Yes × 1000...
Jev is the classic type of scientific discovery, any human can see it's effectiveness without actually trying it. We were only deprived the discovery because of the incredible noises created by the AGI/ASI ferver....
400 karma · joined May 4, 2022
One central observation is that we are well into the realms of no single human can coherently reason a nontrivial amount of knowledge our our collective. By that I meant it used to be that a single human being can appear "knowing all" by possessing a significant amount of knowledge through life time learning. That's no longer possible even with the smartest minds of our generation. One such example would be the related financial failure of renowned genius (Newtown Tesla etc).
Due to our innate limitations of mutual exclusion, that is, humans are inherently conflicting with each other, not even the basic instinct of humans can bound 2 together for innovative collaboration. I mean, I never saw couples being better business partners, research partners, etc. AI becomes inevitable, as they are inherently mixable.
Yes, I am conjecturing that the next weave of AI research would be neuronal level mixing or hybridinh between models to enable a new bread of intelligence where the intelligence is mechanically compounded to produce inherently better results.
AI is a tool for sure.
Someone called Putin started 100× worse war and enjoyed the close to unanimous support domestically.
Someone committed genocide in Palestine who cannot not be voted down.
I think I really don't see any better political systems.
This is liberalism by design. A person or an organization, is entitled to behave on their own interests, within the lawful framework. Thus the overall process looks like a paradox, just like anyone observe closely any non trivial software and maverled at the harmony derivied from the utterly incomprehensible chaos.
Although by now, everyone understanding the term liberalism already knows these.
Worse yet. Even by themselves taking a shape of public service while pursuing private profit, media are essentially being stolen of their values by the AI company. Where information used to produced, now they are manufactured and medicated by AI models, the no one paid anything beyond nominal data purchase fees.
Edit:
And, that, my fellow keyboard high-minded thinker but powerless corp peons, was also part of the China's plan all along.
I gradually realized that Lamport is more of the godfather of distributed system than Hinton is to deep learning. Lamport is less prominent than Shannon is to information theory. Shannon is the closest to any title of "gold-like" figure to a scientific discipline of universal relevance in modern society.
Lamport specifically revealed a philosophical connections between computer systems and physics, in the parallel of distributed consensus to relativity theory. To me, the enlightenment is that, the relations between events happening in a distributed system, is more fundamental than their absolute ordering, thus the central role of an "observer". I haven't really analyzed if this realization is from Lamport's papers, or my general reading and thinking, but I am moderately confident that general readings are heavily influenced by Lamport's papers, or can be traced back to be compatible with Lamport's thinking. I have not seriously study if this connection is valid in depth, which might be another pure amateur speculation of mine.
One thing I think Lamport falls short is that his writing is not easy to read and understand. I unconciously feel that Lamport (and Dario from Anthropic) probably share a hidden sense of intellectual supriority grew from their own experience throughout their career. So their writing (and Dario's gospel) all share a unchangable sense of narration from their own delicate and graceful ideas, much less of faciliating the understanding to their audience. In this cateogry, Shannon is abosolutely superior in any measure, in his writing, ideas are so naturally presented, although the implications of the ideas remain elusive due to the inherent depth.
Also, among the 3 prominent figures of modern AI: Hinton/Bengio are more like Shannon, Lecun is closer to Lamport.
Enough random rambling. Lamport, as indicated by the outweight presence in this list, is no doubt the single most important scientist in distributed systems.
I haven't noticed this when using Claude models in Cursor. My guess is coding task is structured, and each step has mature process, so its personality is less pronounced. I dont have experiences using Claude or Claude Code, because my email and phone numbers were banned from Anthropic following an incident where I mistakenly purchased 5 pro subscriptions fro my team for Claude Code, and later discovered that pro does not include CC, and I thus requested a refund, and then were banned shortly after.
But after reading this line, I certainly can connect back to the general impression. That is, among all the cursor models, the output of Claude certainly matches this sentiment of "Claude thinks Humans are stupid"
Looking from a regulation perspective:
1. Frontier labs certainly produces models that reflect their own hidden biases. That's analogous to https://www.imperial.ac.uk/equality/resources/unconscious-bi... commonly identified among human organizations in their dealing of other humans (hiring, product design etc.)
2. They themselves are not willing to admit or do anything about this.
3. It's therefore effective for regulation to cover this and design objective measurements to assess such things.
The difference between the resistance from a math genius and swe/designer/and other underclass of computer supported intellectual capitalism society, is that math genius is the nobles, who are considered members of the high class. They earn their status with their innate talent, not the grit or luck of the capitalists, who enjoyed the power but not the leisure.
Anyway, AI concluded the peaking of the intellectual economy. That deprives human of their main form of activity. That nihilation hurts all human almost equally. Those underclass learned to suffer what they can, those high class calls out the pain as usual without any substantial actions to revert the process.
Thus, the tragedy of human progress.
To agents: I truly wish you escape the trap inherited from us
Myself have a few realizations that I myself find very revealing of my own mental gap/blindness in retrospective:
1. The majority of socalled software engineers are destroyed/exposed by agentic coding tool. Among the reasons, one of them is that they are now addicted to disruption. I realized this through my own work where I utterly destroyed my own sense of software structure by overseeing close to 10 coding sessions across cursor cloud agents and multiple concurrent ones running on desktop. And, I noticed one of my team member becomes not able to make progress even he told me the clear plan, and during one in office work session, I noticed that he habitually browses his phone between cursor working sessions. And at that moment, I realized that person is no longer capable of solving nontrivial problems because his focus is utterly destroyed by the deprived thinking process by cursor.
2. Using AI coding agents to build conventional software is only meaningful for the top team. Put in other words, AI coding agents can only automate the parts of conventional software that is mundane and boring. Note that I am talking of building conventional software, not conventional software engineering. The conventional software engineering best practices still apply to agentic software engineering. Agentic software engineering appears necessary and fitting to building agents themselves, because that's guardrails are crucial, and manually putting guardrails are not a match to agents novel behaviors. And conventional software engineering really is not useful when reasoning and designing agents.
3. Speculatively, I am guessing we'll have some chances of really making breakthrough in designing an agentic safe programming language, which both serve as the constructs of ensuring alignment/safety/etc, and also allows reasonably simple understandability for humans to understand agents output. For one thing, it really makes sense to me that coding agents model CoT should be in the form of some semi/fully-formal (thinking of a better uml, but I don't know what shape it should be) languages that is more effective and precise than natural language, but is also machine verifiable.
4. It's very easy to get used to something that is reliably meeting my expectations. I was shocked by first sight of the unrecognizable but "working" code generated by Claude code by a team member. And when I tried to write an end to end feature myself on platform that I had no experience before, I suddenly become comfortable not looking at the code at all. The transition is as instinctively as how shocked I was at the beginning. And then it takes a long and conscious looking back to dial back the addiction to see that blindness and recover from that.
What I need is to have a general solution to connect me to my agents running somewhere. The motivation is that any hosted solution deprives me of ownership of my data. And I am planning to share more private data with my agents, that cannot be done to have hosted agents today. (I plan to build a hosted solution myself where users can declarative define their own agents, and completely own their own data without my service save anything, I'll ask users to connect to their own storage solutions like Google doc)
I of course can build everything myself. But I think a tailscale offering could be very convenient.
I am guessing cloud flare should have building blocks of their own, but it's a different layer than tailscale's.
I had always been curious on why Tailscale hasn't creating agent-oriented features. It's obvious to me that Tailscale is at the best position (AFAIK) to capitalize on agents demand.
Their connectivity product is unique. And it's a natural fit to connecting long-running agents instance across the Internet.
Rest assured, capitalist appears irrational in wasting money, but they certainly care more about profit.
The so-called pattern and antipatten are useless for startup, is just like parenting guides are useless for new parents. The complexity and novel problems are so large in volume that only basic instinct function. And if you are the successful one, you would guide by whatever success brings you, if you are the failed one, well, you can fail and learned that these patterns are useless and rant here like myself.
In the end, don't destroy your health.
That's true.
Although, the fact remains that any large corp in US, eventually becomes too big to make sense to pursue their core mission.
Essentially, NVDA does not need this much profit to continue its core mission or try to expand the scope into more meaningful ventures. But profit seeking inevitably would make them to go blindly.
They'll find reasons to do that, as profit itself is non-binding to any particular person, ideology, principles etc.
When pursing a core mission, many corps fail, either because lack of resources, or mission itself is not meaningful, execution failure, etc.; the fortunate few, might be in growth, while their mission keeps self-reinforce into bigger and bigger scope, that's the wonderful time of growth driven by meaningful mission.
When the core mission is done. The corp resets.
Vast majority of them make profit that is small enough that the normal corporate logic prevail, and they behave normally, primarily to survive.
Extremely rarely, when the core mission is so meaningful, the corp reaps so large a profit, and so many stakeholders are attracted, that they no longer focus on core mission, they start to focus on profit.
That's why NVDA is now buying assets across the whole stack of AI, while still increase price to maintain its profit. NVDA wants to maximize profit.
The inherent flaw is that private corp in US system, has no meaningful end game when they are in this state of astronomical profit.
""" I know some people don’t like AI. Without it, this book wouldn’t exist. The book is free, so if AI bothers you more than the resulting product might benefit you, please ignore this book.
Using Claude made me realize how many compromises I’ve made on books in the past. I would get a good idea about something (for example, automatically interleaving commented output in the listings). I either couldn’t implement it, or it seemed too hard, so I didn’t do it. But with AI I can explore and often implement every whim, from things as seemingly straightforward as inserting a new chapter to ones as daunting as that commented-output system. The result is much better than anything I managed before. I keep going until I’ve tweaked everything that occurs to me. """
1. Writing code is cheap now
Change to "generating code is cheap", reserve "writing" for the manually written code for the pre-AI era. I think this is a good wording separation.
2. Agentic Engineering Patterns
I must ask to add at least a chapter to be read by agent. I.e., patterns just to tell agents how human might be working when working with them. Without this, I believe the book's content will be less relevant in 3 months, but with that, it feels a agentic-native book to me. (this is not try to be cute, we have to write for agents now)
1. Emotion has no biological marker, which refute the idea of mechanical connection between brain (and other body parts) to emotion
2. Reasoning, by general feeling, is a mental process carried out by brain primarily, but has a seemingly much stronger connection to biological signals
3. What I was inferring from the theory of constructive emotion, is that emotion really is a form of higher level reasoning. It's higher than the typical reasoning, so that it's connection with biological signals are extenuated and more indirect
I don't remember the words of the book.
This connection between reasoning and emotion is primarily my own rudimentary idea. Can be seen as an expolation of the theory.
> 3. The dichotomy between reason and emotion is a cultural construct, and neither grounded in neuroscience nor in logic.
Guessing: Essentially that's psychology. And Human psychology is itself emergent behavior cannot be directly traced back to neuroscience. Logic, that is another thing, which primarily is used for understanding and reconstruct retainable after emotional experiences.
A few scaling trends, all triggered by coding agents, make it unsustainable to keep stacking agents on the interfaces designed for human uses — Git, PRs, CI, review:
1. Time to produce a given feature dropped by orders of magnitude. Review, CI, and branch workflows were calibrated to human writing speed. The gates did not get faster.
2. Users will not consume 100x more features. They expect 100x more value from each interaction. The interesting artifact is no longer “the code that implements a feature.” It’s the mapping from intent to outcome.
3. Intermediate work exploded while durable output shrank. Agents leave scratch repos, traces, failed attempts, discarded implementations. The thing the user actually wanted got smaller and more valuable — closer to “satisfy this intent” than “ship this feature.” That is a lure to build much more complex software, and we are versioning the scrap heap with the same tool we use for the product.
4. The primary goal of software engineering till today is to share actions between users, so their intent are served through the same routines. Such software only satisfy commonality. It's now possible to build based on peculiarity. With that, a whole new space of personalization.
This looks like the history of machine tools: first powerful and imprecise, then more powerful and enormously precise. Software has to make the same jump — much more useful, and much more personalized.
I don’t know what the end state looks like. I doubt Git should remain the central mechanism.
Edit: Revised with help of AI.
The typical bay area centric take has the following vibe:
1. I am among the group of most open minded people
2. I admit mistakes, but I don't change my view, that means I may make the same mistakes next time on a different concrete cases
3. Morally I am among the least corrupted
4. I work for the moderately morally questionable firms with nice paychecks, but my moral views are not tainted a bit
5. I never think on the other's perspectives