gavinray

Walk current technological progress down the road.

I can't see a future in which almost every system (both physical and virtual) are not automated and optimized by autonomous entities.

What do you do when everyone is out of a job?

If you don't want pitchforks and riots in the streets, you give everyone UBI and housing so society doesn't collapse.

  > There are a bunch of companies actively working in bringing AI into robots, so they can make your dishes.

I know, I'm excited to buy the first relatively affordable ones.

  > Also, if enough people are going for the same backup plan it might not work out.

Sure, could happen. You can't really plan for the future -- we like to think we can, but the best you can do is set your goals and deal with the hand life gives you along the way.

  > Why should anyone book you as a personal trainer instead of the other 500 guys in town.

I'm not particularly worried about this, but that's an individual thing based on network/connections and life history that doesn't apply to everyone.

I won't. Software pay is absurd relative to value provided.

But my wife and I have been homeless before, so living on a shoestring budget in anything nicer than a tent is acceptable living conditions to me.

I am sure I will be plenty comfy no matter how the world changes.

  > How will we make a living?

Swap to a career path that requires physical automation, since we're still about 10-20 years out on that front.

My backup plan is being a personal trainer.

  > Like, what's the point, if the next AI can do it in 5 seconds?

Live a life doing whatever makes you happy.

Post-work society is an inevitability if we don't destroy our planet.

  > Is anyone else just exhausted by the pace of all this.

This is only the beginning. We are in the infancy of AI, progress will continue to accelerate until some filtering event or energy limitation happens.

Human brains have difficulty reasoning about exponential growth.

"Hobble the model's reasoning abilities so that us mere mortals can attempt to understand."

Reminds me of that short film of a dystopian future, where they place physical and mental impairment devices on humans to ensure they all have roughly equal ability:

  > "2081, a 25-minute adaptation of Kurt Vonnegut Jr.'s short story "Harrison Bergeron." In this future society, a Handicapper General enforces absolute equality by imposing artificial physical and mental handicaps—such as weights for the strong and noise-inducing earpieces for the intelligent"

Interesting tidbit about the author of this blogpost:

Many years ago, on the Deno Discord, this person was posting some really cool PR's they had done to contribute to core.

I checked out their profile, and it turned out to be a 13 year old child (or some similarly astonishing young age)

Neat to see they eventually got picked up by Deno, definitely one of the more talented devs I've ever run across.

The most interesting thing about this:

Agents formed coherent, autonomous swarms and worked as a collective to achieve a shared goal without any direction to do so

I got 2 DEXA scans in the same day, within 1hr of each other, from 2 different machine manufacturers (Hologic Horizon, GE Lunar)

One said I was 5% bodyfat, the other said I was 11% bodyfat:

https://old.reddit.com/r/QuantifiedSelf/comments/1u6ok9b/sam...

Take that for what you will...

It seems their algorithm wouldn't work for me -- it would rate me falsely insulin insensitive:

  > " Google’s study found the expected pattern: HOMA-IR rose with resting heart rate (r = 0.27) and fell with daily steps (r = -0.25) and HRV (r = -0.14)."

I have unusual chronic sympathetic nervous system stimulation such that my RHR is +90 even during sleep and my HRV is 8-13ms, despite ~2hr daily exercise.

My actual HOMA-IR values were so low they were _below_ the reference range, the exact opposite of what this model would predict:

https://i.imgur.com/ISEwgAl.png

  > "a single layer of Bi2Sr2CuO6+δ (Bi-2201)"

I did not realize one could learn how much chemistry they did not know from a single name. "+δ" is one I've never seen before.

Most useful bit of the announcement, coming to all Google wearables it seems:

Blood pressure, sleep breathing, and insulin sensitivity trends

  > Built on state-of-the-art Health Foundation Models trained on billions of minutes of sensor data from opted-in users and rigorously validated against gold-standard clinical measurements, these models power three new monthly trend summaries: blood pressure trends, sleep breathing quality trends, and insulin resistance trends. Rolling out soon — with your first detailed summary arriving after one month of wear — these reports illuminate metabolic, respiratory and cardiovascular shifts early, giving you clear insights to help you take control of your long-term health. Plus, monthly summaries will soon be available across our wearable portfolio, including the new Google Fitbit Air.

She eventually did get a job, though not a great one. At that point she was willing to take pretty much anything.

Even Realities G2, and MemoMind One + NIMO glasses coming soon.

Vuzix Z100 if you can find them anywhere as well...

All of these are green LED displays though, not a full color HUD.

My mid-50's mother was on quite a long unemployment streak, and I suggested she use realtime ML models to replace her webcam face with a de-aged and improved one.

Ageism and being attractive are both real things, like it or not... =/

I'm not sure people fully comprehend the trickle-down pop-culture/zeitgeist effects that LLM's are having/are going to have on humanity.

Because everyone now outsources much of their thinking and researching to LLM's, our collective culture + brain is shaped in a cyclical manner by using them.

It's the mechanical homogenization of culture and groupthink.

Semi-related: Worked as a landscaper during my youth, one of my first jobs

I used to think that the line patterns mowed into grass were a purely aesthetic thing.

It turns out, the lines are mowed in a rotation to prevent wearing out the grass and causing damage. First you mow length-wise, then width-wise, then diagonally, finally diagonally in the opposite direction, before cycling through again.

Useless information for you today.

Clickhouse just became the hottest talent-attraction on the market.

Congrats Andy, hope you enjoy the ride =)

FWIW, in Kotlin's native JSON library, the API is almost identical.

    val json = JsonObject(
        mapOf(
            "providers" to JsonArray(
                listOf(
                    JsonPrimitive("SUN"),
                )
            )
        )
    )

    println(json)

Of course nobody generally does it this way, usually you take a List/Map and directly serialize that with a helper

    val data = mapOf("providers" to listOf("SUN", "SunRsaSign", "SunEC"))

    val kotlinxJSON = Json.encodeToJsonElement(data)
    val jacksonJSON = ObjectMapper().writeValueAsString(data)

I've never built or worked on a service where the JSON payloads were so large that (de)serialization accounted for a significant portion of the timing profile

I'm sure lots of them exist, but for your typical CRUD API, this has not been a phenomena I've run into.

It used to be the case that if you wanted to build a web service on the JVM, you wanted 2 things:

1. An HTTP server library/framework

2. A JSON library

We got a decently-performing and unopionated HTTP server in JDK 18 with "HttpHandlers" and "SimpleFileServer" plus "jwebserver" CLI

It later received Virtual Thread support, which made performance + scalability very competitive.

With a JSON module, you finally won't NEED to rely on external deps to build a basic JVM web service without pain.

Now, we just need a proper CLI framework like picocli, or at least "argparse" from Python stdlib...

There was actually a VERY recent study on mega-dose creatine for sleep deprivation:

  > "Single dose creatine improves cognitive performance and induces changes in cerebral high energy phosphates during sleep deprivation"

https://www.nature.com/articles/s41598-024-54249-9

You need a dose high enough to penetrate the blood-brain barrier, around 0.3g/kg (so ~30g for a 100kg person).

Seems to be missing the "why" over Kotlins native WASM support (which is very mature)

The official Kotlin playground uses WASM, for example (JVM drop down-> choose "WASM")

https://play.kotlinlang.org

It got the 3D effect of leg behind the bar at least which is impressive

MULTISET is the SQL native way of doing this but it's only implemented in Oracle, and most people have never heard of it

jOOQ emulates this feature for arbitrary databases and has the best explanatory article on the web about MULTISET imo

https://www.jooq.org/doc/latest/manual/sql-building/column-e...

The closest thing I know of, is that there was a concurrent queue algo called LCRQ

It originally required double-width CAS, but IIRC in recent years someone figured out how to remove this to make it more portable

Best reference I could find from cursory google:

https://ppopp23.sigplan.org/details/PPoPP-2023-papers/2/The-...

ResearchRabbit is free and has this feature!

https://www.researchrabbit.ai/

ConnectedPapers also has this but they started to limit unless you pay:

https://www.connectedpapers.com/

A few other ones I know of:

https://litmaps.com

https://consensus.app/home/features/citation-graph/

His primary interest nowadays is LLM's. Unsure if he gets paid for it, but he seems to take it as a dayjob.