kubiton
I expressed a feeling which communicates a type of commentary.
Another comment questioned another comment in a normal way with personal touch.
There are plenty of useless comments on hn. Plenty of personal anecdotal evidence which people don't get.
If you want a pure discussion a link to sources would be a sane default
Whom to trust?
/S
Any sources?
Usb-c just fits.
Do you mean the real USB plug the bigger one? Those are dependent on my device. The USB a port on my desktop case are okay, the ones at the back of my Mainboard way to tight.
Never seen this happening. In contrary still not every team is doing code review and plenty of people regularly fix bugs in production.
One ex colleague invalidated all apple device certificates, didn't get fired.
A previous tech lead wrote code which deleted customer data and we found that a half year later, no one was fired.
And no one got fired at a code review.
And I clearly showed an example how LLM is more an interface than a answering machine.
If a LLM understands the basics of law it is by sure much better than a lot of paralegals of transforming the info into search queries for a fact database.
And I'm pretty sure there are plenty of mistakes in existing law activities
The magic is not that it can tell you thinks but that it understands you with a very high probability.
It's the perfect interface for expert systems.
It's very good in rewriting texts for me.
It's very good in telling me what a text is about.
And it's easy enough to combine a LLM with expert systems through apis.
I for example mix languages when talking to chatgpt just because it doesn't matter.
And yes it's often right enough and for GitHub copilot for example it doesn't matter at all if it's always right or only 80%.
It only has to be better than not having it and 20 bucks a month.
And yeah as you said with domain knowledge it works very well
And 70 years ago woman were not allowed to vote.
It's so common that even today you hear people defending rapists because either it wasn't rape or a family member or it would be shameful to the family to have a dirty person.
While your one sided analysis might also have some merits the past was not known at all to be full of facets.
This is an achievement of modern times thanks to more global and faster communication through the internet and also denser population.
And yes it is a real problem when everyone has a smartphone and uses it constantly. The answer? Time budgeting build into our phones.
Works very well when using a vector db and apis as you can easily send context/rbac stuff to it.
I mentioned it before but I'm not impressed that much from LLM as a form of knowledge database but much more as an interface.
The term os was used here a few days back and I like that too.
I actually used chatgpt just an hour ago and interesting enough it converted my query into a bing search and responded coherent with the right information.
This worked tremendously well, I'm not even sure why it did this. I asked specifically about an open source project and prev it just knew the API spec and docs.
But I feel well entertained watching them fall. Like using them and experimenting around.
But it also shows the road ahead quite clear. For example were is the money coming from? From millions of people paying for GitHub copilot for example.
How is it sold? Per webui, API and cloud providers.
Digital twin will also play a huge role in this as a bridge between AGI <> real world.
Old material always has some use an we do live in a timeless time now.
Reusing the lid and getting inspired by it is part of humans creativity
"Generate cartoon in style of"
I also describe things and that also works quite well.
The progress on so many fields is fast.
And a ton is already available to use.
All the nerfs, most of Nvidia topics, etc.
Or all the character stuff, those things are in games and in the industry.
And even the few which show the direction make it very obvious were the road is going n the next 5-10 years.
I'm honestly surprised that you thinknhe is naive/to hyped.
Alone the Nvidia ml denoiser and real time ray tracing is basically redefining graphs. We are in the middle of all of it.
Stuff like certain architectures, reading LLM for promoting multi modal llms.
Then we have stuff like insteuctgpt, ml models for robots, lots and lots of research from Nvidia for virtual simulation and transfer to real world, digital twin is also a relevant art in agi.
Object detection is also much better and has nothing to do with llms. Segment anything from FB for example.
Whisper and sd are also not LLM.
There are a ton of puzzle peaces slowly falling in place left and right.
Would have taken me much more time to figure it out than what chatgpt did at first try.
My company also got it immediately and is rolling it out globally.
GitHub copilot is already helpful. GitHub copilot for docs (announced at GitHub next) is a game changer.
I used openai to reformulate emails and suddenly got positive feedback about my announcement emails.
I communicate with openai German and English how ever I see fit.
It's very hard NOT to see it than the other way around.
And we got so far with only one company pushing this!
There is no option for the others to alsolo out tons of money into ai.
And besides openai, ai/ml is huge in what Nvidia and others are doing with it. Texture compression, 2d and 3d generation.
What we see is also potentially something like a new operating system.
And it makes it so much more accessible.
I never had a tool like llms which are able to take a bad copy pasta of a pdf and pulling out facts from it.
Let's just take the responsibility of yourself and transfer it to some magic place called 'someone else's problem' and you get the shit we have today.
But hey your negative and simple comment could also be true who knows.
The trust issue is real, china's great firewall is real and the crack down of sec is also real.
And without anyone exchanging your bitcoins no one cares.
And I'm comparison to our fiat a ton of critical features are missing like money laundering.
Binance has let go 1000 people in summer and just again 100 in Sept.
Gold, shares etc.
I believe the criticism is correct as the current driver of crypto is either a 'i put that much money in I'm not selling until it increases again' or gambled los.
After all the miners want to get paid.
But hey binance and others struggle let's see if there is a collapse soon
And when you played around with something the next and better version is already around the next corner!
I never seen something like this :)
Not a single avg human I know even tried crypto...