Good morning. It’s Friday, May 9th.

On this day in tech history: 1949: The EDSAC (Electronic Delay Storage Automatic Calculator) executed its first calculation at the University of Cambridge.

In today’s email:

• Chrome’s On-Device AI Catches Scams In Real-Time

• OpenAI’s Stargate Testimony and Developer Releases

• 5 New AI Tools

• Latest AI Research Papers

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Chrome’s On-Device AI Catches Scams In Real-Time

Google has embedded Gemini Nano—an on‑device large language model—into Chrome’s Enhanced Protection on desktop and Android. By analyzing page content locally, it flags phishing, tech‑support fraud and deceptive push notifications in real time, labelling suspect alerts as “Possible scam” and letting users block or override them. Early results show an  80% cut in scammy Search results and hundreds of millions of blocked scam attempts daily.

Cost‑saving for developers

The Gemini 2.5 API now supports implicit caching: requests sharing a prefix with a prior call earn automatic cache hits and a 75% token discount, no explicit setup needed. Minimum prompt lengths have dropped to 1,024 tokens for Flash and 2,048 for Pro, widening eligibility. Usage metadata now reports cached token counts; explicit caching remains available for guaranteed savings.

Gemini on iPad

Gemini 2.0 Flash’s image‑generation update improves text rendering and loosens content restrictions. Google also launched a dedicated Gemini iPad app with split‑view multitasking, bringing the AI assistant’s capabilities to tablet workflows ahead of further Google I/O announcements. A GitHub notebook is available for those looking to experiment with the new features.

OpenAI Fortifies Regional Data Control, Unlocks Bespoke AI Tuning

OpenAI’s massive Stargate initiative—backed by SoftBank, Oracle and MGX—will deploy AI supercomputing hubs worldwide under the banner of “democratic AI.” Beyond expanding access to cutting‑edge models, Stargate advances OpenAI’s soft‑power strategy, forging government partnerships and balancing sovereignty with economic opportunity.

Regulatory and Infrastructure Push

At a Senate hearing, OpenAI’s Sam Altman, AMD’s Lisa Su, CoreWeave’s Michael Intrator and Microsoft’s Brad Smith pressed for streamlined permitting of data centres, power plants and chip fabs to underpin the AI tech stack. Altman cited the $500 billion Stargate project and warned that fragmented rules or strict export controls risk ceding ground to China. Senators flagged data privacy, cybersecurity and global competition, with Ted Cruz proposing an AI sandbox and Brad Smith stressing that ‘no country can win AI alone’.

OpenAI also rolled out reinforcement fine‑tuning (RFT) on its o4‑mini reasoning model, enabling enterprises to define Python‑based grading functions that score outputs (0–1) and train models on custom reward signals. Early adopters saw a 39% lift in tax analysis accuracy, 12‑point ICD‑10 gains and a 20% F1 boost on legal citation extraction. RFT runs at $100/hour (pro-rated) with a 50% discount for shared datasets; GPT‑4.1 nano supervised fine‑tuning also launched for all paying developers.

Following its Europe rollout, OpenAI’s Asia data‑residency program lets ChatGPT Enterprise, Edu and API customers store data at rest in Japan, India, Singapore and South Korea. The move addresses regional sovereignty rules and complements OpenAI for Countries, building local infrastructure for regulated sectors like finance and healthcare.

Meta Redefines Perception Standards For AI Glasses

Meta’s FAIR lab has rolled out a suite of open-source models pushing new boundaries in perception, localization, and reasoning. The Meta Perception Encoder leads with top-tier zero-shot performance on image and video tasks. The Perception Language Model (PLM), trained on 2.5M human-labeled videos, excels in video QA and spatiotemporal reasoning. Meta Locate 3D decodes natural language prompts for pinpoint 3D object localization, while the Collaborative Reasoner enhances multi-agent collaboration in large language models—enabling more transparent and reproducible AI systems.

Super-Sensing Smart Glasses

Meta’s AI-powered smart glasses—Aperol and Bellini— are currently being tested with an always-on “super-sensing” mode.

Activated by “Hey Meta, start live AI,” the glasses continuously track your surroundings, flagging forgotten items or offering reminders. Current Ray-Ban hardware runs super-sensing for only 30 minutes; the new models aim for multi-hour battery life. Meta is also overhauling its privacy and safety protocols to balance real-time data capture with user control, with ear-worn devices featuring integrated cameras in the works.

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• Apple Eyes AI Search, Threatens Google Deal

•  iPhone obsolete by 2035?

• AI-Powered Search by Anthropic Sets Sights on Google

• Mistral claims its newest AI model delivers leading performance for the price

• Microsoft Expands AI Agent Interop, Calibrates Phi 4 Outputs

• Microsoft Integrates A2A Protocol

• Figma releases new AI-powered tools for creating sites, app prototypes, and marketing assets

• Jensen Huang says 100% of Engineers Will Have AI Agents

• Hybrid AI model crafts smooth, high-quality videos in seconds | MIT

• By 2026, most firms expect to have a Chief AI Officer on staff

• Amazon introduces Vulcan: an AI-powered warehouse robot with a sense of touch

• Neuralink implant enables patient to make YouTube videos with generative AI's help

• IBM says AI and AI agents have cut hundreds of HR jobs

• World-first: Humanoid robots to race, play soccer, dance at China's robo sports games

• Microsoft employees are banned from using DeepSeek app, president says

• Watch: How Amazon Plans To Catch Google And Microsoft In The Quantum Computing Race

• Scientists discover how to use your body to process data in wearable devices

• AI tool uses face photos to estimate biological age and predict cancer outcomes

• Salesforce starts $500m Saudi AI plan with new hire

📄 Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities

📄 ZeroSearch: Incentivize the Search Capability of LLMs without Searching ​​

📄 PrimitiveAnything: Human-Crafted 3D Primitive Assembly Generation with Auto-Regressive Transformer

📄 On Path to Multimodal Generalist: General-Level and General-Bench

📄 Flow-GRPO: Training Flow Matching Models via Online RL 

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