Music Album Covers with Televisions on Them

36 albums covers featuring TVs on them.

Ah, the good old television. TV, tube, boob tube, telly, idiot box. A piece of furniture, a glowing shrine, background noise, babysitter, cultural glue, and eventually just another rectangle in our lives competing for attention.

The word “television” itself was introduced by Russian engineer Konstantin Perskyi at the 1900 Paris Exposition during the International Congress of Electricity. He combined Greek and Latin roots into a neat term meaning, roughly, “seeing at a distance,” replacing clunkier technical descriptions floating around at the time. It was the perfect debut venue: a world fair dedicated to showing off the future through electricity, machinery, and spectacle.

In this album cover mosaic, we collected examples of televisions appearing on album covers in all their forms: glowing consoles, portable sets, static-filled screens, rabbit ears, surveillance monitors, and late-night blue light. TVs on album covers can signal comfort, alienation, mass culture, boredom, nostalgia, or just the simple fact that for decades the television sat at the center of domestic life.

As usual with these mosaics, we’re not trying to be exhaustive. There are plenty of examples we missed, forgot, or perhaps once saw at 1 a.m. illuminated by the flicker of a CRT screen.

01 Foretaste – "Terrorist TV" (2008)
02 Lichen – "The End is Near" (2018)
03 Graham Parker – "Imaginary Television" (2010)
04 Cocksure – "T.V.M.A.L.S.V." (2014)
05 Dramarama – "Color TV" (2020)
06 Frank Zappa – "A Token Of His Extreme Soundtrack" (2013)

07 Kacy & Clayton, Marlon Williams – "Plastic Bouquet" (2020)
08 Kiyotaka Sugiyama – "Kona Weather" (1987)
09 Roger Waters – "Amused to Death" (1992)
10 The Bees – "TV Mentality" (1979)
11 DelicTrips. – "Motivated Abstract" (2017)
12 The Cars – "Moving in Stereo The Best of The Cars" (2016)

13 Sweet – "Waters Edge" (1980)
14 Berlin – "Pleasure Victim" (1982)
15 Family – "Bandstand" (1972)
16 Benny Golson – "Tune In, Turn On The Hippest Commercials Of The Sixties" (1999)
17 Lizzy Borden – "Visual Lies" (1987)
18 Tai Verdes – "TV" (2021)

19 A Flock of Seagulls – "A Flock of Seagulls" (1982)
20 Elton John – "The Fox" (1981)
21 George Harrison – "Brainwashed" (2002)
22 Joni Mitchell – "Wild Things Run Fast" (1982)
23 Proctor and Bergman – "TV Or Not TV A Video Vaudeville In Two Acts" (1973)
24 Various Artists – "100 Greatest TV Themes" (2011)

25 AC-DC – "Blow Up Your Video" (1988)
26 The Tubes – "Remote Control" (1979)
27 Holger Czukay – "Movies" (1979)
28 Monty Python – "Monty Pythons Flying Circus" (1970)
29 Rebel Kicks – "A Portrait of Man, Pt 1" (2020)
30 Lou Reed – "New Sensations" (1984)

31 Rush – "Power Windows" (1985)
32 Harry Nilsson – "That's The Way It Is" (1976)
33 Fish – "Vigil in a Wilderness of Mirrors" (1990)
34 World Party – "Private Revolution" (1986)
35 Tom Jones – "Reload" (1999)
36 Randy Newman – "12 Songs" (1970)

La Dolce Metà

Showing your sweet side and your better half.

I meant to ask our friend and Italian barista: “where is your better half?” referring to her husband. What came out of my mouth was: dov’è il tuo dolce lato. That was followed by laughter. Oops! I got burned by a false friend and a too-literal translation. The correct way is to say la tua dolce metà.

“Dolce lato” sounds like an overly sweet new dessert. “Dolcelatte” is a similar to gorgonzola. So maybe I asked her where her cheese was?

Other traps include:

• Sono freddo — “I’m a cold person” VS Ho freddo — “I’m cold”. Italian uses avere (to have) for physical states.

• Prendo una foto — “I’ll take this photo” (with me, almost like grab it) VS Faccio una foto - “I’ll take a photo” (take a picture).

• Ti ho perso — “I lost you” (in the crowd, e.g.) VS Mi sei mancato — “I missed you”.

They all share the same pattern because you recognize the words, you trust the structure and the sentence is technically understandable. But it lands…off.

Foraging Aglio Orsino in Fiobbio and Using it Fresh Pasta with Friends

Some meals start in the kitchen. Others start in the woods.

Our day began with a walk near Fiobbio, a small village on the slopes of Monte Misma in the Val Seriana area above Bergamo. We’ve done several hikes in and around Misma. See: A Walk from Albino to Bergamo via Monte Misma, Monte Misma – Just Outside Our Window, and Le Vie di Misma - Trails 511 and 510.

  
Left: Algio orsino (or bear garlic) growing along the Lujo stream.
Center: A walk in Fiobbio, Italy to collect algio orsino (Allium ursinum).
Right: Fresh ravioli stuffed with ricotta and aglio orsino, decorated with pesto made with aglio orsino.

From our friends’ house, we set out on foot toward the Lujo stream, baskets in hand and a clear objective: find aglio orsino (Allium ursinum), also known as wild or bear garlic.

Early spring is the moment for it. In damp woodland, the plant spreads in thick green carpets, announcing itself before you even see it. The air carries that unmistakable garlicky scent. Crush a leaf between your fingers and the smell intensifies instantly; a small chemistry experiment happening right there on the trail.

That chemistry is part of what makes aglio orsino so interesting. In the intact leaf, sulfur-containing compounds like alliin are stored separately from an enzyme called alliinase. When the leaf is cut or crushed, the enzyme converts alliin into allicin, the compound responsible for the sharp, pungent garlic smell. Allicin is powerful but unstable, and when heated it quickly transforms into milder sulfur compounds that soften the flavor.

This detail became important later.

After collecting a generous bundle along the stream, we made our way back, stopping briefly at Ca’ La Stongia before returning to Elena and Matteo’s kitchen. The plan was simple: fresh pasta and whatever we could make from the wild garlic we had gathered.

The kitchen quickly turned into a small workshop. Flour on the counter, eggs cracked into a well, dough kneaded and rolled through the pasta machine. We made two pastas: tagliatelle and ravioli. The ravioli were filled with ricotta and our freshly foraged aglio orsino, and dressed with a pesto made from the same leaves.

But first we did something that might seem counterintuitive for garlic lovers: we boiled the leaves briefly. The reason goes back to that chemistry. Heat disables the enzyme that produces more allicin and breaks down the allicin already present. The result is a gentler flavor—still garlicky, but greener and more rounded. Our friends had tried using the leaves raw the week before and found the result overpowering; a quick blanch made the ingredient much easier to work with.

Cooking together has its own rhythm. Someone rolls pasta while someone else shapes ravioli. Someone tastes the filling and adds a little more salt. Conversations jump from food to walks to whatever else comes up. Hours pass without anyone noticing.

In the end, the table filled with bowls of pasta: ravioli with ricotta and wild garlic, tagliatelle with pesto alla trapanese. Dessert followed—pastiera we brought to share and a colomba waiting on the counter.

It’s satisfying to eat something you’ve gathered yourself, but the real pleasure is the chain of events behind the meal: the walk through damp woods, the smell of crushed leaves, the small bit of chemistry that transforms a sharp plant into something delicate, and the shared work of turning it all into lunch.

Meals that start in the woods tend to taste better.

Photos

  

Left: Chiesa di Sant'Antonio da Padova in Fiobbio, Italy.

Center: Allium ursinum flowers (edible but we didn't use) in our pesto.
Right: Allium ursinum leaves.

 

Left: Fresh ricotta at Ca' La Stongia in Fiobbio, Italy.

Right: Selling pesto algio orsino: not thanks we are making it ourselves!

 

Allium ursinum (aglio orsino in Italian) growing alongside the Lujo (stream).

   

Making ravioli. Rolling out pasta. Making filling with ricotta and bear garlic (parboiled), and putting filling inside rolled out pasta dough.

 

Fresh ravioli stuffed with ricotta and wild garlic. Ready to be boiled and plated with spots of wild garlic pesto and decorated with primrose and violet flowers. 

 

Tagliatelle was also made and served with pesto alla trapanese.

From Scrapbook to Storyteller: Our Very Own Primer

We didn’t mean to build a storyteller. We meant to build better search capabilities over our personal information. But stories are what surfaced, threads we hadn't realize we’d left for ourselves, links between moments separated by years, and reminders that small details matter.

Overview ~ Literary déjà vu ~ How it works ~ First impressions ~ Examples

Overview

Back in February 2024, we shared an update on our Scrapbook project, a tool we've used for many years to organize our lives. As we have described in different posts on the subject, Scrapbook is like our memory chest: searchable, organized, and expandable. In the last year, something interesting has happened. It's learned to talk back.

What we've done is woven a large language model (LLM) into the heart of Scrapbook. It doesn't roam the internet unless we ask it to. It answers questions using our corpus of data. It lives entirely inside our world of words and pictures answering questions, surfacing connections, and connecting threads between moments that even we'd forgotten.

Our data is broken into tens of thousands of entries, with each entry including text, digital assets, and links to other entries. The text of an entry can be anywhere from a few words to thousands of words. In short, there there is fair amount of material for an LLM to work with.

Literary Déjà Vu

The more we use our LLM-enabled Scrapbook, the more it reminds us of Neal Stephenson's The Diamond Age and its Young Lady's Illustrated Primer, a fictional, adaptive book which could teach, guide, and grow alongside its reader.

Like the Primer, our Scrapbook is becoming more than a static repository:

• It adapts — tailoring its responses to the quirks, references, and rhythms of our own material.

• It guides — when we search for a trip, a recipe, or an old photo, it brings back more than just the thing itself; it recalls the surrounding story.

• It connects dots — sometimes between entries years apart, revealing patterns we never set out to find.

The Primer in The Diamond Age was a thought experiment about how a tool could shape its reader’s growth through tailored narrative. Our version isn't teaching martial arts to Victorian ingénues, but it is helping us understand and navigate our own history in a way that's private, persistent, and woven into the things that matter to us.

We didn't set out to build a piece of science fiction. But step by step, feature by feature, Scrapbook has edged closer to being a kind of personal storyteller. Not just a record of where we've been, but a guide to help us decide where to go next.

How does it work

There is a lot going on, but here is the high level overview:

• Our solution creates a ChatGPT-like frontend experience over your own Cosmos NoSQL documents using RAG (Retrieval Augmented Generation).

• We use Azure OpenAI Service to access GPT models, and Azure AI Search for data indexing and retrieval.

• Our assistant is hosted in a Blazor application that has allows for adding and curating data.

First impressions

How's it working? In the first few months (mid 2025) of working with it, we found largely what you find with LLMs: they can be brilliant in the best of times and hallucinatory in the worst of times. Though, when it hallucinates on a body of data we know well, it's almost kind of funny and we can spot it easier.

Then we got to coding and updated the APIs we were using (migration from the Assistants API to Responses API), got access to GPT 5 models, rebuilt vector store for use in AI file search tool, and rewrote our system prompts. After this code push (early 2026), the Scrapbook Assistant was brilliant consistently and stable, with way less hallucinations. Phew! In many cases, it behaves almost like a magician in what it surfaces (correctly).

Given that LLMs work with words, our words matter. How we curate our data matters. No surprise, right? When we create a Scrapbook entry for an important event it really behooves us to be clear about who did and said what if we want to that be surfaced correctly later.

Writing clearly and consistently is key. In fact, after asking questions of our assistant, we often realize we need to go back and do editorial work. After the text changes, and rerunning the indexes for the LLM, the results improve. Another nonsurprise: It seems all new tools we aim at our Scrapbook corpus of data end up shining a light on how important curation is.

To date, our Scrapbook Assistant is great with words and less so with dates and ordering. For example, if we ask it to tell us about hikes (a Scrapbook data category) that we really liked recently, it doesn’t do what you might expect. It returns hikes we rated highly but may include some from recent times and some from way back. We don’t understand enough yet to know how to control this. We are very much in the early phases of this, and our guess is that this too will be something that gets improved.

Examples

There's a certain pleasure in discovering what you experienced but forgot. We now have conversations with our Scrapbook Assistant and collaborate with it.

Give me a rundown of glaciers we have visited.

We get back not just the date, but the glacier in context of what trip we were on, when, and a summary, size depending on model selected.

Tell me about the foods that Ottavia likes to eat?

We get back notes and anecdotes from dinners together we had together. It makes planning future meals together much easier. Our friend has a lot of food dislikes, so it's always good to check.

Explain our tax liability for the year 2024.

Try this looking in a filing cabinet!

What is the booking info for the last time we stayed in Berlin?

Out comes everything you need to understand length, price, contact info, and even what rooms you stayed in and liked. This works because all hotel and accommodations are recorded.

Give me some ideas for a Travelmarx-style blog post for the hike we did recently to Misma?

Hikes and in general large-effort activities are part of Scrapbook. We jot some notes down, and the activity is part of a larger unfolding of events that the assistant can tap into and tell a story. Also, all old blogs (hundreds and hundreds) are archived as entries in Scrapbook, so there is a lot to pull from to understand Travelmarx-style. Result is here: Le Vie di Misma - Trails 511 and 510.

What are some ideas from notes and previous food entries for a gluten-free friend visiting for a few days?

Indispensable guidance.

What is the recipe for a garbanzo bean dish we had in Seville?

No more searching around for recipes to share. And with the Scrapbook Assistant, follow up with “translate into Italian”.

Give me a one paragraph summary of our Japan 2025 trip including places visited and length of time at each stop.

These kinds of quick summaries of past events are super useful when someone asks. We can just ask the assistant without much time spent. We can customize the response for a friend who is interested in tours we took. In the response are links back to each individual item.

Out in the Open: Using AI Together

After reading another article about how bad AI is and how it (or some flavors thereof) can lead toward sycophancy, we decided to tell a different story. We see the sycophancy too, but we have a different way of looking at it. Hear us out.
 
This idea fits naturally with threads we’ve discussed already in Travelmarx: AI as private companion vs. shared artifact, entropy of chats, and the importance of curation. We believe there is a social layer aspect of AI that isn’t talked about enough in the doom-and-gloom articles. Most commentary about AI assistants assumes a private relationship between a person and a machine. But some of the most interesting uses appear when the assistant is brought into the open, into kitchens, living rooms, and conversations between people. 

An AI assistant glad to have started a conversation.

A Third Voice at the Table 

The first time I asked a question out loud to an assistant while sitting next to my partner, it felt… off. Not wrong exactly, but exposed. As if I had broken some small, unspoken rule about how conversations are supposed to work. Questions go to people. Devices stay in the background. 

I could ask anything quietly, of course. That felt normal. But saying it out loud so that someone else could hear the question, hear the answer was something else entirely. 

Phase 1: The Private Whisper 

At first, the assistant lived in a kind of side channel. 

A question here, a clarification there. A quick check on a fact or a translation. It was efficient, almost invisible. The conversation with my partner continued on one track, and the conversation with the assistant happened on another. 

Two parallel threads. No overlap. 

In hindsight, this is also where some of the unease around AI probably comes from. The interaction is private, unexamined, and easy to get lost in. You can ask, refine, and ask again. No friction. No second opinion unless you go looking for one. 

Phase 2: Bringing It Into the Room 

The shift happened almost accidentally. 

Instead of quietly checking something, I asked out loud. My partner heard the question, then the answer. There was a noticeable pause. My partner was slightly hurt and surprised that I was talking to the phone instead of him. That was followed by a look of “what a stupid question, ask it better, you are leading too much!” 

Once we got over those initial hurdles, our reactions to the assistant moved to “That doesn’t sound right!” or “Are you sure? Check again.” or “What about....?”. 

And just like that, the assistant had entered the conversation. 

Initially as an intrusion, then as something to ignite a discussion and even push against. We questioned the answer, rephrased the prompt, asked again. The device was still there, but it had become less of a private tool and more of a shared reference point. 

Something had changed, and it wasn’t the technology. 

Phase 3: The Assistant as a Third Participant 

Over time, this became more natural. 

We’d both ask questions. Sometimes to my assistant, sometimes to his. Sometimes we’d compare answers. Occasionally, we’d ignore them entirely and keep talking. 

What emerged wasn’t a dependence on the assistant, but a different rhythm of conversation: 

• We have a question or thought. 
• We ask the assistant and it offers something. 
• One or both of us disagrees. 
• The real conversation starts. 

The answer is rarely the end point. It’s a starting point. 

In that sense, the assistant behaves less like a search engine and more like a third voice at the table. Not a person, not an authority, but a participant that can be questioned, corrected, or simply set aside. 

Why It Felt Strange 

Looking back, the initial hesitation makes more sense. 

Asking a question out loud to an assistant reveals your thinking process in real time. It’s a bit like showing your notes before you’ve decided what you think. There’s also something faintly performative about it. You’re not just asking; you’re asking in front of someone. 

And maybe there’s a deeper instinct at play. Conversations, at least the ones we value, are supposed to be human. Bringing in a device feels like introducing an outsider. 

But that assumes the device replaces the conversation. In practice, it can do the opposite. 

The Conversation After the Answer 

The most interesting part isn’t what the assistant says. It’s what happens after it stops talking. 

We’ll put the phone down and keep going. The answer lingers, gets reshaped, sometimes discarded entirely. What remains is ours shared interpretation, disagreement, and insight that comes from talking it through. 

It reminds me a bit of how we use our Scrapbook assistant. The value isn’t just in retrieving an answer, but in what that answer connects and sparks next. 

Here, the “retrieval” is happening in real time, in conversation, between two people. 

A Different Way to Use the Tool 

There’s a lot of discussion about assistants creating echo chambers, encouraging passivity, or leading people into private conversational loops. Those risks are real enough. 

But they seem to depend on one key condition: that the interaction stays private. 

When the assistant is brought out into the open, something changes. The answers are no longer final. They are provisional, subject to immediate scrutiny. They become part of a shared space rather than a closed loop. 

It doesn’t eliminate the risks, but it shifts them. 

You might compare this to earlier technologies: 

• calculators in classrooms 
• Wikipedia during dinner conversations 
• smartphones during debates 

At first they felt disruptive; eventually they became shared cognitive tools. 

Closing Thought 

The moment we started asking questions out loud, the assistant stopped being the point. It became a way to keep talking to each other. 

And when the device is set down and the conversation continues, you realize that the assistant was never really the conversation at all but just the thing that helped move it along. 

I made a mistake – Ho sbagliato o Mi sono sbagliato

How to say I made a mistake in Italian? It's one of those cases where Italian looks deceptively simple but the meaning shifts dramatically. Here are your options to say you were wrong: 

• Option 1: "Ho sbagliato" 

• Option 2: "Mi sono sbagliato" 

• Option 3: "Io sono sbagliato" 

Which would you choose? 

A criceto holding a sign for the easiest way to say "I'm wrong".

Option 1: "Ho sbagliato" 

This is the cleanest, most neutral, most widely used way to say "I made a mistake." 

• Literally: "I have erred." 
• Idiomatic meaning: I messed up / I was wrong / I made a mistake. 
• It's direct, non‑reflexive, and works in almost every context. 
• It doesn’t carry the slightly apologetic or self‑correcting nuance of mi sono sbagliato. 

Examples: 

Ho sbagliato il calcolo. → "I got the calculation wrong."
Ho sbagliato a parlare. → "I shouldn’t have said that." 
Ho sbagliato strada. → "I took the wrong road." 

Option 2: "Mi sono sbagliato" 

This is another way to say "I made a mistake" or "I was wrong". 

• It’s reflexive: I got myself wrong → I made an error. 
• Slightly apologetic and admits a mistake in your judgment or assumption.
• It refers to a specific action, not your identity. 

Examples: 

Mi sono sbagliato di numero. → "I dialed the wrong number." 
Mi sono sbagliato a prendere la strada. → "I took the wrong road." 

Option 3: "Io sono sbagliato" 

This means "I am wrong as a person", in the sense of flawed, defective, mistaken in my very nature. It's a statement about identity, not about making a mistake. 

• It sounds existential, heavy, almost self‑blaming. 

• Italians rarely use it unless they truly mean something psychological or moral. 

Example (uncommon, dramatic): 

Io sono sbagliato per te. → "I’m not right for you / I’m the wrong person for you." 

Rule

The guidelines to keep in mind are:

• Use "ho sbagliato" when you want to be neutral and factual. Use for any error (action, choice, behavior). The mistake is the action. 

• Use "mi sono sbagliato" for mistakes where you want to be slightly apologetic, self-correcting. Use when you thought something wrong (misremembered, misjudged). The mistake is in your judgment or assumption. 

• Avoid "io sono sbagliato" unless you’re writing a poem or having an existential crisis. 

Examples to feel the difference between the two more common forms: 

• If you dial the wrong number:
• Ho sbagliato numero (most common) 
• Mi sono sbagliato di numero (also fine, more "oops, my bad") 

• If you say the wrong date: 
• Mi sono sbagliato, era il 12, non il 13. (You misremembered.) 

• If you choose the wrong wine: 
• Ho sbagliato vino. (You selected poorly.)