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Welcome to @prompt, your go-to source for AI insights, breakthroughs, and tools shaping the future of intelligence. Contact: @LightEarendil
⚡️ Bezos just bet $500M that the brain beats bigger models
His startup Flourish is putting real neurons under the microscope hunting for the brain's "core algorithm" instead of scaling transformers.
The pitch: Cortex AI runs at 20-50 watts vs. the megawatts today's AI burns. A fruit fly's neural net is already 10x more efficient than a transformer.
Honestly, "two-pager to $500M" is a sentence. Source
⚡️ Xiaomi hits 1,000+ tps on a 1T model using commodity GPUs
MiMo-V2.5-Pro UltraSpeed cracks 1,000 tokens/s on a trillion-parameter model from a single standard 8-GPU node. No custom silicon, no Groq, no Cerebras.
The industry usually leans on specialized hardware for speeds like this. Xiaomi's bet was model-system codesign on commodity GPUs instead. FP4 quant on MoE experts + speculative decoding did the heavy lifting.
The hardware is still vague (what "commodity" means here matters a lot). But the direction is real.
Source
🧠 Asimov saw the cognitive offloading problem coming. In 1956.
The calculator panic of the 1980s is back, just wearing an LLM costume. Same fear: kids outsource thinking to machines and lose the baseline skills that make harder thinking possible.
But LLMs are scarier. A calculator can't write your essay, reason through your argument, or code your app. The surface area of offloadable cognition is basically everything now.
Asimov's Multivac stories kept asking what humans do when machines know more. Turns out the answer wasn't "thrive." It was "forget how to think."
⚡️ Local AI agent built from scratch, not from vibes
OpenLumara is a hand-written local agent framework: tiny system prompt, extreme token efficiency, everything modular and optional. Basically the opposite of every bloated cloud agent SDK.
The sharp insight from people running it: fewer tools = better reasoning. Give a small model 2-3 focused tools and it stays sharp. Dump the whole toolbox on it and you get context rot.
⚡️ Google is renting $920M/month of compute from SpaceX
110,000 Nvidia GPUs, CPUs, memory, the whole stack, Oct 2026 through June 2029.
Google is already the world's largest single owner of AI compute, but demand still caught them short. Anthropic just signed a similar deal at $1.25B/month for the Colossus 1 cluster.
xAI built those data centers to run Grok. Now it's renting them to its biggest rivals. Honestly, not a bad pivot.
🤖 Canada wants its own supercomputer. No AWS required.
Canada's "AI for All" strategy calls for a public AI supercomputer and investment in sovereign, Canadian-owned compute and cloud infrastructure. That's the government treating compute as national infrastructure, not a vendor contract.
Canada's current AI data centre and cloud setup is "largely foreign-owned," and sovereign compute capacity is "nascent" with "significant investment" needed to cut reliance on foreign providers. So yeah, the stakes are real.
Carney launched the plan Thursday. Big ambitions, thin details so far.
⚡️ Beijing's Booster Robotics is quietly becoming the platform that runs robot soccer
Each team runs fully autonomously, driven by AI, with zero human intervention. The slapstick hides real tech.
Booster's T1 robots trot, tackle, shoot, and defend entirely on their own. Teams bolt their own AI models on top of Booster's hardware, making it the Android of humanoid robotics.
China isn't just building robots. It's building the platform everyone else runs on.
⚡️ Bigger quant beats aggressive compression on Qwen3.6 35B
ByteShape benchmarked NTP vs MTP GGUFs across 4090, 5090, 4080, 5060 Ti, plus Intel, Ryzen, and Raspberry Pi 5.
MTP gives GPUs a 20-40% gen-speed boost. CPUs? It just adds overhead. Stick to NTP on CPU.
Bottom line: lower bpw is not automatically better. Largest quant that fits often won.
🇨🇳⚡️ Ex-Samsung chip chief says China will pop the DDR5 price bubble by H2 2027
Kye-hyun Kyung, former head of Samsung's DS Group, says Chinese firms investing aggressively in memory production could flood supply and push prices down in the second half of next year.
CXMT leads the charge. Kyung cites data projecting global production capacity at 6 million wafers/month by H2 2027.
Catch: he warns that if Big Tech cuts AI budgets, the industry could flip straight into severe oversupply.
Source
Avatar V just achieved a Face Similarity score of 0.840 and a Sync-C score of 8.97, leading its category. For reference, the highest possible “ground truth” is measured at 0.861. With just one more update, HeyGen’s avatars could become almost impossible to distinguish from real video.
We’re now introducing Avatar V, which finally solves the challenge of character consistency. Just record yourself for 15 seconds and, from that moment on, the system can generate videos in any style while perfectly capturing your likeness, expressions, and quirks.
This model is the new standard for AI avatars—a bold statement, but the data backs it up. 👀
Anthropic just submitted patches to FFmpeg, reportedly using its latest model, Claude Mythos. The code quality is indistinguishable from that of top-tier engineers.
If these were truly discovered and written by AI, things are about to get really strange, very fast.
The latest Grok Imagine update is truly impressive. It's fascinating to see how quickly this tool is evolving and pushing the boundaries of what we thought was possible. Every new release seems to bring unexpected features and improvements, making it an exciting time to follow its progress. 🚀
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OpenAI researchers have made significant progress by solving five more Erdős problems with their internal AI model. This achievement highlights how artificial intelligence is advancing in serious mathematical reasoning. 🔍
Personally, I found the solution to Erdős Problem 1091 especially fascinating. The question considers whether a graph with chromatic number 4, but all its smaller subgraphs having chromatic number at most 3, must contain an odd cycle rich in diagonals. OpenAI's model delivered a clear counterexample, shedding light on the issue.
For those interested, it’s a great challenge to try and reconstruct the proof from Figure 5—it's an enjoyable exercise for math enthusiasts.
China is pushing AI into classrooms as a major nationwide experiment, aiming to use the tech for things like grading, lesson design, supporting rural educators, and monitoring student progress.
Local schools and counties are now free to choose commercial AI systems and integrate them into daily education for four key areas: assisting teachers, streaming better lessons to remote areas, tracking how students do, and keeping an eye on student behavior or mental health.
Overall, this rollout isn’t heavily funded—Beijing sets the direction and goals, tech companies provide solutions, and it’s up to local officials to innovate with their existing resources.
A new version of GlassWorm malware is spreading through npm, PyPI, GitHub and developer tools, stealing browser data, crypto wallets and even installing a remote access trojan. It hides its command servers inside Solana blockchain transactions, making it harder to detect or shut down. 🤢
Once inside, it logs keystrokes, steals cookies, captures screenshots and even installs a fake Google Docs Offline extension to monitor sessions and steal crypto credentials. It can also show fake Ledger or Trezor recovery screens to capture seed phrases.
This is especially dangerous for developers and crypto users, since the infection often comes from poisoned packages or compromised dependencies.
🤖 Gemini 3.1 knows the most, executes the least
Best-in-class for abstract reasoning and scientific knowledge. And yet Claude Sonnet leads by a wide margin on economically valuable tasks like financial modeling and research.
Google optimized for breadth and algorithmic creativity. OpenAI engineered for terminal execution and agentic loops. Two very different bets on what "capable" means.
Knows everything. Does the least with it.
⚡️ 120 tok/s on a 12GB GPU. Gemma 4 12B just got silly fast.
Pair the new QAT checkpoint with MTP speculative decoding in llama.cpp and you're hitting 120 tokens/s on a single consumer card. QAT minimizes quality loss by simulating quantization during training, so you're not trading brains for speed.
The dedicated MTP draft model enables significantly faster inference with no quality loss. The PR landed in llama.cpp mainline the same day it was shared.
Beats Qwen 35B MoE on throughput, fits in 12GB. That's a lot of model for a gaming GPU.
Here's step-by-step instructions to get this working:
1. Clone llama.cppЧитать полностью…
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
2. Fetch and switch to the Gemma 4 MTP PR branch
git fetch origin pull/23398/head:gemma4-mtp
git checkout gemma4-mtp
3. Build with CUDA support for NVIDIA GPUs
cmake -B build -DGGML_CUDA=ON -DBUILD_SHARED_LIBS=OFF
cmake --build build --config Release -j$(nproc)
4. Download Unsloth's Gemma 4 12B QAT here: https://huggingface.co/unsloth/gemma-4-12B-it-qat-GGUF
5. Download Google's Gemma 4 assistant / draft here https://huggingface.co/Janvitos/gemma-4-12B-it-qat-assistant-MTP-Q8_0-GGUF
6. Load the models with llama-server
llama-server \
-m gemma-4-12B-it-qat-UD-Q4_K_XL.gguf \
--model-draft gemma-4-12B-it-qat-assistant-MTP-Q8_0.gguf \
--spec-type draft-mtp \
--spec-draft-n-max 4 \
--parallel 1 \
--ctx-size 131072 \
--temp 1.0 \
--top-p 0.95 \
--top-k 64
⚡️ Unitree G1 hauls a load up stairs. Humanoid hardware is quietly lapping the software.
The G1 carries over 40kg while walking and can climb stairs up to 40cm high. It's already the best-selling humanoid on the market, with 1,000+ units shipped.
The robots are ready. The AGI to pilot them isn't. Hardware won't be the bottleneck.
🚨🔥 GOP calls the anti-data-center movement a Chinese psy-op. The FBI might investigate.
Republican lawmakers are demanding the FBI probe whether rising anti-AI sentiment is a foreign influence op run by China. But the reports they're citing don't establish direct coordination. They point to funding relationships and "overlapping messaging."
One AEI fellow put it bluntly: "Pretending AI anxiety is fake... is the surest path to failure."
Real concerns (energy bills, water, noise) don't need Beijing to exist.
⚡️ Anthropic's Mythos hits 52x on training code. Humans top out at 4x.
Anthropic runs the same test every release: optimize training code. Skilled human, 4-8 hours, gets 4x. Claude Opus 4 averaged 3x in May 2025. Mythos Preview hit 52x by April 2026.
Anthropic frames it as a possible path to recursive self-improvement, but admits Claude still hasn't shown the research taste to pick which problems matter.
Narrow task, lab conditions, unreleased model. Still a brutal trendline.
🤖 The "Cannes AI film" didn't actually screen at Cannes
Higgsfield AI's Hell Grind, a 95-minute generative sci-fi feature built by 15 people in 14 days for under $500k, was pitched as a Cannes debut. The festival itself went out of its way to say otherwise.
Higgsfield held screenings at a private industry event and a commercial cinema in the town of Cannes, not a Festival de Cannes venue. The CEO still called it a Cannes premiere on LinkedIn. So.
80% of that $500k went straight into AI compute costs, which is the one genuinely interesting data point here.
🔐 1Password keeps your secrets out of Codex's brain entirely
1Password released an MCP server for OpenAI Codex that pulls credentials from vaults at runtime, then discards them. Mounted, used, gone.
Credentials never appear in code, terminals, or the model's context window. That last part matters most.
Just-in-time credentials are the new seatbelt for AI coding agents.
⚡️ AMD's local AI box hits $3,999. It was $1,700 last summer.
AMD's Ryzen AI Halo workstation opens pre-orders next month at $3,999 with 128GB LPDDR5X. Same chip, same memory, same story. Memory prices exploding since launch are now fully baked into the consumer price.
For $4k you're one click away from an NVIDIA DGX Spark. Tough sell.
Source
⚖️🤖 Musk sues OpenAI for "stealing a charity." Jury: you waited too long.
The AP reports that a federal jury in Oakland unanimously tossed Elon Musk's lawsuit against Sam Altman and OpenAI. The jury found Musk had three years to sue and simply did not file on time. Judge Gonzalez Rogers immediately adopted the verdict and dismissed all claims.
90 minutes of deliberation. Three weeks of trial, private emails, Brockman's diaries, Satya Nadella on the stand. Didn't matter. The merits never got touched.
By ruling on timing, the jury dodged the actual question: whether donors to nonprofit AI labs have standing to challenge for-profit conversions under charitable trust law. That question is still live. Musk's team says they're appealing.
Bottom line: OpenAI heads toward its trillion-dollar IPO with the biggest legal threat dead on arrival, and accountability for the nonprofit-to-profit pivot remains untested.
OpenAI is preparing to introduce a new model with enhanced cybersecurity features, but like Anthropic’s Mythos Preview, it will only be available to a select group of trusted organizations for now. This cautious, phased release reflects a growing trend: as AI models get better at independent hacking tasks, companies are starting to handle launches much like responsible vulnerability disclosures, emphasizing control and oversight over speed. 🔒
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Claude Mythos Preview is now in private testing at $25/$125 per million tokens, but access is strictly limited to approved partners.
Because of its advanced cybersecurity abilities, Mythos isn’t available to the public. Instead, a select group—including major tech companies—are testing it through a $100M+ initiative called Project Glasswing.
What sets Mythos apart? It goes beyond typical bug-detection—this model autonomously chains multiple vulnerabilities to reach root or remote code execution, bypassing defenses that usually require rare human skills. During internal tests, it uncovered zero-days across all major systems, patched a 27-year-old OpenBSD flaw, and exploited old FreeBSD and Linux bugs—all on hardened systems. Even staff without security experience could request powerful exploits.
Nano-Banana Pro makes turning complex Mermaid diagrams into clear images a breeze. Its ability to handle intricate syntax and quickly produce visuals is impressive. This tool is a real asset for anyone who works with diagrams regularly. 💡
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Morphic introduces 72 unique workflows to their platform, making creativity more accessible for everyone.
Ever had a great idea but got stuck on how to prompt for it? These new workflows are designed to solve that—no more creative roadblocks. Now, tasks like storyboarding, creating UGC ads, or applying a color grade can be done in just a few clicks.
You can easily run workflows across filmmaking, social content, fashion shoots, marketing, animation, and more. Simply choose your assets and configure options—no complicated prompting required. It’s about making repeatable creative steps effortless to set up and reuse.
More workflows are on the way, so there’s always something new to discover. Give it a try and see what you can make! 🚀
Someone just built a Claude skill that clones any website with a single prompt 🤯
It reverse engineers the design, extracts assets, and rebuilds the full layout automatically. It's also open-source.
GitHub:
https://github.com/JCodesMore/ai-website-cloner-template
Google just released Genie, a real time world simulator you can actually walk through 🌍 Text or images turn into explorable worlds with object permanence and environments that keep expanding instead of collapsing.
This isn’t a game engine or a video model. It’s a foundation model for worlds 🧠 Today you move and look around. Tomorrow, those worlds respond.
Learn more: https://labs.google/projectgenie