I have been struggling with the same thing. Reading the other comments make me agree with you even more. The best I can come up with is two fold. First that humans will have jobs verifying the verifiers. That is, for important initiatives where something must be right, agents can be doing most if not all of the work, but it will still be a human’s job to investigate what was done and sign off on it. The second is that humans will still have to make agreements with other humans for resources, capital, and the like. Somethings will be scarce, others will become scarce. And humans will always own scarce things that other humans will need to use - and they won’t be making deals with machines.
Another frame I’ve heard is that people will only trust humans when it comes to their kids, health, and money. That’s the simpler view.
There is a comment in the intro of that book about the pinnacle of human labor being the simulation of consciousness. Very prescient for being written in the 60s.
Completely agree. All of the pieces are there and it's just waiting to be acted upon. I haven't seen any of the major players really doubling down on this, but would be so compelling.
I’ve felt the same way. It’s so inefficient to have two patterns - OLAP and OLTP - both using SQL interfaces but requiring syncing between systems. There are some physical limits at play though. OLAP will always take less processing and disk usage if the data it needs is all right next to each other (columnar storage) where as OLTP’s need for fast writes usually means row based storage is more efficient. I think the solution would be one system that stores data consistently both ways and knows when to use which method for a given query.
Have there been any updates to Claude 3.5 Sonnet pricing? I can't find that anywhere even though Claude 3.7 Sonnet is now at the same price point. I could use 3.5 for a lot more if it's cheaper.
One thing I have not seen commented on is that ARC-AGI is a visual benchmark but LLMs are primarily text. For instance when I see one of the ARC-AGI puzzles, I have a visual representation in my brain and apply some sort of visual reasoning solve it. I can "see" in my mind's eye the solution to the puzzle. If I didn't have that capability, I don't think I could reason through words how to go about solving it - it would certainly be much more difficult.
I hypothesize that something similar is going on here. OpenAI has not published (or I have not seen) the number of reasoning tokens it took to solve these - we do know that each tasks was thoussands of dollars. If "a picture is worth a thousand words", could we make AI systems that can reason visually with much better performance?
I think this is a key argument in how powerful AI can become. We may be able to create incredibly intelligent systems, but at the end of the day you can’t send a computer to jail. That inherently limits the power that will be given over to AI. If an AI accidentally kills a person, the worst that could be done to it is that it is turned off, whereas the owners of the AI would be held liable.
When steam and coal engines gave way to gas and electric engines in factories, it took decades before factories were reconfigured to adjust to the smaller sized engines that didn't require one major axle running through the entire factory. As a consequence the first gas engines were huge - over time they shrunk. I bet the same will happen with robotics, where humanoid will be the primary form factor at first for general tasks, then more efficient forms will emerge as processes are updated.
I wouldn't be surprised if the slowest part of the system is the API call to a legacy warehouse management system that takes several seconds to respond to get the next bin to target.
I've felt this way and have started celebrating inputs - the work involved in building something - rather than outputs (the sale, the deployment, etc.). Once it closes or the deployment is successful it's always onto the next thing immediately and there's no time to sit back and reflect on the hard work and enjoy the time spent with others in the process.
I think the compelling difference is truthfulness. There are certain people / organizations that I trust their synthesis of information. For LLMs, I can either use what they give me in low impact situations or I have to filter the output with what I know as true or can test.
After a recent 3 week driving trip through Europe, I can anecdotally back this up. It’s not even the manual transmission, but also the much smaller roads with no shoulder where at times you meet a car, have to slam on the brakes, and decide in the moment whether you or the other car will back up to a turn out. You have to pay constant attention and there’s little room for looking at phones, eating, etc. In the US we have such large roads and shoulders that you can zone out and are more easily tempted to take your eyes off the road.
Agreed. The same data privacy argument was used by people not wanting their data in the cloud. When an LLM provider is trusted with a company’s data, the argument will no longer be valid.
I think this is where it's going. Particular Mastodon servers will provide certain guarantees to their users and about their users. It's easy to envision a white-glove server + service that provides user screening, phone support, etc. at a price. Over time when certain celebrities join it becomes the popular server and sought after as a username destination.
I agree that taxation is part of money’s value, and there are also other factors. If money is backed by a commodity (i.e. gold) then part of its value comes from the value of the commodity.
For fiat currencies where new money is mostly created as debt, the common refrain is that its value is based on common trust. I think it’s more than that. Debt is an obligation between two entities regarding future outcomes - namely, the repayment of the loan plus interest. When looked at this way the value of money comes from humanities ability to affect future outcomes. If I take out a mortgage, the bank trusts me to repay based on evidence I’ve demonstrated, and I trust the bank due to the bank’s reputation, the laws that govern banking, etc.
I am not an economist and wouldn’t be surprised if these concepts are already in some theory I’m not aware of. I do think that the sentiment that money created out of nothing is not really correct - rather it’s money created out of expected future value.
I know nothing about optics. What is the effect that causes the 6 or 8 points of light of come off of bright objects? Does it have to do with the hex-shaped mirrors on JWT?
I’d like to understand more about the perception that the Economist is a liberal publication. I’ve heard this before and it’s hard for me to reconcile this view with the articles I read. In my opinion, the economist more often than not errs on the side of being comprehensive and including facts that may or may not be relevant. Some of those facts may point to liberal conclusions, sometimes not.
I also know that they’ve taken a strong conservative stance on gender-specific sports. If they were “unabashedly biased” that would not fly.
A couple of months ago I stopped checking the news except for once a week, and found weekly news summaries from the Economist to be extremely helpful. I found that I was more relaxed during the week, more contemplative about the events of the world, and had stronger reactions to things that occurred because I didn’t feel bombarded by so much information.
I am teaching my 10 year old Python using Nano, and he’s picked it up surprisingly quickly. When I wanted him to upgrade to VS Code, he preferred the terminal! Nano’s a great product, thanks for the hard work on it all.
Another frame I’ve heard is that people will only trust humans when it comes to their kids, health, and money. That’s the simpler view.