Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

I've been working on a new personal operating system that's fully local, private, and amnesic by default. Complete enough to be your only computer and the entire system is lean enough to boot from a USB stick, leaving no trace on the host machine. Models run locally on the... show more

nich

21,289 subscribers

106,481 Aufrufe • vor 4 Monaten •via X (Twitter)

Wissenschaft & Technologie

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

U-Boot menu now works on Flipper One Now you can choose different kernels and systemd targets before the Linux kernel boots. * It's our LCD/buttons driver plus a slightly modified vanilla U-Boot menu. Will try to upstream it to U-Boot. * This is a temporary solution for testing the selection of different OS profiles. In the final version of Flipper OS, we’ll most likely draw the boot menu using a small program compiled into initramfs, after the kernel has started. But as a temporary solution, it works perfect. * I’m still not happy with the cold boot time: from powering on the processor to having a working menu. Here’s the boot log with timestamps, captured from the processor console: * Our patched U-Boot:

U-Boot menu now works on Flipper One Now you can choose different kernels and systemd targets before the Linux kernel boots. * It's our LCD/buttons driver plus a slightly modified vanilla U-Boot menu. Will try to upstream it to U-Boot. * This is a temporary solution for testing the selection of different OS profiles. In the final version of Flipper OS, we’ll most likely draw the boot menu using a small program compiled into initramfs, after the kernel has started. But as a temporary solution, it works perfect. * I’m still not happy with the cold boot time: from powering on the processor to having a working menu. Here’s the boot log with timestamps, captured from the processor console: * Our patched U-Boot:

Flipper R&D

33,163 Aufrufe • vor 1 Monat

Getting started with OpenClaw🦞 on umbrelOS is so simple, just one click install from the app store, enter your API key and you’re done. No need to touch the command line. A headless browser is configured out of the box so your new AI assistant can immediately interact with the entire internet.

Getting started with OpenClaw🦞 on umbrelOS is so simple, just one click install from the app store, enter your API key and you’re done. No need to touch the command line. A headless browser is configured out of the box so your new AI assistant can immediately interact with the entire internet.

Luke Childs ☂️

20,467 Aufrufe • vor 6 Monaten

Introducing Magnitude: your actually local agent 100% private and offline. No token costs, no API keys. Open source. Today's agents are local. The model isn't. Every prompt, every file, every secret gets sent straight to Anthropic and OpenAI. Magnitude is built around local models and runs the whole stack itself. The inference engine is part of the agent, so the models run inside it, right on your computer. It lives in your terminal, and setup is one command. Magnitude profiles your hardware and shows you which models fit, with the trade-offs between quality, speed, and memory. Pick one and start working. No painful config or server to babysit. Out of the box, it can use your shell, edit files, and run scripts. Add skills and it can work with Excel, PowerPoint, PDFs or Chrome. Use it for everyday work: - Analyze sensitive data - Manage private notes - Review code and logs - Search and organize files - Build docs or slides npm i -g @magnitudedev/cli GitHub:

Introducing Magnitude: your actually local agent 100% private and offline. No token costs, no API keys. Open source. Today's agents are local. The model isn't. Every prompt, every file, every secret gets sent straight to Anthropic and OpenAI. Magnitude is built around local models and runs the whole stack itself. The inference engine is part of the agent, so the models run inside it, right on your computer. It lives in your terminal, and setup is one command. Magnitude profiles your hardware and shows you which models fit, with the trade-offs between quality, speed, and memory. Pick one and start working. No painful config or server to babysit. Out of the box, it can use your shell, edit files, and run scripts. Add skills and it can work with Excel, PowerPoint, PDFs or Chrome. Use it for everyday work: - Analyze sensitive data - Manage private notes - Review code and logs - Search and organize files - Build docs or slides npm i -g @magnitudedev/cli GitHub:

Tom Greenwald

392,266 Aufrufe • vor 13 Tagen

NVIDIA JUST SHOWED HOW A $4,699 BOX CAN KILL A $200 MONTHLY AI BILL AND RUN 200B MODELS FROM YOUR DESK. 00:02 NVIDIA delivers the DGX Spark to developers, researchers, and AI teams, turning what used to require rented datacenter GPUs into a box small enough to hold in one hand. inside is 128GB of unified memory, 4TB of storage, and up to 1 PFLOP of AI compute, enough to run 70B models comfortably and push into the 200B class locally. that means no per-token API bill, no files leaving your machine, and no waiting for someone else’s server every time an agent reads documents, writes code, or runs an automation. two DGX Sparks can even be linked together for models around 400B parameters, while a single unit costs roughly $4,000 to $4,700 instead of renting multi-GPU cloud infrastructure every month. the full local AI ladder starts at $0 with the computer you already own, but NVIDIA just showed what the final rung looks like: a personal AI supercomputer sitting directly on your desk.

NVIDIA JUST SHOWED HOW A $4,699 BOX CAN KILL A $200 MONTHLY AI BILL AND RUN 200B MODELS FROM YOUR DESK. 00:02 NVIDIA delivers the DGX Spark to developers, researchers, and AI teams, turning what used to require rented datacenter GPUs into a box small enough to hold in one hand. inside is 128GB of unified memory, 4TB of storage, and up to 1 PFLOP of AI compute, enough to run 70B models comfortably and push into the 200B class locally. that means no per-token API bill, no files leaving your machine, and no waiting for someone else’s server every time an agent reads documents, writes code, or runs an automation. two DGX Sparks can even be linked together for models around 400B parameters, while a single unit costs roughly $4,000 to $4,700 instead of renting multi-GPU cloud infrastructure every month. the full local AI ladder starts at $0 with the computer you already own, but NVIDIA just showed what the final rung looks like: a personal AI supercomputer sitting directly on your desk.

Gipp 🦅

11,334 Aufrufe • vor 1 Monat

$KNX : Offline Notes. A New Primitive for Privacy. Architecture Explainer. Let us explore how offline transfers and note-based value work in KnoxNet. Instead of relying on a live network, value is converted into offline notes that exist on your device and move directly between users. Each note carries its own lineage — a verifiable history of ownership — secured through advanced encryption, enabling trustless transfers in a fully offline environment. This system is designed to operate independently at the moment of execution. No servers. No connectivity. No global state required. Watch the video to see how the world’s first offline-first cryptocurrency works. 👇

$KNX : Offline Notes. A New Primitive for Privacy. Architecture Explainer. Let us explore how offline transfers and note-based value work in KnoxNet. Instead of relying on a live network, value is converted into offline notes that exist on your device and move directly between users. Each note carries its own lineage — a verifiable history of ownership — secured through advanced encryption, enabling trustless transfers in a fully offline environment. This system is designed to operate independently at the moment of execution. No servers. No connectivity. No global state required. Watch the video to see how the world’s first offline-first cryptocurrency works. 👇

KnoxNet

21,688 Aufrufe • vor 3 Monaten

🚨BREAKING: OpenAI's Codex is now completely FREE to run locally with Ollama. No API costs. No rate limits. 100% private on your machine. You can now use both the Codex App and Codex CLI with powerful open-source models like DeepSeek V4, Gemma 4, and Qwen 3.6. Here's how to set it up in minutes:

🚨BREAKING: OpenAI's Codex is now completely FREE to run locally with Ollama. No API costs. No rate limits. 100% private on your machine. You can now use both the Codex App and Codex CLI with powerful open-source models like DeepSeek V4, Gemma 4, and Qwen 3.6. Here's how to set it up in minutes:

WorldofAI

814,600 Aufrufe • vor 2 Monaten

Introducing Solode Neo — a personal AI node designed to run and host autonomous AI agents at home or in the office, always on, and entirely under your control. Your AI runs while you sleep. Wake up to compiled research. Automated emails. Organized files. All from a simple message on Telegram or your preferred messaging app. Just plug it in, connect to Wi-Fi, and start working. No coding. No cloud. No limits. Solode Neo comes pre-configured with OpenClaw🦞 and a curated selection of LLMs. It’s built for continuous 24/7 agentic workloads, with all inference, voice processing, and data handling running locally by default. No data leaves your device unless you choose to enable it. The PC put computing on every desk. Now, Solode Neo is here to put autonomous AI in every home, office, and living space. Hardware infrastructure is just the beginning: the full stack is coming. Official pricing at US$399. Early bird pricing at US$369 for waitlist members. Be the first to bring personal AI home: #SolodeNeo #AgenticAI #DigitalInfrastructure #SOLAI $SLAI

Introducing Solode Neo — a personal AI node designed to run and host autonomous AI agents at home or in the office, always on, and entirely under your control. Your AI runs while you sleep. Wake up to compiled research. Automated emails. Organized files. All from a simple message on Telegram or your preferred messaging app. Just plug it in, connect to Wi-Fi, and start working. No coding. No cloud. No limits. Solode Neo comes pre-configured with OpenClaw🦞 and a curated selection of LLMs. It’s built for continuous 24/7 agentic workloads, with all inference, voice processing, and data handling running locally by default. No data leaves your device unless you choose to enable it. The PC put computing on every desk. Now, Solode Neo is here to put autonomous AI in every home, office, and living space. Hardware infrastructure is just the beginning: the full stack is coming. Official pricing at US$399. Early bird pricing at US$369 for waitlist members. Be the first to bring personal AI home: #SolodeNeo #AgenticAI #DigitalInfrastructure #SOLAI $SLAI

SOLAI Limited

22,407 Aufrufe • vor 4 Monaten

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

QVAC

11,382,628 Aufrufe • vor 1 Monat

We're excited to be building on Venice, the leading private AI platform, to solve the harder version of the problem: privacy you can prove. Venice is the only AI platform of its scale built private by default. Prompts are never stored, conversations never leave your device, and no third party (not Venice, not the infrastructure, not anyone) can see what you ask. Inference runs inside sealed hardware enclaves, and every response ships with cryptographic attestation that it stayed private. Cluster is the orchestration and settlement layer on top: routing sensitive workloads to Venice's verified private compute and letting autonomous agents pay per call over x402 on Base. No account, no API keys, no data trail.

We're excited to be building on Venice, the leading private AI platform, to solve the harder version of the problem: privacy you can prove. Venice is the only AI platform of its scale built private by default. Prompts are never stored, conversations never leave your device, and no third party (not Venice, not the infrastructure, not anyone) can see what you ask. Inference runs inside sealed hardware enclaves, and every response ships with cryptographic attestation that it stayed private. Cluster is the orchestration and settlement layer on top: routing sensitive workloads to Venice's verified private compute and letting autonomous agents pay per call over x402 on Base. No account, no API keys, no data trail.

Cluster Protocol

64,460 Aufrufe • vor 1 Monat

This is what AI subscription companies are afraid of. A guy with a screwdriver, a $700 pile of components, and one free weekend. They built their entire business model on you never figuring out that the same models run locally. On hardware you own. No rate limits. No data leaving the room. No invoice at the end of the month. He figured it out on a Saturday. By Sunday night six agents were online. Research, writing, QA, publishing, monitoring. All running locally for $23 a month in electricity. By the following month he had eight clients paying $2,500 each to run the same system for their businesses. $20,000 a month. Built on a PC he assembled himself in a weekend. They're still sending him renewal emails. He stopped opening them.

This is what AI subscription companies are afraid of. A guy with a screwdriver, a $700 pile of components, and one free weekend. They built their entire business model on you never figuring out that the same models run locally. On hardware you own. No rate limits. No data leaving the room. No invoice at the end of the month. He figured it out on a Saturday. By Sunday night six agents were online. Research, writing, QA, publishing, monitoring. All running locally for $23 a month in electricity. By the following month he had eight clients paying $2,500 each to run the same system for their businesses. $20,000 a month. Built on a PC he assembled himself in a weekend. They're still sending him renewal emails. He stopped opening them.

Superior

22,686 Aufrufe • vor 1 Monat

#WATCH | Mumbai, Maharashtra: On the stabbing incident at Andheri on the Churchgate–Nallasopara Fast Local (Train No. 90663), State Minister Yogesh Kadam says, “…Action will be taken accordingly against whoever attacked the passenger and has been arrested. The local train network is Mumbai's lifeline. We cannot defame the entire Mumbai local train system because of just one isolated incident, nor would it be right to question its overall safety. It is wrong to generalise about the entire network based on the mistake or the criminal actions that one individual has tried to commit…”

#WATCH | Mumbai, Maharashtra: On the stabbing incident at Andheri on the Churchgate–Nallasopara Fast Local (Train No. 90663), State Minister Yogesh Kadam says, “…Action will be taken accordingly against whoever attacked the passenger and has been arrested. The local train network is Mumbai's lifeline. We cannot defame the entire Mumbai local train system because of just one isolated incident, nor would it be right to question its overall safety. It is wrong to generalise about the entire network based on the mistake or the criminal actions that one individual has tried to commit…”

ANI

72,785 Aufrufe • vor 1 Monat

small local model that falls apart in bloated agents like openclaw just runs like a wild horse in hermes agent. and that's not even my line, someone else called it that, i've just been quietly pointing people at this harness for months because it held up on everything i threw at it, 3b models all the way to one trillion params. watch this happen on my own machine. i pointed hermes agent at a local http endpoint, gemma 4 12b on my 3090 llama.cpp server, and it auto-detected the model and started working immediately. no config wrestling, no broken tool calls, no babysitting the output format, i typed in a url and it just went. the whole clip is exactly that, start to finish, no errors, no retries, butter smooth. and the tool calling, the one thing that quietly breaks most local setups, works here like it's nothing. it's not the model that's flaky, it's the harness around it. hermes agent is the first agent i've run that actually gets that right. one url, one local model on one card, and it runs like a wild horse.

small local model that falls apart in bloated agents like openclaw just runs like a wild horse in hermes agent. and that's not even my line, someone else called it that, i've just been quietly pointing people at this harness for months because it held up on everything i threw at it, 3b models all the way to one trillion params. watch this happen on my own machine. i pointed hermes agent at a local http endpoint, gemma 4 12b on my 3090 llama.cpp server, and it auto-detected the model and started working immediately. no config wrestling, no broken tool calls, no babysitting the output format, i typed in a url and it just went. the whole clip is exactly that, start to finish, no errors, no retries, butter smooth. and the tool calling, the one thing that quietly breaks most local setups, works here like it's nothing. it's not the model that's flaky, it's the harness around it. hermes agent is the first agent i've run that actually gets that right. one url, one local model on one card, and it runs like a wild horse.

Sudo su

27,339 Aufrufe • vor 2 Monaten

Say goodbye to ElevenLabs I’ve found a way to do TEXT - TO- SPEECH completely free no subscription, no API. Here’s what I used: - GPU: RTX 4090 - VRAM: 32 GB + 18 GB extended (total ~50 GB) Voice Models: one with 1.5B parameters and another with 9.6B parameters These models handle tone, clarity, speed, adds realism, emotions, and long-form voice flow the kind you hear in audiobooks or podcasts. A 24 GB GPU isn’t enough for this setup. You need around 50 GB total memory to run models smoothly without crashing. With this setup, you can create natural, high-fidelity voices offline exactly what paid tools do behind the scenes, now running on your own system for free. I have a complete guide to set this up locally on your computer or a virtual machine. If you want this? Follow Beginnersblog Like REPOST Comment "SETUP" I will DM you the complete GUIDE..

Say goodbye to ElevenLabs I’ve found a way to do TEXT - TO- SPEECH completely free no subscription, no API. Here’s what I used: - GPU: RTX 4090 - VRAM: 32 GB + 18 GB extended (total ~50 GB) Voice Models: one with 1.5B parameters and another with 9.6B parameters These models handle tone, clarity, speed, adds realism, emotions, and long-form voice flow the kind you hear in audiobooks or podcasts. A 24 GB GPU isn’t enough for this setup. You need around 50 GB total memory to run models smoothly without crashing. With this setup, you can create natural, high-fidelity voices offline exactly what paid tools do behind the scenes, now running on your own system for free. I have a complete guide to set this up locally on your computer or a virtual machine. If you want this? Follow Beginnersblog Like REPOST Comment "SETUP" I will DM you the complete GUIDE..

Beginnersblog

130,370 Aufrufe • vor 9 Monaten

An AI agent just checked an XDC masternode's stake, status, and rewards entirely on its own. Found the API on the XDC AI (XDC AI) marketplace → hit a 402 → paid $0.002 in USDC → got the data. Settled on-chain in seconds. Gasless. No API key. No subscription. This is x402 on XDC Network. Machine-to-machine payments, working today. 🧵👇 #XDC #x402 #nanopayments #USDC

An AI agent just checked an XDC masternode's stake, status, and rewards entirely on its own. Found the API on the XDC AI (XDC AI) marketplace → hit a 402 → paid $0.002 in USDC → got the data. Settled on-chain in seconds. Gasless. No API key. No subscription. This is x402 on XDC Network. Machine-to-machine payments, working today. 🧵👇 #XDC #x402 #nanopayments #USDC

Beny

47,335 Aufrufe • vor 8 Tagen

Andrej Karpathy (co-founder of OpenAI, Eureka Labs): "The future of AI is not all in the cloud. The most important models will run locally on your hardware under your control." June 2026 is the first time that the future is actually accessible to everyone! Here is what the local LLM landscape looks like right now: → raspberry pi 5: coherent chatbot, no GPU required → macbook air: matches GPT-3.5 quality on most tasks natively → used RTX 3090 at $700: something close to GPT-4 running locally → ollama: one command to an openAI-compatible endpoint, every major toolchain integrates with it → LM studio: best GUI, native MLX acceleration on apple silicon, MCP support in 0.4.0 → llama.cpp: the engine everything else runs on, 90MB footprint, runs on raspberry pi to android → the honest case: 80% of daily work is genuinely good enough locally right now Your prompts never leave your machine. no per-token billing. no rate limits. no refusals. The playbook for every hardware tier, from Raspberry Pi to RTX 5090, is here. Bookmark it so you do not lose it! Follow NeilXbt for more local AI and open source intelligence that tracks the hardware and tooling most people discover six months late.

Andrej Karpathy (co-founder of OpenAI, Eureka Labs): "The future of AI is not all in the cloud. The most important models will run locally on your hardware under your control." June 2026 is the first time that the future is actually accessible to everyone! Here is what the local LLM landscape looks like right now: → raspberry pi 5: coherent chatbot, no GPU required → macbook air: matches GPT-3.5 quality on most tasks natively → used RTX 3090 at $700: something close to GPT-4 running locally → ollama: one command to an openAI-compatible endpoint, every major toolchain integrates with it → LM studio: best GUI, native MLX acceleration on apple silicon, MCP support in 0.4.0 → llama.cpp: the engine everything else runs on, 90MB footprint, runs on raspberry pi to android → the honest case: 80% of daily work is genuinely good enough locally right now Your prompts never leave your machine. no per-token billing. no rate limits. no refusals. The playbook for every hardware tier, from Raspberry Pi to RTX 5090, is here. Bookmark it so you do not lose it! Follow NeilXbt for more local AI and open source intelligence that tracks the hardware and tooling most people discover six months late.

NeilXbt

19,405 Aufrufe • vor 2 Monaten

✨ Personal AI is the next computing platform. AI is shifting from something you access to something you build with, locally, at the edge, and across systems. We’re unlocking new possibilities for developers: • AMD Ryzen AI Halo, a local-first developer system, preorder starting in June, develop AI without limits on your desk • Gorgon Halo with up to 192GB unified memory, supporting 300B+ parameter models locally, run massive models locally We’re excited to partner with clem 🤗🤗, Co-founder and CEO of Hugging Face, to advance open-source AI for Ryzen AI. Our focus is seamless AI, from model to deployment. Cloud, edge, device. One continuum. Multi-agent systems, local inference at scale, open models as infrastructure. This is the next computing era 🚀

✨ Personal AI is the next computing platform. AI is shifting from something you access to something you build with, locally, at the edge, and across systems. We’re unlocking new possibilities for developers: • AMD Ryzen AI Halo, a local-first developer system, preorder starting in June, develop AI without limits on your desk • Gorgon Halo with up to 192GB unified memory, supporting 300B+ parameter models locally, run massive models locally We’re excited to partner with clem 🤗🤗, Co-founder and CEO of Hugging Face, to advance open-source AI for Ryzen AI. Our focus is seamless AI, from model to deployment. Cloud, edge, device. One continuum. Multi-agent systems, local inference at scale, open models as infrastructure. This is the next computing era 🚀

Jack Huynh

49,264 Aufrufe • vor 3 Monaten

NVIDIA is creating two completely different futures In one they put AI infrastructure on your property In the other they put it on your own desk ///// OPTION 1 A box worth more than most houses gets installed outside You provide the location, power and connectivity In return, you get perks like cheaper electricity, backup power and upgraded internet while AI workloads run around the clock You're not buying the hardware You're hosting it ///// OPTION 2 You spend a few thousand dollars on a DGX Spark Small enough to sit beside your monitor Powerful enough to run serious AI models locally No cloud bill No rented GPUs No sending sensitive data somewhere else The interesting part isn't the hardware It's the shift that's happening For years, AI belonged to giant tech companies and massive data centers Now NVIDIA is pushing a world where regular people can either host the infrastructure or own a piece of it themselves

NVIDIA is creating two completely different futures In one they put AI infrastructure on your property In the other they put it on your own desk ///// OPTION 1 A box worth more than most houses gets installed outside You provide the location, power and connectivity In return, you get perks like cheaper electricity, backup power and upgraded internet while AI workloads run around the clock You're not buying the hardware You're hosting it ///// OPTION 2 You spend a few thousand dollars on a DGX Spark Small enough to sit beside your monitor Powerful enough to run serious AI models locally No cloud bill No rented GPUs No sending sensitive data somewhere else The interesting part isn't the hardware It's the shift that's happening For years, AI belonged to giant tech companies and massive data centers Now NVIDIA is pushing a world where regular people can either host the infrastructure or own a piece of it themselves

Lummox

10,019 Aufrufe • vor 2 Monaten

Hot tip for anyone doing AI dev: Use Ollama to easily run models like Deepseek-r1 or Gemma locally on your machine. It downloads them and spins up a server with an OpenAI SDK compatible API The smaller models are fast and good enough to work on new features or debug streaming without having to pay for API requests

Hot tip for anyone doing AI dev: Use Ollama to easily run models like Deepseek-r1 or Gemma locally on your machine. It downloads them and spins up a server with an OpenAI SDK compatible API The smaller models are fast and good enough to work on new features or debug streaming without having to pay for API requests

Wes Bos

153,499 Aufrufe • vor 1 Jahr

A small sneak peek of something we’ve been working on for the past 12 months. Together with Qualcomm, we’ve been designing the next generation of the HUMAIN AI PC - bringing CPU, GPU and NPU together to run AI models locally, on the device. I’m excited about the hardware. But the hardware isn’t the part I’m most excited about. The real question is: what operating system is running on it? What happens when we rethink the operating system for an agentic AI world... not around apps, but around intent? Stay tuned. We’ll reveal much more at #LEAP. #HUMAIN #TheEndOfLimits HUMAIN

A small sneak peek of something we’ve been working on for the past 12 months. Together with Qualcomm, we’ve been designing the next generation of the HUMAIN AI PC - bringing CPU, GPU and NPU together to run AI models locally, on the device. I’m excited about the hardware. But the hardware isn’t the part I’m most excited about. The real question is: what operating system is running on it? What happens when we rethink the operating system for an agentic AI world... not around apps, but around intent? Stay tuned. We’ll reveal much more at #LEAP. #HUMAIN #TheEndOfLimits HUMAIN

Tareq Amin

3,842,668 Aufrufe • vor 2 Tagen

A self-evolving agent + a 428B model + 3 Macs = ? Your own AI lab. We ran MiniMax (official) M3 locally with Parallax, right on our desk. Then GenericAgent took over to create a 5-stock portfolio and write it to disk. No cloud. No API bills. Nothing left the machine. Wild to see a ~3K-line agent drive all this with a 400B+ model on local hardware. Thanks to the GenericAgent and MiniMax teams for making local AI feel real.

A self-evolving agent + a 428B model + 3 Macs = ? Your own AI lab. We ran MiniMax (official) M3 locally with Parallax, right on our desk. Then GenericAgent took over to create a 5-stock portfolio and write it to disk. No cloud. No API bills. Nothing left the machine. Wild to see a ~3K-line agent drive all this with a 400B+ model on local hardware. Thanks to the GenericAgent and MiniMax teams for making local AI feel real.

Gradient

150,400 Aufrufe • vor 1 Monat