the pills every morning, but I'm still the heaviest thing in the house, in the world. I will sink us all, and Mom's eyes say she knows that, but she will always reach out her hand and let me drown her."

mafuyu's self is getting smaller, drowning deeper down the lake, twisting the key harder to keep the door locked, she cannot let her true feelings burden and bother and worry her parents, the house is stifling it cannot contain both mafuyu, the true self and the image of what her mother sees her to be, the true self needs to die. when her mother intrudes her privacy her personal space into her room, the solitary place which connects mafuyu to niigo, her place where she can say she lives, that place too is constantly invaded by her mother's surveillance. the swallowing and digestion in one glance is like as the true self gets smaller and as mafuyu displays a convincing illusion of her mother's desired image the easier living in the surveillance and heightened presence of mother will be.

the meds question comes again just like the mother's demands for mafuyu to be the daughter that the mother believes her to be. If the true self gets smaller it'll surely not cast a shadow, that is leave a single trace to be caught as something that diverges the mother's desired image

the answer as always is yes and with every yes, with the swallowing of everything said and asked from her, her heart is heavy with all the whirlwinds of confusing feelings, her wings can't lift her up and now the weight of expectations and darkness over her reduces the chances of ever flying even more, she'll just let her many huge suppressed feelings sink her heart deep down just like the true self.

"Mom's eyes walk away, and I look at my window. I will be able to fly away, far, far, far, and Mom's eyes won't see me. I imagine I have wings, but I'm not a bird. I'm an anchor. My only view is the bottom, and I will sink down, down, down.

I need to make myself smaller. I need to not take up so much room. I am a vacuum that takes every breath meant for others. Mom pauses where my door used to be."

the eyes walking away and shifting focus to the window, for mafuyu that window is her device screen which is a portal between her and niigo, here she can feel a sense of what it'd like to be if she could fly away breaking free from the marionette strings tying her down.

the view beneath the surface is dark and nothingness, the true feelings that are a burden only stay underneath the surface deep down where they wouldn't be expressed and bother others. like a vaccum that sucks every breath meant for others, mafuyu's true self is something that is better suppressed, everyone around is happier when she isn't who she truly is.

"They all stop when they pass, but Mom is the one whose eyes hurt. She asks me in the only language we now speak, "Did you take your meds?"

Yes. It's always yes. The pills are round like a seashell, but I can't hear my own voice no matter what I press my ear to."

the only language they speak is when her mother demands or ask her for something and she answers a yes. their connection is completely faulty. the loss of hearing her own voice, mafuyu's self is soo deep down the lake that sounds don't reach herself, in yoko ogawa's words, "when you lost your voice, you lost the ability to make sense of yourself", after losing herself and then the power of making sense with a self that isn't herself, she is lost, the tides of suppression have devoured her whole.

"Mom walks away, and I'm tired. So, so tired. I think of sun. The beach. A single gull that circles the sky. I want to find that child who collected shells, holding them out to her mother who put them in a bucket like treasure. It's too far away to see clearly, but I keep looking out the window."

mafuyu too had a special memory of her mother taking care of her when she fell ill, it's too far away, she has a long way and their relationship is only crumbling, yet mafuyu can feel that similar sense of warmth through the window, the screen that connects her to niigo

[iowa-mentioned]

Rinard IA

[sunaleisocial]

MIT researchers introduce generative AI for databases

New Post has been published on https://sunalei.org/news/mit-researchers-introduce-generative-ai-for-databases/

MIT researchers introduce generative AI for databases

A new tool makes it easier for database users to perform complicated statistical analyses of tabular data without the need to know what is going on behind the scenes.

GenSQL, a generative AI system for databases, could help users make predictions, detect anomalies, guess missing values, fix errors, or generate synthetic data with just a few keystrokes.

For instance, if the system were used to analyze medical data from a patient who has always had high blood pressure, it could catch a blood pressure reading that is low for that particular patient but would otherwise be in the normal range.

GenSQL automatically integrates a tabular dataset and a generative probabilistic AI model, which can account for uncertainty and adjust their decision-making based on new data.

Moreover, GenSQL can be used to produce and analyze synthetic data that mimic the real data in a database. This could be especially useful in situations where sensitive data cannot be shared, such as patient health records, or when real data are sparse.

This new tool is built on top of SQL, a programming language for database creation and manipulation that was introduced in the late 1970s and is used by millions of developers worldwide.

“Historically, SQL taught the business world what a computer could do. They didn’t have to write custom programs, they just had to ask questions of a database in high-level language. We think that, when we move from just querying data to asking questions of models and data, we are going to need an analogous language that teaches people the coherent questions you can ask a computer that has a probabilistic model of the data,” says Vikash Mansinghka, senior author of a paper introducing GenSQL and a principal research scientist and leader of the Probabilistic Computing Project in the MIT Department of Brain and Cognitive Sciences.

When the researchers compared GenSQL to popular, AI-based approaches for data analysis, they found that it was not only faster but also produced more accurate results. Importantly, the probabilistic models used by GenSQL are explainable, so users can read and edit them.

“Looking at the data and trying to find some meaningful patterns by just using some simple statistical rules might miss important interactions. You really want to capture the correlations and the dependencies of the variables, which can be quite complicated, in a model. With GenSQL, we want to enable a large set of users to query their data and their model without having to know all the details,” adds lead author Mathieu Huot, a research scientist in the Department of Brain and Cognitive Sciences and member of the Probabilistic Computing Project.

They are joined on the paper by Matin Ghavami and Alexander Lew, MIT graduate students; Cameron Freer, a research scientist; Ulrich Schaechtel and Zane Shelby of Digital Garage; Martin Rinard, an MIT professor in the Department of Electrical Engineering and Computer Science and member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Feras Saad, an assistant professor at Carnegie Mellon University. The research was recently presented at the ACM Conference on Programming Language Design and Implementation.

Combining models and databases

SQL, which stands for structured query language, is a programming language for storing and manipulating information in a database. In SQL, people can ask questions about data using keywords, such as by summing, filtering, or grouping database records.

However, querying a model can provide deeper insights, since models can capture what data imply for an individual. For instance, a female developer who wonders if she is underpaid is likely more interested in what salary data mean for her individually than in trends from database records.

The researchers noticed that SQL didn’t provide an effective way to incorporate probabilistic AI models, but at the same time, approaches that use probabilistic models to make inferences didn’t support complex database queries.

They built GenSQL to fill this gap, enabling someone to query both a dataset and a probabilistic model using a straightforward yet powerful formal programming language.

A GenSQL user uploads their data and probabilistic model, which the system automatically integrates. Then, she can run queries on data that also get input from the probabilistic model running behind the scenes. This not only enables more complex queries but can also provide more accurate answers.

For instance, a query in GenSQL might be something like, “How likely is it that a developer from Seattle knows the programming language Rust?” Just looking at a correlation between columns in a database might miss subtle dependencies. Incorporating a probabilistic model can capture more complex interactions.   

Plus, the probabilistic models GenSQL utilizes are auditable, so people can see which data the model uses for decision-making. In addition, these models provide measures of calibrated uncertainty along with each answer.

For instance, with this calibrated uncertainty, if one queries the model for predicted outcomes of different cancer treatments for a patient from a minority group that is underrepresented in the dataset, GenSQL would tell the user that it is uncertain, and how uncertain it is, rather than overconfidently advocating for the wrong treatment.

Faster and more accurate results

To evaluate GenSQL, the researchers compared their system to popular baseline methods that use neural networks. GenSQL was between 1.7 and 6.8 times faster than these approaches, executing most queries in a few milliseconds while providing more accurate results.

They also applied GenSQL in two case studies: one in which the system identified mislabeled clinical trial data and the other in which it generated accurate synthetic data that captured complex relationships in genomics.

Next, the researchers want to apply GenSQL more broadly to conduct largescale modeling of human populations. With GenSQL, they can generate synthetic data to draw inferences about things like health and salary while controlling what information is used in the analysis.

They also want to make GenSQL easier to use and more powerful by adding new optimizations and automation to the system. In the long run, the researchers want to enable users to make natural language queries in GenSQL. Their goal is to eventually develop a ChatGPT-like AI expert one could talk to about any database, which grounds its answers using GenSQL queries.   

This research is funded, in part, by the Defense Advanced Research Projects Agency (DARPA), Google, and the Siegel Family Foundation.

[jcmarchi]

MIT researchers introduce generative AI for databases

New Post has been published on https://thedigitalinsider.com/mit-researchers-introduce-generative-ai-for-databases/

MIT researchers introduce generative AI for databases

A new tool makes it easier for database users to perform complicated statistical analyses of tabular data without the need to know what is going on behind the scenes.

GenSQL, a generative AI system for databases, could help users make predictions, detect anomalies, guess missing values, fix errors, or generate synthetic data with just a few keystrokes.

For instance, if the system were used to analyze medical data from a patient who has always had high blood pressure, it could catch a blood pressure reading that is low for that particular patient but would otherwise be in the normal range.

GenSQL automatically integrates a tabular dataset and a generative probabilistic AI model, which can account for uncertainty and adjust their decision-making based on new data.

Moreover, GenSQL can be used to produce and analyze synthetic data that mimic the real data in a database. This could be especially useful in situations where sensitive data cannot be shared, such as patient health records, or when real data are sparse.

This new tool is built on top of SQL, a programming language for database creation and manipulation that was introduced in the late 1970s and is used by millions of developers worldwide.

“Historically, SQL taught the business world what a computer could do. They didn’t have to write custom programs, they just had to ask questions of a database in high-level language. We think that, when we move from just querying data to asking questions of models and data, we are going to need an analogous language that teaches people the coherent questions you can ask a computer that has a probabilistic model of the data,” says Vikash Mansinghka, senior author of a paper introducing GenSQL and a principal research scientist and leader of the Probabilistic Computing Project in the MIT Department of Brain and Cognitive Sciences.

When the researchers compared GenSQL to popular, AI-based approaches for data analysis, they found that it was not only faster but also produced more accurate results. Importantly, the probabilistic models used by GenSQL are explainable, so users can read and edit them.

“Looking at the data and trying to find some meaningful patterns by just using some simple statistical rules might miss important interactions. You really want to capture the correlations and the dependencies of the variables, which can be quite complicated, in a model. With GenSQL, we want to enable a large set of users to query their data and their model without having to know all the details,” adds lead author Mathieu Huot, a research scientist in the Department of Brain and Cognitive Sciences and member of the Probabilistic Computing Project.

They are joined on the paper by Matin Ghavami and Alexander Lew, MIT graduate students; Cameron Freer, a research scientist; Ulrich Schaechtel and Zane Shelby of Digital Garage; Martin Rinard, an MIT professor in the Department of Electrical Engineering and Computer Science and member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Feras Saad, an assistant professor at Carnegie Mellon University. The research was recently presented at the ACM Conference on Programming Language Design and Implementation.

Combining models and databases

SQL, which stands for structured query language, is a programming language for storing and manipulating information in a database. In SQL, people can ask questions about data using keywords, such as by summing, filtering, or grouping database records.

However, querying a model can provide deeper insights, since models can capture what data imply for an individual. For instance, a female developer who wonders if she is underpaid is likely more interested in what salary data mean for her individually than in trends from database records.

The researchers noticed that SQL didn’t provide an effective way to incorporate probabilistic AI models, but at the same time, approaches that use probabilistic models to make inferences didn’t support complex database queries.

They built GenSQL to fill this gap, enabling someone to query both a dataset and a probabilistic model using a straightforward yet powerful formal programming language.

A GenSQL user uploads their data and probabilistic model, which the system automatically integrates. Then, she can run queries on data that also get input from the probabilistic model running behind the scenes. This not only enables more complex queries but can also provide more accurate answers.

For instance, a query in GenSQL might be something like, “How likely is it that a developer from Seattle knows the programming language Rust?” Just looking at a correlation between columns in a database might miss subtle dependencies. Incorporating a probabilistic model can capture more complex interactions.   

Plus, the probabilistic models GenSQL utilizes are auditable, so people can see which data the model uses for decision-making. In addition, these models provide measures of calibrated uncertainty along with each answer.

For instance, with this calibrated uncertainty, if one queries the model for predicted outcomes of different cancer treatments for a patient from a minority group that is underrepresented in the dataset, GenSQL would tell the user that it is uncertain, and how uncertain it is, rather than overconfidently advocating for the wrong treatment.

Faster and more accurate results

To evaluate GenSQL, the researchers compared their system to popular baseline methods that use neural networks. GenSQL was between 1.7 and 6.8 times faster than these approaches, executing most queries in a few milliseconds while providing more accurate results.

They also applied GenSQL in two case studies: one in which the system identified mislabeled clinical trial data and the other in which it generated accurate synthetic data that captured complex relationships in genomics.

Next, the researchers want to apply GenSQL more broadly to conduct largescale modeling of human populations. With GenSQL, they can generate synthetic data to draw inferences about things like health and salary while controlling what information is used in the analysis.

They also want to make GenSQL easier to use and more powerful by adding new optimizations and automation to the system. In the long run, the researchers want to enable users to make natural language queries in GenSQL. Their goal is to eventually develop a ChatGPT-like AI expert one could talk to about any database, which grounds its answers using GenSQL queries.   

This research is funded, in part, by the Defense Advanced Research Projects Agency (DARPA), Google, and the Siegel Family Foundation.

[oregontennis]

Girls 4A District 1 All-Conference Teams

First Team

Ryan Lomber, Valley Catholic

Amanda Perez, Catlin Gabel

Sami Shivakumar, Valley Catholic

Ella Li, Oregon Episcopal

Jiya Mehta/Elise Kim, Catlin Gabel

Marin Roseman/Ava Do, OES

Ria Kamineni/Lucy Bergland, OES

Olivia Morrison/Lily Wang, Catlin Gabel

Second Team

Nina Rinard, Riverdale

Cici Ji, Oregon Episcopal

Madeline Johnson, Trinity Academy

Sarah Fisher, Westside Christian

Lucie Polvogt/Ayla Clark, St Helens

Jaya Kover/Leela Kover, OES

Journi Brouhard/Rebekah Werner, Tillamook

Grace Weber/Sophie Schindler, Blanchet Catholic

Andreea Dan/Catherine Rocha, Valley Catholic

All-Conference Honorable Mention

Ruthie Murphy, Riverside

Jackie Espina, Trinity Academy

Meret Pajikic, Catlin Gabel

Ariel Vasquez, Tillamook

Makalya Heinz, St. Helens

Sofia D'Uva, Riverdale

Maylise Abrogoua, Tillamook

Halle Shearer, Riverdale

Satya Semenchalam/Ava Thuret, Valley Catholic

Sophia Hu/Violet Kozak, Catlin Gabel

Addison Raab/Ozzy Chaney, St Helens

Svannah Augustus/Keira Augustus, St Helens

Cosette Milla/Eda Daim, St Helens

Rachael Yang/Brooke Kopetz, Valley Catholic

Natalie Howard/Kyonna Picard, Scappoose

[gebo4482]

Spider-Man: Into the Spider-Man by Yuhki Demers / Ernie Rinard

[bodhitreebluebird]

i have been personally murdered by the raven paradox

[happyplantroots]

Rinard Orchid Greenhouse 10/12/21

[cucircula]

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via https://repaircreditfile.wordpress.com/rinard-iowa-credit-repair-888-502-1260/ September 26, 2019 at 02:13PM Copyright © September 26, 2019 at 02:13PM

[elwynten]

Haruhime

[goeighthe]

Rinard Road Cleveland, Ohio Credit Repair | (888) 502-1260

Rinard Road Cleveland, Ohio Free Credit Repair Counseling call (888) 502-1260 remove bankruptcy, free consumer report, fix bad credit, check your annual Equifax, TransUnion, Experian credit report.

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Credit is a way of life in Rinard Road Cleveland, Ohio. Without good credit, you have to take your seat in the second-class section of our economy. But, if your credit is in shambles, you may not be willing to wait for seven years while your credit report repairs itself.

Is there anything you can do to speed your credit repair? Many authorities, such as the news media, will tell you there is nothing you can do to repair your credit. Newspapers, magazines, and TV news journals all seem to be unanimous in discouraging you from making any effort to repair your credit before the seven year limit.

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  https://youtu.be/w70PTBqCVHI

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from Rinard Road Cleveland, Ohio Credit Repair | (888) 502-1260 via Rinard Road Cleveland, Ohio Credit Repair | (888) 502-1260 June 07, 2019 at 01:08AM Copyright © June 07, 2019 at 01:08AM

[rolaymens]

Rinard Road Cleveland, Ohio Credit Repair | (888) 502-1260

Rinard Road Cleveland, Ohio Free Credit Repair Counseling call (888) 502-1260 remove bankruptcy, free consumer report, fix bad credit, check your annual Equifax, TransUnion, Experian credit report.

Call Rinard Road Cleveland, Ohio credit repair (888) 502-1260 to see how we really actually work. Why is it so common to hear that bad credit can’t be repaired? What does the law say about repairing your credit? What is the truth about credit repair companies? Can they really do what they say they can do? How do you go about completely repairing your credit and getting new credit lines, mortgages, etc.? Can you add good credit to your credit report by having another person add you as an authorized user to one of their credit cards? Why is it so common to hear that bad credit can’t be repaired?

Credit is a way of life in Rinard Road Cleveland, Ohio. Without good credit, you have to take your seat in the second-class section of our economy. But, if your credit is in shambles, you may not be willing to wait for seven years while your credit report repairs itself.

Is there anything you can do to speed your credit repair? Many authorities, such as the news media, will tell you there is nothing you can do to repair your credit. Newspapers, magazines, and TV news journals all seem to be unanimous in discouraging you from making any effort to repair your credit before the seven year limit.

  http://chandler-az-85225.blogspot.com/p/downtown-downtown-business-district_56.html?m=1

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    https://www.youtube.com/channel/UClhzrsORG5u3r9-xyu8pvCQ/about

  https://youtu.be/w70PTBqCVHI

    copyright © 2016 Privacy Policy

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[narcbrain]

Rinard Greenhouse holds free meditation for students

MUNCIE, Ind.(NewsLink) – Making an attempt to equilibrium school and all other activities can be demanding for some learners. 

The Counseling Centre has supplied to aid college students deal with stress by hosting meditation groups that are no cost for Ball State pupils. 

The initial Tuesday of just about every thirty day period they host meditation circles. 

Tuesday, the Counseling Middle came…