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Hi there, this is your daily ☕️ AIpresso.
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In today's newsletter: 🦠 New malware uses AI to plan attacks 💰 OpenAI cuts GPT-6 API prices in half 📱 Qualcomm chip runs 30B AI on phones 🤖 Claude Opus 5.5 matches Fable's quality ⚙️ vLLM adds support for more chips Plus: 🎁 7 other news you might like, 🛠️ 4 engineering & practice picks, 🧰 7 tools, and 📚 5 papers.
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🦠 New malware uses AI to plan attacks
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- Cisco Talos documented ClosedQuorum, a Go-based Windows implant that queries Gemini, DeepSeek, Qwen, and Mistral models to autonomously pick its next post-compromise action with no human operator in the loop.
- The malware feeds reconnaissance data to a voting panel that chooses from a fixed decision set, including shellcode injection via process hollowing or Early Bird APC, then exfiltrates stolen data through a Discord webhook, making the chain fully automated after delivery.
- Talos calls it the first public Windows implant delegating tactical C2 to an AI panel, tying the developer to 2025 carding forum posts, though the analyzed build lacks a lateral-movement handler and can stall on API rate limits, malformed output, or downtime.
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💰 OpenAI cuts GPT-6 API prices in half
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- OpenAI cut API prices for its new GPT-6 Sol and Luna models by 50% versus their GPT-5.6 counterparts, with Luna output tokens dropping 58% as more affordable alternatives to flagship GPT-6 Astra.
- GPT-6 Sol now runs $2 per million input and $10 per million output tokens, while Luna hits $0.10 and $0.50, alongside caching upgrades that raise default cache-hit rates and preserve earlier context when reasoning effort or tool availability changes.
- A new Prompt Caching Dashboard surfaces reuse metrics and flags missed caching opportunities, with GitHub reporting fresh-processing token share fell over 50% across billions of requests, though the 90% cached-input discount just matches existing GPT-5.6 pricing.
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📱 Qualcomm chip runs 30B AI on phones
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- Qualcomm's new Snapdragon 8 Elite Extreme Gen 6 chipset can run up to 30B-parameter MoE models directly on phones via its Hexagon NPU, a jump from the ~4B-parameter ceiling most on-device hardware has faced.
- Unveiled Tuesday at the Snapdragon Summit alongside the Snapdragon 8 Elite Gen 6, the platform targets ambient agentic workloads through the Oryon CPU, Hexagon NPU, and an X105 5G modem, prioritizing battery efficiency and parallel GPU throughput.
- Both chips will ship in 2027 flagships from Samsung, Xiaomi, Motorola, OnePlus, Oppo, Vivo, and others, with the Motorola Signature 27 named as one of the first, though Qualcomm hasn't disclosed the full device lineup at launch.
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🤖 Claude Opus 5.5 matches Fable's quality
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- Anthropic shipped Claude Opus 5.5 today, delivering Fable 5.1-level quality on most work while costing roughly 40% less to run than Opus 5, which arrived under two months ago.
- Token prices drop 20% versus Opus 5, output runs 30%+ faster, and Box reports the model used a third of the tokens with answers 40% less verbose, no accuracy loss.
- Deloitte says the lowest effort setting caught 72% of known bugs versus Opus 5's 56% at high effort, though safeguards reroute cybersecurity requests to Opus 4.8 and biology tasks to Opus 5.
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⚙️ vLLM adds support for more chips
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- vLLM is adding a set of hardware-agnostic layers so it can keep serving diverse models across older GPUs, prosumer cards, and out-of-tree accelerators, even as frontier "flat" model definitions break compatibility with torch.compile.
- The portable layers, built entirely from native PyTorch and DSLs like Triton and Helion, land within 3.4% of native token throughput on NVIDIA H100 across three recent models, sometimes edging past CUDA-optimized FlashAttention and CUTLASS paths.
- Enabled via USE_HW_AGNOSTIC=1 with the transformers backend and already validated on IBM Spyre for Gemma 4, Qwen3, and Granite 4.2, though state-of-the-art performance on Blackwell and CDNA 4 is explicitly not a goal of these definitions.
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🛠️ Engineering & Practice
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> How OpenAI Built GPT-Live: OpenAI's GPT-Live uses a fast voice model that listens and talks simultaneously while delegating hard questions to a bigger reasoning model, so conversations stay natural without pauses.
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Other
news & articles you might like
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Meta’s Muse is outpacing ChatGPT’s early mobile launch
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China's ByteDance gained access to over 2,000 Nvidia B200 chips through Norway data center
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Training data provider Snorkel AI raises $350M at $3.5B valuation
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European neocloud Verda raises $189M to build the AI infrastructure of tomorrow
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Text handoffs slow AI models down. C2C lets them communicate through KV caches instead
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DevDay: New Plans and new platform for building AI apps
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Introducing DigitalOcean Managed Agents: One AI-native stack to power your intelligence
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📚 Trending papers & reports
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> AI-watching-AI safety checks map the sneaky ways one AI overseer might secretly collude with the AI it's supposed to police, giving companies a clearer test for whether such oversight can actually be trusted before deployment.
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> Risk-averse AI training shows that teaching a model to play it safe on small bets carries over to enormous ones, lifting cautious choices from 2% to ~70%, a possible safety net if AIs turn out misaligned.
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> Nuclear escalation in AI agents persists across 13 models even when prompts explicitly warn of nuclear harm, showing that ethical judgment scoring well on isolated dilemmas often fails to steer behavior in complex, high-stakes strategy scenarios.
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> Audio AI reasoning tends to lose track of what it actually heard as it thinks longer, but a new training method fixes this, roughly doubling perception accuracy to ~64% and boosting overall performance to ~75%.
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> Sign-based training math pins down exactly when a popular shortcut for teaching models beats the standard method, showing it can improve faster per dollar of compute in noise-heavy settings.
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🧰 Tools & repos
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Ruby UTCP: ruby implementation of the Universal Tool Calling Protocol, letting AI agents call native APIs directly via JSON manifests without MCP wrapper overhead.
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Lumiko: records your screen and auto-generates cursor-tracked zoom and pan effects, with browser trimming, secret blurring, webcam bubble, and 4K local exports.
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Zella: records and edits screen or camera videos on-device, auto-generating captions, cutting silences, removing filler words, and adding zoom effects offline.
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Compute:Arena: community-sourced benchmark database for local AI models, comparing token speeds across hardware, runtimes, and quantisation levels to guide your setup choices.
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redcell: an AI red-team platform where autonomous LLM agents run full penetration tests in a Kali container and generate reports.
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BiBimba: stores searchable clipboard history and screenshots, using on-device AI to extract text from images, then translate, summarize, and rewrite locally on Mac.
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You can check the previous tools here, or add your tool here
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