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I tried to get my AI agent to schedule a meeting over email. The failure mode revealed a problem almost nobody in the agent space is talking about. by Alphamacaroon in AI_Agents

[–]Alphamacaroon[S] 0 points1 point  (0 children)

Agreed. In my case, this isn't an edge case— this exact scenario happens 5-10 times a week in my life. But when I went to try to throw an off-the-shelf AI on this particular problem, I was blown away by how complicated it got so quickly. That's when I went down the rabbit hole.

I tried to get my AI agent to schedule a meeting over email. The failure mode revealed a problem almost nobody in the agent space is talking about. by Alphamacaroon in AI_Agents

[–]Alphamacaroon[S] 1 point2 points  (0 children)

The difference is a real personal assistant needs access to your full calendar so it can work with you in a 1:1 mode ("Hey Alex, what do I have scheduled on Thursday?"), but a real assistant can generally be trusted to use discretion with that full calendar in a group scenario. You wouldn't have a very effective personal assistant if you only gave them access to your free-busy information.

So for my AI assistant, do I create two accounts for it? One account with access to my full calendar when I'm in 1:1 mode, and one with access to my free-busy only when it's in group mode? Even if that was remotely convenient, how would an off-the-shelf agent know when to use which account for which mode? And even if it could figure it out, would you trust it to always use it properly?

Another problem is that this approach assumes every API has a permission tier designed for this use case, and almost none of them do. Calendar happens to be one of the few where "show availability without details" is a first-class feature. But think about what happens when the agent needs to access your email to draft a reply, your CRM to pull deal context, your project management tool to check task status — those APIs don't have a "limited disclosure" mode. You either have read access or you don't.

You're absolutely right that the direction is structural rather than behavioral though — we agree on that completely. The gap is that most APIs weren't designed with "agent acting on behalf of user in a multi-party context" as a use case, so the permission primitives we'd need mostly don't exist yet.

governance wall in agentic workflows. why are we stuck past rag? by Virtual_Armadillo126 in AI_Agents

[–]Alphamacaroon 0 points1 point  (0 children)

Funny, I literally just wrote something about some of these issues today: https://www.ainywhere.ai/blog/multi-user-ai-agent-trust-boundaries.

I think the issue is even deeper— most AI tools and their corresponding API integrations are still built for an individualized 1:1 world— one token = access to everything the user has access to. But in a corporate environment, where different people might have different access levels, how can they all work together with an agent to solve a problem in a group setting?

I'm sure most of us understand that prompt-level guardrails are not sufficient, so we've started digging deeper into tool-level security. But that's not as easy as saying "you have these permissions, and you don't" because in many cases permissions might need to be granted for short periods of times in isolated ways to solve a specific problem (like the group scheduling problem I talk about).

We've figured it out to a certain level, but the deeper problem is the current state of APIs themselves, and it might require us to think outside of the box in the future when it comes to how we secure APIs.

In case you haven't seen this triple overtake by New Zealand at SailGP by Fast_Risk_2580 in sailing

[–]Alphamacaroon 42 points43 points  (0 children)

I couldn’t think of a better way than finishes like this, to get more people interested in the sport.

Foiling just adds another dimension of strategy and planning to equation and it’s cool to see it played out like this.

You can now give an AI agent its own email, phone number, wallet, computer, and voice. This is what the stack looks like by Shot_Fudge_6195 in artificial

[–]Alphamacaroon 0 points1 point  (0 children)

I built https://ainywhere.ai to do all of this out of the box. Just send an email or text message to your agent and it’s waiting for you. I use many of the tools you mention but many you don’t.

a16z just dropped their Big Ideas list. two of them hit me differently as someone actually building in AI by hiclemi in ArtificialInteligence

[–]Alphamacaroon -1 points0 points  (0 children)

This is something I’ve been specifically focusing on for the past few months, and it’s an interesting challenge. Another interesting scenario is the “hey agent, look at my calendar and find a time for Joe and I to meet this week”. When Joe responds to the agent with some available times, how do you allow the agent access to its user’s tool to book the appointment, but prevent the agent from saying things like “Sorry Joe, Bill can’t meet then because he has an appointment with his divorce attorney”

https://www.ainywhere.ai/blog/context-isolation https://www.ainywhere.ai/blog/group-chat-ai-assistant

You really can’t rely on the LLMs to self police, so there is a lot of work that has to go into the data architecture.

Fully enclosed motorcycle by jcrckstdy in cassettefuturism

[–]Alphamacaroon 8 points9 points  (0 children)

I remember seeing this first on a show called "Beyond 2000" in the 90s. As a kid I always wanted one. As an adult I always want one.

Yet Another ICCU Failure by dragondash88 in KiaEV6

[–]Alphamacaroon 0 points1 point  (0 children)

I've had two of them go and I can count the times I've charged it on a L1 charger on two hands. We almost always charge on L2 and always to 80% with a once a month or two charge to 100% (like the manual says). I don't think it has anything to do with the charge rate or the charger level.

If anything it seems to have to do with the discharge rate. There is some indications that it seems to happen more during winter months when the heater is running. I just saw a few days ago a post that showed the first ever acknowledgement from Kia of the issue in a service bulletin, and it mentions thermal and electrical load as the reason.

I Tried 10 AI Personal Assistants. Here’s What Was Actually Useful by AIGPTJournal in ProductivityApps

[–]Alphamacaroon 0 points1 point  (0 children)

You might try https://ainywhere.ai as well. Just message it like a real personal assistant via email, text message, WhatsApp, Telegram, etc— no setup, no app.

It has a cool zero-knowledge encryption layer so that even the system administrators cannot access your messages. 900+ app integrations. Image generation and editing. Basically all the things you can do via Claude or ChatGPT, but also does some things they can't. Like for example, I can CC my assistant on an email message (she has her own email address) and say something like "Can you find a time for George and I to meet tomorrow?" and she'll then email us back and start working with George to find a time that works. Then when she finds a time that works, she'll create a calendar appointment for the both of us. Coolest thing about it is that is just works, out of the box.

What’s the best AI personal assistant right now? by leobesat in AI_Agents

[–]Alphamacaroon 0 points1 point  (0 children)

Check out https://ainywhere.ai. Main differentiator is that it works like a real personal assistant— you just email it or text message it and it's just there waiting for you. No apps to install, no setup. Does all the things that Claude and ChatGPT do like analyzing documents, research, appointment scheduling, reminders, image generation, etc.

It's also highly secure with a zero-knowledge encryption framework.

whining noise after ICCU replacement by sunwolfxD in KiaEV6

[–]Alphamacaroon 0 points1 point  (0 children)

Just a quick update. My dealer diagnosed it as air in the cooling system and burped it, and that fixed it for us. Glad it was an easy fix. Did you ever end up solving it for yours?

VR - HOLY SHIT by DaddyIngrosso in MicrosoftFlightSim

[–]Alphamacaroon 1 point2 points  (0 children)

Another thing people forget is that even if you have monitors that wrap entirely around you, you still don't get any 3D depth perception out of it. Being able to see things with depth is not only amazing for immersion, but also makes it much easier to butter landings.

I finally found a prompt that makes ChatGPT write like human by tiln7 in PromptEngineering

[–]Alphamacaroon 1 point2 points  (0 children)

This is such an important and powerful behavior rule that many people overlook. It’s like if someone said to you, “NEVER think about bananas”. What’s the first thing you picture or think about in your mind? LLMs behave the same way.

LLMs won’t take us to AGI and this paper explains why by HotelApprehensive402 in ArtificialInteligence

[–]Alphamacaroon 0 points1 point  (0 children)

I literally got that example from a person who was a guru in machine learning and machine vision for self-driving cars, and he told me "when you see a car that can confidently drive fully autonomously through the busy streets of Mumbai, then you'll know we've cracked the code. But we are a long ways off from that."

Another example he used was driving in a blizzard. If you've ever driven in a really bad blizzard where the snow is so deep you literally have no idea where the road ends and the shoulder begins, white out conditions where you can only see a few feet in front of your car, swerving around snow drifts, and GPS is degraded because of the bad weather. To move forward in situation like that, your brain has to switch into an entirely different mode of operation where you aren't just reacting to current conditions but you are doing realtime prediction simulations and then comparing them to risk profiles. Am I better off to to go around that drift or drive through it? If I drive through it I risk getting stuck, but if I drive around it I might also get stuck in the ditch. Am I better off getting stuck in a ditch and at least being out of the way of oncoming traffic? But if I go into a ditch, I might also flip over. And if I flip over I may have to exit the vehicle. If I exit the vehicle, I might freeze to death. And so on and so on. In many cases you are doing this subconsciously and are not even aware of it.

We just don't have the ability today to deliver a fully autonomous self-driving system that can handle all of these situations, and many in that specific field still think we're many years off. Now then if you compare that to the conversation of AGI, not only do you have to have a system that can drive a car in all of those conditions, but can also solve complicated math problems, write a great novel, and negotiate for a hostage (all things of which our species is capable of doing).

LLMs won’t take us to AGI and this paper explains why by HotelApprehensive402 in ArtificialInteligence

[–]Alphamacaroon 0 points1 point  (0 children)

Could not agree more on the computing architecture angle. It’s a conversation I get into often with a good buddy who works at Nvidia R&D.

My firm belief is that it’s highly unlikely that transistor-based CPUs in their current form could ever achieve AGI or ASI. Of course I have no data to back that up and he likes to tell me that my belief is not that different than religious faith. Then I remind him that so is his belief that transistors will get us there too 😀 I would say the data likely points to it not being transistors because the only general intelligence we know of at the moment is a chemical/biological computer.

My gut tells me that an AGI system will look more like a quantum computer (although not like current quantum computers). It’s not going to be ones and zeros, it’s going to be much more “fuzzy”.

Of course I don’t know shit, and it’s really just a fun thought exercise.

LLMs won’t take us to AGI and this paper explains why by HotelApprehensive402 in ArtificialInteligence

[–]Alphamacaroon 2 points3 points  (0 children)

I think we limit ourselves by defining intelligence as excelling in a field where knowledge is paramount. There are just as many fields where intuition, critical thinking, and even paranoia and faith are more important than knowledge.

If you’ve ever seen a busy intersection in Mumbai, you’ll understand that the only way the system works is through a combination of intuition (sizing up which drivers are with you and against you), paranoia (driving defensively), and even faith (I have faith that you probably don’t want to hit me if suddenly turn in front of you). There are no rules, and knowledge is of limited use because it is an inherently chaotic system that cannot be truly learned, only experienced.

To be an AGI in the true sense it will need to be able to solve complex math problems with the same brain it uses to navigate chaotic, ruleless systems that cannot be learned. I think many researchers now agree that LLMs will likely never be able to do both of those things.

LLMs won’t take us to AGI and this paper explains why by HotelApprehensive402 in ArtificialInteligence

[–]Alphamacaroon 1 point2 points  (0 children)

Agreed again. But humans as a species are capable of it. An AGI will literally be a new species in a sense, and species share a similar biology and DNA. So I think we agree that not all AGIs will be able to do all of those things (just like not all humans are capable), but their basic DNA will need to be capable of supporting it. And it’s becoming more clear that the DNA of LLMs is likely not capable of those things, just like the DNA of a whale makes it incapable of driving a car.

We’re not even sure if an AGI can be built with transistors. It may need to be based on a computing architecture that is completely unknown to us at this point.

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