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95% of generative AI pilots at companies are failing – MIT report

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Re: 95% of generative AI pilots at companies are failing – MIT report

#161

> The data also reveals a misalignment in resource allocation. More than half of generative AI budgets are devoted to sales and marketing tools, yet MIT found the biggest ROI in back-office automation—eliminating business process outsourcing, cutting external agency costs, and streamlining operations. Makes sense. The people in charge of setting AI initiatives and policies are office people and managers who could be…

I think this is being overly complimenting to AI. I think the most obvious reason is that for almost all business use cases its not very helpful. All these initiatives have the same problem. Staff asking 'how can this actually help me,' because they can't get it to help them other than polishing emails, polishing code, and writing summaries which is not what most people's jobs are. Then you have to proofread all of t…

3D apps are particularly bad for AI. The LLMs are fantastic at web apps that produce an HTML DOM. But they suck at generating code for a 3D app that needs rendering, game logic, physics and similar stuff. All of that is much more complicated than a DOM. Plus, there is 100x the amount of training data for web apps. It is similarly harder to test 3D apps. Testing web code is glorious. You can access the UI via the DOM, execute events, and then check the DOM for success. None of that is possible in 3D, where there is just an image and a mouse, and no way to find and push a button or check the results. A few of the LLM IDEs allow you to add images, which could really help cross this gap, but most do not, and those that do are not designed to be able to detect rendering artifacts, or detect if a given object is in the right place.

Re: 95% of generative AI pilots at companies are failing – MIT report

#162

Earlier quoted context omitted.

> I, as a human, rarely have questions to ask This is an eye-opening sentence. It's quite hard to imagine how to live one's daily life with "few questions to ask." Perhaps this is a neurodivergent thing?

I always ponder how many people have a refrigerator in their home their entire life, and what percentage of them don't know how it works. I've asked several gfs, and they don't have even a hint of how it works. Guy friends do a bit better but not as well as you'd think. So yes, people live their entire lives not asking obvious questions.

I’d bet it’s 1 in 10, I doubt I would know the answer if I didn’t work in an HVAC adjacent field.

The answer is ‘vapor compression cycle’ which consists of a condenser, evaporator, compressor, and expansion valve along with some tubing and a refrigerant. The cycle is compressor -> evaporator -> expansion valve -> condenser and then the cycle repeats. The refrigerant absorbs heat in the evaporator and rejects it through the condenser.

Re: 95% of generative AI pilots at companies are failing – MIT report

#163

Earlier quoted context omitted.

Drones are expensive. Solid six figures expensive. And they are used around or on things that are even more expensive. You wouldn't want ChatGPT piloting them.

Under $50k for a Geran-2 level drone.

Much more for an oil rig platform surveillance drone. And if it crashes into something important, more expensive still.

Re: 95% of generative AI pilots at companies are failing – MIT report

#164

Nobody actually wants half the useless tools companies are coming up with because most of the solutions are not really novel. They are just wrapping an LLM. It's kinda like what I realized with the meta Ray-Bans: I can have these things on my face, they can tell me the answer to virtually any question in 10 seconds or less. But I, as a human, rarely have questions to ask. When you walk in to your local grocery store…

"Because the customer wasn't the user - it was their boss and shareholders".

Previous management fads: https://en.wikipedia.org/wiki/Management_fad

Obviously in the right contexts, these methods provided value. But they became widely misapplied, causing a lot of harm.

And the Wikipedia list is far from exhaustive.

Re: 95% of generative AI pilots at companies are failing – MIT report

#165

Earlier quoted context omitted.

I always ponder how many people have a refrigerator in their home their entire life, and what percentage of them don't know how it works. I've asked several gfs, and they don't have even a hint of how it works. Guy friends do a bit better but not as well as you'd think. So yes, people live their entire lives not asking obvious questions.

some of us have other things to do

Obviously we have infinite things to do. But we also waste a shocking about of time on random leisure and braindead nonsense. The interesting part to me is that we obviously do 'must do' and 'should do' and even 'want to do' things before we utterly waste time.

I'm just shocked that "learn how this important object in my home works" is not somewhere on either of those 3 lists.

Re: 95% of generative AI pilots at companies are failing – MIT report

#166

Earlier quoted context omitted.

I always ponder how many people have a refrigerator in their home their entire life, and what percentage of them don't know how it works. I've asked several gfs, and they don't have even a hint of how it works. Guy friends do a bit better but not as well as you'd think. So yes, people live their entire lives not asking obvious questions.

I’d bet it’s 1 in 10, I doubt I would know the answer if I didn’t work in an HVAC adjacent field. The answer is ‘vapor compression cycle’ which consists of a condenser, evaporator, compressor, and expansion valve along with some tubing and a refrigerant. The cycle is compressor -> evaporator -> expansion valve -> condenser and then the cycle repeats. The refrigerant absorbs heat in the evaporator and rejects it throu…

Correct, and that's more detailed than I'd even expect. I'd be satisfied with "I think it has something to do with the rule we learn in physics or chemistry about gasses warming up and cooling down when compressed and decompressed. So a gas gets squeezed, cooled down, and let out and it's even cooler then".

Sometimes I wonder how much more interesting school would be if it just explained how everything works instead of random concepts no one remembers apparently long enough to tie to objects in their life.

Re: 95% of generative AI pilots at companies are failing – MIT report

#167
post #98

Earlier quoted context omitted.

But do you need AI for those answers? I sometimes do the same thing, but Google/DDG/whatever works fine for most, and a niche app works for others (IDing a bird = Merlin app, for example).

Last year one of my berry bushes had browning leaves with some spots. Google search said infection, treatment plan, etc. This year I snapped a pic and sent to chat gpt. Normal end of year die off, cut the brown branches away, here is a fertilizer schedule for end of year to support new growth for the next year. ChatGPT makes gardening so much easier, and that is just one of many areas. Recipes are another, don't trus…

Exactly brother! F the F-ing haters making gardening tips and recipes is a trillion dollar industry, maybe a trillion trillions even!

Re: 95% of generative AI pilots at companies are failing – MIT report

#168

Earlier quoted context omitted.

> There is like one or two really clever uses I've seen - disappointingly, one of them was Jira. The internal jargon dictionary tool was legitimately impressive. Will it make any more money? Probably not. Sounds like Microsoft 365 Copilot at my org. Sucks at nearly everything, but it actually makes a fantastic search engine for emails, teams convos, sharepoint docs, etc. Much better that Microsoft's own global search…

My favorite copilot use is when I join a MS Teams meeting a few minutes late I can ask copilot: what have I missed? It does a fantastic job of summarizing who said what.

Isn't there another problem with an employee coming routinely late to meetings, so much that the employee could use a service to bandaid this behavior, asking for a friend

Re: 95% of generative AI pilots at companies are failing – MIT report

#169

Nobody actually wants half the useless tools companies are coming up with because most of the solutions are not really novel. They are just wrapping an LLM. It's kinda like what I realized with the meta Ray-Bans: I can have these things on my face, they can tell me the answer to virtually any question in 10 seconds or less. But I, as a human, rarely have questions to ask. When you walk in to your local grocery store…

I've tried to express a similar sentiment to people in the past - that 443rd redesign of the UI for JIRA that moves a button from one side to another. It isn't actually for you. You aren't the user of the software. The user of the software is the product manager (or equivalent role). They need to justify their current role or their next promotion.

Sadly, it takes away from my productivity when I was already used to the position of the button previously.

I do understand that sometimes things need to be redesigned. But crowing like you landed on the moon because your new phone icons now have "rounded edges with shading" or somesuch fuckery that will just slow down the rendering.. gets old and annoying really fast.

Re: 95% of generative AI pilots at companies are failing – MIT report

#170

Nobody actually wants half the useless tools companies are coming up with because most of the solutions are not really novel. They are just wrapping an LLM. It's kinda like what I realized with the meta Ray-Bans: I can have these things on my face, they can tell me the answer to virtually any question in 10 seconds or less. But I, as a human, rarely have questions to ask. When you walk in to your local grocery store…

> But I, as a human, rarely have questions to ask.

I realistically have between 10-100 questions I ask per day about things not immediately related to work. Double that if you include work based questions.

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