- cross-posted to:
- technology@lemmy.ml
- cross-posted to:
- technology@lemmy.ml
The new global study, in partnership with The Upwork Research Institute, interviewed 2,500 global C-suite executives, full-time employees and freelancers. Results show that the optimistic expectations about AI’s impact are not aligning with the reality faced by many employees. The study identifies a disconnect between the high expectations of managers and the actual experiences of employees using AI.
Despite 96% of C-suite executives expecting AI to boost productivity, the study reveals that, 77% of employees using AI say it has added to their workload and created challenges in achieving the expected productivity gains. Not only is AI increasing the workloads of full-time employees, it’s hampering productivity and contributing to employee burnout.
I have the opposite problem. Gen A.I. has tripled my productivity, but the C-suite here is barely catching up to 2005.
Have you tripled your billing/salary? Stop being a scab lol
The opposite, actually.
Cool too
What do you do, just out of interest?
Soup to nuts video production.
Sounds like a very specific fetish
I don’t know what that is. What is it?
“Soup to nuts” just means I am responsible for the entirety of the process, from pre-production to post-production. Sometimes that’s like a dozen roles. Sometimes it’s me.
OK. Where on earth does that phrase come from? Makes no logical sense!
It comes from when a full course dinner would always begin with soup and end with nuts.
Same, I’ve automated alot of my tasks with AI. No way 77% is “hampered” by it.
I dunno, mishandling of AI can be worse than avoiding it entirely. There’s a middle manager here that runs everything her direct-report copywriter sends through ChatGPT, then sends the response back as a revision. She doesn’t add any context to the prompt, say who the audience is, or use the custom GPT that I made and shared. That copywriter is definitely hampered, but it’s not by AI, really, just run-of-the-mill manager PEBKAC.
I’m infuriated on their behalf.
E-fucking-xactly. I hate reading long winded bullshit AI stories with a passion. Drivel all of it.
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What have you actually replaced/automated with AI?
Voiceover recording, noise reduction, rotoscoping, motion tracking, matte painting, transcription - and there’s a clear path forward to automate rough cuts and integrate all that with digital asset management. I used to do all of those things manually/practically.
e: I imagine the downvotes coming from the same people that 20 years ago told me digital video would never match the artistry of film.
They’re right IMO. Practical effects still look and age better than (IMO very obvious) digital effects. Oh and digital deaging IMO looks like crap.
But, this will always remain an opinion battle anyway, because quantifying “artistry” is in and of itself a fool’s errand.
Digital video, not digital effects - I mean the guys I went to film school with that refused to touch digital videography.
All the models I’ve used that do TTS/RVC and rotoscoping have definitely not produced professional results.
What are you using? Cause if you’re a professional, and this is your experience, I’d think you’d want to ask me what I’m using.
Coqui for TTS, RVC UI for matching the TTS to the actor’s intonation, and DWPose -> controlnet applied to SDXL for rotoscoping
Full open source, nice! I respect the effort that went into that implementation. I pretty much exclusively use 11 Labs for TTS/RVC, turn up the style, turn down the stability, generate a few, and pick the best. I do find that longer generations tend to lose the thread, so it’s better to batch smaller script segments.
Unless I misunderstand ya, your controlnet setup is for what would be rigging and animation rather than roto. I do agree that while I enjoy the outputs of pretty much all the automated animators, they’re not ready for prime time yet. Although I’m about to dive into KREA’s new key framing feature and see if that’s any better for that use case.
I was never able to get appreciably better results from 11 labs than using some (minorly) trained RVC model :/ The long scripts problem is something pretty much any text-to-something model suffers from. The longer the context the lower the cohesion ends up.
I do rotoscoping with SDXL i2i and controlnet posing together. Without I found it tends to smear. Do you just do image2image?
A lot of people are keen to hear that AI is bad, though, so the clicks go through on articles like this anyway.
This may come as a shock to you, but the vast majority of the world does not work in tech.
I’m not working in tech either. Everyone relying on a computer can use this.
Also, medicin and radiology are two areas that will benefit from this - especially the patients.