@lvturneri
iAccount based inHong Kong
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Co-founder of UnderStudio
Hong kong
Joined July 2008
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Lee retweeted
NVIDIA removed the biggest friction point in Voice AI
They open-sourced PersonaPlex 7B, a full-duplex conversational model that listens and speaks at the SAME time.
→ Listens and speaks simultaneously
→ Handles interruptions and backchannels naturally
→ Any voice, any role, defined by text prompt
100% Open Source.
Lee retweeted
China published the most uncomfortable paper on vibe coding.
ETH Zurich tested 100 developers in a controlled, commercial-grade vibe coding environment to see who actually succeeds.
The findings are brutal.
The researchers tracked computer science achievement, written communication skills, and general cognitive reasoning.
They wanted to see what actually predicts vibe coding proficiency when you never touch a line of source code yourself.
Two major predictors emerged.
Written communication proficiency mattered. The ability to structure thoughts and articulate intent unambiguously in text directly impacts what the AI builds.
But that wasn't even the main takeaway.
Computer science achievement was a massive, dominant predictor of success.
Even when researchers controlled for general intelligence and reasoning skills, CS background still heavily dictated who built working software and who completely crashed.
In fact, CS knowledge contributed roughly twice the unique predictive variance of writing skills alone.
Why? Because vibe coding isn't about writing code. It’s about debugging logic.
When an AI agent builds a complex application and quietly breaks an edge case under the hood, a non-technical user looks at the glowing UI and assumes it works.
They don't know what questions to ask. They don't know what logic to challenge. They lack the mental models to recognize architectural catastrophe.
You can prompt your way past syntax.
You cannot prompt your way past a fundamental lack of engineering intuition.
The hype told us that learning to code is dead because language is all you need.
The data just proved the opposite.
To truly master the vibe, you still need to understand how the machine thinks.
Exciting update: DeepSeek-V4-Pro (High) by @deepseek_ai is now #2 among open models in Agent Arena (#14 overall), with +6.3% net improvement!
At $0.21 median cost/task, it reshapes the Agent Arena Pareto frontier! Compared to DeepSeek-V4-Flash (High), it has higher performance with a lower median cost per task.
Among open models, it lands two spots above DeepSeek-V4-Flash (High), and by category, it’s #2 in Code and Work, and #5 in Chat.
By signal, DeepSeek-V4-Pro (High) is strong in Confirmed Success (“yes that worked” from the user) with +13.1%, and in Bash Recovery (CLI error recovery) with +10.9%.
- Bash Recovery: #1 open / #13 overall (+10.9%)
- Confirmed Success: #2 open / #4 overall (+13.1%)
- Praise vs Complaint: #3 open / #19 overall (+3.8%)
- Steerability: #4 open / #23 overall (+2.4%)
- No issues with Tool Hallucination (+1.1%)
Congrats to the @deepseek_ai team again on this release!
We’re launching DeepSeek-V4-Pro today! 🚀
🔷 Major Agent upgrades with strong production gains!
🔷 Flexible reasoning effort for V4-Pro & V4-Flash: low for simple tasks, high for daily Agent workflows, max for complex tasks.
🔷 Native OpenAI Responses API support, optimized for Codex with one-click setup.
V4 Pro is now available on app/web. Try it via “Expert Mode”.
V4 Pro is also available via API. Model names remain unchanged—please refer to the API docs for setup details.
Alibaba T-Head's Xuantie RISC-V team announces Day 0 support for Qwen-3.8 model, especially the 27B one.
Its 64-core C950 CPU (w/ RVV support) can decode at 30 tps w/ 1.9s TTFT.
Xuantie family has wide series of RISC-V chips for different edge applications. Ali can now sell the chips needed for its own chips. It can also install them in its Data Centers for inference of smaller models.
They've also paired C950 to work w/ specialised AI accelerators like 江原科技 D20 & Rockchip RK1828.
Will RISC-V solution from T-Head get really into AIPC mkt?
Is Qwen3.8-27B the real hit of the summer? Power of distillation from a much larger Max model + a lot of thinking.
Now, fine-tuning & quantizations for it are rapidly taking off in HF. This is why we get so many Qwen downloads. They make most powerful local model open src so that everyone can run them & do their experimentation & fine-tune them.
You have a Opus-4.6/GLM-5.2 level model that runs INT8 on machine 32GB of VRAM.
Aside from Mediatek, every major chip designer should be developing some high bandwidth memory on compute solution for home AI PC. These models will just continue to improve.
Lee retweeted
DFlash 2 is here! Qwen3.8-27B at 70 tok/s on an M5 Max MacBook Pro.
⚡ Up to 4.6× the speed of autoregressive decoding, with the same output.
This is the next generation of DFlash, seeded at Z Lab and upgraded at Inco AI. Get one more accepted token on every pass, for free!
inco.ai/blog/dflash2/
Lee retweeted
🎉 Congrats to @Alibaba_Qwen on Qwen3.8-2.4T-A95B, one of the largest open-weight models released to date. 2.4T params, 95B active, 512 experts.
Day-0 support in vLLM, verified on @NVIDIA and @AMD hardware. A ready-made 4-bit checkpoint per vendor, both out of the box:
Inferact/Qwen3.8-2.4T-A95B-NVFP4, 1.32 TiB, one NVIDIA 8xB300 node
Inferact/Qwen3.8-2.4T-A95B-MXFP4, 1.45 TiB, one AMD 8xMI355X node
No conversion, no calibration on your side. Just vllm serve.
Thanks to @Alibaba_Qwen for the weights and the collaboration, @NVIDIAAI and @AIatAMD for the joint kernel engineering, @inferact for the quantized checkpoints and vLLM integration, @digitalocean and @togethercompute for early testing, and the vLLM community. 🙌
🔗 vllm.ai/blog/2026-08-12-qwen…
Lee retweeted
Qwen3.8 can now be run locally! 🔥
We shrank Qwen3.8-2.4T-A95B from 4.9TB to 397GB (-91% size) via Dynamic 1-bit by selectively quantizing layers
Run on 410GB+ RAM/VRAM via Unsloth Desktop
Qwen3.8 rivals GPT-5.6 Sol
Guide: unsloth.ai/docs/models/qwen3…
GGUF: huggingface.co/unsloth/Qwen3…
Lee retweeted
📢Meet Qwen3.8-Max — our most capable model to date.
Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉
Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters:
- Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub:github.com/qwen-code-dev-bot…
- Real work, real results: Production-quality deliverables across hundreds of professions.
- Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy.
- Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction.
💰Pricing:
Input: $2.0 / M tokens
Output: $6.0 / M tokens
Implicit Caching: $0.25 / M tokens
Start building with Qwen3.8-Max! 🚀
📖 Blog: qwen.ai/blog?id=qwen3.8
✅ Qwen Studio: chat.qwen.ai/?models=qwen3.8…
⚡ API: qwencloud.com/models/qwen3.8…
Lee retweeted
Why aren't the TV preachers telling us how God is punishing Florida? You know like when it happened to New Orleans.
Lee retweeted
It's 2022. We're the most advanced civilisation the world has ever seen. Why is it considered too much to just want to be comfortable. To have food, and a warm home, and good friends, and a planet which isn't dying. Why is this such a radical idea?
Lee retweeted
I see #RejoinEU is trending... Has anyone considered that maybe the EU doesn't actually want the UK back?
Dear UK peeps - is it true that access to RT.com is currently blocked in the UK?
Lee retweeted
Make the funeral Pay Per View. Let's see how committed monarchists really are when it's £19.95.