2,526 karma · joined October 15, 2012
E-mail: sixdimensional ATAT [dimensionsix DOT com] minus the ATAT and brackets.
I want them to succeed as a business so I can use their products, but trust does erode over time. I wish they would realize this and value their customer more.
"Normal accidents, or system accidents, are... inevitable in extremely complex systems. Given the characteristic of the system involved, multiple failures that interact with each other will occur, despite efforts to avoid them... while operator error is a very common problem, many failures relate to organizations rather than technology, and major accidents almost always have very small beginnings. Such events appear trivial to begin with before unpredictably cascading through the system to create a large event with severe consequences." [1]
I don't have formal benchmarks for that, but I can anecdotally say the SIMD work made a measurable improvement in the performance of the calculations vs. just plain Go. I'm very optimistic about how these improvements will help make the Go runtime an even better target for more of these types of work going forward, especially since it is cross-platform.
First they came for all the dev tooling - uv, Cursor, etc. Now the routers and providers - Open Router, Hugging Face...
Who or what is next? And what is the endgame I wonder??
I like to hope that those in positions of power do have a sense of morality though too.. but their worldview is quite different than an ordinary citizen.
I think nondeterminism does not have to be the same as non-coherency - i.e. just because something is randomly sampled does not mean the result has to be incoherent or inconsistent.
Also, if we speak purely about LLM based on how they are implemented now, I feel that is different than speaking about artificial intelligence. The field of AI is much more than just an LLM by itself, and the promise of these companies is not just LLM, whether the underlying models are limited to that technology or not.
FWIW, I have built rule based expert systems, used logic based reasoning systems like NASA CLIPS or rete-algorithm based systems, mathematical/symbolic solvers, written plenty of terrible case/conditional logic in programming languages, worked with ML in its infancy and now worked in AI/LLMs - I give this context only to clarify that I understand what an LLM is and isn't.
With all that said, LLMs have allowed humanity to make advances, at great cost to society (IMHO), and I'd hate to see the opportunity be wasted.
There is plenty of room past "attention is all you need" still to do incredible work, especially at the crossroads between deterministic and nondeterministic behaviors.
We've seen this pattern before several times.. I hope they are listening and address this publicly.
I'm not sure what is going on, some users report it works fine or great, others report the degradation. I've experienced both at times, and it's been such a different experience it has made me wonder if there isn't some sort of hidden A/B test or model router in the background silently downgrading requests at times.
Also, regarding the subsidized access to models, in my opinion, the frontier companies owe it to society to continue it. After mining the public content of all of humanity, I personally feel it is a service they owe the public in return.. not that my feeling of this counts for anything though.
I can't help but feel deep down somewhere inside though - boy.. $400M is so much money - whenever I see these kind of huge raises, I kind of wonder, how likely is it to fail when you have been granted such an enormous opportunity, plus all the other money they've raised.
This question isn't limited to Lovable of course.. but it's just.. wow.. it's so much runway... will they end up spending it wisely? I feel like a lot of companies end up spending this on scaling out sales, sales engineering, marketing, advertising, splinter/side efforts, tons of hiring/headcount expansion, global expansion, acquisitions... and this often makes the companies big, slow-moving behemoths, but does it really advance the core mission, technology, infra, etc.?
Will be interesting to see where this takes lovable. Congratulations to their team!
Thank you for taking the time to respond to my comment, I appreciate all you do!
The only dictionary definition of "operating system" I see is like the technical one on Wikipedia [1], which IS more like Windows, Mac or Linux.. not like an app or platform.
From my concise Oxford English Dictionary, for example.. "operating system, n. the low-level software that supports a computer's basic functions".
Like, would it be better if it was just called the "Cloudflare App"? Or the "Cloudflare App Platform"? or the "Cloudflare Platform App"?
Those aren't clear winners either, they could easily be confused for product offerings or other things.
They could name it, like, "Cloudflare Rocket" (random product name) or "Cloudflare Jane" (e.g. personality) and then say, "this is the desktop app for Cloudflare Jane, which is a platform where we put all these tools and capabilities that combine with agentic powers".. but then it wouldn't have the marketing flair either.
FWIW, I am a sociotechnical specialist so I watch these things carefully.
Actually, I think Cloudflare OS quite possibly a good name for this case - especially with some of the history of coming from Sandstorm and what Sandstorm was trying to do for users. I super appreciate the background you shared about what you were doing here (and the secret master plan), and it makes complete sense to me actually.
I am also very sure of what I am saying about so many other things popping up with the "OS" tagged on - from both technical and non-technical use cases/companies.
I also appreciate your honesty about cleverness - LOL.. two hard things right? :)
Just as one example though of the larger trend I am watching, look at the launches on ProductHunt that have OS in the name (some are old, of course, but even in the last few weeks I've seen about 5 new things in this vein) [1].
I think this is a case of the hive mind actually coalescing around an idea (and even I was having the same idea), and I am not sure yet what the result will be, but my strong suspicion is some sort of new real operating system (potentially built with current OS foundations) that is built from AI-first principles, and a lot of other people trying to make it seem like their app is an "OS", either because they are using a nontechnical definition (or trying to piggyback on a technical one).
Non-technical people don't always think of an OS as the computer OS. To them, sometimes it means more like standard operating procedure or process - a standard way of doing things.
Secondly, for tech products, calling yourself an OS, you are associating yourself with things like Windows, Mac or Linux. You are indirectly trying to grandstand and position yourself as meaningful enough to be an "OS" when clearly, that is far from what an app layer + AI/LLM on top of a real OS is.
The biggest giveaway is this, and I'm exposing it right here -from a technical perspective, what operating system computer technology was built from scratch from first principles around AI/LLM?
Someone wants to be the first company to get huge sums of money/funding to be that startup/project, so that is also a positioning tactic.
The issue is of course, most people are standing on the shoulders of giants at this point... and OS has this conflicted meaning with nontechnical users also about work process vs the software that runs my computer.
Context - I have over 25+ years in software, and I have this observation - being introduced to a new codebase as a human is difficult, especially depending on the scale/size and complexity of it.
Yes, you do start to learn it as you work through it, but if the scale is truly huge, it may just not be possible to fully read and understand all the code and paths etc.
I have found systems-thinkers (I believe I am one, sometimes they are architects) to be able to kind of "see the whole picture" while not knowing all the details, to the point of being able to guess how the system/software should be behaving, even if it is not actually yet. This is a hugely valuable skill and I think takes a certain kind of brain too.
That said, I think recently I may have realized something - we rely on statistics and confidence levels in order to make statements about larger populations. If we can represent a codebase as a, perhaps stratified population of code, interfaces, docs, etc. etc. etc. we may be able to take a valid random sample, review portions of the code, and make some kind of assertions about the state of the larger system - potentially, from that.
I am trying to implement this as a side project right now to see if there is anything to it, basically, a combination of AI/LLM + stats/sampling + facilitated expert human review.
I'd be interested to know if anybody is doing anything similar.
A privately owned physical book and the public-domain work embodied in it are different things. Keeping an old book in a dresser, even without providing access to it, is also meaningfully different from deliberately acquiring the sole remaining copy in order to extract its content, destroy the artifact, and preserve exclusive commercial control over the only remaining usable version.
Destroying the sole surviving copy would not literally steal publicly owned property. But it could irreversibly remove a public-domain work from practical human access and destroy a unique piece of cultural heritage.
In that very narrow situation, preservation, archival deposit, digitization, or public-access requirements may be justified, especially when the material is acquired for commercial use that depends on destroying or withholding the only surviving source.
The company would not be reasserting copyright in the legal sense. It would, however, be creating copyright-like control over practical access.
The work would remain legally free for everyone to reproduce, while the company’s conduct made it impossible for anyone else to obtain it.
I know there are more pressing issues than this one in the world, particularly those involving immediate human life.
But I also believe that the value we assign to human life is connected to the value we assign to human knowledge, memory, invention, and culture. When those things are casually treated as disposable inputs for extraction, something important erodes.
Companies should be free to use public-domain material commercially. The issue arises when that use creates a negative externality by permanently destroying the public’s future opportunity to access and use the work.
Mining our cultural heritage and locking away what remains is still extraction and exclusivity.
Let's say one of the books to be digitized and destroyed is the sole remaining copy of a book from 1850, which is now considered public domain.
On one hand, hoarding such a book, stealing its content from the public domain, locking its content behind a for-profit machine, and destroying the only remaining copy is clearly wrong. It's equivalent to stealing a public resource, just like mining minerals or oil on public lands without a permit or mineral rights. Pure extraction.
On the other hand, taking care to digitize the copy and making it available for free in perpetuity, as well as being required through regulation to provide access to that content through, let's say a public utility LLM/AI available for free through libraries and online... and perhaps after fair due diligence being required to preserve physical copies in a public archive of rare books of which there are no known remaining physical copies...
That seems much more reasonable to me at least. I can imagine there are many who would not see it that way though. Do we see it happening or gaining regulatory, moral and/or public support?
[1] https://htmx.org/essays/future/#writing-research-and-standar...
[1] https://en.wikipedia.org/wiki/Fourth-generation_programming_...
It's awesome, I'm not criticizing Htmx at all to be clear, I am criticizing our seemingly inability to advance the core web technology of HTML in browsers to include this kind of tech natively.
If somebody from the WhatWG, e.g. Apple, Google, Microsoft, Opera, and Mozilla, etc. wants to embrace and support the creators of Htmx and wrap this into the browser natively, I will proudly retract my comment.
Presumably we haven't heard as much after Northrop bought them?
I think it's awesome that Scaled Composites is involved... they really have such specialized knowledge of all kinds of aeronautical engineering.
Duplicates are not always what they seem - duplicates have a relative quantity of how duplicate they are, for example - 100% duplicate identical is what it sounds like, but then what is a 50% duplicate? Well.. that could be a duplicate where semantic meaning that only a human is aware of (missing information) could be used to determine that these two datum are in fact duplicates in different forms, where 50% is identical, but the other 50% is semantically identical. Or 50% truly identical could, in some case, be "good enough" to be considered identical. These are just examples.
Why this example is relevant is because, when deduplicating data, we often have to consider which value(s) we keep as the true singular representation.
The problem is, long after the data is created, this may be impossible to do.
The solution? Often times it is no better than flipping a coin and guessing, i.e. randomly keeping one datum and discarding what we consider to be the duplicate. Or you can try to be fancy and merge the data or choose, based on some rule, what you assume is the data with the highest valid signal and discard or ignore the noise.
This happens every day in practical information systems with messy data.
I always come to the conclusion that in the end, one cannot truly replace missing signal precisely - one can only infer the correct signal. If the information was not recorded and or compressed or corrupted beyond recoverability, there is no way to get it back - only to infer or guess with some degree of confidence, and accept or reject the outcome.
This to me actually clarifies something deeply about the conversion between the real world to the digital one as data, and the conversion of data into information- it is a real physical process.
In my mind it makes clear that the recording of data (or generation of data) is a real physical process of transfer, from an instrument making observations to physical bits in a physical system, which become the raw data.
Without the raw, precise, complete data, your observation is lossy, and therefore everything above it is as well- e.g. information/interpretation, etc.
This isn't a negative. If stated correctly, the above just helps to explain how we imperfectly navigate through the real world with our tools.
All the same, we can do some pretty amazing things in the absence of data, even if some of it is "false" or "wrong".
Unfortunately, capitalism of today appears to find public goods and strong, public, healthy public goods to be undesirable investments. Yet, it seems inevitable that some things trend that direction.
I feel if we could get a better handle on what goods fall into which category, and find ways to make those things sustainable and even grow, the situation could get better.
I'm speaking purely from observations here but it also looks like in some ways, the "invisible hand of the economy" (i.e. Adam Smith) might sort these things out by itself, albeit, painfully.
We could look at the fact that LLMs were mostly created from the public domain (except when they were not), and the resulting products/services (expensive to create/operate, benefits a huge swath of humanity, has all kinds of externality issues) as something that perhaps should again almost be considered as a public good.
If we look at the struggles LLM/AI companies have had with legal structure choices, such as nonprofit, for profit, etc and pricing (e.g. do we make it accessible at a loss? Do we extract huge profits?) as a kind of moral dilemma of classifying this new economic good (LLM-based AI).
In the US, the government has been taking investment interests in some tech companies, and recent proposals even include establishing sovereign wealth funds around AI/LLM. I think this is further evidence that the system is trying to figure out how to classify these new economic goods and corporations.
I'm curious about how the unifying architecture is going to evolve between CPU/GPU having direct access to a singular pool of memory/storage also.
I also keep wondering when memristor technology might enter the ring, because as I understand it, it would be like moving compute into the memory, which would potentially remove the need to move the data in and out of storage as much also.
It feels like computing hardware infrastructure is fundamentally evolving.
I am wondering about.. SQL as a declarative structured query language that can be optimized into essentially any kind of distributed, directed acyclic graph of processing - vs the special characteristics of relational databases (relational algebra, relvars, etc. etc.) is an important distinction as - of yet, I see the author linking both together so I'm trying to understand what it is about relational structures that specifically helped here (just not seeing it yet, not that it isn't there).
Also, wondering if ISO/IEC 9075-15:2023 SQL standard for multidimensional arrays (MDA) is of any use here? Paper describing SQL/MDA here [2].
[1] https://madlib.apache.org/documentation.html
[2] https://www.ifis.uni-luebeck.de/~moeller/Lectures/WS-19-20/N...