⏱ 4-min read

AI is moving from cloud chatbots into real-world systems. This issue covers Google’s Coralboard for local edge AI, Sesame’s new voice agents, ElevenLabs Music v2, OpenAI’s $250M fund for AI’s economic impact, and the growing split between jobs being cut and AI skills being rewarded.

Let's get into it. ↓

Google introduced the newest Coral board — a tiny, efficient, on‑device AI computer built for real‑time perception and control. No cloud. No latency. No privacy tradeoffs.

The demos say everything:

Here’s where it gets interesting: Coralboard runs Gemma‑class models locally. That means robotics, wearables, smart devices, and embedded systems can now run modern AI without a server — or a GPU farm.

The barrier between “I have an idea for an AI device” and “I built one” just collapsed.

Why it matters for builders: edge AI is no longer gated by power, bandwidth, or cloud cost. It’s gated by imagination. That’s a completely different game — and most hardware teams haven’t realized the rules just changed.

👉 Start building → https://developers.google.com/coral
👉 Coralboard setup → https://developers.google.com/coral/products

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🔥This week in AI

Sesame just released an iOS preview of its lifelike voice agents — characters that respond with human‑level timing, run parallel searches mid‑sentence, and weave real‑time results into natural conversation. The update adds voice‑first search cards, notes, deep dives, new personalities, and an Incognito mode for ephemeral chats.

ElevenLabs just launched Music v2 — a major upgrade with sharper vocals, richer instrumentation, multilingual range, and genre‑bending control. It handles fast rap, opera‑to‑metal transitions, sound‑effect layering, and precise inpainting so you can regenerate any section without touching the rest.

PrismML just launched Bonsai Image 4B — ultra‑compressed 1‑bit and ternary diffusion models that run high‑quality image generation directly on laptops, iPads, and even iPhones. The models shrink a 7.75GB transformer down to under 1.3GB while keeping strong visual fidelity.

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OpenAI’s new Foundation is putting $250M toward one goal: preparing society for the economic shock AI is already triggering. The fund will back new ways to measure AI’s impact, support workers navigating disruption, and prototype long‑term security models that don’t rely solely on wages.

The shift worth watching: governments usually react after economic change. OpenAI is trying to build the infrastructure before the change hits. That’s a different posture and a different kind of power.

Why it matters: AI won’t just reshape jobs. It will reshape the rules of the economy itself.

Moda is an AI design product where you prompt what you need, get a complete on-brand design, and edit every element on a full canvas. 

Our viral launch hit 4.4M views in days, tens of thousands signed up, and executives at major finance and tech companies now use it.

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15,000+ roles disappeared in one week as companies called it an “AI pivot.” But job openings also hit a 12-month high. That’s the real story.

This week's Sunday Special breaks down the roles replacing old ones, the AI skills employers now expect, the $240K+ ElevenLabs hackathon still open, and the free courses worth your weekend.

Plus: Gartner says Agentic AI has reached peak hype. The next phase will expose who is experimenting and who is actually building.

Lovable now lets you turn a simple description into a fully working anime‑prompt generator — layout, styling, form fields, output cards, and copy‑to‑clipboard logic included. You describe the tool, Lovable builds the app.

The part worth noticing: these aren’t mockups. They’re real, polished, production‑ready tools that would normally cost thousands to design.

Read the full guide →

Most e-commerce sellers juggle 6–8 tools and pay hundreds monthly to keep operations running. StoreClaw replaces the stack with one autonomous AI engine that monitors competitors, optimizes listings, automates marketing, and tracks profit 24/7. Connect your store and let AI handle the work — no prompts, no complex setup, no credit card required.

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Carnegie Mellon and Cleveland Clinic trained CMR-CLIP on 13,000+ cardiac MRI scans more than most cardiologists see in a lifetime. It reached 99% accuracy on certain heart conditions and outperformed general-purpose AI models by 35%. The future of cardiac imaging may start with pattern recognition no human can hold in memory.

This week's AIHealthTech Insider: Issue #102 tracks how AI is reading the heart with near-specialist accuracy and the bigger question now facing healthcare: what happens when machines start seeing patterns no human could hold in memory?