gamerDude

I feel like this is a cultural symptom and something many people are hoping to solve in healthcare. Basically we treat solving problems as amazing rather than preventing problems. You get rewarded if you treat a sickness instead of keeping a healthy person healthy.

This is the same thing. We need to reward things never going wrong as a society since this is pervasive.

I agree, but I think this is a skill in all parts of life. Some design has always been add, add, add. The skill to remove and simplify has always been valuable, but few do it.

In weight loss, many people take the approach of add and it doesn't work. Do what you are doing now and take this pill or run further or do more. But mostly the secret is eat less.

In design and engineering, it's often removing things instead of overcomplicating them.

In communication, it's often, remove lots of your side points and just focus on your core argument.

We may have removed a constraint that allows people to do more, but the skill has always been to choose, prioritize and remove the things that are making it worse

In a way, I think coercion is a requirement to be ethical. Ethics is determined based on what current society believes to be the right thing to do. We see that there are a variety of different cultures and ethics around the world, which would indicate that humans wouldn't just automatically follow a universal set of rules.

Thus to be ethical in your society, usually means you must follow the rules determined by a collective group of your nations ancestors or you will be shunned/jailed/harmed/etc. Which is essentially coercion. "Act this way or be punished."

To me, the opportunity may be in reading for entertainment. Maybe to expand on a side story or flesh out part of a world I want to read about.

For opinion pieces, I'd rather the human work through an opinion and read about that personal journey!

Well, they had the data around if the answer would be harmful to the students learning. AI was scored at 3.5% harmful answers and 12% of law professor answers were considered harmful.

"so... Catnip in tacos?" Excellent, but I got an error when I tried to give it 5 stars.

Seems like a business opportunity. Face to face authentication in every major city that can authenticate people when needed.

I worked for a couple of years in education and I think this sentiment is so harmful:

It's also difficult to experiment or strike out on your own as an educator when the future of the students in front of you could be negatively impacted by any mistakes made (not to mention job/test scores/etc) so most just ride the rail all the way down.

It's pervasive and makes things move so slowly. The biggest issue I have with it is that the system is so protective of doing no harm, but doing no harm to a system that is failing students is a poor decision imo. We should be more experimental if things are generally bad. Be protective of the mechanisms when we have good results, not when we have bad ones.

You need to be one side of the marketplace first. Uber started by the founders being the drivers.

That means either being the traveler and carrying things for others. Or be the demand and start shipping things this way and get some other people to carry packages for you.

Or did they hire a team of cybersecurity specialists with the vast amount of funding at their disposal? I don't think its reasonable to assume they used none of their other resources to search for something that could be a very profitable marketing campaign.

Do we know this is true? Did Anthropic release the exact prompt they used to uncover these security vulnerabilities? Or did they use it, target it like a black hat hacker would and then make a marketing campaign around how Mythos is so incredible that its unsafe to share with the public?

I got 5 out of 9 and have never used the london underground. The repeat multiple choice, a good memory, and me reading that the jubilee line makes a screech in the comments pushed me over that 50% mark!

I find it useful. It has been a big solve from a motivation perspective. Getting into bad API docs or getting started on a complex problem, it's easy to have AI go with me describing it. And the other positive is front end design. I've always hated css and it's derivatives and AI makes me now decent.

The negatives are that AI clearly loves to add code, so I do need to coach it into making nice abstractions and keeping it on track.

In response to having a community and building a brand. This is not necessarily human anymore. Most famous people are not someone you will actually meet. Plenty of people do meet them, but nowhere near the amount that composes their fans.

And we have AI generated influencers now, ex. https://www.instagram.com/imma.gram, so why wouldn't people care about an AI the same way they do about people they never meet?

I'm an LLMs are being used in workflows they don't make sense in-sayer. And while yes, I can believe that LLMs can be part of a system that actually does think, I believe that to achieve true "thinking", it would likely be a system that is more deterministic in its approach rather than probabilistic.

Especially when modeling acting with intent. The ability to measure against past results and think of new innovative approaches seems like it may come from a system that may model first and then use LLM output. Basically something that has a foundation of tools rather than an LLM using MCP. Perhaps using LLMs to generate a response that humans like to read, but not in them coming up with the answer.

Either way, yes, its possible for a thinking system to use LLMs (and potentially humans piece together sentences in a similar way), but its also possible LLMs will be cast aside and a new approach will be used to create an AGI.

So for me: even if you are an AI-yeasayer, you can still believe that they won't be a component in an AGI.

I imagine it has to do with vulnerability. When you are asking for something or sharing something, being turned down feels personal. When doing it for someone else, it's no big deal if they say no.

Legalizing it is also a total war against the suppliers in most cases (just economically instead of with guns). By legalizing, you usually replace the current suppliers with ones you like.

I think this is a real challenge for everyone. In many ways potentially we need a restart of a wikipedia like site to document all the valid and good sources. This would also hopefully include things like source bias and whether it's a primary/secondary/tertiary source.

When I'm working with new developers I always have to convince them to simplify their setup. Why are we on autoscaled, pay by the query infra when we are serving a few people. Then they complain how expensive it is. I had someone tell me that their costs were $1500/mon when they were in demo stages. I asked them why they aren't hosting on a single small server for $20. And they responded that it didn't matter because they were using free credits.

Except that those free credits will go away and you'll find yourself not wanting to do all the work to move it over when it would've been easier to do so when you just had that first monolith server up.

I think free credits and hyped up technology is to blame. So, basically a gamed onboarding process that gets people to over-engineer and spend more.

Well Waymo is coming to Denver, so it's about to get tested in some more difficult conditions.

Of course. It's a computer designed to figure out the question of life, the universe and everything to which the answer is 42.

In Poland, they have a "universal child benefit" that pays a stipend for every child you have.

They do pay for it and it is expensive, but apparently it made a large reduction in child poverty, so that's a win.

From my understanding, it also reduced women in the workforce and reduced investment in childcare infrastructure since more mothers were then taking care of children at home.

So this is possible, it just depends on what you want to incentivize.

I assume if you are applying to AI roles, you use AI to find and possibly apply for you. So, we don't even need to understand what the titles mean because AI can do it for us.

I'm tempted to use /s, but then again...

I don't think I agree. I think it's the same and there is great potential for totally new things to appear and for us to work on.

For example, one path may be: AI, Robotics, space travel all move forward in leaps and bounds.

Then there could be tons of work in creation from material things from people who didn't have the skills before and physical goods gets a huge boost. We travel through space and colonize new planets, dealing with new challenges and environments that we haven't dealt with before.

Another path: most people get rest and relaxation as the default life path, and the rest get to pursue their hobbies as much as they want since the AI and robots handle all the day to day.

Rate per person does not counter neuroelectrons hypothesis.

If you have 100 people standing around for a year, they probably have lower injuries than the same 100 people who are using heavy machinery over the course of a year. And it's not like most corporations are efficient.

SpaceX may have less redundancy in their workforce causing the injury rate to go up since more people are working more often.

Or SpaceX is overworking people in unsafe conditions and causing way more injuries.

Either way, rate per person does not negate people working vs. Not.

Now that's impressive. I've worked with and managed many humans and almost never do I get want I want back in one prompt.

Even ones with detailed specs and the human agreed to them don't come back exactly as written.

And this is exactly what this study showed too.

"Brain connectivity systematically scaled down with the amount of external support: the Brain‑only group exhibited the strongest, widest‑ranging networks, Search Engine group showed intermediate engagement, and LLM assistance elicited the weakest overall coupling."

It took me 10 tries...

Hypothetically, could this be fixed by changing the input method. For instance, I just quickly looked up how humans process imagery.

"the primary visual cortex, located at the back of the brain, receives the visual signals and processes basic visual features like edges, lines, and orientations."

So, potentially if we did a pre-processing step to get more features out beforehand we would see different results in the output.

Great points. I think the idea of this calculator could just be simply extended to specific use cases to make the statistical calculation simple and take into account additional variables. Moving being one example.