Can you imagine how many LinkedIn thought leaders are going to be in attendance? Perhaps the greatest gathering of minds since the Manhattan Project.
Could you explain what that means - please?
Double click with us.
Strangely enough, I can work quite well without your help. I've been doing it professionally for 35 odd years. I'm "just" an engineer - no capital E - I simply studied Civil Engineering at college and ended up running an IT company and I'm quite good at IT.
What I would really like to see is really well indexed documentation written by people ie an old school search engine. Google used to do that and so did Altavista, back in the day.
I do not need or want a plethora of trite simulacra web sites dripping with AI wankery at every search term.
That’s an odd flex to roll with for someone who has long been a member of a community of technology enthusiasts, but you be you.
LLMs are tools, not religions. They don’t need to be elevated to a dogmatic level.
Do you have any suggestions for a linux-based, qt-tolerant, LLM-integrated IDE? I’d love to try one.
All of my trades are likewise threatened, but I've found various AI options to be useful augments or interesting toys. Things like having ChatGPT check if a particular game already exists, or analysing cost/effort of lining a shed with gyprock vs ply, or analysing a chicken orchard with steel or timber, or instantly culling lists of extraneous options, or summarising someone's public writings on a particular topic, name ideas in various languages. If you have an experience eye to review suggestions, it's fantastic. Or having CoPilot/similar quickly juicing up a web page - something I could do manually, but would rather save time. Or learning how to build a game in a different language.
These are very different propositions.
You probably already use various code automation tools in your work. At the lower end, Copilot is exactly that, just a bit smarter.
You write "const [getFoo, set" and it autocompletes "Foo] = useState(". Who wouldn't want that?
It's entirely within your control how far you stray into adopting code that you don't thoroughly understand or haven't thoroughly vetted.
If nothing else, use Dall-E to draw stupid pictures to make you and friends laugh. :)
I really tried and I was both impressed and horrified in equal measure. I advise people to use them but treat them like a calculator that snorts cocaine.
A calculator is a useful tool but when they start going off the rails, things can start to get nasty.
I should be more precise: After messing around with generic questions and answers, I went for VMware PowerCLI to test it out. PowerCLI is PowerShell for VMware boxes. PowerShell is very popular so loads of input. PowerCLI is VMware so lots of input too but not quite so much as PS itself.
I tried to get ChatGPT to generate a PS script to patch a VMware cluster. The result was horrific and not even close. Bear in mind that the entirety of the VMware docs for PowerCLI are public and I wrote a script myself - its not perfect but good enough.
Oh and I am dropping VMware for good in favour of Proxmox. I have been a VMware consultant for 20+ years. Oh well.
I do find that for big tasks I generally have to scaffold it a bit, lead it in the right direction.
But it's also impressive the way it can do tasks that I can't: like writing complex TypeScript. I could spend hours on certain TypeScript challenges and not actually find a workable solution. With ChatGPT I can usually either get a solution, or convince myself it's not going to happen, within 5-10 minutes.
Indices are, by definition, lossy representations of their underlying data. If you use stemming and lemmatization to preprocess both documentation and query text, you're already departing from a truly hand-optimized indexing system, and choosing to have imperfect algorithms do things in a more scalable way. And indexing by embedding vectors that use LLMs to determine context are a natural extension of this, in my view. And on top of that, when you have a massive amount of candidate text to display to the user... is displaying sentence fragments one on top of the other the most optimal UX there? At a certain point, RAG becomes the answer to this question.
The problem, as you note, is that search engines and social media systems are incentivized to allow garbage content into the original set of things they index and surface, if that garbage content drives more attention to advertisements. But that's not a reason to reject the benefits that the underlying LLM technology can bring towards building good indexing on top of human-written documents. It just won't be done by the companies that used to do it.