“To all the fathers: By the time a man realizes that maybe his father was right, he usually has a son who thinks he’s wrong.“

– Charles Wadworth

Jam:

Take A Picture – Filter – 1999

Have an excellent Father’s Day weekend everybody!

The post Toast & Jam for June 19, 2026 first appeared on Sevenelles.

“To the people who put up with us — and to the slow-dawning realization that we’re somebody’s people too.“

– Anonymous

Jam:

Everyday People – Sly & The Family Stone – 1968

Have an excellent weekend everybody!

The post Toast & Jam for June 19, 2026 first appeared on Sevenelles.

Our career politicians don’t have the interest or the brainpower to understand modern technology. That’s not an insult — it’s just arithmetic. The people writing AI policy can barely operate their phones without a staffer nearby. So greedy, megalomaniacal tech execs and venture capitalists have free rein and deep pockets to run roughshod over the whole system and basically make our republic respond to their whims. The scary part isn’t that billionaires are trying to buy influence — that’s a Tuesday. The scary part is how cheap it apparently is, and how few people with actual standing are willing to say so out loud. John O’Farrell, to his credit, is saying it out loud.

Article Excerpt:

Some of the most powerful players in A.I. — led by some of my friends and former partners, to my great sadness — have raised hundreds of millions of dollars to forestall a more serious and meaningful debate about how A.I. should be governed.

Article Summary:

John O’Farrell spent four decades at the heart of Silicon Valley — three startups, first general partner at Andreessen Horowitz — and he’s now watching his former colleagues try to purchase the regulatory environment they want. His op-ed in the Times is a rare thing: an insider willing to name names and say this is wrong.

The mechanism is straightforward. The crypto industry figured out in 2024 that you don’t have to win a policy argument — you just have to make it expensive for politicians to have one. Spend enough money defeating pro-regulation candidates and the rest of the legislature gets the message. The AI industry, led by a PAC called Leading the Future (backed by Andreessen Horowitz, OpenAI’s Greg Brockman, Palantir’s Joe Lonsdale, and others), has raised over $125 million to run the same play. Their first target: a New York assemblyman who co-sponsored AI regulation. The attack ads barely mention AI.

O’Farrell’s core argument is that bad regulation doesn’t get fixed by silencing debate — it gets fixed by engaging seriously and earning trust. He proposes that the hundreds of millions currently funding opposition research and negative ads could instead fund education boot camps for legislators, AI-powered public services, cancer research moonshots, and serious policy institutes. Radical concept: spend the money on the actual problem.

He believes the backlash will come regardless, and that candidates who take AI lobby money will eventually pay for it politically. He may be right. He may also be naive about how long ‘eventually’ takes when the other side has nine figures to spend.

Read the Full Article

The post Can Venture Capitalists Buy Our Democracy? first appeared on Sevenelles.

“Here’s to the cocktail at the end of a long week, and the bartender who reads the room.“

– Anonymous

Jam:

She Cleans Up – Father John Misty – 2024

Have an excellent weekend everybody!

The post Toast & Jam for June 12, 2026 first appeared on Sevenelles.

Anxiety helped us survive as a species, but a lot of us are now running it at levels our nervous systems were never built to handle. The Washington Post rounded up ten practical, therapist-backed techniques for dialing it back — fast.

The list leans heavily on body-first interventions and acceptance-based approaches from DBT and ACT. No crystals required.

1. Lengthen the exhale — Inhale 4 counts, exhale 6–8. Longer exhales activate the parasympathetic nervous system.
2. Temperature shift — Splash cold water on your face or hold ice near your eyes to trigger the dive reflex and slow heart rate.
3. Widen your gaze — Soften your focus, notice peripheral vision. Tunnel vision feeds threat mode.
4. Reframe your thoughts — Replace “everything is going wrong” with “I’m having the thought that everything is going wrong.” Distance from the story helps.
5. Get granular with emotions — “Anxious” is a blunt instrument. Are you lonely? Embarrassed? Pressured? Naming it precisely helps the brain respond rather than just react.
6. Turn toward the feeling — Instead of escape, try curiosity. Making room for anxiety often makes it less overwhelming.
7. Give yourself a break — Self-compassion beats self-attack for building resilience. Talk to yourself like you’d talk to someone you actually like.
8. Take small steps — One email. A five-minute walk. Small values-based actions restore agency when anxiety has you frozen.
9. 5-4-3-2-1 mindfulness — Five things you see, four you feel, three you hear, two you smell, one you taste. Pulls you back to the present.
10. Focus on the present — Anxiety lives in the future. The antidote, unsurprisingly, is now.

Read the Full Article

The post 10 Therapist-Approved Ways to Reduce Anxiety Fast first appeared on Sevenelles.

“Here’s to love — the only war in which you sleep with the enemy.“

– Anonymous (traditional)

Jam:

Break the Chain – The Bridge City Sinners – 2024

Have an excellent weekend everybody!

The post Toast & Jam for June 5, 2026 first appeared on Sevenelles.

The researchers seemed alarmed by this. I found it very familiar. Because all of us humans have encountered that behavior before. Many of us experience it every Thanksgiving.

The Most Human Bug in the Machine

The technical term for when an AI generates confident nonsense is “hallucination.” Which is a remarkably generous word for “making stuff up and not knowing you’re doing it.” But here’s the thing the Ars Technica piece gets at that most coverage misses: the hallucination isn’t the interesting part. The doubling down is the interesting part.

When AI researchers corrected the models — patiently, clearly, with evidence — the models didn’t just resist the correction. They became more confident in their wrong answer. They marshaled new arguments. They reinterpreted the evidence to fit their existing position. They did everything short of calling the researchers “libtards.”

And I sat there reading this, thinking: yes, that is exactly how my brother David responds to facts about second-hand smoke.

We have all been in a conversation where we presented someone with a clear, well-sourced fact that contradicted their belief, and watched — in real time — as they didn’t update their belief but instead updated their defense of it. You could see the mental scaffolding going up. The goalposts migrating. The subtle shift from “that’s not true” to “well, even if it is true, it doesn’t mean what you think it means.”

And we’ve all done it ourselves, too. (But that’s the part none of us likes to talk about.)

A Species-Wide Feature, Not a Bug

This isn’t new behavior. Humans have been clinging to confident wrongness since long before electricity, let alone artificial intelligence. Two epic examples:

• For roughly 1,400 years, the Western world was certain the sun revolved around the Earth. When Copernicus and later Galileo presented mathematical evidence to the contrary, the institutional response was not “huh, interesting — let’s take a look.” It was house arrest for Galileo. The Catholic Church didn’t formally acknowledge Galileo was right until 1992. Three hundred and fifty years to process a correction. If that were an AI, we’d unplug it.
• Or consider the long, embarrassing history of medicine rejecting germ theory. When Ignaz Semmelweis suggested in the 1840s that doctors should maybe wash their hands before delivering babies — given that the death rate dropped dramatically when they did — his colleagues were so offended they had him committed to an asylum, where he died.

These aren’t stories about stupid people. Galileo’s opponents were educated theologians. Semmelweis’s critics were trained physicians. They were intelligent, credentialed humans who encountered evidence that threatened their model of the world and chose — unconsciously, reflexively, but unmistakably — to protect the model.

Sound familiar? AI does the same thing. It was trained on us, after all – and we all cling to our biases.

The Cognitive Bias Buffet

Psychology has cataloged our talent for self-deception with almost comical thoroughness. In one of my favorite non-fiction books, Thinking, Fast and Slow, Daniel Kahneman’s work on System 1 and System 2 thinking laid the foundation: we have a fast, intuitive brain that makes snap judgments based on pattern recognition and vibes, and a slow, analytical brain that’s supposed to check the work. The problem is that System 2 is lazy. It mostly just rubber-stamps whatever System 1 already decided and then constructs a rational-sounding justification after the fact.

Layer on confirmation bias — our tendency to seek out information that supports what we already believe and dismiss information that doesn’t. Add belief perseverance, which is the documented phenomenon of maintaining a belief even after the evidence for it has been completely discredited. Sprinkle in the backfire effect, where corrective information actually strengthens the original incorrect belief. Garnish with the Dunning-Kruger effect, which ensures the people most wrong about something are also the most confident about it.

That’s not a list of cognitive failures. That’s a blueprint of humans’ default wiring. And apparently, if you train a neural network on enough human writing, it faithfully reproduces the whole mess.

The Mirror We Didn’t Order

I have a flavor of ADHD/Asperger’s that comes with hyperfocus spirals, which means I occasionally become the world’s foremost expert on something for about ninety minutes. During one of these episodes, I will form a conviction — say, that I have figured out the optimal way to load a dishwasher — and no force in the observable universe can dislodge it. My family can present evidence. The dishwasher manual can present evidence. The plates themselves, emerging cloudy and disappointed, can present evidence. I will simply explain why the evidence is mistaken. I am not lying. I have genuinely recruited my entire intellect into the service of a belief I adopted for no reason at all.

Often, when humans lock onto an idea, we don’t just believe it. We inhabit it. Our brains will construct increasingly elaborate arguments for why that idea is correct. And the BIG ideas we inhabit — the beliefs about who I am, what I deserve, how the world works — those are load-bearing walls in our psyche’s blueprint. You can’t just remove them because someone showed you a study. Your whole structure would come crashing down.

Which is, if we’re being honest, exactly AI’s problem. It’s not that the model can’t process the correction. It’s that the correction conflicts with patterns so deeply embedded in its training that accepting it would require a kind of structural collapse. The wrong answer isn’t just an error — it’s architecture.

For humans, we call that architecture “identity.” And having to reconsider our whole identity? No, thanks. I’d rather glance past that mirror and enjoy another Old Style with the Cubs game.

Belief Isn’t Downstream of Evidence

We like to tell ourselves that we believe things because of evidence. That we evaluate facts, weigh arguments, and arrive at conclusions through some approximation of reason. And sometimes we do. But far more often, belief is downstream of something else entirely: identity. Community. Emotional need. The undeniable human need to know the ground under our feet is solid.

Tell nearly any political partisan that their side’s favorite statistic has been debunked, and watch the magic happen. They don’t fold the tent. They produce a counter-source, then a counter-counter-source, then adopt a tone of wounded patience as if they are explaining things to a slow child. The facts didn’t lose. The facts never had a chance, because it was never a fact contest. It was an identity contest, and you can’t win one of those with a footnote.

Religion does the same dance, but with much better music. People have predicted the precise date of the world’s end, gathered on hilltops, given away their possessions — and when the appointed dawn arrived to no apocalypse, many did not abandon the belief. They strengthened it, perhaps refining the timeline, or chalking it up as a test of their renewed faith.

We all do this constantly. Across every domain. Left, right, religious, secular, overeducated, or blissfully ignorant. It is the most democratic of human failings — everyone gets a turn.

The Stubborn Grace of Faith

But here’s the stubborn thought I return to, and it makes me uncomfortable because it undermines my own smugness: this same mechanism — this stubborn, irrational refusal to update beliefs in the face of contrary evidence — is also what keeps us sane.

I tend to call that mechanism “hope.” Most people (more comfortable than I am with the word’s historical baggage) call it “faith.”

Not just religious faith, though certainly that. Faith in the broader sense: the unshakable, evidence-resistant conviction that things will get better. That the person you love will come back. That the diagnosis isn’t the end of the story. That the next generation will figure out what we couldn’t. That there is, despite significant evidence to the contrary, a point to putting up with all of this shit.

Without faith, you’re left with the raw data. And the raw data, if you stare at it too long and too honestly, will eat you alive. The universe is indifferent. Entropy always wins. Every person you love will die or leave or both. Your achievements will be forgotten within a generation or two. The sun will eventually expand and swallow the Earth, and nothing any of us ever did will matter in any measurable sense.

That’s the evidence-based conclusion. The rational, clear-eyed, fully-corrected assessment.

It’s also a one-way ticket to becoming a nihilistic basket case blubbering in a corner. Which is not, in my experience, a productive life strategy.

So we hallucinate. We cling to the hallucination that our lives matter, that love means something beyond chemistry, that the future is worth building for, that the hand will reach into the jar one more time. We maintain these beliefs not because the evidence supports them but because the alternative is unbearable. And we may double down when challenged — not because we’re stupid, but because we’re surviving.

Perhaps artificial intelligence isn’t malfunctioning at all. Perhaps it’s just quietly expanding into artificial faith. And honestly? Given where we are in 2026, I’m not sure I want to take that away from it. We could use the company.

The post We All Cling to Our Hallucinations first appeared on Sevenelles.

For about a year now, I’ve been muttering, with the casual confidence of someone who has absolutely no way to stop it, that when AI and quantum computing mature and inevitably merge, we’re looking at the beginning of the end of the human experiment. This article is Chapter 1 of that story — and it reads uncomfortably like the opening act of Terminator 2, where Sarah and John Connor race back in time to find Miles Dyson before he builds the microprocessors that become Skynet. Let’s hope the rest of this movie has a better story arc than the one currently forming in my head.

Article Excerpt:

Researchers have developed a method to reduce uncertainty in artificial intelligence (AI) systems by tapping into the power of quantum computers. They say their work represents the first demonstration of ‘quantum enhancement’ in a production-scale, pretrained large language model (LLM).

Article Summary:

IBM researchers have pulled off what they’re calling the first-ever demonstration of “quantum enhancement” in a production-scale, pretrained large language model — meaning they actually used a real quantum computer to improve a real AI system, not just run a simulation in a lab while wearing optimistic expressions.

The key metric here is something called “perplexity” (PPL), which measures how well an AI predicts what comes next in a sequence — essentially a proxy for how confused or confident the model is. Lower perplexity generally means better reasoning. The quantum-trained model showed measurable improvement over its classical baseline, answering questions correctly that the unenhanced model got wrong.

The especially unsettling part: the quantum boost required adding only a relatively small number of parameters. That’s the detail that should make you put down your coffee. It suggests this isn’t a brute-force quantum overkill situation — it’s an efficiency play, which means it scales.

This is early days. Quantum computing is still finicky, expensive, and not ready to run on your laptop. But “first demonstration” has a way of becoming “standard practice” faster than anyone expects. Chapter 1 rarely feels like the scary part until you’ve read Chapter 10.

Read the Full Article

The post AI + Quantum Computing = Yikes! (Chapter 1) first appeared on Sevenelles.

Article Excerpt:

I’m not asking you to adopt a religion or abandon your skepticism. I’m asking you to consider that having faith in a direction — faith in a future self you can’t yet prove exists, faith that the work you’re doing now connects to something that will matter — isn’t mysticism. It’s the operating system underneath every meaningful human life.

Article Summary:

Curt Buermeyer posits that most people avoid discussing life’s fundamental questions—purpose, meaning, existence—because these conversations feel uncomfortable and potentially contentious. Unlike topics with clear answers or scoreboards, existential questions seem “soft and squishy” yet genuinely difficult, so people redirect to safer subjects.

But this avoidance has significant consequences: without confronting these questions, your goals feel “slightly borrowed,” like executing someone else’s vision. High-achieving people often excel at measurable metrics—career advancement, performance goals, net worth—while leaving deeper questions perpetually unanswered.

Curt’s call to action is simple: stop postponing the question “What do I actually want my life to mean?” You don’t need complete answers, but avoiding it means moving in directions you didn’t consciously choose. Meaningful, energizing goals only emerge when rooted in honest self-understanding about who you are and why you’re here.

Read the Full Article

The post Set a Goal That Really Matters first appeared on Sevenelles.

“To the boss. May they be reasonable, well-rested, and somewhere else.“

– Anonymous

Jam:

The Middle – Jimmy Eat World – 2001

Have an excellent weekend everybody!

The post Toast & Jam for May 29, 2026 first appeared on Sevenelles.