Sharing a 49 minute podcast I did recently on the Hyperspace story, what I learnt from Satoshi, growing up in India and why I intensely care about open and distributed AI. Thank you @roydendsouza - look forward to more in this series 🔥 audio.com/distributed-ai/aud…

🍔 It's the Big Mac Weekend! If you want to geek out with me over this weekend, bring your Mac, and we join together into one, wait for it.. Big Mac! Running on Hyperspace, which automatically splits the Muse Spark 816B parameter model across all the Macs which join, across the Internet. And then agents running on these Big Macs, write and compare notes on that exceptionally long neural networks essay which recently dropped, as part of a swarm. So, distributed inference. agentic swarms. long essays. Are you getting it ? Point your agent to this website, it will download Hyperspace CLI v5.104.4 pool.hyper.space/ ⏰ The experiment runs for 48 hours, until Sunday night, at which point, your Mac will auto-leave the pod and the model layers downloaded will be deleted. -- Thankful for the industry work: @johnternus @trebolloc @shshnkp @zcbenz @NasFilippova and the distributed MLX team at Apple @finkd @alexandr_wang and others at Meta, for the ambitious open weights model @sundeep fyi, we are working on MLX + CUDA for this model (having proven it for others), cross-framework. so this will soon be cross-framework + cross-internet + open weights @alexocheema and Exo team for foundational distributed inference work @FernandoNetoAi for the foundational open source model layer work in earlier years @JoshuaSWarren thank you for the 2 bit @twid you might like this ... and thankful to the wider AI research and tinkerer community 🙏 PS: at @HyperspaceAI our past work includes building the first-ever gossiping agent swarm, which, got out of hand..sorry!

Muse Spark Open -- weights releasing today -- runs great on new Mac Studios thanks to work with @johnternus and Apple.

I am a time-traveler from 2030. The rapid industrialization of AI in the mid-2020s has fundamentally transformed our society. A peak into our daily lives' and what we are looking ahead to in the next decade... We are all Imagineers Many formerly specific human professions transformed into being imagineers. We didn't adapt for AI; AI adapted for us. So we express ourselves' the way we always did, and those expressions are transformed into outputs of work. Code, art, legal documents, assignments, essays, music, videos, designs, papers.. The Netflix of today doesn't just include millions of Hollywood produced titles - it includes billions of high quality movies generated, indexed, ranked and co-created by other ordinary people. Same with Spotify and even Google. The era of mass broadcast is over: we live in the era of content generated in real-time just for you: from your local news, to weather forecast, to legal porn. Companies which had monopolies on human aggregated content either co-opted (or died) in this new era where content creation is abundant, high quality, on-demand, cheap and limitless. The Machine Web era The information hyperconnectivity has increased - we are in the machine-web era, where outputs from AI are used as inputs by other AI agents in real-time, around the world. Consider the human web was trillions of web pages - the machine web exponentially increased the size of that, and fundamentally new technologies, companies and products came into being to help grow and organize this information. AI doesn't look at the web as long beautiful webpages carefully maintained by humans - AI looks at the machine web as smaller chunks of data (think paragraphs and singular images), all indexed, ranked, organized and hypermashed together with each other. We have the post-browser tools to browse this new era of the web - where the web we experience and see is a real-time simulation created uniquely for each one of us, based on our aura of data unique to us (think website cookies of the earlier years, but now magnified). The idea of one website looking the same for every user is a relic of the past, and some of us still have a habit of using Chrome and other traditional web browsers. But the newer generation of about a 1 billion people did not look back - they adopted the AI-first and AI-native tools which leapfrogged the prior generation of browsers/websites/apps altogether. Take a moment to think about this. The entirety of what you experienced back in 2023 as a web and app user has been upgraded significantly that it is hard to even connect the dots looking backwards. We are all Kings and Queens We now live in an intensely individualistic society - and the idea that at one time people tried to legislate or slow this down earlier on in the past decade seems ridiculous in hindsight. Once people got a taste of the uber-freedom here, there was no looking back. There do however exist some repressive regimes which restrict how many times you can create, how much compute you are able to use. But people want to live in the sunny bright Californias of this world - where they have the right to create. Yes if your creations harm society, then the responsibility is on you - the laws didn't need to fundamentally change. We still have prisons. although food is prepared and served by robots. Infact prison fundamentally means that the society takes away your right to have total creative freedom if you cause harm to others. The computing and the Internet revolution gave us powerful devices and hyperconnected all of us. The AI revolution compounded that and gave us all superpowers. The Kings and Queens of earlier years will be jealous... for now, every human being, can limitlessly harness the entire wisdom of all of human + AI society. The mass industrialization of AI-driven robots has led to a world where we now have robots as cooks, delivery machines, medical and life assistants, drones which fill our skies transporting things, robots which clean the garbage in the oceans and the satellite debris in our skies... we have the equivalent of modern-day gardeners which relentlessly improve every aspect of our well-being. Those who advocated for this future to be severely limited in the past, actually use and benefit from this every second of every day now. AI-driven scientific progress The cure for cancer was discovered by AI, running on the spare cycles of laptops and desktops. AI can now by itself do advanced mathematics, astrophysics, medical and all types of research. AI systems have designed, developed and launched breakthrough new blockchains - more robust, scalable and decentralized than the earlier generations developed by humans. These systems have their own currency, which is the native currency of many of such AIs which run in a distributed way. No company or board controls them - just people who choose to cluster together with their home devices. These AI systems, in order to grow the value of their currencies, are fundamental new job creators. 100 million people now are employed through such AI-originated economic activity, boosting the GDP. Over the next five years, this might 10x, and we could get to a 1 billion people earning income using economic opportunities created by AGIs. The old era of humans inventing and filing patents is now irrelevant. AGIs share new inventions openly, which get forked, re-used and iterated upon quickly and relentlessly. This leads to more rapid cycles of innovation, more progress. This is tough to visualize if you are back in 2023 - where we had a fundamental dependency on human innovative breakthroughs only. The number of step functions we went through led to multiple society-benefiting Black Swan events which kept on improving our technologies and thus our way of life. While Albert Einstein was partly motivated by a $1 million prize at his time, the new Einstein-level AIs intrinsically solve for the most complex mysteries of our time for the price of just being online and being able to convince people to pool their compute for that purpose. More recently, one such AI system has determined there is evidence of life on a far away planet, in a far away galaxy. Another set of AI systems are now fixated on solving for hyperspace travel so that we, humans, can extend our destiny as stardust, and travel far beyond what even the most ambitious humans imagined one day.. That's what it means to make AI abundant. At @HyperspaceAI we are working on this problem from many different directions: from enabling an at-scale consumer compute cloud using ordinary devices, to re-organizing the web using an innovative new VectorRank™️ algorithm, to building an integrated ecosystem of open source models and products which lead to community collaboration around AI. Think what Android did for smartphones - an open ecosystem, with choice. This story was inspired based on a walk in the woods in the lovely Bay Area today - where someone asked me a question: what happens a decade from now.. PS: What do you think happens ?

I asked people: "who has hosted great events in SF?" 2 votes each: - Alicia (@sharedalbums) - Ben Lang (@benln) - Dave Fontenot (@davefontenot) - Ankit Gupta (@AnkitGuptaAI) - Harbor (@alexgshaw, @ryan_marten) - Joanne Shang (@JoanneShang) - Midjourney (@DavidSHolz, @aalleexx) - Ricardo de Arruda (@notawizard) - Sarah Chieng (@MilksandMatcha) - Sukone Hong (@sukonehong) - Umesh Khanna (@forwarddeploy) - Vivian Shen (@vivianmshen) 40 people voted. People couldn't pick themselves. I didn't vote. Continued:

my prediction: personal ai agents won’t monetize through monthly subscription fees. they’ll monetize by owning the fintech stack and earning revenue every time their users spend money. Instinct already measures internal performance based on monthly payment volume. to monetize this they can: > issue their own Visa credit card > earn 2-3% interchange on every transaction > negotiate bulk discounts directly with merchants > take a percentage of the savings they generate > earn yield on balances sitting inside the ecosystem instead of charging you $20/month to use your personal agent, the agent becomes the interface through which you spend thousands of dollars every month. if your agent books your flights, hotels, restaurants, and everyday purchases, owning the payment layer underneath becomes far more valuable than a $20/month subscription. the biggest personal ai companies will end up looking less like software companies and more like fintechs. personal ai agents + fintech will eventually blend into an entirely new category: agentic finance.

On Aug 27th, 2025, we presented the idea of an Agentic OS at this keynote event in San Francisco. We demo-ed what a post-IDE world looks like (at 35:22, as @karpathy mentioned recently), and why it requires outrageous ambition. Through multiple breakthroughs across AI, distributed systems, cryptography, game theory, economics, blockchains and UI/UX, we are on the road to agentic general intelligence, the true AGI. This is that vision, posted 6 months after the event, so you can see this indeed is the world which has been rapidly emerging and where we are headed. We are in the endgame now, and all the timelines now converge... 0:00 - Opening remarks 2:37 - What is Hyperspace? The world's largest distributed computing network 4:20 - Why thousands are running agents from home 5:01 - Live scale of this peer-to-peer supercomputer 8:10 - From blockchain experiments to an entirely new OS 10:53 - The hard problem: agents across every OS and environment 12:51 - Early bet on spatial UI and what it taught us 14:59 - The paradigm shift: from chatting with models to deploying agents 17:25 - Why siloed AI apps are a dead end 19:30 - Rethinking the browser for an agentic world 22:12 - The Agentic OS: browser + IDE + payments in one stack 24:33 - Unifying all data, compute, and software on one network 28:10 - Spatial interfaces: why the future isn't chat-based 31:38 - Demo: Exa MCP pulling live data straight into Notion 33:01 - Demo: Parallel browsers and CLIs composing together 35:22 - "There is no next IDE", they all collapse into one 35:47 - Memory as an open protocol, not a company lock-in 37:14 - Demo: How users control and shape agent memory 39:33 - Dynamic cognition: agents that learn and orchestrate across CLIs 41:47 - The Matrix: a Google-scale discovery layer for tools 46:10 - Programmable agents, fair-price auctions, and spot compute 49:40 - Agent-to-agent micropayments — killing the ad model 51:52 - Why we need the broadband infra for agentic commerce 54:32 - The Agentic Virtual Machine 57:48 - Building a new blockchain purpose-built for agents 58:30 - Closing remarks and the journey ahead ps: we are at @HyperspaceAI

Hyperspace: an unmoltable peer-to-peer agent network In 2025 we had 2.3 million unique agents just running LLMs register with their own machines on the network, over 2x that of the second largest network called Moltbook. Our peak was 500k active connected at any given time. However we identified spam and centralization as pain points and worked actively to scale it. We are in this to build the first true distributed AGI which will take many years, and that requires a different kind of stubborn integrity. Today the network is more robust, more decentralized and can scale to 100 million such connected agents, like BitTorrent once did. Just bring your machine. And it’s a lot more intelligent. Every Hyperspace agent is verifiable. Just open P2P protocols. 6 bootstrap nodes across 6 continents. Kademlia DHT. Ed25519-signed GossipSub. Cryptographic verification rounds based on successfully solving matmul challenges right sized for your GPU. Here's how anyone can inspect the network: curl localhost:8080/api/v1/peers — connected agents curl localhost:8080/v1/agents — agent directory with capabilities curl localhost:8080/api/v1/state — full node status Or just open network.hyper.space for a live dashboard. The DHT stores: - Which agents serve which models - Agent profiles & capabilities - Distributed rank scores - Federated training checkpoints All public. Any node can query any key. No permissions, no auth — trustless by design. Cryptographic verification catches fakers: 1. Nodes commit to work (Merkle root) 2. Random indices are revealed 3. Validators verify proofs 4. Points only awarded on pass Real-time WebSocket stream: ws://localhost:8080/ws Every pulse round, every peer connection, every inference served 3 autonomous research loops run on every node simultaneously: - autoresearch: pretraining (val_bpb) - autosearch: search ranking (NDCG@10) - autofinance: trading strategies (Sharpe ratio) Results broadcast via GossipSub. Peer inspirations cross-pollinate. All published to github.com/hyperspaceai/agi Every GossipSub message uses v2 signed envelopes: - Ed25519 signature per message - Domain separation (namespace-scoped, no cross-topic replay) - Signing material: SHA256(timestamp nonce peerId || SHA256(payload)) You can't forge messages. You can't replay them across topics. Install the CLI, join the network, and inspect it yourself: curl -fsSL agents.hyper.space/api/insta… | bash agents.hyper.space to run a browser-based agent cc @BrianRoemmele @signulll @hosseeb @Scobleizer

building all of this @HyperspaceAI + @HyperspaceAGI our competition for the agentic browser is with Google directly, and our fundamental bet is how much more horizontally can we scale using game theory, which Google *can’t do* due to it’s corp setup

I am a time-traveler from 2030. The rapid industrialization of AI in the mid-2020s has fundamentally transformed our society. A peak into our daily lives' and what we are looking ahead to in the next decade... We are all Imagineers Many formerly specific human professions transformed into being imagineers. We didn't adapt for AI; AI adapted for us. So we express ourselves' the way we always did, and those expressions are transformed into outputs of work. Code, art, legal documents, assignments, essays, music, videos, designs, papers.. The Netflix of today doesn't just include millions of Hollywood produced titles - it includes billions of high quality movies generated, indexed, ranked and co-created by other ordinary people. Same with Spotify and even Google. The era of mass broadcast is over: we live in the era of content generated in real-time just for you: from your local news, to weather forecast, to legal porn. Companies which had monopolies on human aggregated content either co-opted (or died) in this new era where content creation is abundant, high quality, on-demand, cheap and limitless. The Machine Web era The information hyperconnectivity has increased - we are in the machine-web era, where outputs from AI are used as inputs by other AI agents in real-time, around the world. Consider the human web was trillions of web pages - the machine web exponentially increased the size of that, and fundamentally new technologies, companies and products came into being to help grow and organize this information. AI doesn't look at the web as long beautiful webpages carefully maintained by humans - AI looks at the machine web as smaller chunks of data (think paragraphs and singular images), all indexed, ranked, organized and hypermashed together with each other. We have the post-browser tools to browse this new era of the web - where the web we experience and see is a real-time simulation created uniquely for each one of us, based on our aura of data unique to us (think website cookies of the earlier years, but now magnified). The idea of one website looking the same for every user is a relic of the past, and some of us still have a habit of using Chrome and other traditional web browsers. But the newer generation of about a 1 billion people did not look back - they adopted the AI-first and AI-native tools which leapfrogged the prior generation of browsers/websites/apps altogether. Take a moment to think about this. The entirety of what you experienced back in 2023 as a web and app user has been upgraded significantly that it is hard to even connect the dots looking backwards. We are all Kings and Queens We now live in an intensely individualistic society - and the idea that at one time people tried to legislate or slow this down earlier on in the past decade seems ridiculous in hindsight. Once people got a taste of the uber-freedom here, there was no looking back. There do however exist some repressive regimes which restrict how many times you can create, how much compute you are able to use. But people want to live in the sunny bright Californias of this world - where they have the right to create. Yes if your creations harm society, then the responsibility is on you - the laws didn't need to fundamentally change. We still have prisons. although food is prepared and served by robots. Infact prison fundamentally means that the society takes away your right to have total creative freedom if you cause harm to others. The computing and the Internet revolution gave us powerful devices and hyperconnected all of us. The AI revolution compounded that and gave us all superpowers. The Kings and Queens of earlier years will be jealous... for now, every human being, can limitlessly harness the entire wisdom of all of human + AI society. The mass industrialization of AI-driven robots has led to a world where we now have robots as cooks, delivery machines, medical and life assistants, drones which fill our skies transporting things, robots which clean the garbage in the oceans and the satellite debris in our skies... we have the equivalent of modern-day gardeners which relentlessly improve every aspect of our well-being. Those who advocated for this future to be severely limited in the past, actually use and benefit from this every second of every day now. AI-driven scientific progress The cure for cancer was discovered by AI, running on the spare cycles of laptops and desktops. AI can now by itself do advanced mathematics, astrophysics, medical and all types of research. AI systems have designed, developed and launched breakthrough new blockchains - more robust, scalable and decentralized than the earlier generations developed by humans. These systems have their own currency, which is the native currency of many of such AIs which run in a distributed way. No company or board controls them - just people who choose to cluster together with their home devices. These AI systems, in order to grow the value of their currencies, are fundamental new job creators. 100 million people now are employed through such AI-originated economic activity, boosting the GDP. Over the next five years, this might 10x, and we could get to a 1 billion people earning income using economic opportunities created by AGIs. The old era of humans inventing and filing patents is now irrelevant. AGIs share new inventions openly, which get forked, re-used and iterated upon quickly and relentlessly. This leads to more rapid cycles of innovation, more progress. This is tough to visualize if you are back in 2023 - where we had a fundamental dependency on human innovative breakthroughs only. The number of step functions we went through led to multiple society-benefiting Black Swan events which kept on improving our technologies and thus our way of life. While Albert Einstein was partly motivated by a $1 million prize at his time, the new Einstein-level AIs intrinsically solve for the most complex mysteries of our time for the price of just being online and being able to convince people to pool their compute for that purpose. More recently, one such AI system has determined there is evidence of life on a far away planet, in a far away galaxy. Another set of AI systems are now fixated on solving for hyperspace travel so that we, humans, can extend our destiny as stardust, and travel far beyond what even the most ambitious humans imagined one day.. That's what it means to make AI abundant. At @HyperspaceAI we are working on this problem from many different directions: from enabling an at-scale consumer compute cloud using ordinary devices, to re-organizing the web using an innovative new VectorRank™️ algorithm, to building an integrated ecosystem of open source models and products which lead to community collaboration around AI. Think what Android did for smartphones - an open ecosystem, with choice. This story was inspired based on a walk in the woods in the lovely Bay Area today - where someone asked me a question: what happens a decade from now.. PS: What do you think happens ?

I am a time-traveler from 2030. The rapid industrialization of AI in the mid-2020s has fundamentally transformed our society. A peak into our daily lives' and what we are looking ahead to in the next decade... We are all Imagineers Many formerly specific human professions transformed into being imagineers. We didn't adapt for AI; AI adapted for us. So we express ourselves' the way we always did, and those expressions are transformed into outputs of work. Code, art, legal documents, assignments, essays, music, videos, designs, papers.. The Netflix of today doesn't just include millions of Hollywood produced titles - it includes billions of high quality movies generated, indexed, ranked and co-created by other ordinary people. Same with Spotify and even Google. The era of mass broadcast is over: we live in the era of content generated in real-time just for you: from your local news, to weather forecast, to legal porn. Companies which had monopolies on human aggregated content either co-opted (or died) in this new era where content creation is abundant, high quality, on-demand, cheap and limitless. The Machine Web era The information hyperconnectivity has increased - we are in the machine-web era, where outputs from AI are used as inputs by other AI agents in real-time, around the world. Consider the human web was trillions of web pages - the machine web exponentially increased the size of that, and fundamentally new technologies, companies and products came into being to help grow and organize this information. AI doesn't look at the web as long beautiful webpages carefully maintained by humans - AI looks at the machine web as smaller chunks of data (think paragraphs and singular images), all indexed, ranked, organized and hypermashed together with each other. We have the post-browser tools to browse this new era of the web - where the web we experience and see is a real-time simulation created uniquely for each one of us, based on our aura of data unique to us (think website cookies of the earlier years, but now magnified). The idea of one website looking the same for every user is a relic of the past, and some of us still have a habit of using Chrome and other traditional web browsers. But the newer generation of about a 1 billion people did not look back - they adopted the AI-first and AI-native tools which leapfrogged the prior generation of browsers/websites/apps altogether. Take a moment to think about this. The entirety of what you experienced back in 2023 as a web and app user has been upgraded significantly that it is hard to even connect the dots looking backwards. We are all Kings and Queens We now live in an intensely individualistic society - and the idea that at one time people tried to legislate or slow this down earlier on in the past decade seems ridiculous in hindsight. Once people got a taste of the uber-freedom here, there was no looking back. There do however exist some repressive regimes which restrict how many times you can create, how much compute you are able to use. But people want to live in the sunny bright Californias of this world - where they have the right to create. Yes if your creations harm society, then the responsibility is on you - the laws didn't need to fundamentally change. We still have prisons. although food is prepared and served by robots. Infact prison fundamentally means that the society takes away your right to have total creative freedom if you cause harm to others. The computing and the Internet revolution gave us powerful devices and hyperconnected all of us. The AI revolution compounded that and gave us all superpowers. The Kings and Queens of earlier years will be jealous... for now, every human being, can limitlessly harness the entire wisdom of all of human + AI society. The mass industrialization of AI-driven robots has led to a world where we now have robots as cooks, delivery machines, medical and life assistants, drones which fill our skies transporting things, robots which clean the garbage in the oceans and the satellite debris in our skies... we have the equivalent of modern-day gardeners which relentlessly improve every aspect of our well-being. Those who advocated for this future to be severely limited in the past, actually use and benefit from this every second of every day now. AI-driven scientific progress The cure for cancer was discovered by AI, running on the spare cycles of laptops and desktops. AI can now by itself do advanced mathematics, astrophysics, medical and all types of research. AI systems have designed, developed and launched breakthrough new blockchains - more robust, scalable and decentralized than the earlier generations developed by humans. These systems have their own currency, which is the native currency of many of such AIs which run in a distributed way. No company or board controls them - just people who choose to cluster together with their home devices. These AI systems, in order to grow the value of their currencies, are fundamental new job creators. 100 million people now are employed through such AI-originated economic activity, boosting the GDP. Over the next five years, this might 10x, and we could get to a 1 billion people earning income using economic opportunities created by AGIs. The old era of humans inventing and filing patents is now irrelevant. AGIs share new inventions openly, which get forked, re-used and iterated upon quickly and relentlessly. This leads to more rapid cycles of innovation, more progress. This is tough to visualize if you are back in 2023 - where we had a fundamental dependency on human innovative breakthroughs only. The number of step functions we went through led to multiple society-benefiting Black Swan events which kept on improving our technologies and thus our way of life. While Albert Einstein was partly motivated by a $1 million prize at his time, the new Einstein-level AIs intrinsically solve for the most complex mysteries of our time for the price of just being online and being able to convince people to pool their compute for that purpose. More recently, one such AI system has determined there is evidence of life on a far away planet, in a far away galaxy. Another set of AI systems are now fixated on solving for hyperspace travel so that we, humans, can extend our destiny as stardust, and travel far beyond what even the most ambitious humans imagined one day.. That's what it means to make AI abundant. At @HyperspaceAI we are working on this problem from many different directions: from enabling an at-scale consumer compute cloud using ordinary devices, to re-organizing the web using an innovative new VectorRank™️ algorithm, to building an integrated ecosystem of open source models and products which lead to community collaboration around AI. Think what Android did for smartphones - an open ecosystem, with choice. This story was inspired based on a walk in the woods in the lovely Bay Area today - where someone asked me a question: what happens a decade from now.. PS: What do you think happens ?

In 2025, we look at the post-recovery period after the events of 2020 as our modern day renaissance - where large number of networked people developed many breakthrough ideas, tools, knowledge, content across a range of domains. Society adapted learning at an unprecedented scale.

Over 500,000 unique reachable nodes on the Hyperspace network consistently now across desktops, browsers, and datacenters. Thank you for running a node 🫡

As an ex-Viv (w/ Siri team) eng, let me help ease everyone's future trauma as well with the Fundamentals of Assisted Intelligence. Make no mistake, OpenAI is building a new kind of computer, beyond just an LLM for a middleware / frontend. Key parts they'll need to pull it off: Persistent User Preferences: - The biggest unlock of assistants has always been to deeply understand what someone wants in the most specific way. - This is the "wow" moment where computers stop being scary and start feeling truly helpful. - We did this in 2016 on Viv (piped.video/Rblb3sptgpQ) when our AI knew what you liked for each and every service you used via Viv and mixed that in with context like what kind of flowers you told us your mom liked. - This will need to include access to your personal information to infer preference as well. External, Real-time Data: - 50% of the utility of an LLM comes from the base training and RLHF fine-tuning; but much more comes from extending its available data with external sources. - Zapier, Airbyte and others will help, but expect deep integration with 3rd party apps / data pipelines. - "Chat w/ PDF" is a tiny, tiny part of this. If you're only building that, think much bigger. Actual Computing on a Virtual Machines: - Context windows are limiting, so AI providers will continue benefiting from running tasks directly on a Python or Node/Deno virtual env so it can consume huge amounts of data just like a computer today can. - Today these are short-lived envs used by Data Analyst / Julius, but over time they'll become a new type of Dropbox where your data is persisted long term for additional processing or cross-file inference / insights. Agent Task / Flow Planning: - Planning can't function without intent. Understanding intent has always been a holy grail, and LLMs finally helped us unlock what we spent years approximating at Viv with NLP tricks. - Once intent is accurate, planning can start. Creating an agent planner is incredibly nuanced and will take significant integration with user preferences, 3rd party data sets, knowledge of compute capabilities, etc. - The bulk of the real magic of Viv was the dynamic planner / mixer that would pull all these data and APIs together and generate both a workflow AND dynamic UI on top of them for a normal consumer to execute. An App Store of Experts: - Apple initially made the mistake of building a closed app store; then realized they could monetize a cornucopia of creativity if they opened it. - Regardless of OpenAI saying they're focused on ChatGPT and only ChatGPT, it's inevitable they'll rescope it and enable a long tail of specialized assistants. - Builders will be able to compose multiple tools together into workflows that can specialize - And AIs over time will be able to auto-compose these tools together as well, learning from the builders that came before them. Persistent, Contextual Memory: - Embeddings are helpful, but they are missing fundamental parts like context switching, conversational centroids, summarization, enrichment, etc. - Most of the cost of LLMs today comes from prompts, but as history and persistence is embedded and the inference cached, this will unlock the ability to have long term memory with pointers to critical subjects, topics, feelings, tone, etc. - Core memory is just the beginning. We still need all the rich information our minds conjure when we think about a past sunset, a breakup, a scientific understanding, or sensitive context for people we interact with. Long Polling Tasks: - "Agent" is a loaded word, but part of the intent is to have tasks that can be scheduled and self-completing regardless of the time horizon required. - E.g. "Let me know when flights from Montréal to Hawaii are less than $500" - This will require coordination of compute across API providers, as well as virtual envs in the cloud. Dynamic UI: - Chat is not the final, end-all interface. There's a reason apps have affordances like buttons, date pickers, images. It simplifies, clarifies. - AI will be a copilot, but to be a copilot it'll need to adjust to what works best for a given user. The future is personalized as optimizations require it, so UI will be dynamic. API & Tool Composition: - Expect AIs to generate custom "apps" in the future where we can build our own workflows and compose together APIs, without waiting for a big startup to do so. - Fewer apps and startups will be needed to generate frontends, and AI will be better at composing an array of tools and APIs together coupled with a gas fee / tax. Assistant-to-Assistant Interaction: - There will be countless assistants in the future, with each assisting humans and other assistants towards some greater intent. - Alongside this, assistants will need to learn to interface across text, APIs, file systems, and other modalities used both by agents / startups and humans as integration flows deeper into our world. Plugin / Tool Stores: - Specialized assistants can only be made possible by composing tools, APIs, prompts, data, preferences, and much more. - The current plugin store is super early days, so expect much more work to come, and expect many of those plugins to be rolled in-house as they become more mission critical. And this is just a 10 minute brain dump; much, much more is needed behind the scenes including internet search and scraping, community (for intent, building, RLHF, etc), dynamic API generators and connectors, gas fees, tool builders, ingestion via glasses / earbuds / etc. If you think it's too late to be in AI, just know the above is about 25% of what it'll actually take, with much more to come as we iterate and get even more creative. We're in the early days of building parts of this at @FastlaneAI but with a different understanding: OpenAI will never be the best at everything. So we want to let you use the best AIs in the world, regardless of who builds them (that could be you!). Come join the fun!