Nvidia swallows Groq for $20B, Apple-Google Gemini deal shocks + real-time inference wars Cahn’s AI Canvas #Ed. 37 | Jan 16-23

TL;DR

Nvidia Acquires Groq for $20B

Nvidia quietly bought Groq’s LPU IP and engineering team, locking in ultra-fast, energy-efficient inference.

Why it matters: Inference is now the real battleground. Groq’s LPUs deliver up to 10× faster responses than GPUs — Nvidia just secured the speed layer.

Builder takeaway: Real-time AI (voice, video, gaming) just got an unfair advantage. Nvidia’s roadmap is now your moat. Read Here

Apple + Google Gemini for Siri

Apple is integrating Gemini into Siri — a major win for Google as it becomes the intelligence layer for iOS.

Why it matters: Even Apple couldn’t go solo in AI. Frontier models now require alliances.

Builder takeaway: Expect multimodal, context-aware Siri by 2026. Design iOS apps for voice-first, OS-native intelligence. Read Here

OpenAI + Cerebras $10B Compute Deal

OpenAI signed a multi-year deal with Cerebras for wafer-scale inference compute through 2028.

Why it matters: Specialized chips beat cloud generalists. Faster inference = cheaper tokens = mass adoption.

Builder takeaway: Latency will drop. “Instant AI” becomes the baseline — delays become a UX flaw. Read Here

Claude’s New Constitution

Anthropic rewrote Claude’s alignment framework — shifting from rule-based safety to reason-based ethics.

Why it matters: This hints at early acknowledgment of AI moral status, not just safety compliance.

Builder takeaway: Expect smarter refusals, deeper reasoning, and more nuanced responses — with slightly slower deliberation. Read Here

DEMO THEATER

The anti-pattern: Another screenless AI gadget nobody asked for.

We’ve seen this movie. Humane AI Pin: $700, returned by ~80% of buyers. Rabbit R1: CES hype, dead by summer. Now the speculation loop—earbuds, pins, “something new.”

Sam Altman says OpenAI’s device will feel serene and surprisingly simple. Maybe. But simplicity isn’t novelty—it’s fit.

The pattern that works: Augment what exists. Don’t replace it.

Lenovo’s Qira flows across laptops and Motorola phones. Google’s Gemini powers Siri because Apple knows users won’t abandon iPhones for AI hardware.

The rule is brutal and consistent: hardware fails when it asks users to change behavior. It wins when it disappears into what they already do.

OpenAI has Jony Ive and $10B in compute. The real question isn’t whether the device is beautiful—it’s whether anyone will actually wear it.

Know More

What actually shipped this week (and actually works)

ChatGPT Health

OpenAI launched ChatGPT Health, letting users connect medical records and wellness apps for personalized health guidance. Conversations are encrypted and not used for training.

Production readiness: High. HIPAA-compliant, encrypted, clear privacy lines.

Who’s using it: Health coaches, nutritionists, chronic-care startups. Early wins: meal planning, med reminders, symptom tracking.

The gap: No hospital EMR integrations yet. The opportunity is obvious: Epic, Cerner, Meditech.

MedGemma 1.5 (4B)

Google released MedGemma 1.5 4B, a lightweight medical model for 3D imaging (CT/MRI), longitudinal comparisons, and structured medical reasoning. Ships with MedASR, cutting dictation errors by 82%.

Production readiness: Medium. Powerful, but not plug-and-play.

Who’s using it: Radiology startups, telemedicine platforms, diagnostic tooling.

The gap: Performance drops on out-of-distribution edge cases. Mission-critical builds need human-in-the-loop validation.

CLEAR-IR (Robotics Vision)

Researchers introduced CLEAR-IR, a U-Net system that reconstructs clean images from infrared feeds, enabling robotic navigation in total darkness.

Production readiness: Low. Research-stage, no commercial API.

Who’s experimenting: Autonomous vehicles, warehouse robotics, defense.

The gap: Requires custom hardware integration—but it solves a core low-light autonomy problem.

Claude Cowork (Desktop AI Assistant)

Anthropic expanded Claude Cowork to Pro users (macOS only). It’s a desktop AI that can autonomously build apps from natural language using Claude Opus 4.5.

Production readiness: Medium. Research preview, Mac-only.

Who’s using it: Founders and operators building MVPs, internal tools, and POCs in minutes.

The gap: No Windows or web version yet. Fastest path from idea to prototype—but expect rough edges at scale.

The money reality nobody likes to admit

→ Cerebras Cloud Inference API: Access 750MW of wafer-scale compute for ultra-fast LLM inference. Request early access at cerebras.ai/cloud.

→ MedGemma Developer Toolkit: Fine-tune medical AI models with 3D imaging support. Includes MedASR for clinical dictation. medgemma

→ Openwork Desktop AI Coworker: Autonomous coding assistant with background edits, web search, and skills that load on demand. openwork.ai

→ HINDSIGHT Agent Memory: New framework separating episodic, semantic, and working memory for AI agents. Reduces token usage by 60%. Vectorize.io

The 3-Rule Filter (steal this)

 If you’re building voice AI: Design for the Nvidia-Groq inference stack. Real-time latency becomes table stakes by Q3 2026.

✓ If you’re building on iOS: Assume Gemini-powered Siri goes live in iOS 18.1. Plan multimodal features and OS-level context sharing.

✓ If you’re building health tech: ChatGPT Health + MedGemma create a two-layer opportunity—consumer wellness at the top, clinical diagnostics at the bottom. Pick your layer and ship.

✓ If you’re building hardware: Don’t compete with OpenAI’s device. Build accessories, integrations, and ecosystem tools around it. When it launches H2 2026, you want to be the first app in their store.

✓ If you’re raising funding: Highlight inference partnerships (Cerebras, Groq IP, etc.) in your tech stack. Investors now ask how fast your AI responds, not just how accurate.

Cahn’s Two Cents 

→ Can HINDSIGHT agent memory framework reduce API costs by 60% in production? (Testing with customer support bot)

→ Does Openwork’s background edit feature actually work for autonomous multi-session coding? (Testing with e-commerce rebuild project)

→ How does MedGemma’s 3D imaging compare to radiologist accuracy on CT scan analysis? (Testing with public datasets)

“The moment a device asks people to LEARN, WEAR, or REMEMBER something new adoption collapses. Convenience always beats novelty.”

Funding

• Merge Labs raised $252M for AI-powered data integration platform

• Anthropic plans $10B fundraise at $350B valuation (nearly double from 4 months ago)

• Thinking Machines loses co-founders to OpenAI amid misconduct allegations (Barret Zoph returns to OpenAI)

Acquisitions

• Nvidia acquires Groq for $20B (IP + engineering team)

Market Moves

• Google hits $4 trillion valuation on Gemini momentum and Apple partnership

• OpenAI becomes #2 in India market (2.5x growth YoY)

• Samsung targets 800M Galaxy AI devices by end of 2026 (doubling from 400M)

Business Model Shifts 

• OpenAI plans to introduce ads in ChatGPT (free and Go tiers) starting in the US to support broader access

• Meta signs 10+ billion dollar nuclear power deal to support AI infrastructure

Quick Beats

→ Forward this to a founder building hardware. They need to see the OpenAI timeline.

→ Hit reply and tell me: Are you building for real-time inference? What’s your biggest latency bottleneck?

→ Next week: We’re breaking down the Apple-Google deal and what it means for iOS developers.

Fireside Chat

If AI is everywhere now, what’s the last interface that actually matters — the screen, the voice, or the operating system itself?

They didn’t add tools. They subtracted steps.