pedalpete

I'm curious if you've tried any methods to increase your endogenous GLP-1 activity?

These include things like loading your body earlier in the day with heavy protein and fermented foods, eating proteins and vegetables before carbs (make less room for carbs), and of course there is still the lower stress, improve sleep and exercise.

I'm not suggesting these are replacements, but potentially like a micro-dose response.

The majority of people have no idea what linux is. They don't know that it us running the websites they visit, or that their phone (Android) is linux based.

You may be right that AI needs it's linux moment, if that is to mean that it is quietly running in the background and nobody actually knows anything about it, the world is just magically better for them.

That isn't the future that is currently being sold though, and I don't see AI going in that direction.

For those not familiar with AlterEgo - https://www.alterego.io/ I'm not sure if they are still active or not, but it looks like their last social media post was also their first from just over a year ago.

We don't have a wash here at our office, we just use a small container with IPA.

We have a UV cure cube, but often I just cure under a $20 amazon desktop UV light.

Look at the first image with the people in the field. That looks to me like a very poorly generated image, not a real image of people, and not even a high-quality AI generated image.

Is this what we can expect of the new apple? I'm not against AI generated imagery, but I expect them to be of equal quality to a real photo.

Or am I wrong, and it isn't AI generated?

The things that make me think it is just poorly made are 1) the angles of the laptop on the black case, 2) the lack of any lighting on the back panel, 3) the size of the hand on the woman in the back, and the squareness of what she is holding (if it is even supposed to be another mac).

I'm wondering if we could create one-off phone numbers similar to one-off credit cards when we have to give a number to a service we don't want to be regularly receiving messages from.

I wonder if the entire thing would be better if the first step was for the LLM to try to understand the final goal of the user, rather than just the simple instruction.

For instance, the LLM may have an understanding that the ball is easier for it to pick-up than the elephant (which it seemed to struggle with, which also made it a strange choice for the demo).

How much of an LLM understanding the physical limitations of the robot would help the task be accomplished in a way that satisfies the goal, without following the exact directions.

I'm in Australia

Dentistry needs an overhall in general. It seems antiquated, and I was hopeful when Wally Dental care raised VC funding that this was a new direction for dentistry, but it seems to be just dentist as a subscription.

I've never really had problems with my teeth and don't go to the dentist often. The last time I went they told me I needed to get my wisdom teeth out. Do they both me? No. Not only that, but in order to get them out, because I have deep roots, they would need to chip away at both my jaw and cheek bones to get them out.

I thought the entire thing was funny when I kept pushing for the "why do these need to come out" and the response was, well, without taking them out, we can't guarantee that you won't need to get them out later and that would be even more difficult then.

But the one way we can guarantee we don't need to take them out later is to take them out now.

I haven't been back to the dentist again.

I think data centers and power are the dark-fiber of this current "bubble".

Inference is 2/3rds of the power used in AI, and I expect the majority of inference to go local in the next 2-3 years, about the time these data centers will come online.

The other 3rd is training, and the major labs are training 6-7 times a year right now. But I suspect we will see a few things. 1) training iterations will slow as the improvements between training runs gets lower and lower. Is it worth spending an extra $500M(ish) for the small improvement in quality? Who is paying for that?

2) Training improvements and improvements in GPUs will require less power. Along with fewer training runs, as we add more and more tokens, the amount of power needed for a training run will likely asymptote at some point.

The point is not that these ideas were wrong, but that they were incomplete, yet were assumed to be complete.

I work in neurotech and specifically with EEG, some would find it surprising that I 100% agree with this take.

When we understood the world of fluid-dynamics, we looked at the body as blood going through a pump delivering materials (oxygen, minerals, etc) to different parts of the body. We though to ourselves "we know how this works!".

Then we discovered electricity, slapped our collective foreheads and said "oh! It's electrical!" now I get it.

We still don't.

Let's learn what we can from what we can and use this knowledge to our benefit, but let's not assume we understand the underlying mechanisms just because we can find correlations.

I'd add that we've seen how the leadership/reputation of different AI leaders, and with 2 decades of history with Larry and Sergey, they seem to come up on top as the most respectable.

Did they ever really abuse the power Google could have wielded? I could be missing something, but for the most part they seem to just get down to building and pushing technology/science forward and avoid drama rather than welcome it.

Let's not ignore the economy where the agent is the buyer.

Video editing and website design being the example here. If the video is an ad, or the website is a sales site, if an agent is a buyer these change considerably. That is an entirely new economy, similar to how we did not understand the knowledge economy until it was fairly well developed in the mid 1900s (someone smarter than me might have better info here).

I have no doubt the economy will change, but we as humans operating in the world will still have needs that need to be met.

In addition, with a shrinking population in all developed nations, we may well still have a shortage of workers in 30 years, not an oversupply.

From what I could see in the blog, pneedleman asked AI about the perfect alarm clock, but didn't ask his daughter.

Did the daughter get involved in the design/build process at all?

It seems like a great opportunity to engage the daughter in some way. Better than buying off Amazon, better than just having AI do it.

Maybe I'm wrong or missed it in the blog, but I didn't see any reference to the daughters involvement at all.

An interesting thought experiment, but I'm not sure I follow the reasoning of these two statements, which is the crux of why open software fits this mold.

1. Reproducible, meaning executable, as well as modifiable, and 2. Reliable, meaning that the results are consistently trustworthy

Why does modifiable fit reproducible. Modifiable fits the open source theme, but not the science theme. Can someone set me straight on this if I am missing something?

Number 2 is something I've been thinking about more recently, and the definition of science from the post being "testable hypothesis and predictable".

Medicine is testable and predictable, but not reliable. To me reliability is the job of engineering. To take what is known in science and make it reliable.

I used to work at CSIRO (Australia's science and technology org) and I remember my boss telling me that researchers always think their work is ready to go from the lab into the real world, but it is our job as engineers to make that translation so that the work outside of the lab. That's what I think about when I think of reliable.

Thoughts?

I was hoping to see something like this, though I didn't know what form it would take.

A few months ago I was at a demo night in SF and 4 people demo'd essentially the same tool for managing PRs. At the time my thought was "are we really going to be dealing with PRs in 2 years.

I don't know if Delta is the right solution, but Zed is at least questioning the current paradigm, which I think is important.

Part of the question may be how do you change the users expectations.

If you are building a product the user already knows, that might not be difficult.

We work in the sleep space, where everyone expects a hypnogram and a sleep score. Even though these things don't actually tell you anything real. They are of little value to most people, but that is the expectation.

The better way is to never have those features in your pipeline already.

Are you sure this is a bandwidth issue?

I always assumed it was more about the position and size of the microphone.

I think this is a direction as well, though I'm also conscious that it may be something else we're mostly unaware that we do.

This is mostly seems to be looking at the past to define the future, as if we are going to go back to a similar way of living and that the current "work" was a fever-dream which captured the entire population.

But I see the past as more of a trajectory than a closed-circle.

Prior to industrialization, most of us would have though of ourselves and our work as physicality. We have physical bodies which do the farming, the sewing, the waring, the metal working, etc. etc.

Yes, we used our minds and understood the idea of a creative class, but that would have been a very small minority of the population.

As industrialization took over the physicality of many jobs, we transferred to our thinking selves. Most work does not involve physical inputs. They are mental inputs.

If we spoke to a pre-industrialized person, would they even recognize that their mental inputs would be considered work or a job?

Therefore, with this mentality, is there something we are doing today which is part of our humanness, which we don't currently recognize the value of, but will become the next level of "work"?

As a Canadian, I agree this is ridiculous.

Having worked in the mapping sector for a bit, it makes sense.

Google/Apple are not deciding what the lake is called. They are pulling data from the GNIS.

This way people in a region will see what their government decides is the correct version for their people.

Let's take this out of the heated debate.

In the most of the world and Iran (strangely we agree on this), we recognize a body of water known as the Persian Gulf. For the Arab League states, they call this the Arabian Gulf.

Is that Google being evil? Should Google decide what this is called? Or just leave it to the region to decide themselves.

What about the border of Kashmir? How should they handle that?

I think of this every time I see something/someone advertising electrolytes!

I recently built our knowledge management system based (loosely) on the Karpathy LLM-Wiki model.

I'm not sure I understand why it is so important to be multi-agent, or for each agent to define who they are and what changes they made.

Our process uses git for tracking, so much of these details are captured natively in the merge.

Our process is

Drop a change, or something to document in an "inbox". Agent makes a branch, processes the inbox materials, updates the documents that need to be updated, updates timelines, makes a note of others on the team that may need to be notified of changes.

Creator reviews the PR and ensures the changes match how they want the document to be updated. Anyone that needs to be updated is now a reviewer on the PR.

I've just started rolling this out to the rest of the team, thankfully we are an engineering heavy organization so everyone is comfortable in Git.

The system keeps a running audit log, input is never deleted, it's stored, documents are updated, people are notified, etc. etc.

I'm just not sure what the service is offering, and how being multi-agent is solving a problem, but maybe I just haven't hit that problem yet.

I'm amazed how many people I see taking photos of their coffee. Like "this is the one I want to remember". It's like the joy of novelty has been replaced by the potential and short-lived dopamine of a social like.

We wrote about the "why" on our blog a few months ago [1], but the short version

Sleep is a complex interplay of multiple systems within the body. A consistent/regular schedule means the brain/body is not guessing what you are asking of it. It knows when to reduce cortisol, drop body temperature, etc. etc.

A simple example: When you force yourself to stay awake longer, your body attempts to compensate by increasing cortisol, then when you try to go to bed later, it can't just switch off the cortisol. It needs to clear it in your system. Then the next domino falls of when does your brain/body expect you to wake up? What are you asking of it?

[1]https://blog.affectablesleep.com/p/the-hidden-work-of-sleep-...

I always come at this angle.

If you had the data, what would you do to change it? Would you recommend everyone go outside? You can do that without the data.

Would you wear your own oxygenated supply of air? You can do that without the data.

Would you make recommendations that the office should improve air quality? You can do that without personalized real-time data.

I'm not against data in general, but the idea that if only we had data we would make changes in our lifestyle is not valid. We see it all around us.

We had bathroom scales for over a century, but the data or insights didn't put a dent in the obesity epidemic.

You're right about "the problem will solve itself", but it isn't the data that will help to solve the problem, it's creating a simple and obvious solution.

A friend has a start-up in the commercial air quality space which solves for this problem (in some ways). But the benefit isn't the air quality, it's the cost of maintaining the healthy levels required in commercial buildings. Air quality is the secondary benefit of reduced electricity demand in air circulation.

Based on the current status of my shadowbanned account (I suspect a competitor in our space retaliating), it looks like `banall` only flags posts from the last 6 years.

Of course, nobody can view my profile anymore anyway (I'm waiting on appeal), but on my account, only posts from the last 6 years have the "Sorry this post was removed by reddit filters" message.

It doesn't work until it does.

The same thing has been said about robotics, AI, space travel, etc. etc.

I'm not saying this is the way, and I have significant questions of understanding thought based on reading brain activity, but I wouldn't put down the entire ultrasound field.