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GPT-4o with scheduled tasks (jawbone) is available in beta

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Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#41
post #4

I'm sure it's brilliant, but I have no idea what it's capable of. What will it do? Send me a push notification? Have an answer waiting for me when I come back to it in a while? I switched over to the "GPT4o with scheduled tasks" model and there were no UI hints as to how I might use the feature. So I asked it "what you can you follow up later on and how?" It replied "Could you clarify what specifically you’d like me…

Yep, this is a truly bad feature launch. I have no clue what this model does. Did they somehow lose their competent product people?

Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#42
post #28

Amazon had an insane number of people working on just the alarms feature in Alexa when they interviewed me for a position years ago. They had entire teams devoted to the tiniest edge case within the realm of scheduling things with Alexa. This is no doubt one of the biggest use cases in computing: getting your computer to tell you what to do at a given time.

Considering my iPhone alarm still sometimes fails to go off (it just shows the alarm screen silently), I'd be inclined to believe you.

Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#44
post #7

Earlier quoted context omitted.

So basically canibalizing Siri ?

Siri has access to a wealth of private existing and future on-device APIs to fuel context sensitive responses to queries on vendor locked devices used all day long. (Which Apple has apparently decided to just not use yet.) OpenAI doesn't, they just have a ton of funding and (up to recently) a good mass media story, and the best natural language responses. The moat around Siri is much deeper, and I don't really see an…

I think there is an argument that currently Google Gemini is best place to tie everything together. Assuming Google executes on it well.

Most people use Gmail, Docs, Google Maps, Google Calendar above Apples alternatives. Gemini could really tie them up well.

Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#45

This is going to eat software, and is the beginning of agents. The orchestrator of these tasks will come, and OpenAI will turn into a general purpose compute system, the endgame of workflow software. Soon there will be a database, and your prompts will be able to directly read and write to an openai hosted postgres instance. And your CRUD app will begin to disappear. Programming will feel pointless

Bit of advice: you might want to actually use an offering before claiming it is revolutionary.

I've got 15 years of engineering experience, worked on some of the largest distributed systems at FAANG. Its coming

Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#46

Earlier quoted context omitted.

Glad to see that the thriving 2010 market of TODO list apps will see a resurgence in the AI era.

A todo app that you can write and modify by editing a natural language prompt, and that can parse inputs from the whole web with flexibility and nuance, is not a small thing.

That also seems to not get timezones right, has a confusing search function...?

More seriously, todo apps are about productivity, not just about becoming a huge bucket of tasks. I've always found that the productivity comes from getting context out of my head and scheduled for the right time. This release appears to be more about that big bag of tasks and less about productivity. I'm all for AI in products, I think it can be powerful, but I've not had a use-case for it in my todo app.

Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#47
post #23

Earlier quoted context omitted.

Possibly, but that's going to require 100% consistent, accurate outputs (tricky as that's not the nature of LLMs). Otherwise, you'll have a lot of systems dependent on these orchestrators creating hard-to-debug mistakes up and down the pipeline. With software, you can reach a state where it does what you tell it to without having to worry if some model adjustment or API change is going to break the output. If they so…

Its inevitable. You can argue about what's possible right now, but I'm not looking at it from that angle. I think these issues will be solved with time

That belief is at odds with the mechanics of how LLMs work. It's not a question of more effort/investment/compute/whatever, it's just a reality of how the underlying systems work (non-deterministic). If you can find a way to make the context window on the scale of the human brain, you may be able to mostly mitigate this.

People want us to be at "Her" levels of AI, but we're at a far earlier stage. We can fake certain aspects of that (using TTS), but blindly trusting an AI to run everything is going to be a big mistake in the short-term. And in order for the inevitability of what you describe to take place, the predecessor(s) to that have to work in a way that doesn't scare people and businesses away.

The plowing of money and hype into the current forms of AI (not to mention the gaslighting about their ability) makes me think the real inevitability is a meltdown in the next 5-10 years which leads to AI-hesitancy on a mass scale.

Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#48

The beta is inconsistently showing (required a few refreshes to get something to show up), but my limited usage of it showed a plethora of issues: - Assumed UTC instead of EST. Corrected it and it still continued to bork - Added random time deltas to my asked times (+2, -10 min). - Couple notifications didn't go off at all - The one that did go off didn't provide a push notification. --- On top of that, only usable w…

I'd rather have buggy things now than perfect things in a year.

Worked out great for Sonos when their timers and alarms didn’t work.

Re: GPT-4o with scheduled tasks (jawbone) is available in beta

#49
post #23

Earlier quoted context omitted.

Possibly, but that's going to require 100% consistent, accurate outputs (tricky as that's not the nature of LLMs). Otherwise, you'll have a lot of systems dependent on these orchestrators creating hard-to-debug mistakes up and down the pipeline. With software, you can reach a state where it does what you tell it to without having to worry if some model adjustment or API change is going to break the output. If they so…

Its inevitable. You can argue about what's possible right now, but I'm not looking at it from that angle. I think these issues will be solved with time

They are using infinity compute and can’t do simple notifications. How will changing the architecture slightly or ingesting more data change that?
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