I can't, I'm colourblind. That's why I had to drop electronics and go into software. It was a hard requirement in the UK in the mid-90s when I needed to make a choice.
To be fair though...I haven't used a through hole resistor in a long time.
Once you get down below 0603 there are not even labels on most resistors.
Yeah I learned the color codes way earlier in to my training...but it is largely irrelevant nowadays.
Also, it isn't just brown/dark red. Gold band can look like brown at times. Causes issues on 5 band resistors where the multiplier is gold. [1]
I had someone in industry with a board they were testing techs with that had one of these snuck in. I was the only one to figure it out...took me 10min. Some of the long term techs never fixed it. (I suspect one of the assemblers did it on purpose because they all knew the answer when I found it).
It's can't customise the response to the person asking the question in quite the way putting a massively expensive compute behind each user interaction.
And that is the huge problem here; it's not "search on steroids", it's "Ministry of Truth" on steroids.
I don't think that 2 is true though. It's exactly the argument we made against open source software.
Yes these models make exploits easier to exploits. Lets use a construction analogy: they've made all of the defects in our buildings easy to see. We have a choice. We either fix those defects, or we ban the tools which lets us see them.
It's clear to me what we do: we use these new tools. Then we fix the defects. Yeah sure it'll mean some work for us but at the end we're in a much much better position.
Anthropic, Open AI and Grok are arguing for hiding the defects. For making us weaker and more vulnerable. For their own profit.
Agreed, and if you look at the public information about various attacks the individual vectors are not particurarly sophisticated. The Huggingface incident for example had agents in a sandbox that was about as useful as a wet paper bag, and the attacks on remote infrastructure were basically enabled by bad sanitation. None of the techniques are novel.
These are not hard problems to fix, nor should anyone find it acceptable to have them be so prevalent. A determined human attacker could easily exploit defects like the agents found. Bad input sanitation, SSRF attacks, exploiting stupidly implemented token verification... all techniques that have been widely known for decades and there should be no excuse for publishing software that is riddled with exploits that enable the use of them.
..and they had basically 0 monitoring of it. Sure if it's a 5-person company then you can forgive them. Only these labs are massive companies who are spending $50B+ a year, it's extremely negligent.
They've also apparently deployed the best-of-the-best in Silicon Valley and this is what they deliver? Really?
One challenge is that we’re still constantly generating defects even with these tools. And you need the next gen model to spot the mistakes of the previous one. The exploits get more and more complicated and involved of course. But now:
* there’s a long tail of software that just won’t get secured or will take a very long time
* exploits have transformed from an expertise problem to a compute time search.
This is very different than any problem faced before. I’m not saying I’m convinced by the “slow down” approach, but I don’t think it’s as simple as you point out.
In the things published in public, they're using existing exploits and hitting systems which have been poorly maintained. It won't end at that, obviously, especially with humans behind the wheel.
Yet I'm convinced that we can create extremely resilient software systems. I've been involved in the entire life-cycle of one. We know how to be very defensive and it's a choice to build "cheap, crappy and disposable" software.
LLMs are turning the needle there and I think that's a good thing.
I hated the FUD when Microsoft were funnelling millions into it. Especially as I really liked their frameworks, languages and some of their operating systems and tools (Windows 2000, Windows XP, Windows 7, SQL Server, .Net, Office 2000, Office 2003 and Office 2007 were all excellent products).
Now the two AI companies born with help of Microsoft have a decent core product but have gone full FUD slop on us.
AFAIK the problem in NL is due to chronic underinvestment in the grid infrastructure since the big privatisation wave. Combined with the heavy subsidy of industry causing the issues.
Solvable but we need to be much smarter and redirect the fossil subsidies to reducing risk for grid-scale batteries and adding more grid capacity.
There's a possibility that the postal and telecoms systems did but I can't give you a counter. For everything else it has not been particularly effective; but a lot depends on what is privatised and how it's actually ran.
Water. Energy. Public transport (which is partially privatised). Healthcare has been a disaster.
Same thing for the UK but the results there were much much worse, especially the water (Brexit made it 10x worse). It was driven by the actions of the Unions in the 1970s (where they were taking the mickey) but of course went way way way too far. What was needed was to tweak the system such that the unions couldn't blackmail the Labour governments. Not to break it all up and sell it off for pennies on the dollar.
In most areas it made things worse. One could argue that the only exception are ISPs/cellular operators. But for public transport, healthcare, energy, etc. I can't say it was an improvement.
But yeah, we have one party that is most often in government that just loves privatisation, taxing workers more and the rich less, etc. and engages in a lot of short-term thinking. Apropos short-term thinking, one of them was a prime minister for 14 years and cut defense spending and did not even consider increasing spending when Russia invaded Crimea. And now he is the secretary general of NATO. Talking about failing upwards. Though he is probably primarily chosen for being able to communicate with Trump.
Oh that's who Mullenweg is? I had a bit of an argument with him on one of the socials, I was making the argument that Zuck has very much jumped the shark but he seemed to be a big fan.
He didn't have particularly good arguments though, given the abject failure to create anything interesting since the original Facebook site (they've been making also-ran clones before buying the competition OR going into new markets and failing since the early 2010s). He has obviously ran the core money machine ruthlessly once he won social.
The training data and knowledge is the edge, you need to build that up and maintain it. And of course mine everything you can from the American and Chinese models, like they mined everything from the internet / films / music / games etc.
Specifically we have American models which were built on extremely crappy data in insane quantities. What happens when you use same models to build a corpus of extremely high quality training data. Say for Math, coding etc. Then use that to train models. Can you get the same performance from models 10% of the size? Or 1%? Or 0.01%?
From what I've been seeing we're clearly getting to a position where models are getting "good enough" for some tasks to be really cool assistants to skilled people. And they're limited more by being extremely slow and expensive to run. What happens when they're not?
I can't see the model providers winning enough to make their valuations real.
reply