weeklyAI
TertulIA · courses
You are not learning a tool. You are learning to judge one.
Not from the company that sells it, not from someone who learned it last month, not from an influencer: from a professor with twenty-five years on how people come to know what they know, who looks at these systems critically and teaches you to.
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Tell me what you want to be able to do, and I tell you which course teaches it, which lesson is free, and what it costs.
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Course · 20 lessons
Understand
What you learn
How generative AI works, and why an answer can be persuasive and wrong.
Where it comes from
A career spent on how you know what you know.
The answer looked right. It was wrong, and it was sure. This course opens the machine so you can see why: where the next word comes from, what the model read and what it never saw, why it forgets, how to pin it to a document so it stops inventing, and what happens to your own thinking when you let it do the thinking. Twenty lessons, nothing to install and no code: for anyone who uses these tools or lives with someone who does. After them you look at any AI answer the way a doctor looks at an X-ray.
Lesson 1 · 31:46
Trailer · 1:23
All 20 lessons →
- E01 · Everything Is Numbers
You trace what a scanner, a chat box or a phone threw away to turn your document into numbers, and check whether the wrong thing was lost.free - E02 · The Pile That Reads You Back
You leave able to name the pile somebody gathered behind any AI answer, and to build the count your own work needs.subscribe - E03 · Why Your AI Doesn't Think
You leave naming what each of four mind words hides, pointing to where the understanding lives, and asking questions that can be answered.subscribe - E04 · Where Does The Next Word Come From
You draw the loop that picks every next word, work the dial that sharpens or flattens it, and say whose job the checking is.subscribe - E05 · What Did The Model Actually Read
You leave able to predict where an artificial intelligence comes up thin, ask who measured its high-quality data, and test the Spanish label with your own voice.subscribe - E06 · Is The New One Actually Better
You leave with three questions for any AI score: better at what, measured how, and better for whom.subscribe - E07 · Where Confident Wrong Answers Come From
You run one check on any AI citation, in your own field's registry, before it matters.subscribe - E08 · What Did The Model Just Forget
You carry a working number for every AI, put what matters at the start or end, and read the notes the machine keeps about you.subscribe - E09 · Anchor Your AI To A Document
You attach your own document to an AI, make it hand back the passage it used, and read that passage against the claim before acting.subscribe - E10 · When AI Thinks Step By Step
You leave with one habit: check the single load-bearing step of any worked answer against the world, not the machine.subscribe - E11 · The Six Dimensions Of Every Prompt
You name the six dimensions every prompt already occupies, tell a choice you made from one made for you, and walk the six before blaming the machine.subscribe - E12 · The Energy And Waste Of Using AI
You read any AI energy or water number by asking what it includes, then find the boundary behind two figures that disagree.subscribe - E13 · What's Free For You, What Costs Money
You file any free AI banner under one of five kinds and name what it takes back from you.subscribe - E14 · Pay Less, Depend Less
You read the six dials on any AI bill, turn the three that were always yours, and know which errands deserve no meter at all.subscribe - E15 · Tool Choice As Values Choice
You answer four questions about any AI vendor from its own public documents and name the values cost your choice accepts.subscribe - E16 · The Privacy Floor
You leave with three kinds of personal detail that never go into any AI tool, and a two-second postcard test for any sentence before you send it.subscribe - E17 · Cognitive Offloading And Your Own Mind
You place any AI use on the line between helping and deciding, and keep three rules that hold your thinking.subscribe - E18 · AI As Something You Check
You run three checks on one AI answer that affects a decision you own, and you say who performs them when nobody is watching.subscribe - E19 · When The Machine Runs Without You
You leave with three questions for any system acting in your name: what it can touch, what bounds it, and who reads what it did.subscribe - E20 · Model Collapse And What Comes Next
You trace a 2024 model collapse headline back to the paper and name the one word that fell out on the way.subscribe
Then, with your own hands
Course · 1 lesson
Start here
What you learn
How to get a Google account on your own terms, anonymous if you want it and deletable whenever, and how to reach Colab with it.
Where it comes from
The course on information management and privacy created at Sacramento State and taught there since.
Twenty minutes and you have a workshop: a Google account that belongs to you and no one else, anonymous if you want it, gone the day you say so, and the page where every notebook in these courses runs. No download, no card, no trace. Everything else starts here.
Lesson 1 · 4:56free
The one lesson →
- A Google Account, On Your Terms
You build a working Google account from an invented name and a phone number you control, run a Colab notebook, and delete the account whenever you choose.free
Course · 10 lessons
Create
What you learn
Text, images, music, voice and video, calling the models through their APIs in notebooks the AI writes for you.
Where it comes from
Generative film and poetry since 1998, with festival awards from Moscow to Red Rocks.
A song by Friday. A film by the end of the month. A voice that reads your words back to you. Not by pressing a button on someone's app, but by calling the models at their own door, in a notebook the AI writes while you decide what to ask, and with a workshop where the whole chain runs and your data never leaves your hands. Seven lessons. You leave with things you made and the code that made them, which is the part no one else gives you.
Lesson 1
Trailer · 1:34
All 10 lessons →
- C01 · The Machine That Continues
You can read the twenty seven lines behind any chat window, say what the model does, and name the slot that decides who a message is aimed at.free - C02 · Run The Function Yourself
You run the chat function yourself, swap one line to ask about your own town, and check one generated claim against a source the machine never wrote.subscribe - C03 · What The Machine Did And Never Did
You write a commission for an image AI, purpose first, and read its strange habits as signatures instead of surprises.subscribe - C04 · Cross To The Engine, Keep The Receipt
You commission a campaign's three pictures through a chat door and an engine, judging each against its purpose and reading the session's receipt.subscribe - C06 · Two Questions For Every Voice
You read a synthetic voice's full name, pick its name and speed yourself, and ask any AI voice what text it got and who chose its name.subscribe - C07 · Make The Voice That Taught You
You leave with an audio file made from your own sentence, in a voice you chose, its name and date proven in the filename.subscribe - C08 · You Already Own The Instrument
You read the four-cent price and its August 2026 date, brief a thirty-second intro in tempo, instruments and mood, and keep one of four takes.subscribe - C09 · Watch The Refusal, Then Play The Song
You turn a sentence into a song, keep two takes that never match, and read the bill for what it cost.subscribe - C10 · Why The First Answer Is Empty
You order an eight-second ident from the video engine, read its ticket and price, wait out the errand, and judge the take with your own eyes.subscribe - C11 · Buy The Wait, Trust Only The File
You leave with a three-step notebook that turns a sentence into video, a file that states its own truth, an ident chosen by eye, and a printed bill.subscribe
Course · 9 lessons
Research
What you learn
Public archives turned into evidence you can cite, their APIs opened by code the AI writes while you ask the questions.
Where it comes from
The method behind Requiem Diurnus, AI News Social, and weeklyAI.
Every law the United States has published, every word said in Congress, every presidential paper, decades of television news, the world's headlines as data: it is all public, and almost no one knows how to open it. Nine lessons open nine of these archives through their APIs, the AI writing the code, you asking the question, each one ending in evidence with a citation. It is the method the publication itself runs on every week.
Lesson 1
Trailer · 1:27
All 9 lessons →
- I01 · The Federal Register API
You leave with a spreadsheet of signed Federal Register decrees about Mexico from 2018, each with its title, date and number.free - I02 · The Media Cloud API
You pick a fortnight, a field and search terms, then count and sample the press coverage in MediaCloud yourself.subscribe - I03 · The GovInfo Congressional Record API
You ask the Congressional Record what Congress said about NAFTA in 1994 and read the speeches yourself.subscribe - I04 · The GovInfo Compilation of Presidential Documents API
You ask the presidential archive what a president said about Latin America on a named night, and read the sentence yourself.subscribe - I05 · The Arctic Shift Reddit Archive
You ask a Reddit community's own threads what people said while their money died, and leave with dated rows and votes.subscribe - I06 · The GDELT TV API
You ask a television archive how often a name was said, on which stations, in which week, and read the count it returns.subscribe - I07 · The Internet Archive TV News Archive
You leave with a catalog of real Haiti earthquake broadcasts, each with its full title, air time, and a link that opens the tape in your browser.subscribe - I08 · The American Presidency Project
You leave with President Kennedy's own dated words on the Alliance for Progress, pulled from the American Presidency Project, beside what was said about him.subscribe - I09 · The CNN Transcripts Archive
You leave with a whole broadcast day from transcripts.cnn.com, readable hour by hour in one file you built from the record.subscribe
Course · 6 lessons
Know
What you learn
The scholarly record, read through the APIs that hold it, with no university badge and no code of your own.
Where it comes from
Peer-reviewed research published in two languages.
Somewhere there is a study on exactly what you are worrying about tonight. This course teaches you to find it and to read it, not the headline about it: six lessons on the indexes that hold the world's science, CrossRef, arXiv, OpenAlex, PubMed and the rest, with no university badge and no code of your own. You leave able to tell a real journal from a fake one and a finding from a press release.
Lesson 1free
All 6 lessons →
- The CrossRef API
You count how many journal articles carry a word in their title, follow a DOI fingerprint to the page, and see what the registry gives free.free - The arXiv API
You leave with the newest unchecked papers on a question of your own, saved in a file, and one open on the desk read by you first.subscribe - The OpenAlex API
You pull a field's most-cited papers from OpenAlex yourself, follow who built on them, and see why two counters give two honest numbers.subscribe - The DOAJ API
You search a Spanish-language open-access journal directory by title, read the encoded address back, and count the results to check the free-access promise.subscribe - The PubMed API
You ask PubMed twice, keep the breath between, and read off the run how much of the medical literature is free to anyone.subscribe - The Library of Congress API
You count what the Library of Congress holds on one word, learn which of its two numbers is the answer, and check a machine's reading against the print.subscribe
Course · 6 lessons
Analyze
What you learn
What a pile of text is really doing, in notebooks that reach the corpus through its API.
Where it comes from
Tablada hipertextual, which reads meaning at the level of the word, and the classroom tools that score reasoning.
Ten thousand comments. A year of speeches. Every review of one product. You cannot read them; the machine can count them, and this course teaches you to make it count honestly: which ideas travel together, what changes between two piles set face to face, what one word is doing across all of it, how the whole thing feels. Six lessons, in notebooks that reach the texts through their API. You leave able to answer "what does all this say?" and show your work.
Lesson 1
Trailer · 1:23
All 6 lessons →
- A01 · The Shelf and the Cloud
You build a shelf of two hundred open-access misinformation abstracts, read its inventory, and see what a word cloud cannot show.free - A02 · Counting Honestly
You leave with your own filler list, a bar read rank by rank, and two shapes of one count.subscribe - A03 · Ideas Travel in Pairs
You open the phrase count to pairs and trios, then read the sentences that show whether papers name or fight the phrase.subscribe - A04 · Two Piles, Face to Face
You split two hundred abstracts at a year you say out loud, compare the piles by rate, then move the line one year and watch the chart change.subscribe - A05 · One Word at Work
You follow one word through a journal's years, read the sentences it points to, and say which word you chose.subscribe - A06 · How the Pile Feels
You score two hundred misinformation abstracts, check the mood score against the sentences, and say what no chart can tell you.subscribe
Course · 10 lessons
Expand
What you learn
Research with paid APIs: a key of your own, a file that survives the session, and the cost of every call in front of you.
Where it comes from
The paid lanes of the systems run every week, where a key, a quota and a bill are part of the method.
The day free is not enough, you will be asked for a card, and this is where you learn what to buy and what to walk past. Ten lessons on the paid doors: a search that answers one question a thousand ways, the records of the world, any web page read whole, the voices on video and their words as text, a workshop that runs in the cloud and a file that does not vanish when the tab closes. You leave knowing what each costs, what it is worth, and how to buy cold.
Lesson 1
Trailer · 1:27
All 10 lessons →
- A1 · The File That Doesn't Vanish
You leave with a file in your own Drive, ten real rows, and a rule for growing it without erasing it.free - A2 · The Cloud Workshop
You build a research workshop in Drive from one sentence, with backups and charts folders, a dated copy, and a chart, each with an address.subscribe - A3 · One Question, Many Answers
You pay for one search and leave with a list of doors, a fact card and a labelled machine opinion, plus the meter reading of what it cost.subscribe - A4 · The World's Records
One changed word in last lesson's code turns the same key on Google News and Google Scholar, and you keep ten rows from each in one file.subscribe - A5 · What the World Is Asking
You read an engine's autocomplete list as a map of public doubt, file those questions beside documents with the window and country noted, and try a second window.subscribe - A6 · Through the Door
You turn five of your ten press links into whole stored articles with a named key, and note the one door that would not open.subscribe - A7 · Finding the Voices
You search the video platform with the same key and leave with twenty voices stored by their identity, the poster and not the speech.subscribe - A8 · The Spoken Word
You turn a video's identity into a transcript with minutes and seconds, and store the speech beside your articles in the same file.subscribe - A9 · Buying Cold
You walk five steps alone on a service you have never used, from reading its price to a working transcript minutes after the key is born.subscribe - A11 · Choosing from the Menu
You put five questions to any data service, pick a shelf by need, and read the date before the price.subscribe
Who makes thisQuién hace esto
Diego Bonilla, Ph.D.Diego Bonilla, Ph.D.
Full Professor of Communication Studies, Sacramento State, California, United States
Graduate instructor, Universidad Nacional Autónoma de México (UNAM), MexicoProfesor titular de Estudios de la Comunicación, Sacramento State, California, Estados Unidos
Docente de posgrado, Universidad Nacional Autónoma de México (UNAM), México
I am a professor of communication at Sacramento State, where I created the course Information Management and Privacy and have taught it many times, and at UNAM, in Mexico City, I teach the graduate course Electronic and Generative Literature with AI. In both I teach AI. I have taught since 1989, at first mathematics and physics to children who found them hard, and since 1997 one subject that has changed its name many times: media literacy, computer literacy, digital literacy, information literacy, ICT literacy, and now AI literacy.
This page exists because most people cannot go back to a university, and these systems are changing their work, their children's schooling, their parents' care and their vote all the same. What a university teaches about them should reach the people who need it, every week, in plain language, without enrolling anywhere. That is what I do here, and it is what I do on Thursday mornings in a seminar for the Renaissance Society at Sacramento State, built on this publication, where anyone can send a question and hear it answered.
In 2003 my doctorate at Syracuse measured what a machine can infer about a person from the traces they leave, and what I found became the privacy course I still teach. In 2007 and 2009 I sat on the committee at ETS in Princeton that set the national standard for digital literacy, and from 2014 to 2016 I was the California State University's ICT Literacy Ambassador. Six names, one job: helping people not be at the mercy of the newest machine.
Soy profesor de comunicación en Sacramento State, donde creé el curso Gestión de la Información y Privacidad y lo he dado muchas veces, y en el posgrado de la UNAM, en la Ciudad de México, doy el curso Literatura electrónica y generativa con IA. En los dos enseño inteligencia artificial. Doy clases desde 1989; al principio, matemáticas y física a niños a los que se les hacían difíciles, y desde 1997 una sola materia que ha cambiado de nombre muchas veces: alfabetización mediática, informática, digital, informacional, en TIC, y ahora en inteligencia artificial.
Esta página existe porque la mayoría de la gente no puede volver a la universidad, y estos sistemas les están cambiando el trabajo, la escuela de sus hijos, el cuidado de sus padres y su voto de todos modos. Lo que una universidad enseña sobre ellos debe llegar a quien lo necesita, cada semana, en lenguaje llano, sin inscribirse en ninguna parte. Eso es lo que hago aquí, y es lo que hago los jueves por la mañana en un seminario para la Renaissance Society de Sacramento State, construido sobre esta publicación, donde cualquiera manda una pregunta y la oye contestada.
En 2003 mi doctorado en Syracuse midió lo que una máquina puede inferir de una persona por los rastros que deja, y lo que encontré se volvió el curso de privacidad que sigo dando. En 2007 y 2009 formé parte del comité de ETS en Princeton que fijó el estándar nacional de alfabetización digital, y de 2014 a 2016 fui el embajador de alfabetización en tecnologías de la información de la Universidad Estatal de California. Seis nombres, un solo oficio: que la máquina más nueva no lo agarre a usted desarmado.
I have also worked on the other side of the counter. In 2000 I began making films that a machine assembles differently for every viewer; the first of them took first prize at the Moscow International Film Festival in 2004, two decades before the industry shipped a generative model. A generative video poem I made with a poet at UNAM is in the field's definitive anthology, and in 2025 my VR work took an award at an AI film festival. My recent published research is on AI and elections, and on how these models represent the cultures they were not trained on. The systems these courses explain run under my hands daily; they made the pictures and the voices you will see inside.
También he trabajado del otro lado del mostrador. Empecé en el internet en español antes de que hubiera qué vender en él, con una revista literaria en línea en 1995. Desde el año 2000 hago cine que una máquina arma distinto para cada espectador; la primera de esas películas ganó el primer premio del Festival Internacional de Cine de Moscú en 2004, dos décadas antes de que la industria vendiera un modelo generativo. Big Data, un poema en video generativo hecho con el poeta Rodolfo Mata de la UNAM, quedó en la antología definitiva del campo, y en 2025 mi obra en realidad virtual ganó un premio en un festival de cine de inteligencia artificial. Mi investigación reciente publicada es sobre inteligencia artificial y elecciones, y sobre cómo estos modelos representan a las culturas latinoamericanas, que es justamente la pregunta que esta región tiene que hacerle a una tecnología entrenada en otra parte. Los sistemas que estos cursos explican corren a diario bajo mis manos: ellos hicieron las imágenes y las voces que va a ver adentro.
The vendors began teaching AI literacy two years ago, because before that there was nothing to sell. I am not against them. I am simply not one of them, and no one who sells these systems pays for this page.
Los vendedores llevan dos años enseñando alfabetización en inteligencia artificial, porque antes no había nada que vender. No estoy en contra de ellos. Simplemente no soy uno de ellos, y nadie que venda estos sistemas paga esta página. Esta edición no está traducida: la escribo en español, para la región, porque así empecé y a esto vuelvo.
The record, datedLa trayectoria, con fechas
- 1989 Teaching begins, Mexico CityEmpiezo a dar clases, Ciudad de México
- 1995 Hypergraphia, an early Spanish-language web and hypermedia publisherHypergraphia, editorial de hipermedia y una de las primeras revistas literarias en la web en español
- 1996 Mercadotecnia e imagen en Internet, with Jesús del Toro, a book on marketing on the Internet, among the first in Spanish, Editorial IberoaméricaMercadotecnia e imagen en Internet, con Jesús del Toro, libro sobre mercadotecnia en Internet, de los primeros en español, Editorial Iberoamérica
- 1998 Autorretrato, first generative poem, published by UNAM's Instituto de Investigaciones FilológicasAutorretrato, primer poema generativo, publicado por el Instituto de Investigaciones Filológicas de la UNAM
- 2003 Ph.D., Syracuse University, Doctoral Prize, for the dissertation The Medium Is the Measure of ItselfDoctorado, Syracuse University, Premio Doctoral, por la tesis The Medium Is the Measure of Itself
- 2004 A Space of Time: First Prize, Internet/Multimedia, XXVI Moscow International Film FestivalA Space of Time: primer premio, Internet/Multimedia, XXVI Festival Internacional de Cine de Moscú
- 2007, 2009 ETS iSkills committee, PrincetonComité iSkills de ETS, Princeton
- 2008 Making Sense of Tracking Data, a book on how the traces a person leaves online allow inferences about them, including how they think, VDM VerlagMaking Sense of Tracking Data, libro sobre cómo los rastros que una persona deja en línea permiten inferir cosas de ella, incluso cómo piensa, VDM Verlag
- 2011, 2012 Keynotes on generative work, UNAM and the CONACULTA symposiumConferencias magistrales sobre obra generativa, UNAM y simposio de CONACULTA
- 2014–2016 ICT Literacy Ambassador, California State University · California Open Educational Resources CouncilEmbajador de alfabetización en TIC, Universidad Estatal de California · Consejo de Recursos Educativos Abiertos de California
- 2019 Big Data, with Rodolfo Mata: Electronic Literature Collection, Volume 4Big Data, con Rodolfo Mata: Electronic Literature Collection, volumen 4
- 2020 Tablada Hipertextual, with Rodolfo Mata, UNAM: the computer reads a poet's words and builds a different reading from them, the ground the language models now work onTablada Hipertextual, con Rodolfo Mata, UNAM: la computadora lee las palabras de un poeta y construye con ellas una lectura distinta, el terreno en que hoy trabajan los modelos de lenguaje
- 2021 Uku Pacha, a generative VR film: world premiere, Vancouver International Film FestivalUku Pacha, película generativa en realidad virtual: estreno mundial en el Festival Internacional de Cine de Vancouver
- 2023 Keynote on the representation of Latin American cultures in AI, Ibero-American Meeting of Audiovisual Narratives, Trujillo, Peru · Graduate teaching at UNAM beginsConferencia magistral sobre la representación de las culturas latinoamericanas en la IA, Encuentro Iberoamericano de Narrativas Audiovisuales, Trujillo, Perú · Empiezo a dar posgrado en la UNAM
- 2023–2026 Directed the faculty learning community Advancing AI Literacy, Sacramento State · Principles for Cognitive and Pedagogical SovereigntyDirigí la comunidad docente Advancing AI Literacy, Sacramento State · Principios de Soberanía Cognitiva y Pedagógica
- 2024 A weekly AI publication run on real pipelines, every week sinceUna publicación semanal sobre inteligencia artificial hecha sobre procesos reales, cada semana desde entonces
- 2025 Best AI Short Film, Red Rocks AI Film FestivalMejor cortometraje de IA, Red Rocks AI Film Festival
- 2026 Keynote, with Nancy Huante-Tzintzun, Latin American and Caribbean Digital Humanities symposium, UT San Antonio · AI Watch, a weekly seminar for the Renaissance Society at Sacramento StateConferencia magistral, con Nancy Huante-Tzintzun, simposio de Humanidades Digitales de América Latina y el Caribe, UT San Antonio · AI Watch, seminario semanal para la Renaissance Society de Sacramento State
What it costs
$44.95 a month
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