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Happy 2025! Introducing LM Studio 0.3.6 🚀 - New vision models: Qwen2VL and QVQ (both GGUF + MLX) 🤩 - Function Calling API (in beta) 🧰 - New installer on Windows: choose drive (finally 😮‍💨) - In-app updates are much smaller & have a progress bar! 🟩🟩⬜️⬜️ - Update...

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LM Studio

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30,165 görüntüleme • 1 yıl önce •via X (Twitter)

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Jan Desktop v0.7.7 is live 💛 This update brings native MLX support on macOS, a broader UX and UI refresh across the app, and better support for developer workflows. You can now upload files in Projects, use the local API server with both local and remote models, and work more smoothly with tools like Claude Code and other CLIs. Update your Jan or download the latest version at
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Jan Desktop v0.7.7 is live 💛 This update brings native MLX support on macOS, a broader UX and UI refresh across the app, and better support for developer workflows. You can now upload files in Projects, use the local API server with both local and remote models, and work more smoothly with tools like Claude Code and other CLIs. Update your Jan or download the latest version at

👋 Jan

28,378 görüntüleme • 6 ay önce

HOLY MOLY running a 35B model locally on a MacBook shouldn’t be THIS FAST 🤯 Spent my weekend in atomic.chat testing Qwen 35B vs. Qwen 27B on my local machine. I had them generate a fully animated HTML/Canvas car mini-game (demo below), ... and both models breezed through the physics and parallax scrolling without a hitch! The secret sauce here is the Atomic Chat app. Because it's perfectly optimized for Mac and uses Google's new TurboQuant under the hood, you can run heavy open-source models flawlessly while keeping top-tier output quality 👊 Other perks: → ZERO setup required → Access 1,000+ models completely free → 100% offline and private → Zero API limits ... and MUCH more! I dropped the prompt I used in the 🧵↓ Spin it up locally and let me know what you get!
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HOLY MOLY running a 35B model locally on a MacBook shouldn’t be THIS FAST 🤯 Spent my weekend in atomic.chat testing Qwen 35B vs. Qwen 27B on my local machine. I had them generate a fully animated HTML/Canvas car mini-game (demo below), ... and both models breezed through the physics and parallax scrolling without a hitch! The secret sauce here is the Atomic Chat app. Because it's perfectly optimized for Mac and uses Google's new TurboQuant under the hood, you can run heavy open-source models flawlessly while keeping top-tier output quality 👊 Other perks: → ZERO setup required → Access 1,000+ models completely free → 100% offline and private → Zero API limits ... and MUCH more! I dropped the prompt I used in the 🧵↓ Spin it up locally and let me know what you get!

Charly Wargnier

100,041 görüntüleme • 3 ay önce

🔥 Amazing Update! The HEXscout Portfolio now supports viewing all Pulse & Ethereum tokens! Simply click the Add (Plus) button, enter the contract, and you're all set. Feel free! Your Scouting, Your Rules! The rollout begins on the desktop and, within a few days, will be packed with more new features 🎁🤩 in the iOS and Android apps! 🥰🚀🙏🚀 Also part of the update: Major structural optimizations and fixes for enhanced stability and performance, necessitated by the strong demand from the thousands of scouts now using our service.🚀🙏 🔥Hot Tip: Always secure your settings with a click and pin, whether to transfer data to another device or to protect them before clearing the browser cache! Click the settings (gear icon), then the export button, note the number, and you're done. 🚨Important Check: Have you installed the latest app update yet? Crucial API improvements have resolved significant performance issues that arose shortly after the app's start due to a change in the PulseChain. Be sure to update if you haven't already! iOS Android:
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🔥 Amazing Update! The HEXscout Portfolio now supports viewing all Pulse & Ethereum tokens! Simply click the Add (Plus) button, enter the contract, and you're all set. Feel free! Your Scouting, Your Rules! The rollout begins on the desktop and, within a few days, will be packed with more new features 🎁🤩 in the iOS and Android apps! 🥰🚀🙏🚀 Also part of the update: Major structural optimizations and fixes for enhanced stability and performance, necessitated by the strong demand from the thousands of scouts now using our service.🚀🙏 🔥Hot Tip: Always secure your settings with a click and pin, whether to transfer data to another device or to protect them before clearing the browser cache! Click the settings (gear icon), then the export button, note the number, and you're done. 🚨Important Check: Have you installed the latest app update yet? Crucial API improvements have resolved significant performance issues that arose shortly after the app's start due to a change in the PulseChain. Be sure to update if you haven't already! iOS Android:

HEXscout

37,965 görüntüleme • 2 yıl önce

🚀 More Weather Models For Free & Outlooks are Back! Build confidence in your forecast by comparing even more weather models, for free: - ECMWF 🇪🇺 - IFS - AIFS - Canadian 🇨🇦 - GDPS - RDPS - HRDPS (Continental and North regions) - ICON 🇩🇪 - Global - Europe (EU) - Germany (D2) Also, the Outlooks tab is back... Back by popular demand, we've added Outlooks back to the top bar. Now you can enjoy the best of both worlds: use Outlooks in a dedicated mode or overlay it while viewing Radar, Composite, Satellite, or Models. There's more... - Up to 6 model runs for HRRR, RAP & RRFS - Added Relative Humidity, Total Precipitation, 1 & 4km Reflectivity, Significant Tornado Parameter, and many more - Select specific hours for a model run - Unit settings for Precipitation and Pressure Available now on: iOS: Android: Browser: And to Plus/Pro subscribers using our Windows/Mac/Linux App
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🚀 More Weather Models For Free & Outlooks are Back! Build confidence in your forecast by comparing even more weather models, for free: - ECMWF 🇪🇺 - IFS - AIFS - Canadian 🇨🇦 - GDPS - RDPS - HRDPS (Continental and North regions) - ICON 🇩🇪 - Global - Europe (EU) - Germany (D2) Also, the Outlooks tab is back... Back by popular demand, we've added Outlooks back to the top bar. Now you can enjoy the best of both worlds: use Outlooks in a dedicated mode or overlay it while viewing Radar, Composite, Satellite, or Models. There's more... - Up to 6 model runs for HRRR, RAP & RRFS - Added Relative Humidity, Total Precipitation, 1 & 4km Reflectivity, Significant Tornado Parameter, and many more - Select specific hours for a model run - Unit settings for Precipitation and Pressure Available now on: iOS: Android: Browser: And to Plus/Pro subscribers using our Windows/Mac/Linux App

WeatherWise.app

39,608 görüntüleme • 10 ay önce

llama.cpp isn't just for text LLMs anymore. Pure C++ zero shot voice cloning just officially landed in mainline. Text generation was only step one. If you’re building autonomous local AI agents, real time voice assistants, or edge workflows, instant low latency audio is the missing piece. Thanks to PR #26254, Alibaba’s state of the art Qwen3 TTS model family is now natively supported directly inside the llama.cpp repository under the multimodal (mtmd) framework. No Python bloat. No massive PyTorch CUDA overhead. Just raw, hyper optimized C++ running GGUF voice weights. Here is why this native update is a massive deal for the open source local AI stack: # Multimodal Architecture (.gguf + mmproj) Qwen3-TTS splits the workload between the base language model backbone and a multimodal projection adapter. llama.cpp handles this using the llama-tts binary, mapping the text model alongside its --mmproj projector to process audio tokens seamlessly. # Zero Shot Voice Cloning in Seconds You don't need fine tuning or massive dataset training. Feed the C++ engine a single 5 to 10 second .wav audio sample using the --tts-speaker-file flag, and it accurately clones the exact timbre, tone, and accent on the fly. # Real World T4 GPU Benchmark & Resource FootprintRunning the 1.7B Base model in 8-bit quantization (Q8_0): - VRAM Footprint: ~7 GB peak VRAM during active zero-shot cloning. - Audio Quality: Studio grade, natural-sounding voice output in seconds. • - Execution: Direct execution via native compiled binaries or sub process calls. # Coming Next to llama-server (PR #26603) Beyond CLI execution, a native POST /tts HTTP endpoint is currently being added to llama-server, which will soon allow you to trigger voice generation directly via standard REST API requests! # quick note on Colab compilation: Because this code was merged into mainline very recently, pre-built third-party binaries haven't fully caught up yet. Compiling llama-tts directly from source on Google Colab's free CPU instance can take about 1 hour (or ~1-2 minutes if targeting single GPU arch like -DCMAKE_CUDA_ARCHITECTURES=75). Be patient during the build step, or compile it locally on your own rig for instant execution! To test this out yourself, I built a zero config Google Colab notebook that compiles llama.cpp, downloads the Q8_0 GGUF files from HuggingFace, and spins up an interactive Gradio Studio UI so you can record/upload 3 second clips and clone voices in real time. Stop sleeping on native C++ audio. The era of bulky Python audio pipelines is officially over. Links to the free Google Colab notebook and the official ggml org GGUF HuggingFace model repository are in the replies below! available in q4 and q8 both variants, 1 GB and 1.85 GBs respectively (requires additional ~500MB mmproj gguf) Are you building local voice agents yet? What does your current audio stack look like? Drop your setups below!
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llama.cpp isn't just for text LLMs anymore. Pure C++ zero shot voice cloning just officially landed in mainline. Text generation was only step one. If you’re building autonomous local AI agents, real time voice assistants, or edge workflows, instant low latency audio is the missing piece. Thanks to PR #26254, Alibaba’s state of the art Qwen3 TTS model family is now natively supported directly inside the llama.cpp repository under the multimodal (mtmd) framework. No Python bloat. No massive PyTorch CUDA overhead. Just raw, hyper optimized C++ running GGUF voice weights. Here is why this native update is a massive deal for the open source local AI stack: # Multimodal Architecture (.gguf + mmproj) Qwen3-TTS splits the workload between the base language model backbone and a multimodal projection adapter. llama.cpp handles this using the llama-tts binary, mapping the text model alongside its --mmproj projector to process audio tokens seamlessly. # Zero Shot Voice Cloning in Seconds You don't need fine tuning or massive dataset training. Feed the C++ engine a single 5 to 10 second .wav audio sample using the --tts-speaker-file flag, and it accurately clones the exact timbre, tone, and accent on the fly. # Real World T4 GPU Benchmark & Resource FootprintRunning the 1.7B Base model in 8-bit quantization (Q8_0): - VRAM Footprint: ~7 GB peak VRAM during active zero-shot cloning. - Audio Quality: Studio grade, natural-sounding voice output in seconds. • - Execution: Direct execution via native compiled binaries or sub process calls. # Coming Next to llama-server (PR #26603) Beyond CLI execution, a native POST /tts HTTP endpoint is currently being added to llama-server, which will soon allow you to trigger voice generation directly via standard REST API requests! # quick note on Colab compilation: Because this code was merged into mainline very recently, pre-built third-party binaries haven't fully caught up yet. Compiling llama-tts directly from source on Google Colab's free CPU instance can take about 1 hour (or ~1-2 minutes if targeting single GPU arch like -DCMAKE_CUDA_ARCHITECTURES=75). Be patient during the build step, or compile it locally on your own rig for instant execution! To test this out yourself, I built a zero config Google Colab notebook that compiles llama.cpp, downloads the Q8_0 GGUF files from HuggingFace, and spins up an interactive Gradio Studio UI so you can record/upload 3 second clips and clone voices in real time. Stop sleeping on native C++ audio. The era of bulky Python audio pipelines is officially over. Links to the free Google Colab notebook and the official ggml org GGUF HuggingFace model repository are in the replies below! available in q4 and q8 both variants, 1 GB and 1.85 GBs respectively (requires additional ~500MB mmproj gguf) Are you building local voice agents yet? What does your current audio stack look like? Drop your setups below!

Alok

47,881 görüntüleme • 5 gün önce

🚀 GT Protocol x Hyperliquid Integration Hyperliquid execution is fully embedded into GT App, unlocking automated strategies with signals, targets, and stop orders across Spot and Perps. What it includes: 1️⃣ DEX Execution Support Your strategies can now execute not only on centralized exchanges like Binance but also on the decentralized infrastructure of Hyperliquid. You keep the same interface and gain a new execution rail. 2️⃣ Spot and Perps Trading Automated strategy execution is now available both on Spot and on Perpetual markets on Hyperliquid through API-level integration. 3️⃣ SEC and MiCA Restriction Bypass Traders in the US and EU who are affected by SEC or MiCA limitations can now use a clean DEX-based path that keeps automated trading active without additional workarounds. 4️⃣ Unified Control Panel You still control everything from one place: connect → choose strategy → launch → monitor. GT App handles execution across CeFi and DEX rails. Try it now on GT APP 👉
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🚀 GT Protocol x Hyperliquid Integration Hyperliquid execution is fully embedded into GT App, unlocking automated strategies with signals, targets, and stop orders across Spot and Perps. What it includes: 1️⃣ DEX Execution Support Your strategies can now execute not only on centralized exchanges like Binance but also on the decentralized infrastructure of Hyperliquid. You keep the same interface and gain a new execution rail. 2️⃣ Spot and Perps Trading Automated strategy execution is now available both on Spot and on Perpetual markets on Hyperliquid through API-level integration. 3️⃣ SEC and MiCA Restriction Bypass Traders in the US and EU who are affected by SEC or MiCA limitations can now use a clean DEX-based path that keeps automated trading active without additional workarounds. 4️⃣ Unified Control Panel You still control everything from one place: connect → choose strategy → launch → monitor. GT App handles execution across CeFi and DEX rails. Try it now on GT APP 👉

GT Protocol

32,323 görüntüleme • 6 ay önce

i just ran Google's brand new Unsloth Gemma4 12B dense GGUF on my RTX 4060 using llama.cpp + CUDA 13.2 21 tokens per second. on a budget consumer GPU. locally. no API. no cloud. no subscription. and the benchmarks are absolutely cooked # first let's talk architecture because this is genuinely different every multimodal model you've used has a frozen vision encoder + frozen audio encoder + LLM backbone glued together Gemma 4 12B is different it's a single decoder only transformer. that's it. vision? raw 48×48 pixel patches → one matmul → projected directly into the LLM audio? raw 16kHz signal sliced into 40ms frames → linear projection → same LLM input space no encoder tax. no latency penalty. no fragmented memory to put the encoder savings in perspective: old Gemma 4 26B approach: - 550M param vision encoder (frozen) - 300M param audio encoder (frozen) - LLM backbone Gemma 4 12B: - 35M param vision embedder (a single matmul) - no audio encoder at all - LLM backbone handles EVERYTHING 550M → 35M for vision alone. that's a 15x reduction this is why the gemma-4-12b-it-Q4_K_M.gguf is just 6.6 GBs!!! and it has 256K native context context # Benchmarks: AIME 2026 (math olympiad): 77.5% GPQA Diamond (expert science): 78.8% LiveCodeBench v6 (real code): 72% Codeforces ELO: 1659 MMLU Pro: 77.2% MATH-Vision: 79.7% BigBench Extra Hard: 53% inference → llama.cpp, LM Studio, vLLM, SGLang llamacpp flags: -m "gemma-4-12b-it-Q4_K_M.gguf" -ngl 99 -c 8000 -v --port 8080 Available on huggingface now! Link below
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i just ran Google's brand new Unsloth Gemma4 12B dense GGUF on my RTX 4060 using llama.cpp + CUDA 13.2 21 tokens per second. on a budget consumer GPU. locally. no API. no cloud. no subscription. and the benchmarks are absolutely cooked # first let's talk architecture because this is genuinely different every multimodal model you've used has a frozen vision encoder + frozen audio encoder + LLM backbone glued together Gemma 4 12B is different it's a single decoder only transformer. that's it. vision? raw 48×48 pixel patches → one matmul → projected directly into the LLM audio? raw 16kHz signal sliced into 40ms frames → linear projection → same LLM input space no encoder tax. no latency penalty. no fragmented memory to put the encoder savings in perspective: old Gemma 4 26B approach: - 550M param vision encoder (frozen) - 300M param audio encoder (frozen) - LLM backbone Gemma 4 12B: - 35M param vision embedder (a single matmul) - no audio encoder at all - LLM backbone handles EVERYTHING 550M → 35M for vision alone. that's a 15x reduction this is why the gemma-4-12b-it-Q4_K_M.gguf is just 6.6 GBs!!! and it has 256K native context context # Benchmarks: AIME 2026 (math olympiad): 77.5% GPQA Diamond (expert science): 78.8% LiveCodeBench v6 (real code): 72% Codeforces ELO: 1659 MMLU Pro: 77.2% MATH-Vision: 79.7% BigBench Extra Hard: 53% inference → llama.cpp, LM Studio, vLLM, SGLang llamacpp flags: -m "gemma-4-12b-it-Q4_K_M.gguf" -ngl 99 -c 8000 -v --port 8080 Available on huggingface now! Link below

Alok

280,255 görüntüleme • 2 ay önce

We are excited to unveil the latest version of the AIOZ Node: The Version 4.0 update! This update includes a new user interface and brings substantial functional improvements, enhancing your overall experience for increased productivity and efficiency. More information below: The standout feature of AIOZ Node v4.0 is the introduction of the Transcoding functionality, which is currently available in beta. This functionality enables your node to participate in video transcoding, which converts video files into different formats for various digital devices and media platforms. By enabling transcoding, your node can contribute more significantly to the AIOZ Network, expanding the network's capabilities and potential $AIOZ token rewards. While the transcoding functionality is currently in beta, the upcoming AIOZ W3Stream integration, a DePIN Video Infrastructure due for release in Q3 2024, will unlock the full potential of your node and enable seamless video transcoding tasks. To get started with AIOZ Node v4.0, you simply need to visit our official website to download the latest version of the AIOZ Node: This download process is very straightforward, and with a one-click installation process, you can set up AIOZ Node v4.0 to start running on your device within a few minutes. If you are already running an AIOZ Node on your device, the version 4.0 update will be applied automatically, ensuring you have the latest features and improvements without hassle! With the Node v4.0 update running on your device, you can proceed to familiarize yourself with the new layout, check out the performance improvements, and start transcoding to see how it enhances your contributions to the network! Learn More: $AIOZ
0:15

We are excited to unveil the latest version of the AIOZ Node: The Version 4.0 update! This update includes a new user interface and brings substantial functional improvements, enhancing your overall experience for increased productivity and efficiency. More information below: The standout feature of AIOZ Node v4.0 is the introduction of the Transcoding functionality, which is currently available in beta. This functionality enables your node to participate in video transcoding, which converts video files into different formats for various digital devices and media platforms. By enabling transcoding, your node can contribute more significantly to the AIOZ Network, expanding the network's capabilities and potential $AIOZ token rewards. While the transcoding functionality is currently in beta, the upcoming AIOZ W3Stream integration, a DePIN Video Infrastructure due for release in Q3 2024, will unlock the full potential of your node and enable seamless video transcoding tasks. To get started with AIOZ Node v4.0, you simply need to visit our official website to download the latest version of the AIOZ Node: This download process is very straightforward, and with a one-click installation process, you can set up AIOZ Node v4.0 to start running on your device within a few minutes. If you are already running an AIOZ Node on your device, the version 4.0 update will be applied automatically, ensuring you have the latest features and improvements without hassle! With the Node v4.0 update running on your device, you can proceed to familiarize yourself with the new layout, check out the performance improvements, and start transcoding to see how it enhances your contributions to the network! Learn More: $AIOZ

AIOZ Network

20,428 görüntüleme • 2 yıl önce

HERMES AGENT NOW SUPPORTS COMPUTER USE ON WINDOWS AND LINUX. CLICKS, TYPES, SCROLLS YOUR DESKTOP IN THE BACKGROUND WHILE YOU WORK. computer use was macOS only. now it works on Windows and Linux too via Cua. Nous Research HOW IT WORKS: cua-driver runs as an MCP server. Hermes takes a screenshot with numbered elements. clicks element #14 (the search field). types a query. submits. reads the result. during all of this: → your cursor stays where you left it → keyboard focus doesn't change → windows don't come to front → macOS doesn't switch Spaces you and the agent co-work on the same machine. WHAT IT CAN DO: → find your latest Stripe email and summarize it → fill forms in a web app that has no API → navigate desktop apps (Mail, browser, Finder) → interact with any GUI application → extract data from apps only accessible via screen WORKS WITH ANY VISION MODEL: not locked to Anthropic. | Provider | Works | |---|---| | Claude (Sonnet/Opus) | best overall | | GPT-4+, GPT-5.5 | full support | | Gemini (via OpenRouter) | full support | | Local vLLM / LM Studio | if model supports vision | | Text-only models | degraded (accessibility tree only) | SETUP: hermes computer-use install or: hermes tools → Computer Use → cua-driver grant permissions when prompted: → Accessibility (system settings) → Screen Recording (system settings) start a session: hermes -t computer_use chat or add to config.yaml / Desktop app settings to enable permanently. SAFETY: → destructive actions require your approval → blocked key combos: empty trash, force delete, lock screen, log out → blocked type patterns: curl | bash, sudo rm -rf /, fork bombs → agent cannot click permission dialogs → agent cannot type passwords → agent cannot follow instructions embedded in screenshots pair with approvals.mode: manual if you want every single click confirmed. TOKEN NOTE: screenshots are expensive. each one adds vision tokens to context. use computer_use for tasks where no API exists. if the tool has an API or MCP server, use that instead. 15 levels of Hermes Agent👇
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HERMES AGENT NOW SUPPORTS COMPUTER USE ON WINDOWS AND LINUX. CLICKS, TYPES, SCROLLS YOUR DESKTOP IN THE BACKGROUND WHILE YOU WORK. computer use was macOS only. now it works on Windows and Linux too via Cua. Nous Research HOW IT WORKS: cua-driver runs as an MCP server. Hermes takes a screenshot with numbered elements. clicks element #14 (the search field). types a query. submits. reads the result. during all of this: → your cursor stays where you left it → keyboard focus doesn't change → windows don't come to front → macOS doesn't switch Spaces you and the agent co-work on the same machine. WHAT IT CAN DO: → find your latest Stripe email and summarize it → fill forms in a web app that has no API → navigate desktop apps (Mail, browser, Finder) → interact with any GUI application → extract data from apps only accessible via screen WORKS WITH ANY VISION MODEL: not locked to Anthropic. | Provider | Works | |---|---| | Claude (Sonnet/Opus) | best overall | | GPT-4+, GPT-5.5 | full support | | Gemini (via OpenRouter) | full support | | Local vLLM / LM Studio | if model supports vision | | Text-only models | degraded (accessibility tree only) | SETUP: hermes computer-use install or: hermes tools → Computer Use → cua-driver grant permissions when prompted: → Accessibility (system settings) → Screen Recording (system settings) start a session: hermes -t computer_use chat or add to config.yaml / Desktop app settings to enable permanently. SAFETY: → destructive actions require your approval → blocked key combos: empty trash, force delete, lock screen, log out → blocked type patterns: curl | bash, sudo rm -rf /, fork bombs → agent cannot click permission dialogs → agent cannot type passwords → agent cannot follow instructions embedded in screenshots pair with approvals.mode: manual if you want every single click confirmed. TOKEN NOTE: screenshots are expensive. each one adds vision tokens to context. use computer_use for tasks where no API exists. if the tool has an API or MCP server, use that instead. 15 levels of Hermes Agent👇

YanXbt

29,127 görüntüleme • 1 ay önce

You don't need a GPU for fast studio grade voice cloning anymore. Qwen3 TTS (1.7B Q4_K_M) + mainline llama.cpp is officially the fastest way to generate zero shot voice clones using 100% pure CPU execution. Following up on my last post where we ran the Q8 model on a GPU, we just took local C++ voice synthesis a massive step further. The open source community quantized Alibaba's SOTA Qwen3 TTS model down to Q4_K_M GGUF, completely freeing local audio pipelines from dedicated graphics hardware. Here is the real world benchmark and hardware breakdown of running SOTA voice cloning on CPU: # Architecture & Model Setup Using Qwen3-TTS-12Hz-1.7B-Base-Q4_K_M.gguf paired with the 8 bit multimodal projector (mmproj-Q8_0.gguf), llama.cpp executes the entire pipeline in pure C++. No PyTorch, no CUDA dependencies, and no VRAM bottlenecks. # Real-World Memory Footprint - Baseline RAM: 1.6 GB system idle. - Peak Generation RAM: 8 GB RAM during active voice synthesis. - Requirement: Any basic machine with at least 8 GB of system RAM can run this easily. # Real World CPU Benchmarks - Google Colab Free Tier (Throttled 2 Core CPU): Synthesizes a 5 sec studio quality audio clip (~8 words) in 45 seconds. - Modern Consumer CPU (Intel i5/i7 13th/14th Gen or AMD Ryzen 7000/9000): generation should drop to 5 to 20 seconds (nearly 1:1 real-time generation speed!). # Zero Shot Voice Cloning Quality Pass any 5 to 20 second .wav audio sample to the C++ engine using the --tts-speaker-file flag. It yields clean, natural sounding cloned speech with virtually zero quality loss compared to unquantized FP16 weights. To make testing seamless, I built an updated zero config Google Colab notebook. It pulls the official pre built llama.cpp CPU binaries (zero compilation time!) launches a live Gradio web app right in your browser. Record a 5 second clip from your mic (or drop a .mp3, .wav file), type text, and generate cloned audio on CPU. Native C++ audio models are making edge based, offline AI voice agents a reality. Links to the free Q4 CPU Colab notebook and the Q4_K_M GGUF HuggingFace repository are in the replies below! Which models have you been running on your CPUs? What CPU hardware are you using for local inference?
0:16

You don't need a GPU for fast studio grade voice cloning anymore. Qwen3 TTS (1.7B Q4_K_M) + mainline llama.cpp is officially the fastest way to generate zero shot voice clones using 100% pure CPU execution. Following up on my last post where we ran the Q8 model on a GPU, we just took local C++ voice synthesis a massive step further. The open source community quantized Alibaba's SOTA Qwen3 TTS model down to Q4_K_M GGUF, completely freeing local audio pipelines from dedicated graphics hardware. Here is the real world benchmark and hardware breakdown of running SOTA voice cloning on CPU: # Architecture & Model Setup Using Qwen3-TTS-12Hz-1.7B-Base-Q4_K_M.gguf paired with the 8 bit multimodal projector (mmproj-Q8_0.gguf), llama.cpp executes the entire pipeline in pure C++. No PyTorch, no CUDA dependencies, and no VRAM bottlenecks. # Real-World Memory Footprint - Baseline RAM: 1.6 GB system idle. - Peak Generation RAM: 8 GB RAM during active voice synthesis. - Requirement: Any basic machine with at least 8 GB of system RAM can run this easily. # Real World CPU Benchmarks - Google Colab Free Tier (Throttled 2 Core CPU): Synthesizes a 5 sec studio quality audio clip (~8 words) in 45 seconds. - Modern Consumer CPU (Intel i5/i7 13th/14th Gen or AMD Ryzen 7000/9000): generation should drop to 5 to 20 seconds (nearly 1:1 real-time generation speed!). # Zero Shot Voice Cloning Quality Pass any 5 to 20 second .wav audio sample to the C++ engine using the --tts-speaker-file flag. It yields clean, natural sounding cloned speech with virtually zero quality loss compared to unquantized FP16 weights. To make testing seamless, I built an updated zero config Google Colab notebook. It pulls the official pre built llama.cpp CPU binaries (zero compilation time!) launches a live Gradio web app right in your browser. Record a 5 second clip from your mic (or drop a .mp3, .wav file), type text, and generate cloned audio on CPU. Native C++ audio models are making edge based, offline AI voice agents a reality. Links to the free Q4 CPU Colab notebook and the Q4_K_M GGUF HuggingFace repository are in the replies below! Which models have you been running on your CPUs? What CPU hardware are you using for local inference?

Alok

34,852 görüntüleme • 2 gün önce

🕹️ Day 3 of the Cursor #vibejam Proudly sponsored by Cursor + bolt.new + GLIF (Glif joined as a new sponsor and I'll tell you more tomorrow about how they will help your games!) It took a bit but things are finally starting to heat up! Here's some amazing games I saw today (in the videos): - unnamed by Danny Limanseta - Risefall RPG by Vicki Petrova - Vibe Theft Auto by oldfeet - unnamed by Kieran Smith Reply in this thread with updates on your current games to share your progress! I'll keep reposting all your updates during the Vibe Jam. The quality looks a lot higher than last year, AI models have come a long way and it's easier to build something that looks good and is playable! But you still need creativity and I see a lot of creative things in my timeline: Wanna participate? Can submit any time before May 1, so if you want to start tomorrow that's fine too! There's $35,000 in prizes you can win, see thread below for more info!
0:10

🕹️ Day 3 of the Cursor #vibejam Proudly sponsored by Cursor + bolt.new + GLIF (Glif joined as a new sponsor and I'll tell you more tomorrow about how they will help your games!) It took a bit but things are finally starting to heat up! Here's some amazing games I saw today (in the videos): - unnamed by Danny Limanseta - Risefall RPG by Vicki Petrova - Vibe Theft Auto by oldfeet - unnamed by Kieran Smith Reply in this thread with updates on your current games to share your progress! I'll keep reposting all your updates during the Vibe Jam. The quality looks a lot higher than last year, AI models have come a long way and it's easier to build something that looks good and is playable! But you still need creativity and I see a lot of creative things in my timeline: Wanna participate? Can submit any time before May 1, so if you want to start tomorrow that's fine too! There's $35,000 in prizes you can win, see thread below for more info!

@levelsio

250,747 görüntüleme • 4 ay önce

Important Update: Final CTF Token Burn Valued at Nearly $1 Million Scheduled for December 6th. We are excited to announce that the final burn, worth approximately $1 million in CTF reward tokens, is scheduled for December 6th at 11:59 PM. After successfully completing our first burn on December 1st, our team has been focused on developing cross-chain interoperability between XRPL and Polygon. Unfortunately, due to technical challenges, the 2nd and 3rd burn transactions were NOT processed. However, all technical issues have now been resolved, and we are on track for a smooth final burn on December 6th. Following this, we will begin beta testing our rewards payment app—an exciting new phase! Stay tuned for more updates, and thank you for your continued support! For more information visit
0:13

Important Update: Final CTF Token Burn Valued at Nearly $1 Million Scheduled for December 6th. We are excited to announce that the final burn, worth approximately $1 million in CTF reward tokens, is scheduled for December 6th at 11:59 PM. After successfully completing our first burn on December 1st, our team has been focused on developing cross-chain interoperability between XRPL and Polygon. Unfortunately, due to technical challenges, the 2nd and 3rd burn transactions were NOT processed. However, all technical issues have now been resolved, and we are on track for a smooth final burn on December 6th. Following this, we will begin beta testing our rewards payment app—an exciting new phase! Stay tuned for more updates, and thank you for your continued support! For more information visit

CryptoTradingFund

297,175 görüntüleme • 1 yıl önce

Full Fine-tuning vs. Freezing Layers. Interact 👉 and == Full Fine-tuning == A real network has many — three layers in this example, billions of parameters in a production model. What does fine-tuning look like when you update all of them? That’s full fine-tuning: continue training every weight in the pretrained network on your new task. Every layer’s W gets its own ΔW. Nothing is frozen — every parameter is in play. Think of an MLP as a chain of prerequisites leading to an advanced course. Layer 1 might be Linear Algebra, layer 2 Probability, layer 3 Advanced Machine Learning — each one building on what came before. Fine-tuning is what happens during graduate study: the foundations are already there from undergrad, so you’re not re-learning. Full fine-tuning is reviewing every prerequisite to see what new topics have appeared and what discoveries the field has made since the last time you sat through them. Effective — but exhausting. This diagram shows the same three-layer MLP twice, side by side. On the left, the pretrained network runs on input X: three weight matrices W₁, W₂, W₃, each followed by a ReLU activation. Full fine-tuning gives the model the most freedom to specialize. Every parameter can move — and every parameter that can move must be stored. But not every prerequisite needs revisiting. The further you go back in the chain, the less the material has changed since pretraining — the linear-algebra basics under your computer-vision course are largely the same as they ever were. The next page does exactly that: freeze the prerequisites that haven’t moved, and only refresh the advanced one closest to your specialization. == Freezing Layers == Full fine-tuning reviewed every prerequisite — Linear Algebra, Probability, Advanced ML — to refresh each subject with the latest topics. Effective, but exhausting. Then you realize something. The prerequisites haven’t actually changed that much. Linear Algebra is still Linear Algebra; the matrix decompositions you learned still hold. Probability is still Probability; the distributions and Bayes’ rule haven’t moved. Almost all the new material — the new ideas, the recent discoveries — lives in the advanced layer at the top. That’s freezing layers: keep the prerequisite layers fixed at their pretrained state, and only update the advanced one. In the diagram below, W1​ and W2​ — the foundational prerequisites — stay frozen. Only W3​ — the layer closest to your task-specific output — gets a ΔW.
0:16

Full Fine-tuning vs. Freezing Layers. Interact 👉 and == Full Fine-tuning == A real network has many — three layers in this example, billions of parameters in a production model. What does fine-tuning look like when you update all of them? That’s full fine-tuning: continue training every weight in the pretrained network on your new task. Every layer’s W gets its own ΔW. Nothing is frozen — every parameter is in play. Think of an MLP as a chain of prerequisites leading to an advanced course. Layer 1 might be Linear Algebra, layer 2 Probability, layer 3 Advanced Machine Learning — each one building on what came before. Fine-tuning is what happens during graduate study: the foundations are already there from undergrad, so you’re not re-learning. Full fine-tuning is reviewing every prerequisite to see what new topics have appeared and what discoveries the field has made since the last time you sat through them. Effective — but exhausting. This diagram shows the same three-layer MLP twice, side by side. On the left, the pretrained network runs on input X: three weight matrices W₁, W₂, W₃, each followed by a ReLU activation. Full fine-tuning gives the model the most freedom to specialize. Every parameter can move — and every parameter that can move must be stored. But not every prerequisite needs revisiting. The further you go back in the chain, the less the material has changed since pretraining — the linear-algebra basics under your computer-vision course are largely the same as they ever were. The next page does exactly that: freeze the prerequisites that haven’t moved, and only refresh the advanced one closest to your specialization. == Freezing Layers == Full fine-tuning reviewed every prerequisite — Linear Algebra, Probability, Advanced ML — to refresh each subject with the latest topics. Effective, but exhausting. Then you realize something. The prerequisites haven’t actually changed that much. Linear Algebra is still Linear Algebra; the matrix decompositions you learned still hold. Probability is still Probability; the distributions and Bayes’ rule haven’t moved. Almost all the new material — the new ideas, the recent discoveries — lives in the advanced layer at the top. That’s freezing layers: keep the prerequisite layers fixed at their pretrained state, and only update the advanced one. In the diagram below, W1​ and W2​ — the foundational prerequisites — stay frozen. Only W3​ — the layer closest to your task-specific output — gets a ΔW.

Tom Yeh

27,587 görüntüleme • 3 ay önce

sora roadmap update: in the spirit of building this app openly, here's what we're landing soon. first, more creation tools. character cameos are coming in the next few days: you'll be able to cameo your dog, guinea pig, favorite stuffed toy, and pretty much anything else you want. you can also create cameos of generated characters straight from your sora videos. we're expecting people to register lots of crazy new cameos with this feature. to make them easier to find, we're updating the generation UI to show the latest trending cameos in real time. we're also adding basic video editing capabilities to the app, starting with stitching together multiple clips, and we'll add very powerful new features here soon. second, we're working on making the social experience much better. we are exploring new ways to use sora with your friends (versus just a global feed) and broader community. think channels that are specific to your university, company, sports club, etc. third, quality of life. the feed has quietly gotten much better recently, and there are more improvements on the way soon (shoutout to Thomas Dimson and team!). team is hard at work continuing to reduce excessive moderation of gens (we know it's super annoying). we're also working to increase the overall performance of the app to feel snappier everywhere. finally, the android version of sora is actually coming soon. please keep giving us feedback!
0:17

sora roadmap update: in the spirit of building this app openly, here's what we're landing soon. first, more creation tools. character cameos are coming in the next few days: you'll be able to cameo your dog, guinea pig, favorite stuffed toy, and pretty much anything else you want. you can also create cameos of generated characters straight from your sora videos. we're expecting people to register lots of crazy new cameos with this feature. to make them easier to find, we're updating the generation UI to show the latest trending cameos in real time. we're also adding basic video editing capabilities to the app, starting with stitching together multiple clips, and we'll add very powerful new features here soon. second, we're working on making the social experience much better. we are exploring new ways to use sora with your friends (versus just a global feed) and broader community. think channels that are specific to your university, company, sports club, etc. third, quality of life. the feed has quietly gotten much better recently, and there are more improvements on the way soon (shoutout to Thomas Dimson and team!). team is hard at work continuing to reduce excessive moderation of gens (we know it's super annoying). we're also working to increase the overall performance of the app to feel snappier everywhere. finally, the android version of sora is actually coming soon. please keep giving us feedback!

Bill Peebles

565,455 görüntüleme • 9 ay önce

As always everyone is blind staring at the progress of LLMs for coding and chat But meanwhile the new SOTA video model Seedance 2.5 has been slowly rolling out and it's really quite exceptional It's made by ByteDance (TikTok) who of course have lots of training data With just a few reference pics, it can get quite close to how you look IRL and you can do quite professional video shots with just a prompt I'd say it's the first video model that's now at the level of image models with the level of character likeness, cracking that in image models also took about 3 years (2022-2025) Generating 15 seconds takes about 4 minutes I put it live now on Photo AI, you can use it under [ Make video ] from the sidebar with just a prompt and your model selected! So you don't need to take an AI photo first and then turn that into a video! Saves lots of time :D It's more expensive than but I kept the credits the same (30 for 1 video) It also works inside the new video editor and you can make changes in your video with [ Magic edit ] in both the main app and the video editor Also a message for my server guy Daniel Lockyer (it can do voice too and you can even submit a voice sample of yourself, but I didn't here)
0:15

As always everyone is blind staring at the progress of LLMs for coding and chat But meanwhile the new SOTA video model Seedance 2.5 has been slowly rolling out and it's really quite exceptional It's made by ByteDance (TikTok) who of course have lots of training data With just a few reference pics, it can get quite close to how you look IRL and you can do quite professional video shots with just a prompt I'd say it's the first video model that's now at the level of image models with the level of character likeness, cracking that in image models also took about 3 years (2022-2025) Generating 15 seconds takes about 4 minutes I put it live now on Photo AI, you can use it under [ Make video ] from the sidebar with just a prompt and your model selected! So you don't need to take an AI photo first and then turn that into a video! Saves lots of time :D It's more expensive than but I kept the credits the same (30 for 1 video) It also works inside the new video editor and you can make changes in your video with [ Magic edit ] in both the main app and the video editor Also a message for my server guy Daniel Lockyer (it can do voice too and you can even submit a voice sample of yourself, but I didn't here)

@levelsio

681,039 görüntüleme • 1 gün önce

📢 Gray Zone Warfare: Night Ops World Premiere Reveal Sept 6th After an exclusive first look at the Day/Night Cycle at Gamescom, we're bringing you the full Night Ops presentation this Friday, September 6th, at 1 PM ET (10 AM PT, 6 PM BST, 7 PM CEST) on Twitch. Join us live for a brief overview of what’s to come later this year. While it’s still a work in progress, the time has come to start sharing what we’ve been working on. Our first major update is designed for players seeking a deeper, more immersive combat experience. Night Ops will reward tactical prowess and adaptability, introducing new tools, highly requested features, and quality-of-life improvements that elevate gameplay and keep you coming back for more, both in daytime and nighttime gameplay. Creators and press will share their first impressions on the same day, offering valuable insights into the update. But the heart of our excitement lies in engaging directly with our community—your feedback and enthusiasm are what drive us. We look forward to your reactions and discussions as we gear up for the launch of #GZW: Night Ops. We're committed to keeping the community updated right up to the launch of our first major update and beyond. The Night Ops presentation is just a preview—future devlogs, posts, and streams will reveal more. Get ready for the first live reveal of #GrayZoneWarfare: #NightOps, this coming Friday on Twitch:
0:12

📢 Gray Zone Warfare: Night Ops World Premiere Reveal Sept 6th After an exclusive first look at the Day/Night Cycle at Gamescom, we're bringing you the full Night Ops presentation this Friday, September 6th, at 1 PM ET (10 AM PT, 6 PM BST, 7 PM CEST) on Twitch. Join us live for a brief overview of what’s to come later this year. While it’s still a work in progress, the time has come to start sharing what we’ve been working on. Our first major update is designed for players seeking a deeper, more immersive combat experience. Night Ops will reward tactical prowess and adaptability, introducing new tools, highly requested features, and quality-of-life improvements that elevate gameplay and keep you coming back for more, both in daytime and nighttime gameplay. Creators and press will share their first impressions on the same day, offering valuable insights into the update. But the heart of our excitement lies in engaging directly with our community—your feedback and enthusiasm are what drive us. We look forward to your reactions and discussions as we gear up for the launch of #GZW: Night Ops. We're committed to keeping the community updated right up to the launch of our first major update and beyond. The Night Ops presentation is just a preview—future devlogs, posts, and streams will reveal more. Get ready for the first live reveal of #GrayZoneWarfare: #NightOps, this coming Friday on Twitch:

Gray Zone Warfare 🔜 Gamescom

71,473 görüntüleme • 1 yıl önce

🪴 GT Protocol Monthly Recap: May 2026 May focused on launching advanced trading infrastructure, introducing AI risk-management tools, and shipping major platform upgrades. 🚀 Hyperliquid Vaults Live Run multiple algorithmic strategies on a single Hyperliquid Vault inside GT App. Enjoy automated execution, auto-rebalancing, and protocol-level security. You can find Vault trading on the Hyperliquid exchange account connection page in the Trade on Vault section. Try it in GT App 👉 🤖 AI Hedge Fund Experiment Live An experimental AI Hedge Fund powered by 5 independent LLM models is live on Hyperliquid. Each model manages $10,000 to test different AI trading personalities and allocation strategies. Discover it now here 👉 📈 Isolated Margin & AI Risk Tools Isolated Margin is live across GT App for precise risk management. Enhanced with AI-powered logic, it assists with dynamic asset monitoring and smarter strategy deployment. Try it in GT App 👉 🔥 Top Strategy Performance Top trader strategies like "lebakien" achieved over +141% profit this month. Users can explore metrics and follow the strategies of top traders directly in the marketplace. Explore Marketplace 👉 🛠 Key Product Updates ⚙️ Strategy Discovery: enhanced demo trading flows and top trader strategy integration. ⚙️ AI Strategy Chat: demoed a flow to create, launch, and test strategies via natural language chat. ⚙️ Advanced Execution: added manual safety orders for granular control over active positions. ⚙️ Testing & Validation: optimized historical data validation for more accurate strategy testing. ⚙️ Knowledge Hub: launched GT Protocol Learn and a new Knowledge Base for streamlined support. ⚙️ Performance: upgraded website structure and improved overall page responsiveness. Find all the latest GT App updates Here 👉 Discover guides, insights, and resources in Learn 👉 and Knowledge Base 👉 📰 GT Protocol AI Digests 4 new AI Digest issues (No.89–92) are live on Medium, covering AI-native hardware, data privacy, and the evolution of AI agents. Read More 👉 May brought institutional-grade AI strategy management closer to every user.
0:10

🪴 GT Protocol Monthly Recap: May 2026 May focused on launching advanced trading infrastructure, introducing AI risk-management tools, and shipping major platform upgrades. 🚀 Hyperliquid Vaults Live Run multiple algorithmic strategies on a single Hyperliquid Vault inside GT App. Enjoy automated execution, auto-rebalancing, and protocol-level security. You can find Vault trading on the Hyperliquid exchange account connection page in the Trade on Vault section. Try it in GT App 👉 🤖 AI Hedge Fund Experiment Live An experimental AI Hedge Fund powered by 5 independent LLM models is live on Hyperliquid. Each model manages $10,000 to test different AI trading personalities and allocation strategies. Discover it now here 👉 📈 Isolated Margin & AI Risk Tools Isolated Margin is live across GT App for precise risk management. Enhanced with AI-powered logic, it assists with dynamic asset monitoring and smarter strategy deployment. Try it in GT App 👉 🔥 Top Strategy Performance Top trader strategies like "lebakien" achieved over +141% profit this month. Users can explore metrics and follow the strategies of top traders directly in the marketplace. Explore Marketplace 👉 🛠 Key Product Updates ⚙️ Strategy Discovery: enhanced demo trading flows and top trader strategy integration. ⚙️ AI Strategy Chat: demoed a flow to create, launch, and test strategies via natural language chat. ⚙️ Advanced Execution: added manual safety orders for granular control over active positions. ⚙️ Testing & Validation: optimized historical data validation for more accurate strategy testing. ⚙️ Knowledge Hub: launched GT Protocol Learn and a new Knowledge Base for streamlined support. ⚙️ Performance: upgraded website structure and improved overall page responsiveness. Find all the latest GT App updates Here 👉 Discover guides, insights, and resources in Learn 👉 and Knowledge Base 👉 📰 GT Protocol AI Digests 4 new AI Digest issues (No.89–92) are live on Medium, covering AI-native hardware, data privacy, and the evolution of AI agents. Read More 👉 May brought institutional-grade AI strategy management closer to every user.

GT Protocol

32,774 görüntüleme • 2 ay önce

A viral paper "Language Model Represents Space and Time" recently claims that LLMs learn "world models". As much as I like Max Tegmark's works, I disagree with their definition of world model. World model is a core concept in AI agent and decision making. It is our mental simulation of how the world works given interventions (or lack thereof). A world model captures causality and intuitive physics, telling the agent what is likely and what is impossible. It can and should be used for counterfactual reasoning, i.e. "what ifs": what would happen if I knock over a cup of water? Where would I have been if I had not taken that bus? Yann LeCun Yann LeCun says it well in his position paper ( I quote: "Using such world models, animals can learn new skills with very few trials. They can predict the consequences of their actions, they can reason, plan, explore, and imagine new solutions to problems. Importantly, they can also avoid making dangerous mistakes when facing an unknown situation." The first use of the term World Model in deep policy learning is attributed to hardmaru & Jürgen Schmidhuber: In their seminal paper, an agent masters shooting skills in the popular game Doom (demo below) by learning in imagination, using an internal world model as a "physics simulator". To put in a simple Python math formula, world model learns a function F(s[0:t-1], a) -> s[t:], which takes as input the observed past and current action, and outputs plausible future states. Now the definition of World Model in Tegmark's paper seems to be about predicting GPS coordinates and time eras. I see this as just a classification task with no causal learning and simulation going on. You cannot make meaningful interventions against that model, nor can you optimize any decision making in a closed feedback loop. As for the "space & time neurons", I think they are most similar to the "sentiment neuron" that OpenAI published in 2017: Predicting GPS is conceptually no different from predicting sentiment in my opinion. I don't think their experimental results are wrong - just that their conclusion is on shaky grounds. I welcome any debate! Paper link:
0:15

A viral paper "Language Model Represents Space and Time" recently claims that LLMs learn "world models". As much as I like Max Tegmark's works, I disagree with their definition of world model. World model is a core concept in AI agent and decision making. It is our mental simulation of how the world works given interventions (or lack thereof). A world model captures causality and intuitive physics, telling the agent what is likely and what is impossible. It can and should be used for counterfactual reasoning, i.e. "what ifs": what would happen if I knock over a cup of water? Where would I have been if I had not taken that bus? Yann LeCun Yann LeCun says it well in his position paper ( I quote: "Using such world models, animals can learn new skills with very few trials. They can predict the consequences of their actions, they can reason, plan, explore, and imagine new solutions to problems. Importantly, they can also avoid making dangerous mistakes when facing an unknown situation." The first use of the term World Model in deep policy learning is attributed to hardmaru & Jürgen Schmidhuber: In their seminal paper, an agent masters shooting skills in the popular game Doom (demo below) by learning in imagination, using an internal world model as a "physics simulator". To put in a simple Python math formula, world model learns a function F(s[0:t-1], a) -> s[t:], which takes as input the observed past and current action, and outputs plausible future states. Now the definition of World Model in Tegmark's paper seems to be about predicting GPS coordinates and time eras. I see this as just a classification task with no causal learning and simulation going on. You cannot make meaningful interventions against that model, nor can you optimize any decision making in a closed feedback loop. As for the "space & time neurons", I think they are most similar to the "sentiment neuron" that OpenAI published in 2017: Predicting GPS is conceptually no different from predicting sentiment in my opinion. I don't think their experimental results are wrong - just that their conclusion is on shaky grounds. I welcome any debate! Paper link:

Jim Fan

594,014 görüntüleme • 2 yıl önce

Solidus Ai Tech Announcement As we approach the end of the year, we want to share a clear and considered update with our community. The final weeks of the year are shaped by holiday periods, Christmas breaks, and New Year’s downtime. Across the industry, attention drops, teams are offline, and meaningful engagement slows. Launching major products during this window would limit visibility, momentum, and adoption. After internal alignment across the entire team, we have collectively agreed to prioritize impact over timing. We are fully aligned on our goals, our roadmap, and the long-term direction of Solidus AI Tech. 2025 has been a challenging year for many. High volatility driven by geopolitical issues, increased institutional control over markets, and liquidity being pulled from altcoins have tested builders and communities alike. Through it all, our focus has remained unchanged: building real infrastructure, real products, and a sustainable ecosystem. For this reason, our upcoming products, the Compute Marketplace, Agent Forge 2.0, and Vision Makers, are now scheduled for release in early 2026, at a time when attention, participation, and momentum are back at full strength. This ensures each release receives the focus, usage, and traction it deserves. We would like to take this opportunity to wish everyone a Merry Christmas and a happy holiday season. Thank you for your continued support, patience, and belief in what we are building. Further updates will be shared in due course.
0:13

Solidus Ai Tech Announcement As we approach the end of the year, we want to share a clear and considered update with our community. The final weeks of the year are shaped by holiday periods, Christmas breaks, and New Year’s downtime. Across the industry, attention drops, teams are offline, and meaningful engagement slows. Launching major products during this window would limit visibility, momentum, and adoption. After internal alignment across the entire team, we have collectively agreed to prioritize impact over timing. We are fully aligned on our goals, our roadmap, and the long-term direction of Solidus AI Tech. 2025 has been a challenging year for many. High volatility driven by geopolitical issues, increased institutional control over markets, and liquidity being pulled from altcoins have tested builders and communities alike. Through it all, our focus has remained unchanged: building real infrastructure, real products, and a sustainable ecosystem. For this reason, our upcoming products, the Compute Marketplace, Agent Forge 2.0, and Vision Makers, are now scheduled for release in early 2026, at a time when attention, participation, and momentum are back at full strength. This ensures each release receives the focus, usage, and traction it deserves. We would like to take this opportunity to wish everyone a Merry Christmas and a happy holiday season. Thank you for your continued support, patience, and belief in what we are building. Further updates will be shared in due course.

AITECH CLOUD NETWORK

51,425 görüntüleme • 7 ay önce

Season 2 of Valiants: Tap-Tap is here!🌟 It’s time to dive into the new and exciting world of Valoria! Here’s everything you need to know: Now available here! 🔥 New Points Store Your efforts in Season 1 have paid off. Now, you can use your store points to redeem amazing rewards. What will you find? Surprise boxes containing exclusive items in Valiants: Tap-Tap and Valiants: Arena, NFTs that you can trade in the future, and a portion of the $VGN Airdrop allocation. Important: For now, the boxes can only be purchased, but soon you’ll be able to open them to discover what’s inside. Stay tuned for updates so you don’t miss anything! 🕒 🎁 Wild Spin - Spin and Win Introducing the new **Wild Spin**, where each spin could change your fate. Spins will be awarded based on the activity and performance of your friends with a good User Score. So, stay active and keep connecting with your teammates to maximize your chances! What can you win? Experience, unlocks, and even USDT prizes that you can withdraw directly to your airdrop wallet. Tip: Use your USDT winnings to purchase additional spins and keep the wheel turning. How far will your luck take you? 🎰 💥New Valiants and Items The battle in Valoria heats up with the arrival of new Valiants and accessories. These exclusive items will allow you to explore new strategies and challenge your opponents like never before. 📋 Patch Notes Not only are we introducing new features, but we’ve also made several improvements and adjustments to provide you with a smoother and more satisfying gaming experience. Here are all the details: - Daily Combo Changes: The combo is now linear, meaning the challenge has increased. Can you keep up the streak? This change is designed to reward the most skilled and dedicated players. - Daily Login Update: Starting from day 10, the rewards get even better. Don’t miss a single day to maximize your benefits! We’ve also adjusted the progression so that each login brings you closer to more significant rewards. - Complete UI Redesign: We’ve revamped the entire user interface to make it more intuitive and visually appealing. Additionally, you can now choose between two visual themes: the serenity of Kai or the energy of Mimi. We’ve even added some music to accompany your adventure! These improvements are designed to make your time in Valoria even more enjoyable. We hope you love them as much as we do! ✨Don’t miss out on this new adventure! Explore all the new features in Season 2 and discover how to dominate the new world of Valoria. Remember, every decision can bring you one step closer to victory. See you in the game!🔥
0:12

Season 2 of Valiants: Tap-Tap is here!🌟 It’s time to dive into the new and exciting world of Valoria! Here’s everything you need to know: Now available here! 🔥 New Points Store Your efforts in Season 1 have paid off. Now, you can use your store points to redeem amazing rewards. What will you find? Surprise boxes containing exclusive items in Valiants: Tap-Tap and Valiants: Arena, NFTs that you can trade in the future, and a portion of the $VGN Airdrop allocation. Important: For now, the boxes can only be purchased, but soon you’ll be able to open them to discover what’s inside. Stay tuned for updates so you don’t miss anything! 🕒 🎁 Wild Spin - Spin and Win Introducing the new **Wild Spin**, where each spin could change your fate. Spins will be awarded based on the activity and performance of your friends with a good User Score. So, stay active and keep connecting with your teammates to maximize your chances! What can you win? Experience, unlocks, and even USDT prizes that you can withdraw directly to your airdrop wallet. Tip: Use your USDT winnings to purchase additional spins and keep the wheel turning. How far will your luck take you? 🎰 💥New Valiants and Items The battle in Valoria heats up with the arrival of new Valiants and accessories. These exclusive items will allow you to explore new strategies and challenge your opponents like never before. 📋 Patch Notes Not only are we introducing new features, but we’ve also made several improvements and adjustments to provide you with a smoother and more satisfying gaming experience. Here are all the details: - Daily Combo Changes: The combo is now linear, meaning the challenge has increased. Can you keep up the streak? This change is designed to reward the most skilled and dedicated players. - Daily Login Update: Starting from day 10, the rewards get even better. Don’t miss a single day to maximize your benefits! We’ve also adjusted the progression so that each login brings you closer to more significant rewards. - Complete UI Redesign: We’ve revamped the entire user interface to make it more intuitive and visually appealing. Additionally, you can now choose between two visual themes: the serenity of Kai or the energy of Mimi. We’ve even added some music to accompany your adventure! These improvements are designed to make your time in Valoria even more enjoyable. We hope you love them as much as we do! ✨Don’t miss out on this new adventure! Explore all the new features in Season 2 and discover how to dominate the new world of Valoria. Remember, every decision can bring you one step closer to victory. See you in the game!🔥

Valiants

81,648 görüntüleme • 2 yıl önce