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*“Yesterday, I Went to Mars ♡”*: Daily Summaries Delivered
by MakotowillOlympusMons
*“Yesterday, I Went to Mars ♡”*Makoto Hoshino, CEO of Makoto Co., Ltd. and Galactic Hitchhikers, shares his journey of pursuing heart-moving experiences and embracing the unknown. In 2017, he summited Everest and all Seven Summits and completed the 250km Gobi Desert Ultramarathon. His future goal: to stand atop Olympus Mons on Mars by 2049. Through this podcast, Makoto reflects on his life’s adventures, celebrating family, global friendships, and the joy of trusting intuition and living freely. Join him as he explores the excitement of breaking free from conventions
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- Yesterday2 min
If Things Aren't Going Well, Try Reaching Out First
This episode reflects on a line that landed hard: the people who feel like they're working hard but nothing good ever happens tend to be the ones who never invite anyone out themselves.It explores why reaching out first matters — how meetings lead to work, information, and opportunities that simply never arrive if you wait — while also pushing back against the opposite extreme: filling a calendar with drinks and networking events until nothing deepens and you've lost track of what you actually want.There's a distinction drawn between quantity and intention. What do you want to learn from this person? What are you taking home? Without that, it's just drifting.The episode also sits with the tension between time spent meeting people and time spent alone — thinking, building, developing the work. Both matter, and one without the other isn't enough.A quiet reminder that what changes a life isn't a wide network, but a handful of encounters with people you actually wanted to reach out to in the first place.
- Yesterday1 min
If AI and Robots Advance, Will Money Still Matter?
This episode takes up a question prompted by something Elon Musk was saying: if AI and robots eventually handle most work and drive production costs down sharply, does money still matter?It works through the logic carefully — the reason we pay for things now is that making them costs something. If that changes, the assumption that you work to earn might start to shift too.But scarcity doesn't disappear. Land stays finite. So do reservations at a popular restaurant, time with another person, rare experiences. Even if the form money takes changes, some system for exchanging value still seems necessary.There's also a small parallel drawn to AI itself: once something becomes available to everyone, what you do with it becomes the thing of value. Physical goods keep getting cheaper; what may carry more weight instead are things that can't be easily reproduced — connection, experience, trust, a sense of identity.A quiet reflection on a future that may be less about how much you have, and more about what kind of value you can create.
- 3 days ago3 min
When Space Becomes a Business— Synthetic Aperture Radar —
This episode looks at SAR — Synthetic Aperture Radar — a satellite technology that uses radio waves to image the Earth through night, rain, and cloud cover, detecting ground movement down to the millimeter.It traces how a technology that once required hundreds of billions of yen and national-scale resources has quietly transformed: satellites have shrunk to around 100 kilograms, launch costs have fallen, and the idea of dozens of small satellites refreshing our picture of the Earth every few hours has become real.There's a closer look at Synspective, a Japanese company whose position in this field is not just selling satellite images, but offering the full chain from data capture through AI-powered analysis — making it possible for municipalities and non-specialists to act on disaster-preparedness decisions without needing expertise in space.An analogy surfaces from Everest: however much equipment, technique, and forecasting advance, the final step still requires the will of the person taking it. SAR might work the same way — however precise the data, whether it connects to real decisions on the ground is a separate question entirely.A quiet look at how space business is drawing steadily closer to everyday life, and how the work of translation — bridging technology and the people who need to act on it — may be just as fundamental as the technology itself.
- 4 days ago2 min
How a Doctor Who Saved Lives Became a Dictator
This episode looks at how François Duvalier — "Papa Doc" — went from being a beloved rural doctor to one of Haiti's most feared dictators, a question raised after coming across news about armed gangs in Haiti.It traces how the nickname "Papa Doc" was originally a term of affection from patients, and how a man who traveled to poor communities to treat infectious disease eventually dismantled every mechanism that might have checked his rule, surrounding himself only with those who agreed with him.There's a quiet observation at the center of the episode: that the familiar phrase "power corrupts" may be less frightening than what it points to — the disappearance of the structures that allow others to say "that's wrong." Elections, courts, a free press. When those are gone, anyone can convince themselves they're right.The episode also touches briefly on what this history prompted closer to home — a reflection on how the longer you lead something, the easier it becomes to assume your own judgment is sound, and why people willing to disagree still matter.A small look at one corner of Haiti's history, and how reading about a cycle of fear and unchecked power left a stronger impression about structures than about the person who dismantled them.
- 5 days ago3 min
On the Giants Called Omniscalers
This episode looks at the idea of the "omniscaler" — a step beyond the hyperscalers like AWS or Google Cloud — and what it means that a small group of companies now competes across AI, semiconductors, robotics, space, and advertising all at once, using the same underlying stack of data and infrastructure.It touches on the McKinsey estimate that nine companies — the so-called "Omni 9" — will together spend around $800 billion on R&D and capital expenditure in 2025. That number lands with some weight, especially alongside an earlier observation about Intel burning through 170 million yen in cash every hour — a single company, compared to nine, across multiple industries, simultaneously.There's a distinction drawn between old-style conglomerates, which simply held unrelated businesses, and omniscalers, which redeploy the same core weapons — cloud, AI, chips, data — into every new field they enter, arriving with advantages that specialists find difficult to match.The episode also considers what remains for those specialists: the medical robotics floor, the regional trust, the safety certifications that capital alone can't shortcut. That territory exists, though it keeps getting smaller.A quiet look at a moment when even an optical shop on an ordinary street is already operating on top of omniscaler infrastructure — and the question of what, in that situation, you choose to keep in your own hands.
- 6 days ago3 min
"gyurareru,"— When Young People Talk About Being Replaced by AI
This episode looks at a piece of Japanese slang spreading among Gen Z and younger students — "gyurareru," derived from "singularity," meaning to have your skills, your work, your accumulated knowledge quietly taken away by AI.It touches on how the word carries both anxiety and a kind of lightness — used self-deprecatingly, even with a hint of welcome, as in "I kind of want my current job to get gyurareru'd." There's a sense that this younger generation isn't brooding over the future so much as shrugging at it, and something almost resilient in that shrug.The episode also works through a practical distinction: what kinds of work are harder to gyuraru? Compiling reports, aligning data, following fixed procedures — these tend to go first. Creating, deciding, building trust in the moment, being the one who finally takes responsibility — these tend to stay.There's an observation that AI isn't arriving all at once, but trimming and replacing piece by piece, which is exactly what makes the shift feel so ambient and hard to point to.A quiet look at what a single word can reveal about how a generation is living with uncertainty — not in spite of the lightness, but through it.
- 6 days ago6 min
From Consulting AI to AI That's Already Finished the Work
This episode picks up a thread from the day before — the observation that major tech companies are now spending as much on AI tokens as on engineer salaries — and uses it as a starting point to look at why so much corporate AI adoption produces no measurable result.The central finding, drawn from a report on AI in corporate finance departments, is striking: 95% of AI rollouts have had no impact on the bottom line. The episode works through why that might be, and lands on a simple structural problem — when AI requires a human to type a prompt every single time, the workflow hasn't changed, only the speed of individual steps within it.The contrast drawn is between that prompt-each-time model and something called background agents: AI systems that trigger automatically from events, like an invoice arriving, and complete the routine work before anyone sits down at their desk. An example from the finance world makes this concrete — by the time a person arrives in the morning, only the items that genuinely need a human decision are waiting.There's also a candid look at how this applies to running a small optical shop, where tasks like cross-referencing appraisal prices, converting lens prescription data, and syncing inventory across platforms each take only a few minutes but together occupy a significant part of the day. The line being drawn isn't about handing everything to AI — it's about identifying exactly where the boundary should sit between what AI handles automatically and what stays with the person who knows the work.A quiet reflection on the difference between AI as a tool you consult and AI as something that quietly finishes the work before you arrive — and what it might mean, for a small shop, to get that distinction right.
- 1 weeks ago3 min
If a $500K Engineer Isn't Burning $250K in Tokens a Year, an Alarm Should Go Off
This episode looks at a line attributed to Jensen Huang that stopped the reader mid-scroll: if an engineer earning $500K a year isn't spending $250K on AI tokens annually, an alarm should go off.It works through what that framing actually implies — token spend as a proxy for effort, measured against salary — and sets it alongside a run of related stories: Salesforce freezing engineer hiring while committing billions to Anthropic tokens, Meta ranking 85,000 employees by token usage, Uber burning through its entire annual AI budget by April.There's also a quieter data point underneath all of it: tech layoffs in 2026 are running at over a thousand people a day, around half attributed to AI, with engineers now being cut at the resume stage who would have sailed through to interviews a year ago.A brief look at one visible pitfall, too — Microsoft engineers reportedly consuming $8,000 in tokens per day each, until leadership stepped in — and what happens when a measurable number becomes a performance metric: the same structure as meaningless overtime at a company that rewards long hours.A quiet reflection on what it feels like when token costs and labor costs start being discussed in the same breath, and why the more important question may not be how much to use AI, but where to hand things off and where to hold the work yourself.
About *“Yesterday, I Went to Mars ♡”*
*“Yesterday, I Went to Mars ♡”*Makoto Hoshino, CEO of Makoto Co., Ltd. and Galactic Hitchhikers, shares his journey of pursuing heart-moving experiences and embracing the unknown. In 2017, he summited Everest and all Seven Summits and completed the 250km Gobi Desert Ultramarathon. His future goal: to stand atop Olympus Mons on Mars by 2049. Through this podcast, Makoto reflects on his life’s adventures, celebrating family, global friendships, and the joy of trusting intuition and living freely. Join him as he explores the excitement of breaking free from conventions
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