121–130 of 247 posts
Earlier quoted context omitted.
No, I'm not offering legal advice, and neither am I stating an opinion. I'm simply quoting Ofcom, the regulatory body responsible for overseeing this law.
> I'm simply quoting Ofcom no, you are doing more than that. you are saying that everyone who has a different interpretation of the parts you are quoting is misinformed. that is an opinion, which you are stating as fact, as someone unaffected by the outcome.
My point is simply that the Ofcom quote clearly states that user comments on an article are not subject to the Online Safety Act. I assume this is a fact, as it's from the horse's mouth.
Some people appear to be basing their opinions on the assumption that the OSA does apply to such comments (hence my use of the offending word).
Everyday I sit down to build a product for my clients. I am a one man shop _now_. Before I had people helping me. My mental state is not good. A very odd thing happens when claude or codex complete code fast, I begin to think of all the other things that are needed to make AI Agent work better. I begin to worry about problems that other people use to help me with and think "Can I do those too?". Problems like product…
you can always course-correct and find your sweeter spot.
What I do feel the issue is with I just having to do everything to keep costs down because hiring another dev vs doing it with AI consideration is real and it has collateral damage: I spend more time trying to build AI agents to do the work and there is 1 or 2 fewer jobs I create.
Another interesting one from 'aphyr -- I think the points around the Ironies of Automation deserve deeper focus, possibly even a separate follow-up post. I would encourage folks to look at the following industries: nuclear safety, commercial aviation, remote surgery. These industries have dealt with the issues of automation for much longer than we have as programmers. In the research I've done, these industries went…
Thank you for this! I really wanted to go deeper on human factors, and I think there's a lot to be said about CRM and sociotechnical systems design, especially when ML gets used for decision support. Ultimately wound up truncating that section (along with more of the economic critique) because the piece was already far too long.
I can only guess as to how much content you would have to explore on that axis.
I recently discovered an example of this phenomenon in a completely unrelated area: navigation. About a week ago, I realized that I couldn't remember the exact turns to reach a certain place I started driving to recently, even after having driven there about 3-4 times over a period of a month. Each time I had used Google Maps. When I used to drive pre-Google-Maps, I would typically develop a good spatial model of a route on my third drive. This skill seems to have atrophied now. Even when I explicitly decide to drive without Google Maps, and make mental notes of the turns, my retention of new routes is now much weaker than it used to be. Thankfully, routes I retained before becoming Google Maps dependent, are still there.
The interesting question to me at the moment is whether we are still at the bottom of an exponential takeoff or nearing the top of a sigmoid curve. You can find evidence for both. LLMs probably can't get another 10 times better. But then, almost literally at any minute, someone could come up with a new architecture that can be 10 times better with the same or fewer resources. LLMs strike me as still leaving a lot on…
However if we throw enough money and smart people at the problems and get enough value from the early sigmoid curves, the effective impact of a large number of stacked sigmoids could theoretically average to a linear impact, but if the sigmoids stay of a similar magnitude (on average) and appear at a higher velocity over time, you end up with an exponential made up of sigmoids*
* To be fair, it has been so long since I have done math that this may be completely incorrect mathematically - I'm not sure how to model it. However I think in practice more and more sigmoids coming faster and faster with a similar median amplitude is gonna feel very fast to humans very soon - whether or not it's a true exponential.
I'm honestly having a very hard time thinking through the likely implications of what's currently happening over the next 2-10 years. Anyone who has the answers, please do share. I'm assuming from Cynafin that it's a peturbated complex adaptive system so I can just OODA or experiment, sense and respond to what happens - not what I think might happen.
Earlier quoted context omitted.
What is the collateral damage? In ensuring that a bunch of endpoints use the same structure using LLMs?
Let's not debate that it's possible to make very large very safe changes. It is possible that you did that. This is about "slop bias". I'd wager that empowering everyone, especially power-positions to ship 50x more code will produce more code that is slop than not. You strongly oppose this because it's possible for you to update an API? I'm stuck on the power-position thing because I'm living it. I'm pro-AI but there…
I think this is the idea you need to entertain / ponder more on.
I largely agree with you, what I don't agree with is the weighting about the individual elements.
My point was that I could do a 30 minutes cleanup in order to streamline hundreds of endpoints. Without AI I would not have been able to justify this migration due to business reasons.
We get to move faster, also because we can shorten deprication tails and generally keep code bases more fit more easily.
In particular, we have dropped the external backoffice tool, so we have a single mono repo.
An Ai does tasks all the way from the infrastructure (setting policies to resources) and all the way to the frontends.
Equally, if resources are not addressed in our codebase, we know at a 100% it is not in use, and can be cleaned up.
Unused code audits are being done on a weekly schedule. Like our sec audits, robustness audits, etc.
The interesting question to me at the moment is whether we are still at the bottom of an exponential takeoff or nearing the top of a sigmoid curve. You can find evidence for both. LLMs probably can't get another 10 times better. But then, almost literally at any minute, someone could come up with a new architecture that can be 10 times better with the same or fewer resources. LLMs strike me as still leaving a lot on…
The interesting question to me at the moment is whether we are still at the bottom of an exponential takeoff or nearing the top of a sigmoid curve. You can find evidence for both. LLMs probably can't get another 10 times better. But then, almost literally at any minute, someone could come up with a new architecture that can be 10 times better with the same or fewer resources. LLMs strike me as still leaving a lot on…
We aren’t anywhere near AGI. They’ve consumed the entirety of human knowledge and poisoned the well, and it still can’t help but tell you to walk to the car wash. A peasant villager was sentient without a single book, film or song. You don’t need this much data to be sentient. They’re using a stupid method, and a better one will be discovered some day.