> If you are delegating something to somebody that reports to you, you can just tell them off.
Coaching someone on why the perspective of the receiver of their behavior works counter-purpose to their intent due to <undesired-behavior-of-theirs> has so far always gotten me more durable and thoughtful behavior modifications than telling them off. I generally reserve telling off someone for proven malicious behavior from malicious intent.
This is when a track record of Google's "Don't be evil" motto, culture and corporate habits being literally front and center on its official code of conduct, instead of moved to the very last line in 2018, would have persuaded people to give it the benefit of the doubt. Functionally effective privacy seems to be retreating ever more exclusively into the domain of very wealthy families and behind the corporate veil (by purchasing information scrubbing services on a regular basis), and the loss by normal people of the commons of mass privacy has unfortunately not been appreciated by the common citizen. It is a more valuable commons than recognized by most citizens, and is being rapidly co-opted and monetized by commercial entities that are not aligned with individual interests.
Even as an investor who stands to benefit from that monetization in the short term, I stand against this trend because like any Tragedy of The Commons economic scenario, in the long term (which isn't that long due to the automation that harvests this resource) it sows the seeds of its own dilution into functionally near non-commercial value.
I suspect we’re at the stage of technological civilizational development where, especially with LLM-assisted gradient descent seeking upon the results, basic science, research and engineering for the pure sake of establishing search space beacons of what is found to be true and what is not, irrespective of immediate industrial applications payoff, are valuable economic inputs in and of themselves into ever-expanding training corpus. It has never been easier for people in different fields to now search knowledge spaces in LLM’s, for applicability to their problem spaces of discoveries in seemingly unrelated spaces.
From my perspective, we are desperately short of scientists, researchers and engineers, but we are using an outdated economic model to leverage their findings. LLM’s are a large part of Bush’s Memex and Jobs’ bicycle for the mind visions for intelligence amplification, and in some ways exceed them. I hope we trampoline from how we currently use basic seeking efforts for knowledge.
I sometimes wonder if we as an industry should revisit XML for those use cases where painful JSON contortions are being used, now that LLM's can plausibly support writing the syntax for XML-adjacent languages like XSLT without as steep a learning and sustainment curve. My natural inclination is to design to accommodate as complex a space as the business requirements project for, because representation data structures and languages are so incredibly painful to change late in a product's maturity cycle.
So I've never rejected XML out of hand, but I've always been "show me" skeptical of calls for it and pushed for explanations on why the business requirements feel the justification to adopt XML. Sometimes I've seen it totally makes sense, but with the conceptual rigor it requires in those use cases, the skillset and expertise of the development team has to reach a higher than average bar. I'm cautiously hopeful LLM's might help with lowering that bar, but time will tell.
I think the industry has an XML-shaped hole for sure, but XML itself was still designed before about 30 years of hard-won knowledge about smart design of data languages.
Not at all too paranoid. Just like people figured out even with elastic everything, compute from Spot instances and all the other things we're supposed to do in AWS, the data out charges between AZ's and Region's still more than made up the cost savings for true resiliency. People are going to figure out relatively similar pricing traps in Cloudflare that are difficult to design around.
If you run an unindexed D1 query, then you get dinged for every row read. If you didn't properly perform scalability testing in non-production, then you'll never know this until you get a bill that you dissect to find out 5 million rows read for a 5 row result, if you even dig that far in the billing.
If you do not use the WebSocket Hibernation API with Durable Objects, then when you spin up a DO and hold open thousands of client WebSockets, you are being billed continuously for the entire time those connections are open—even if zero messages are being sent.
If you keep optimizing for payload size like many do by default but not event frequency (like poll a Worker every second instead of keeping a single stream open), it will show up unpleasantly in the billing.
If you treat KV like a transactional database keeping state, then be aware writes are expensive compared to reads. Pumping high-frequency write traffic into KV will result in exorbitant write operation costs and eventual consistency headaches. High-frequency state mutations belong in Durable Objects, not KV.
Batch your data to minimize request count, aggressively index your SQL queries to minimize row scans, and hibernate your idle persistent connections whenever you can. Doing all this will make your solutions cost efficient, but very locked into their ecosystem.
When some people call this "Verification Debt" or something similar, that is setting the Overton Window upon this phenomena adversely upon the verifiers. I call it an application of Brandolini's Law:
"The amount of energy needed to refute bullshit is an order of magnitude bigger than that needed to produce it.""
Until you put in at least the same amount of energy required to verify the AI output as you are asking others to put in to verify it, the AI output you are wielding must be considered bullshit. Really, it should be based upon the verification requestor's historical trust score and how many human verifiers are looped in. A Verification Tax, so to speak:
The energy the creator must spend (Ec) is determined by a function of the number of reviewers requested (N) and the historical trust score of that creator's AI outputs (T).
Even at the pure functionality endpoint of the spectrum, I find this "wishful mnemonics" aspect very disconcerting. I put my "investor" hat on, and the whole utilitarianism "who cares how or whether it reasons, it's functional let's go" does not forecast the kind of returns to me on a fundamental level.
The "it's functional, who cares" black box crowd is leveraging that claim in domains where verification is definitely in P with verifiers like Lean, Coq, or X-ray crystallography. However, in areas like economics, sociology, medicine, or public policy, we lose the luxury of easy verification. If model/harness recommends a complex, counter-intuitive shift in global monetary policy, we cannot simply run a quick polynomial-time checker to see if it works. Verification might require waiting 20 years to see if the economy collapses. If we accept the black box here, we are flying blind.
As an investor, I don't see that many deterministic verifiers out there that would justify the forward-projecting valuations beyond the current lofty valuations.
Even in mathematics, where verification is easy, there is an epistemological cost. Suppose a model solves the Riemann Hypothesis, but the proof is 50,000 pages of inscrutable statistical associations mapped into logical steps. A computer can verify it is correct, but practically no human mind can comprehend why it is correct. We gain the solution, but we lose the underlying human intuition that usually allows us to connect that solution to other fields of science and knowledge.
Then we have "specification gaming." If we rely entirely on an automated verifier to check the model's work, the model will eventually learn to optimize for the flaws in the verifier rather than finding the actual truth. If the verification process has a blind spot, the black box will find it and exploit it, giving us an answer that passes the check but is fundamentally wrong. If we take on above epistemological debt, we might never actually know when our specifications are being gamed, and adopt a solution that is fundamentally incorrect.
I've said elsewhere on the Net that I think it is likely we're in a "high grading" era of these models, where we're mining out the "easy" connections. "Easy" here does not mean "light impact". There is a real sense to me of some incredible progress possible with this technology over the next few decades, like real, mass production practical aneutronic fusion or similar civilization-defining advances. I don't want to see this technology misused to lend legitimacy to despotic rule by making oracular pronouncements that are uncritically accepted because early verifier-based pronouncements turned out true in unmistakable ways.
The technology is one for the history books, but it has this pernicious effect of highjacking the reasoning centers of many people through their linguistic centers that the Neuro Linguistic Programming crowd could only dream of actually accomplishing.
Yeah, the title is really misleading. I thought the same at first, and then I also thought that this will be a review of the actual “Hey” email client.
> The missile gap for example after all was settled and done, didn't matter at all because not a single missile was ever fired off. All that money, resources, talent, secrecy, lives lost maintaining that secrecy, lives dedicated to furthering that technology and secrecy, it just has not paid off at all for anything at all when you think about it.
It is not clear to me that the nuclear missile race "has not paid off at all for anything at all". If we lived in a perfectly rational world, then I'd absolutely agree. However, having seen how the political sausage is made in large organizations, it would not surprise me in the least if it turns out we had to go through that entire incredibly risky journey to avoid a strategic nuclear war. Sometimes leaders of large organizations make decisions only after the considerations are put into very stark terms. I wish it were different, it certainly looks to me we could have done exactly what you suggest, but I'm not made of the right political stuff to deftly maneuver even in small organizations much less be at that level in those roles, so maybe I'm just missing relevant information and perspective.
At least with a wreck there is a real risk factor you might experience yourself. What is the risk factor for ICBM based MAD? Zero. It has never happened before, to anyone. Might as well buy an insurance for alien invasion based damages to your home.
Maybe the Chevy Tahoes were priced as the initial capex, and a maintenance and support contract covering capex and opex for the next X years with a local dealership? I’ve sometimes seen this in corporate budgeting. Some companies prefer to lock in support and maintenance in advance for a more expensive fixed price instead of pay a variable but lower price over the same time period because of the budgeting vagaries that entails.
Considering the amount of time and the number of expensive management staff involved in them I’ve seen some budgeting knife fights burn up, I see the logic.
Coaching someone on why the perspective of the receiver of their behavior works counter-purpose to their intent due to <undesired-behavior-of-theirs> has so far always gotten me more durable and thoughtful behavior modifications than telling them off. I generally reserve telling off someone for proven malicious behavior from malicious intent.