lucfranken

Ah wow, they got down quite a bit already! Here it's around € 20k it seems. Not bad.

> The Netherlands of all people should understand about sea level rise and the real world capacity available to absorb CO2.

That's interesting!

Good looking but also a quite expensive one! If it will be for masses the prices will likely need to become substantially lower.

And we need the charging capacity for all those vehicles which is a huge issue. For example in the Netherlands this shows the capacity available to use extra power connections:

https://capaciteitskaart.netbeheernederland.nl/capaciteitska...

All red. The goals of the environmental improvements should connect with the actual real world available capacity. Otherwise it's just a dream.

It will be a huge issue which we have to face, organize and regulate.

For sure, we humans cannot handle unlimited amounts of messages, questions and other things.

But it also results in new ideas and experiences which shape humans. And it inspires humans to consider new adventures which is the good side.

Maybe we are already feel it like spam while others have that feeling of a shiny new experience in their area of expertise.

Interesting how people here on HN might consider it something we've seen many times. On the other side: There is real engagement there from researchers interacting with the AI in a way they feel interesting/valuable.

We should not forget the way broader levels of knowledge on topics around the world compared to our own small world.

It's really hard to see anymore where the real money is made and what is a big facade. As it's really simple now to create a huge facade. Before it needed more work to show something big which was actually small. But now you can generate the show.

And there are actually some which are really big. But there are so many more overflowing the world with non existing businesses that it's hard to decipher what is real and what is not. It also makes learning from the successful ones way harder.

Isn't that how they just release all features? So they can do progressive roll outs and telemetry on issues with it?

Not sure if they later move the code from inside the flag check to the main code or that they keep the flag check.

But if they would keep all features behind a flag that would not make most sense as you then would have not many features without telemetry.

Real world stuff, physical stuff, real services are still complicated.

Moving around papers, data and that kind of jobs becomes automated.

The real math problems etc: I think it will create many more interesting problems and challenges. It's not like something is solved and nothing is left. That's the wrong way to look at it I think.

Not sure on that, maybe the options to choose from will be generated and curated. Same as we do with tagging datasets for images. Might be wildly successful for real world decisions.

Blackberry wants it's keyboard back :)

Interesting that there is no mention of running your Bots and Agents directly from this device. It's interesting to think about whether we will keep managing so many apps on a device or that all of those will be merged for the user interface.

Jev is such a different approach where you have to be specific about what you want and which options are open. Really interesting how those things evolve in usable features for people.

Also with this example the speed of new launches based on a launch is just incredible.

I'm also not sure that all downtime is really properly measured now as more and more services are connected and intertwined.

Some measure quite detailled but some just don't summarize the downtime from all providers up and below their own platforms.

The interesting balance between humans having fun in their work and fixing many real security issues. The article mostly focusses on the first part but there are real CVE's getting fixed as well.

An interesting article about the real world impact:

"It has truly taken all the fun out of the job now, and it’s difficult to predict where this road will lead."

Getting really deep into some technical thing becomes way less. Most of it is solved by a prompt.

On the other hand there are new techniques like keeping the agents on track and imagining about which things now became possible.

But the real tinkering: In real life with real physical work.

Outside of this discussion about what is fair and not. This is so highly interesting to think through.

The amount of millions available to do those kind of research cases is practically unlimited.

There are an unlimited amount of cases to work on.

What a huge development would this give to both humans and the world in general. Because in the end better understanding gives new options.

It's deeply interesting that those things now get a concrete economical price which seems to be viable to extrapolate. The enormous additional "production" of knowledge will inherently increase the speed of all pieces of research and development.

Taken into account that it's used wisely, the risks with a strong force are always huge as well.

The reason micro services became fancy is because they could split up large groups of people. They could work on different parts more autonomously without all being dependent on each other.

It has an overhead but as scaling the amount of people was worth it there was an advantage.

Where did this work: where the interfaces between those groups of people were agreed upon.

A team could call: finance->billTrip(TripObject) via an API and the finance team became independent. The micro services had an API which was documented. They could move from Stripe to SAP to a custom solution internally without bothering the other teams.

Now we have AI.

Those interfaces are still needed. But is there still an advantage to hard separating those interfaces in real micro services, with separate databases for each team, over http or other protocols?

On some point it may. A service which needs to scale unlimited (like RenderThumbnails with hundreds of thousands of call per day) might have that. But if you send out 1000 invoices per day it might not be needed for that at all.

In Rails they have active job for it for example. Same codebase but a scalable worker for longer running jobs.

AI is capable of quickly keeping function calls consistent internally. So a hard coded API is way less useful now for those services which don’t need the scale. An interface could suffice just fine. No human would ever read the finance API anyway.

Keeping consistency in the monolith part is way easier. That is statically testable, quicker testable and there are plenty of tools. All disadvantages on micro services on those calls are just a waste.

One thing where I think hard boundaries are useful is on really blocking AI coding tools. With microservices you are able to physically prevent Claude or others to modify the other interfaces. That way it prevents hallucinations, quick fixes and other workarounds the tools like to do. Just because an AI wants to get sometime done it will sometimes skip corners.

I see that as a current state which will be fixed quite soon. The models and their harnesses will become increasingly better in preventing stupid corner cutting to get the fix out.

When that is done: why would you want more complexity with micro services instead of less?

Instead of we all implementing microservices and other structures we should get the harnesses right to respect interfaces and boundaries.

And in the micro services era we had meetings to sync the API’s between them. So maybe the AI’s should meet about the interfaces, with a good coffee.

Interesting piece. Seems to be that the expert cannot falsify things but his opinion is an opinion. So there is no good/bad in that.

Not sure how it legally works, I think in the legal system at least in the US it is quite common that experts are hired and giving opinions based on who hires them?

And then the other party can cross examine? Not enough knowledge on that but it’s interesting if legal people could chime in on how it works.

I hope those expert “opinions” are not taken as facts?

Very readable and interesting outlook on the current developments in the market.

Also really interesting to show that a company which started with a more technical product:

https://stripe.dev/blog/payment-api-design

is now exposing to their investors about how the world GDP and economics are expected to be developing in the coming years.

The vision in the document seems to make sense, is clear and they clearly invest in this trajectory themselves.

Horribly complex challenge. Totally agree.

The problem is simple: We don't know which sources and tools are used. The experts submits a report, talks about it, answers questions. It is never a hard factual check on where he is coming from.

The intentions, generally based on the party who requested the expert, are many times challenged by the attorneys.

In basis it's a reputation issue, is this a trusted expert. But only that does in my opinion not suffice. How many "mistakes" do you accept before a non-compliant expert is caught?

So yes:

> And how do you do that? Do you ask... An expert?

That's what counter-expertise has to handle. Just one expert claiming something is a hard thing to trust.

It's the same thing that the lawyers in cases found that other lawyers were making claims based. on non-existing laws. Hallucinations by ChatGPT in that case. They did the world to verify. Found the issues. The lawyer gets fined (reputation damage).

There is no way around it, the work of verifying has to be done.

They won't destroy the books very likely but also the amount of capacity and money to do this on a huge scale is (as far as I know) totally unprecedented.

And it's irreversible when the books are really destroyed.

That combination makes it an urgent and important issue.

Yes, that's a horrible way of applying the rules. Sometimes things are done according the rules but the outcome is terrible.

Totally agree on your example:

> One day you dig into it and realize I just hard-coded "not today" [0] which is 99.999% accurate.

It only becomes visible when you do the research.

The justice process in this example just has to check and verify the inputs. There is no way around it. Today it is this expert, tomorrow another one.

When someone is caught that's an ethical issue and there could be more structural consequences as well. Like blocking the person as an expert or other means. As the expert becomes untrustworthy.

How it is made should be irrelevant in the process. There is no way to stop people using LLM’s or other tools to create products like this report.

It should be globally a standard check to verify incoming documents and to determine their validity.

The interesting part on this case is that we see the real human aspect of it. Just asking for a report only finding the positive facts instead of doing real research.

That is an ethics question. When behaving like this (and it happened before LLM’s) it should be seen as an ethics violation. If not done there is no value in those legal procedures anymore.

The facts people have to accept is that the only place to check this is the deliverable. They are lucky now to have found the source, the prompts and the background but so many reports are entered without being so obvious.

It’s a terribly huge and complicated task.

It’s ugly. When there are still only some copies available of a certain book and they are all being sold the knowledge is gone. Let alone when it’s the only copy remaining.

That is of course not totally true, the copies are in private digital stores.

But for general public the knowledge is gone. Someone researching let’s say the history of a little village won’t be able to catch it.

This happens as well in current private collections. The physical book gets stored in a private book collection. But many also get out by the years when people are moving or die.

The amount of companies doing this is the real harm. There will be many companies running this process. It is absolutely not comparable to a single book collection getting burned in a house fire or being thrown away instead of donated to a second hand store.

It might feel for some as a not really big issue but actually it is in time.

If you would add some example tweets that would be way clearer to see what it does. Result looks nice!

Just out of curiosity: How did you mentally keep oversight of so many terminal doing things all around the place? Or is this done without too much oversight and do you just look at the results like sales volumes?

Totally agree on that, if you have to look constantly at something 95% there is no value. The expectation of course is that it will be better. But if not at a certain level useless.

Not sure how that research compares to the claims being made by many that a second opinion via ai in the end led to changes in treatment. Likely people spent quite some time searching and figuring out. That would be a different and n=1 result. Don't have enough knowledge of that research to determine how much result can be gained when the models are managed in a way that produces better results.

And of course how much time/effort/cost that would take. How much is custom and how much is an automated programmable flow.

That does make sense but the order of it might be: doctor analysis. Then show LLM as double check to doctor. Doctor assesses and may keep en improve the doctors first analysis?

Why wouldn’t you as a doctor by standard run the images through a certified compliant LLM? The actual cost won’t be it and then you can see if you get any new ideas from it. See if it’s just wrong or that it spotted a little detail you missed?

The LLM doesn’t need to be leading or whatever but then you can have a conversation with the patient. If their ChatGPT reports has differences it can be analyzed as well.

It feels like the time constraint of the 15m doctor sessions is the thing. But if prepared immediately after the scan then why not?

There is always time needed to factor in new developments and innovations and that’s fine. Just moving blindly work from human to LLM is wrong. But learning on and testing with all the ai tools incoming constantly won’t be a waste. There will be more and more tools in those processes outside of human judgement, better improve the workflows now to be able to test and plugin new models and systems when they are ready.

For many thinkers it's in a way a very relaxing occupation in some way. Would have to think about why.

It is a real issue. Makes sense. How are your experiences with it and keeping up with the constant changes in Claude for example? There are many tools which can be installed but it's difficult to imagine how Claude internal develop themselves.