I remember sitting in the dimly lit back room of my parents’ electronics store, surrounded by seafoam green stone walls and a charcoal gray industrial carpet. In the small space reserved for all the backend work of our import/export business, two steel tanker desks - one tan and the other dark gray - were nestled into opposite corners. It also served as a quiet spot for my sisters and me to do our homework after school.
And it was during those dull, calm moments back in 1983, when a sporadic, jarring noise would often jolt us from our work. Our big, beige telex machine, with its perpetual shaking, buzzing, and humming would spit out written messages from some remote part of the world, pulling us away from the task at hand and into the thrilling tales of international dialogue.
The telex machine, with its rattling cacophony of clicks and whirs, was more than just an apparatus in the backroom of our store. Once a cutting-edge device, it enabled text-based communication over long distances using telegraph-style signaling.
It was an important precursor to modern communication technologies, automating the encoding and decoding of messages that was previously done manually. The telex machine was built upon the telegraph system, eliminating the need for human operators and allowing for instant text-based messaging that connected people and businesses across the globe - long before the internet and cell phones did.
As we transitioned into the digital age in the early 90’s, text communication became more accessible and widespread, leveraging new protocols like FTP (File Transfer Protocol) and Telnet (Telecommunication Network) - not over telegraph networks, but through the internet and early computer networks. Plain text data sent over computer networks. Brilliant. (Except they weren’t secure so they kinda faded soon enough.)
I also remember when email was all the rage when I started college in 1991. Instant communication via text sent through electronic mail on your computer. It was mind blowing. And by the time I graduated college in 1995, web browsers became a thing, and we now had a new language and protocol ushering us, nay, thrusting us into the future. People from all over the world didn’t just have to send messages to communicate, they could post their own content on a “web” page that anyone could access from anywhere. Mind-blown yet again.
It was because of the introduction of HTML (HyperText Markup Language) and HTTP (HyperText Transfer Protocol), that the internet underwent a revolutionary transformation.
Why?
Because HTML was a new markup language that, for the first time, allowed us to use tags to define structure and presentation of text and other media (images, video, etc.) on web pages, dictating how content should be displayed in a browser. We now had tags like [p] and [h1] telling the browser to display text as top level headers and indicate where paragraphs started and ended. It was revolutionary - more than just data transmission and command execution!
Meanwhile, HTTP defined how requests and responses should be formatted and transmitted between a client (like a web browser) and a server. This protocol made it possible to fetch and display web pages from remote servers, facilitating seamless communication and information sharing.
This pair of inventions led to an innovation that laid the foundation for web-based integrations and the explosion of SaaS and cloud-based services.
We find ourselves yet again, at a pivotal moment in our technological evolution. The proliferation of SaaS, cloud-based services, and now AI, is causing us to drown in a sea of applications - cluttering our desktops and our minds - forcing us to constantly search, prompt, copy/paste, and hyperlink siloed and scattered information, creating an ever-growing cognitive load.
More apps, more tools, more AI agents, more noise.
What we need - as mentioned in many of our previous posts - is not a new tool, but a new computing environment that captures context. Today, our computers store information, but the context behind that information (contextual data) - the reasons behind our actions, the connections between different pieces of data, and the people who need to be informed - resides in our minds or is lost between apps.
So, while bits and bytes have been the foundational building blocks of computing, they lack the context that enriches human communication and collaboration. Our current systems are excellent for processing large amounts of data, but they miss the nuances of subtleties that make information truly valuable.
That’s why we believe the future of generative AI and computing isn’t about just scaling existing technologies - it’s about innovation that fundamentally changes how we interact with our digital tools. We need our digital tools to carry the burden of context with us, so that our computers can help us organize our work and manage our attention, supporting us as proactive collaborators not as burdensome, glorified, digital containers of our outputs.
To propel us into this future, we need systems that understand the context in which this data exists. This is where the concept of contextual data comes into play. By incorporating context, we can create more intuitive and proactive computing environments.
And to achieve this - you guessed it - we need a new language and protocol designed to capture and process contextual data.
And that’s exactly what we at Reframe have invented - a new language and protocol called Artipoints and Artisync:
Artipoints (or articulation points) are data points enriched with contextual information, providing a deeper understanding of the data’s significance and relationships. They function like “fancy” bookmarks, pointing to content with additional attributes, the most important of which is addressability - the ability to label the bookmark with a list of people, agents, or systems interested in it. This means getting permission to see content without making copies. It’s a new type of tagging/data structure and formalized coordination language for expressing and capturing articulations as we work through the processes of sharing information, making decisions, incorporating learnings, and updating or replanning activities based on the resulting data and insights.
Imagine drafting a project plan in Reframe. An Artipoint could tag a specific taskk not only with its due data but also with the people involved, the related documents, and even the discussions that shaped it. Now, when you revisit that task, Reframe surfaces everything relevant, saving you from searching across emails, chat, and apps.
Artisync - is the protocol designed to synchronize and process Artipoints, ensuring that contextual data flows seamlessly between participants, including people, agents, and systems. Unlike traditional systems where information flows one way, Artisync enables a two-way conversation, keeping everyone and everything up-to-date in real time. This means that each instance where Reframe is running, including servers holding enterprise data for a given organization, can replicate and receive updates directly. Even agents in the cloud can access this organizational data using the Artipoint/Artisync standard, functioning as virtual users with the necessary authentication.
Reflecting on the journey from telex machines to the digital revolution sparked by HTML and HTTP, it’s clear that each leap forward has been powered by new languages and protocols. Now, as we figure out how to enter the next phase in our AI-driven digital landscape, we stand on the brink of yet another transformative era.
The introduction of Artipoints and Artisync by Reframe marks the dawn of a new era in contextual computing. Much like how bits and bytes and HTML revolutionized information processing and presentation, Artipoints and Artisync offer the potential to create truly intuitive and proactive computing environments. By capturing and processing contextual data, these innovations can reduce cognitive load, help us manage the ever-growing complexity of our digital lives, and crucially empower both human and AI agents.
Our digital tools will no longer be mere containers of our work output. Instead, they will become proactive collaborators, understanding the context behind our actions, decisions, and interactions. This shift will enable us to work smarter, make more informed decisions, and ultimately lead more productive and fulfilling lives.
The future of generative AI and computing is about embracing a new paradigm, like Artipoints and Artisync, that can capture the richness of human context and unlock the full potential of our human capacity. And Reframe is excited to lead the way!
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