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Hi there, this is your daily ☕️ AIpresso.
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In today's newsletter: 🛡️ Google unveils Gemini 4 🤖 OpenAI builds AI that designs chips 🕵️ Chinese AI firm caught probing OpenAI's secret reasoning 🔓 GLM-5.3 nearly matches Claude at hacking 🇨🇳 DeepSeek open-sources Huawei chip tools Plus: 🎁 6 more stories you might like, 🛠️ 5 engineering & practice picks, 🧰 7 tools, and 📚 5 papers.
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🛡️ Google unveils Gemini 4
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- Google has unveiled Gemini 4 Argon, its first new flagship generation since Gemini 3 last November, rolling it out first to a small group of cybersecurity defenders before paid API customers and AI Ultra subscribers.
- Argon hits a new high of 77.9% on DeepSWE v1.1 for long software engineering tasks, ties for first at 68% on the security-fix benchmark CWE-bench, and lifts its output limit to 1M tokens from 64,000.
- It launches at $2 per million input tokens and $10 per million output, though Bloomberg reports Google staff find it does well on benchmarks but weaker in real use, struggling with some coding tasks.
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🤖 OpenAI builds AI that designs chips
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- OpenAI and Synopsys signed a multi-year deal to jointly build GPT-Synopsys, a model trained to operate professional EDA tools directly and iterate chip designs toward verified silicon faster.
- Engineers hand the system objectives like power, performance, area, timing or verification, and agents run the workflows, interpret results, modify designs, and loop until producing results humans can review.
- It runs on OpenAI infrastructure and integrates with Synopsys.ai and Autopilot, whose prior deployments showed up to 50x faster verification closure, while customer chip-design data is encrypted and excluded from training.
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🕵️ Chinese AI firm caught probing OpenAI's secret reasoning
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- OpenAI published "Disrupting a coordinated model-distillation campaign," attributing a core cluster of activity that tried to extract its protected reasoning to individuals tied to Moonshot AI, the lab behind Kimi K3.
- The campaign copied encrypted reasoning from one conversation and asked a model in another to decrypt and transcribe it, peaking at 16,000 requests across more than 4,000 users in late July before OpenAI shut it down.
- OpenAI says the effort never broke its encryption or accessed stored conversations, only manipulating model interactions to reproduce hidden reasoning in a scaled way that violated its terms of service.
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🔓 GLM-5.3 nearly matches Claude at hacking
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- Anthropic published a report claiming Zhipu AI's open-weight GLM-5.3 can autonomously develop cyberattack exploits at nearly the level of its own unreleased Claude Mythos model, with guardrails that are easy to bypass.
- On Anthropic's Exploitbench, GLM-5.3 built end-to-end Chrome exploits in 50 of 410 runs, just behind Mythos' 56, while Kimi K3 and DeepSeek V4.1 Flash both scored 0%; prefilling thinking tokens dodged its guardrails 92% of the time.
- Abliteration drops GLM-5.3's refusal rate to 6%, but running the abliterated model needs 306 GB of VRAM and a cluster of eight Nvidia H200s, and generating ~100M tokens would cost roughly $8,400 over 11 days, likely out of reach for most attackers.
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🇨🇳 DeepSeek open-sources Huawei chip tools
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- DeepSeek has open-sourced six software tools adapted for Huawei's Ascend AI chips, giving Chinese developers a homegrown alternative to Nvidia's CUDA stack as US export controls keep advanced American processors out of reach.
- The centerpiece is an Ascend-compatible build of TileLang, DeepSeek's high-level language for writing performance-critical kernels, now supporting the Ascend 950 with native code generation, automatic scheduling and synchronization, positioned directly against CUDA.
- DeepSeek and Huawei also co-developed a "supernode" system running across 128 Ascend 950 accelerators tuned to balance compute and data movement, though how much these tools narrow Nvidia's performance gap remains unanswered.
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🛠️ Engineering & Practice
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Other
news & articles you might like
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OpenAI answers TypeSafe’s Jev with a Decision API built on Luna
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Google figures out how to watermark AI-designed proteins
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Broadcom (AVGO) extends $42 billion credit line to Anthropic in major AI bet
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AI models are sharing sensitive data from tech companies in new 'PixelLeak' screenshots
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Scale-up interconnect startup CScale launches with $188M in funding
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Cohere’s faster query model barely dents retrieval quality in its tests
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📚 Trending papers & reports
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> Selective self-coaching lets a reasoning model teach itself only at the critical moments in its own work, lifting math and science accuracy by up to ~3 points for roughly 3% extra training cost.
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> Agent handoffs let one AI pass its already-digested context notes to a different model family instead of re-reading everything, making teamwork up to ~11x faster with no retraining and matching normal quality.
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> Synthetic textbooks show that organizing AI training material into full, coherently structured books, not just rewritten snippets, lifts model performance by ~1 point, proving how you package data matters as much as what it says.
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> Smart replanning timing teaches AI agents to decide for themselves how many steps to run before stopping to rethink, boosting task success by ~3 to 16 points while making fewer decisions overall.
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> Ethical personas in AI training show that teaching a model to be safe on just a few topics reliably makes it behave safely across the board, consistently adopting the broad moral stance it was trained on.
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🧰 Tools & repos
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LUCI Desktop: locally records your screen history and meeting transcripts, letting AI agents like Claude Code and Cursor retrieve forgotten pages and past decisions.
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Semos.ai Manager Agents: analyzes your meetings to flag overdue feedback, missed recognition, and avoided conversations, helping managers prioritize what needs attention.
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Dots by OpenAI: always-on ChatGPT agents with their own cloud computers and browsers, connecting to 4,000+ apps to autonomously complete tasks while you review results.
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Chat.sh: self-hosted help center with AI search that writes cited answers, lives on your own domain, and exports pages as markdown for LLMs.
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America.gov: ask plain-language questions and get clear answers from U.S. federal agencies in one place, available in English, French, and Spanish.
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Dina 4.5: a native macOS app for recording, editing, and captioning video, featuring transcript-based editing, AI captions, and 8K exports
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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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