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Hi there, this is your daily ☕️ AIpresso.
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In today's newsletter: 🎨 OpenAI's image editor gets sketch-to-image 🧬 DeepMind's DNA map could accelerate rare disease research 🧮 OpenAI declines Navier-Stokes prize ⚡ Diffusion AI hits 1,107 tokens per second 🪱 AI-built worm could hijack WeChat accounts Plus: 🎁 7 other news you might like, 🛠️ 5 engineering & practice picks, 🧰 7 tools, and 📚 5 papers.
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🎨 OpenAI's image editor gets sketch-to-image
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- OpenAI shipped ChatGPT Images 2.5, adding a Sketch feature that turns doodles drawn inside ChatGPT into finished images, letting you draw something and tell the model how to render it from that sketch.
- Activated by typing @Sketch, the tool opens a drawing window, and you can now leave comments on specific parts of an image, like changing a cat's eyes from blue to green, to steer edits directly.
- The 2.5 model adds more natural lighting and richer textures, follows editing instructions better across multiple turns, and cuts generation latency by up to 50% versus Images 2.0, now live for ChatGPT, ChatGPT Work, and Codex users on desktop, mobile, and web.
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🧬 DeepMind's DNA map could accelerate rare disease research
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- DeepMind has released AlphaGenome Atlas, a petabyte of precomputed predictions covering all 9 billion possible single-letter changes in the human genome, free for academic use and validated against UK Biobank and Broad Institute data.
- Each variant carries an AlphaGenome Variant Impact score fusing AlphaGenome with AlphaMissense across coding and non-coding regions, shipping with 2,500+ recurrent DNA motifs and running roughly 30 times larger than the AlphaFold database.
- Exeter's Gareth Hawkes found 22% more non-coding associations across 54,000+ UK Biobank genomes, while Broad's team lab-confirmed a DNM1 splice variant tied to epileptic encephalopathy, though commercial access via Google Cloud has no published pricing yet.
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🧮 OpenAI declines Navier-Stokes prize
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- OpenAI has published a Lean-formalized proof of finite-time singularity formation in Navier-Stokes, yet pointedly declined to claim the $1M Millennium Prize, the clearest sign it doubts the result meets Clay's formal criteria.
- Roughly 10,000 concurrent agents ran for ~88 hours from 1-5 September, burning 2.7M messages and ~130B output tokens on an internal model more capable than GPT-6 Astra, which was relegated to a 17-hour verification pass.
- The Lean proof is machine-checkable by anyone, and OpenAI now credits Alpöge and Buckmaster for concurrent forced-Euler work, though the fluid carries "a smooth force applied throughout," leaving whether a forced blowup satisfies the unforced Clay formulation open.
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⚡ Diffusion AI hits 1,107 tokens per second
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- Inception has released Mercury 2.5, a diffusion LLM that generates 1,107 tokens per second on standard NVIDIA GPUs while supporting a 260K-token context window, tunable reasoning, parallel tool calls, and schema-aligned JSON.
- The model claims a 40% intelligence gain over Mercury 2 with quality comparable to GPT-5.6 Luna at Low reasoning, Gemini 3.5 Flash-Lite, and Claude Haiku 4.5, priced at $0.20/M input and $0.75/M output tokens.
- In production, Augment Code cut context-compaction latency 82% and cost 90% by switching to Mercury, and it's live now via Inception, Baseten, and OpenRouter, though the launch discount to $0.04/$0.15 is temporary at 80% off.
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🪱 AI-built worm could hijack WeChat accounts
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- Cybersecurity firm Calif used AI to build WeWorm, a self-replicating worm targeting WeChat's 1.4 billion users, capable of hijacking accounts by exploiting a memory corruption flaw in the app's VoIP stack.
- The AI discovered the RCE vulnerability in two days and weaponized it into a working worm within one additional week, a task Calif says would have required a larger human team several months to complete.
- WeWorm spreads autonomously through friend lists via unanswered VoIP calls, hitting both Android and iOS, granting full account control, though Tencent patched the vulnerability after Calif's July disclosure.
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🛠️ Engineering & Practice
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Other
news & articles you might like
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Suno trained its v6 AI music models with help from Warner and BMG
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Meta debuts its Muse AI agent. Will consumers trust it?
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The shared clipboard inside the sandbox: Cross-account data leakage in ChatGPT
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OpenAI offers AI for chip design, touts cost advantage over open-source, CFO says
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Meta-backed architecture could make an entire data center operate like one computer
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OpenAI’s 80% price cut triggers 10x surge in AI model usage
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Hackers are stealing Claude tokens from subscribers
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📚 Trending papers & reports
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> Field-adapting robots keep learning new tasks after deployment using only their onboard computer, matching a standard robot's performance with 2.5x less training data across machines like humanoids, drones, and off-road vehicles.
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> Sound-based body tracking reconstructs the 3D poses of several people at once using only audio, showing motion can be captured in the dark or through walls without cameras.
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> Cart companion suggestions now tell apart items truly used together from ones merely bought together, so a camera in your basket prompts a matching lens not another camera, across a store serving over 20 million monthly shoppers.
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> Cause-and-effect tracking automatically spots when the rules driving a changing system shift over time, mapping a fresh cause-and-effect picture for each phase, outperforming existing methods on both simulated data and real IT monitoring.
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> Multi-stream model wiring reveals that widening an AI's internal information highways matters mostly in early layers, since disabling later mixing barely hurt performance while cutting early mixing raised errors 41%, pointing to leaner, cheaper designs.
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🧰 Tools & repos
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Harden: local security tool for AI coding agents that vets tool calls before execution, keeping your repo and session data on your machine.
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Noodle Seed: build a branded, no-code AI app for ChatGPT that captures leads, books appointments, sells products, and syncs to HubSpot automatically.
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ChatGPT Images 2.5: generates and edits images from text or sketches with sharper detail, better reference-photo fidelity, and up to 50% faster output.
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Kopai: turns your expertise into a sellable AI agent priced per message, handling billing, discovery, and encrypted knowledge bases so you monetize answers without coding.
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Catenary: a local-first spatial IDE that wires AI agents together with visual cables, isolated task workspaces, built-in editor, terminals, and browser previews.
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Switch: open-source workspace uniting people and AI agents in one shared room across Slack, Teams, Discord, or Mattermost, preserving context through every handoff.
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You can check the previous tools here, or add your tool here
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Our AI Academy has 330+ step-by-step tutorials on ChatGPT, Claude, Perplexity, and every tool that matters. No fluff — just practical workflows you can use at work. Try it free for 7 days.
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