Author here! Fabien's story resonated with my own founding story a lot, so took the time to share some learnings. I think it is especially relevant in our times of AI (and they didn't raise without any AI slide)
> So no, not fake, not AI, just written under the flu over the weekend.
Well, my apologies then. On the bright side you definitely have a super power when under the flu: the ability to perfectly emulate a chatbot in your writing :D
Hey there, author (Skander from Climate Drift) here.
So for the record: This isn't a chatgpt article, it's something I wrote over the weekend while I was down with a flu (although the idea has been running through my head for a while).
@America's 1930s: Most of US rural electrification happened at this point (90% of urban homes hat electricity, only around 10% of farms). Rural Electrification Act from 1936 changed that: https://en.wikipedia.org/wiki/Rural_Electrification_Act
Hey in the part 3 that introduces PAYG it jumps from $100 down $40-65 a month to $0.21 a day / $1.50 a week.
It seems your mixing up examples since they're off by an order of magnitude. Once I read that my trust in everything else started breaking down and I couldn't be bothered to read the rest with the same level of engagement.
Thanks! Maybe I'm a little too sensitive to AI signals. I actually really love the story and content, but if it was AI generated I didn't know how much to actually believe it. I still don't know who you are, but it's probably less likely to be totally fabricated if a human is responsible for it. So, thanks, I'll give it another read.
Rather than too sensitive, I think you’re making up AI signals. Poor writing (or, in this case, slightly less than perfect writing) is not a phenomenon to which humans are immune.
If you like the idea of human-written content on the Internet, I recommend against joining the chorus of voices baselessly accusing humans of being AI bots - an unfortunate trend lately which only serves to disincentivize future contributions.
just fyi when I ran this through an AI detection tool it came up with likely ChatGPT. 60% written by non-human. So either you've started really writing like an AI or you used AI for this.
It fails the sniff test and the tool test.
You also didnt correct the math mistakes the AI made.
> It worked because it solved a real problem: Kenyans were already sending money through informal networks. M-PESA just made it cheaper and safer.
Here’s why this matters: M-PESA created a payment rail with near-zero transaction costs. Which means you can economically collect tiny payments. $0.21 per day payments.
Why are you lying about this, its clearly written by an LLM
If you are a small to mid-sized team, moving to Bazel is massively painful and basically requires up to one full-time position to provide your team with a good experience.
Grog on the other hand let's you keep your existing build setup while just parallelizing and caching it. It's not a full replacement, but it's more than enough for most mid-sized teams that want to have fast mono-repo builds.
Airy is a conversational platform, built mostly for businesses: most enterprises have a variety of conversational apps and channels they support (from Facebook Messenger & Instagram for Customer Service to their own livechat for sales, etc). Airy helps these businesses bundle these channels, store the conversations and power the different usecases.
It looks like Mixin is an open source cryptocurrency wallet that also has peer to peer chat and a desktop version. So the only common points I see is that both projects are Open Source and use chat as an interface.
After four years of development, we are happy to share Airy with you.
Airy is an Open Source Conversational Platform to store, structure and utilize conversational data in a secure and privacy-compliant way.
With Airy, you can integrate with Conversational AI like Rasa to train smarter models based on actual conversations.
You can host your own open source messaging API to enable your developers to build conversational experiences even for privacy-sensitive industries, such as banking, insurance or healthcare. Airy's core platform is fully open source and runs in your own cloud or even on premise.
We built Airy on Apache Kafka for ultimate scalability, so you can ingest and stream all kinds of conversational data to:
unify your messaging channels
include human agents via an Inbox UI
gain insights from Conversational Analytics
Airy has connectors for conversational sources such as:
Facebook Messenger & Instagram
Google's Business Messages
WhatsApp Business API
SMS (via Twilio)
Airy Open Source Chat Plugin
Custom sources
i have built a similiar thing in the past, called Dialogflow Gateway (https://dialogflow.cloud.ushakov.co), which connects Dialogflow to Web and E-Mail protocols, also open-source
Hi, looks very promising. I would totally consider switching to this streamlined approach to business conversations. However, I don't see any mention of email. Email is IMHO vital for any service that wishes to 'integrate' the full company conversation stack. Do you plan on adding additional integrations?
This is a great point! Email is and will remain _the_ messaging use case for any business. I've created a ticket for adding email as a messaging source so you can track the progress: https://github.com/airyhq/airy/issues/1953
And yes we do plan on adding more sources and are therefore listening to the community to learn which are most in-demand. So thank you very much for the feedback!
Yeah, maybe the word "free" in "Free Open Source
Conversational Infrastructure with Apache 2.0 license" isn't prominent enough. ;)
For Airy Enterprise and Managed Cloud, we usually like to listen to a potential customer's use case first and come up with a custom pricing that makes sense for both sides, usually containing fixed licensing options, volume-based components or even location-based pricing which can make a lot of sense for multi-location enterprises, but rarely works for e-commerce companies.
hey artificialLimbs! Yes, a Teams integration is on the roadmap, as we plan to support all conversational channels and our data model already supports it.
We are working our way through potential channels as we speak, the Teams API was in beta until recently.