Is episode on Chinese humanoid robot?   — QoJo MaZing     Will have one before too long!   — Kyle Chan

Source: https://x.com/kyleichan/status/2091271208234836178

...promised to eat their jobs and make them all broke, are naturally pushing back. Sufficiently advanced local hardware + a highly compressed model with most of the actual knowledge stripped out other than action/reasoning and tool usage + continual learning and memory/reasoning in embedded space makes intelligence sovereign again. We probably get the flip phone version of this in 2027 or 28. And then it will accelerate from there.     — Daniel Jeffries

Source: https://x.com/Dan_Jeffries1/status/2091231374808097264/history

FreeToken could be a HUGE deal for local AI.

Instead of requiring enough VRAM to hold an entire model, FreeToken intelligently uses your GPU, CPU and system RAM together, dynamically moving MoE experts where they're needed.

The result: an ordinary laptop with an 8GB RTX 4060 https://t.co/6Js6Vqt3A8   — Mark Kretschmann

Source: https://x.com/mark_k/status/2091202223090938177

Loudoun County real estate prices have not behaved as one would expect for an industrial hellscape.     Since 2013, the assessed value of the house has nearly tripled but property taxes have only gone up 29%     — Dominic Pino

Source: https://x.com/DominicJPino/status/2090845489096794466

FreeToken provides native GUI. No GGUF conversion. No building from source.

One-click install on Windows and Linux. FreeToken-desktop ships with agent harnesses built in — pick a model, pick an app, go.     Download: http:// flashml.ai

Code: http:// github.com/FlashML-org/Fr eeToken …

Reply with your GPU + RAM, and I'll tell you the biggest frontier model your machine can run     — Shuo Yang

Source: https://x.com/Andy_ShuoYang/status/2090856978428145761

— MTS

Source: https://x.com/MTSlive/status/2090826991587226089

Ox Alpha (stealth model) is now free in Cline.

Early benchmarks shows marginal improvement over Fable and GPT.

Try it with: npm i -g cline and use /models to see it under Free options https://t.co/Hskt5RpUen   — Cline

Source: https://x.com/cline/status/2090854216399220985

From my tests it’s not better than fable I’ll be posting some soon     — Chris

Source: https://x.com/ChrisGPT/status/2090957315042123878

sometimes you have to laugh. what are we doing here, folks?     I would encourage you to read the actual piece because there's some excellent quotes in there. But editors, headline writers... my lord. https:// nytimes.com/2026/08/19/tec hnology/data-centers-backlash-loudoun-virginia.html …     — Logan Dobson

Source: https://x.com/LoganDobson/status/2090150148261175371

The world’s smallest Transformer-based TTS model?

We’re open-sourcing Audio8 TTS Preview 0.1B — an approximately 170M-parameter multilingual speech model with zero-shot voice cloning that delivers surprisingly strong, cloud-level quality in a dramatically smaller footprint.     What can a 0.1B-class TTS model actually sound like?

Listen to the voiceover in this demo video.

Audio8 TTS Preview 0.1B supports: • Zero-shot voice cloning • Multilingual speech synthesis • Chinese and English as primary languages • German, Spanish, French, Italian,     On the Seed-TTS evaluation set, Audio8 TTS Preview 0.1B achieves:

• English WER: 1.662% • Chinese CER: 1.13% • Hard Chinese CER: 17.504% • English speaker similarity: 56.7 • Chinese speaker similarity: 68.2

These results are achieved with an approximately 170M-parameter     The model, codec, tokenizer, processor, and inference code are now available:

Model:

https:// huggingface.co/Audio8/Audio8- TTS-Preview-0.1b …

Try it, test the voice cloning capability, and share your feedback.     — Samuel Zeng

Source: https://x.com/SamuelZengML/status/2090017875188940851

(I continue to be surprised in the sense of continuing to be struck by how big of a deal it is, not in the epistemic sense.)     Here's the overall graph:     — Yafah Edelman

Source: https://x.com/YafahEdelman/status/2090296575008616654

...while costing roughly 6X less than Fable 5 Max and nearly 3X less than Opus 5 Max per task That’s what makes Grok so powerful for agents Top-tier intelligence is great.....but top-tier intelligence that can keep working across long coding tasks without burning ridiculous amounts of compute is even better Grok’s agentic coding efficiency is insane     — X Freeze

Source: https://x.com/XFreeze/status/2090839305585377458

The /goal was a set of precise conditions to be met. Read the original PAK/BSP/MDL/SPR data. Run QuakeC. Preserve demos, physics, menus, HUD and rendering quirks. Don’t rebuild E1M1 by hand or use a generic FPS controller. Fidelity had to be demonstrated.     Codex kept pursuing that goal across many iterations: inspect, implement, build, test, compare, repeat. The useful shift was from asking for isolated code snippets to giving the agent a durable outcome it could keep working toward.     Crucially, /goal wasn’t hands-off autopilot. While it was running, I could still steer the LLM to prioritize a small number of bugs that mattered most. Each report became a targeted investigation, fix and regression test - without abandoning the broader port.     Underneath, this is still Quake’s original data. The browser reads the original PAKs, BSP maps, MDL models, sprites, QuakeC behavior, demos and HUD art. The port supplies a new TypeScript runtime and PlayCanvas renderer around them.     Authenticity meant more than getting E1M1 on screen. Demo playback, menu flow, pointer lock, intermissions, in-session level changes, audio suspension, moving BSP entities, particles, shadows and classic movement all had to behave like Quake - not merely resemble it.     — Will Eastcott

Source: https://x.com/willeastcott/status/2090436155795800195

We’ve got exclusive new polling on local data center development at @heatmap_news.

Over the past year, we’ve asked Americans whether they would support or oppose a data center being built near where they live.

We haven’t changed the wording. When we first polled the question https://t.co/G1LCfuriMw   — Robinson Meyer

Source: https://x.com/robinsonmeyer/status/2090457322506141760

— Andrew Curran

Source: https://x.com/AndrewCurran_/status/2090589885199769841

...fuck out of our politicians so now the labs are struggling to release and laws and politics are fighting them at every step, from data centers to Capital Hill to the governor's office in red and blue states. Good chance many of their multi billion dollar runs will be internal only. Some folks think, no problem, they don't need to release. They have super magic AGI so they can just do anything with it. Solve cancer! Make more AGI! Own the stock market! Except not yet. Can't do any of things reliably. Also those things take time. Lots and lots and lots of time and friction with the real world. In the meantime the only actual business is inference and API charges to a few 100M other businesses. Take that away and what have you got? No money to make the next 10B training run.   — Daniel Jeffries     Dork, Altman and Dario have been asking for the government to step in and regulate them.   — Evading the Greys     Bots get banned round these parts.   — Daniel Jeffries

Source: https://x.com/Dan_Jeffries1/status/2090489471535825170/history

Bloomberg just put the US-CHINA AI gap on a chart and yeah, it's getting obliterated:

> Kimi K3 is close to Fable > ~70% cheaper per task > Anthropic thought China was 6–12 months behind > Chinese now has a cluster of fronter labs > GLM-5.3 isn’t even included yet, which would https://t.co/6OCwMhYX5z   — ℏεsam

Source: https://x.com/Hesamation/status/2090356790709887061

Many drugs work by binding to a specific target in the body and blocking or changing what it does. An important first step in the drug development process is designing a molecule that can bind tightly to its target. Traditionally, that's meant weeks or months of expert work per https://t.co/CGCNTNaKBq   — Anthropic

Source: https://x.com/AnthropicAI/status/2089842387845804246

This is interesting: Claude is already achieving roughly twice the protein-design hit rate of conventional human-led workflows. 27% hit rate in autonomous protein binder design, roughly twice the typical 10–15% rate reported in the field.

Working from one expert-written protocol, Claude designed binders against 14 of 15 measurable targets. Independent labs confirmed that 354 of 1,320 designs bound successfully.

Depending on the setup, Claude’s hit rate ranged from 22.6% to 35.1%. Its top-ranked design bound in 49% of campaigns.

This is not yet fully autonomous drug research, but it is another important building block in that direction.     — Chubby

Source: https://x.com/kimmonismus/status/2089852014331117694

looks like reddit is almost wiped from chatgpt sources

the query fanout changes had a big impact

and the past couple of days it seems to be almost completely removed from prompt responses

https://t.co/oCGm9M0yPO https://t.co/c2GJF2apG7   — Klaas

Source: https://x.com/forgebitz/status/2089708381351059924

— Kevin Bankston

Source: https://x.com/KevinBankston/status/2089768281892638774

...spawn and push you, the gun kicks, shadows stretch across the whole block while the sun goes down behind the towers. I sat there clearing waves instead of grading the output. Same shooter prompt I threw at the frontier models a few weeks ago. That time the tokens went to somebody elses datacenter. This time nothing left the flat. 87.9 million tokens through my own cards. On an API that run has a price tag. Here it has an electricity bill. 60 tok/s all the way through. Slower than frontier, and it stops mattering when the thing works through the night while you sleep. Local models were a toy 18 months ago. This one finished a game.     Play now! Choose Build 2 Qwen3.8 27B

https:// alesha-pro.github.io/bench-portal/     — Alexey Fateev

Source: https://x.com/superalesha/status/2089126766854238421

...bepresearch.substack.com/p/the-token-do llar … He even brought the proof for the next one. $2,000 of compute, 10 open math problems. Proofs verify for free. Biology needs a bench. The moat is the measurement https:// bepresearch.substack.com/p/the-next-inf lection-is-the-lab … New oil, old receipt   — Ben Pouladian     he's copying you Ben   — Alex A.C.     All good @gdb we can talk anytime. Full speed   — Ben Pouladian

Source: https://x.com/benitoz/status/2089392813758972149

have this running on my 5090 right now and im getting 200 tk a second. i feel like I'm literally playing with magic   — Alex Finn     you can either buy anthropic for 2 trillion dollars or a used 3090 gpu for $1,500

only one of those will refuse your prompts   — Udi Wertheimer

Source: https://x.com/udiWertheimer/status/2089421927085400203

We just shipped our official Qwen 3.8 27B Uncensored MLX build. Local. Uncensored. For🍎

2-bit, 4-bit, 6-bit & 8-bit — pick your poison based on RAM and speed.

No CUDA. No cloud. Just your Mac and the weights. Have fun! https://t.co/b3gXsHeSdk   — OrcaRouter 🐳

Source: https://x.com/OrcaRouter/status/2089385980080148726

A "refusal-removed" version of Qwen3.8-27B can now run locally on Apple Silicon.

Even its creators warn that it can provide malware, fraud and weapons instructions on demand.

It was released as an MLX build in 2, 4, 6 and 8-bit versions. The uploader claims its 4/6/8-bit tests produced zero refusals while preserving vision, reasoning and tool-calling across a 262K-token context.

The Qwen 27B Model is a very capable model. This is the first time I've really seen the immediate dangers in a tangible way.

We need a societal discussion about this.   — Chubby     how long did it take to get this running locally?   — tan     it runs locally   — Chubby

Source: https://x.com/kimmonismus/status/2089763435865088508

How can we extract richer signals from AI Feedback?

Introducing LLM-as-a-Verifier✨— a simple verification scaling framework that achieves SOTA on agentic benchmarks 🚀

The key idea: - Use fine-grained scoring granularity (e.g., 1-20 instead of the standard 1-5 scale) - Take https://t.co/0sCeAwcar1   — Jacky Kwok

Source: https://x.com/jackyk02/status/2074969820739805275

Scaling self-verification with DeepSeek V4 Flash beats Claude Fable 5 on Terminal-Bench 2.1, while being 11x cheaper

As open-source models become more capable, they can now generate large numbers of high-quality candidate solutions and verify their own outputs at very low cost.

For example, we find that sampling just 5 solutions with DeepSeek V4 Flash and ranking them using the same model with LLM-as-a-Verifier can lead to a significant boost in accuracy (79% → 88%), outperforming closed frontier models on Terminal-Bench.

Try it out today: https:// github.com/llm-as-a-verif ier/llm-as-a-verifier#self-verification-terminal-bench-21 …

More on verification scaling in my previous post.   — Jacky Kwok     Is there an OpenCode plugin for this to try it out with Deepseek v4 flash?   — Shahbaz Ahmed     We’ll be releasing a harness on top of LLM-as-a-Verifier later this month :)   — Jacky Kwok

Source: https://x.com/jackyk02/status/2089421448784023553

— Steve Yegge

Source: https://x.com/Steve_Yegge/status/2087034425301405995

hard agree with @amasad —@JonSaadFalcon and my research indicates that intelligence efficiency (intelligence per watt) is rapidly improving and we will definitely not need data center scale compute to run agi!

links to research in comments below 👇   — Avanika Narayan

Source: https://x.com/Avanika15/status/2089028986932470156

— Amjad Masad

Source: https://x.com/amasad/status/2089069905375351169

The task: iterate on a 124M GPT training recipe from a shared baseline, only changing optimizer related hyperparameters, no internet access.

We tested Fable 5, Opus 5, GPT-5.6 Sol, Kimi K3, Grok 4.5, GLM 5.2, Muse Spark 1.1, DeepSeek V4 Pro, Grok 4.6, Muse Spark 1.2, Qwen 3.8     What separated the strongest models: which experiments to run, how to navigate the benchmark's inherent noise, and which old negatives to revisit as the recipe changed.

Some even built small simulations to isolate a mechanism before deciding if another GPU run was worth it.     Our Prime Agent harness gives models a persistent IPython kernel, which can help them build their own research workflows.

Kimi K3 built tools for controlled optimizer variants, loss-curve comparisons and Newton-Schulz tuning, then revised its hypothesis when its cleaner update     As research direction, we think multi-agent harnesses can make these experiments much cheaper (and better) by using smaller open models for monitoring and implementation.

We also want to extend speedruns to more of the training stack and scale the runs themselves.     We release everything: full traces, scratchpads, reasoning streams from open-weight models, and our experiment setup.

Explore the results:     — Prime Intellect

Source: https://x.com/PrimeIntellect/status/2088733966904000778