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95% of Companies See 'Zero Return' on $30B Generative AI Spend

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Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#331

Post by hinkley »

beart wrote: post #176
amluto wrote: post #130

Earlier quoted context omitted.

I’d like to see a competent AI replace the time that doctors and nurses spend tediously transcribing notes into a medical record system. More time spent doing the actual job is good for pretty much everyone.

But... that is the actual job. A clear medical history is very important, and I'm not ready yet to cut out my doctor from that process. This reminds me of the way juniors tend to think about things. That is, writing code is "the actual job" and commit messages, documentation, project tracking, code review, etc. are tedious chores that get in the way. Of course, there is no end to the complaints of legacy code bases n…

Not just juniors. Industry is full of senior and some staff engineers who see discipline as a waste of time.

The number of things I do in a day that half my coworkers see as a waste of time until they enjoy the outcomes is basically uncountable at this point.

If something is a “waste of time” it’s possible that you’re just lousy at it.

Self reflection is a rarer commodity than it should be. And most of the tasks you list either require or invite it.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#332

Post by hinkley »

wl wrote: post #281
beart wrote: post #176

Earlier quoted context omitted.

But... that is the actual job. A clear medical history is very important, and I'm not ready yet to cut out my doctor from that process. This reminds me of the way juniors tend to think about things. That is, writing code is "the actual job" and commit messages, documentation, project tracking, code review, etc. are tedious chores that get in the way. Of course, there is no end to the complaints of legacy code bases n…

Charting is for billing. If the point were to have accurate medical records useful for facilitating diagnosis and treatment, we'd structure medical records way differently. Fishing clinically-useful bits of information out of encounter and progress notes is tedious and only done as a last resort.

I presume for malpractice suits as well.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#333

Post by Imustaskforhelp »

ssharp wrote: post #241
dsr_ wrote: post #221

Earlier quoted context omitted.

That would be awesome! But in fact, customer call centers tend not to be able to even know that you called in yesterday, three days ago and last week. This is why email-ticketing call centers are vastly superior.

I've always guessed that they are able to tell when you called/what you called about, but they simply don't give that level of information to their frontline folks.

It might be because its in their interests to do so.

It is our problem that needs fixing, so we can just wait untill either they redirect us to the right person with the right knowledge who might be one of the higher ups in the call centers. Or we just quit the call. Either way, it doesn't matter to the company.

Plus points that they don't have to teach the frontline customer service more details too and it could be easier for them to onboard new people / fire old employees. Also they would have to pay less if they require very low specifications.

man I remember the is 0.001 cent = 0.001 $ video /meme of verizon

https://www.youtube.com/watch?v=nUpZg-Ua5ao

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#334

Post by Workaccount2 »

How unfortunate would it be if people actually read the report

https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Bus...

> While only 40% of companies say they purchased an official LLM subscription, workers from over 90% of the companies we surveyed reported regular use of personal AI tools for work tasks. In fact, almost every single person used an LLM in some form for their work. In many cases, shadow AI users reported using LLMs multiples times a day every day of their weekly workload through personal tools, while their companies' official AI initiatives remained stalled in pilot phase.

Corporate initiatives are failing, but people are using LLMs like crazy at work. This story is not the bombshell it's made out to be, in fact it could even go in the other direction.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#335

Post by josefx »

Jolter wrote: post #260
dsr_ wrote: post #221

Earlier quoted context omitted.

That would be awesome! But in fact, customer call centers tend not to be able to even know that you called in yesterday, three days ago and last week. This is why email-ticketing call centers are vastly superior.

Perhaps doing this suggested auto-summarizing would be what finally solves that problem?

Is doing that going to be cheaper than not doing it?

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#336

Post by zzzeek »

frozenport wrote: post #38
JCM9 wrote: post #16

We are entering the “Trough of disillusionment.” These hype cycles are very predictable. GPT-5 being panned as a disappointment after endless hype may go down as GenAI’s “jump the shark” moment. It’s all fun and games until the bean counters start asking for evidence of return on investment. GenAI folks better buckle up. Bumps ahead. The smart folks are already quietly preparing for a shift to ride the next hype wave…

Yo what’s the next hype cycle that smart folks like us should be working on?

mRNA was set to be huge but US voters apparently didnt want it.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#337

Post by adrr »

doorhammer wrote: post #205
dsr_ wrote: post #86

Earlier quoted context omitted.

Pro-tip: don't write the summary at all until you need it for evidence. Store the call audio at 24Kb/s Opus - that's 180KB per minute. After a year or whatever, delete the oldest audio. There, I've saved you more millions.

Sentiment analysis, nuanced categorization by issue, detecting new issues, tracking trends, etc, are the bread and butter of any data team at a f500 call center. I'm not going to say every project born out of that data makes good business sense (big enough companies have fluff everywhere), but ime anyway, projects grounded to that kind of data are typically some of the most straight-forward to concretely tie to a dol…

Those have been done for 10+ years. We were running sentiment analysis on email support to determine prioritization back in 2013. Also ran bayesian categorization to offer support reps quick responses/actions. Don't need expensive LLMs it.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#338

Post by hinkley »

ghalvatzakis wrote: post #228
the_snooze wrote: post #189

Earlier quoted context omitted.

I'm under the impression that one of the most critical responsibilities a lead has is to establish and maintain a good working culture. Properly vetting new additions feeds directly into that. Why offload it to AI?

Just to clarify, these aren’t interviews for job positions

Clear as mud.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#339

Post by [deleted] »

pipo234 wrote: post #259
FirmwareBurner wrote: post #239

Earlier quoted context omitted.

>Store the call audio at 24Kb/s Opus - that's 180KB per minute Why OPUS though? There's dedicated audio codecs in the VoiP/telecom industry that are specifically designed for the best size/quality for voice call encoding.

Opus is one of those codecs. Older codecs like g711 have better latency and steady bitrate, but they compress terribly. (Essentially just bandwidth and amplitude remapping). Opus is great for a lot of things and realtime speech over sip or webrtc is just one.

[deleted]

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#340

Post by shortrounddev2 »

doorhammer wrote: post #310
la_fayette wrote: post #276

Earlier quoted context omitted.

Yes that sound like important and useful use cases. However, these are solved by boring old school ML models since years...

So, I wouldn't be surprised if someone in charge of a QA/ops department chose LLMs over similarly effective existing ML models in part because the AI hype is hitting so hard right now. Two things _would_ surprise me, though: - That they'd integrate it into any meaningful process without having done actual analysis of the LLM based perf vs their existing tech - That they'd integrate the LLM into a core process their d…

My company gets a bunch of product listings from our clients and we try to group them together (so that if you search for a product name you can see all the retailers who are selling that product). Since there arent reliable UPCs for the kinds of products we work with, we need to generate embeddings (vectors) for the products by their name/brand/category and do a nearest-neighbor search. This problem has many many many "old school" ML solutions to it, and when i was asked to design this system I came up with a few implementations and proposed them.

Instead of doing any of those (we have the infrastructure to do it) we are paying OpenAI for their embeddings APIs. Perhaps openAI is just doing old school ML under the hood but there is definitely an instinct among product managers to reach for shiny tools from shiny companies instead of considering more conservative options

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