Apple Acquires French AI Startup for Siri
Apple acquires French AI startup for Siri intelligence. On-device neural networks improve machine learning. AI innovation enhances user privacy and capabilities
Apple confirmed it's acquiring DatakaLab, a Paris-based AI startup specializing on-device machine learning, for an undisclosed sum. The deal marks Apple's third French AI acquisition in 18 months and signals a clear strategy: keep Siri's intelligence local, not cloud-dependent.
DatakaLab's tech compresses neural networks by up to 70% without sacrificing accuracy, according to benchmarks the startup published last year. That's the kind of efficiency Apple needs to run sophisticated AI directly on iPhones and Macs — no server calls, no latency, no privacy trade-offs.
The Cupertino giant has been playing catch-up with Siri for years. While Google Assistant and Alexa expanded into third-party integrations and smart home ecosystems, Siri remained frustratingly limited. But this acquisition isn't about matching competitors feature-for-feature. It's about taking a fundamentally different path: all processing happens on your device.
Why On-Device AI Actually Matters
Here's what most coverage misses: cloud-based AI assistants send your voice data to remote servers for processing. Apple's betting users will pay a premium for privacy and speed. DatakaLab's compression algorithms could let an iPhone 16 run language models comparable to GPT-3.5 — entirely offline.
The startup's 24-person team will join Apple's Machine Learning Platform group in Seattle and Cupertino. DatakaLab CEO Julien Chaumond declined to comment on the sale price, but sources familiar with French tech valuations estimate $150-200 million range.
Apple's already shipping its own silicon with dedicated neural engines — the M-series and A-series chips have been optimized for machine learning since 2017. But the software side has lagged. Siri still can't handle multi-turn conversations or contextual follow-ups as smoothly as ChatGPT or Claude.
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What Developers Can Expect
DatakaLab's compression tech could open new doors for third-party apps. If Apple integrates these tools into Core ML, developers might finally build truly intelligent apps that don't require constant internet connections or send user data to external servers.
"On-device AI is the only way to build consumer trust at scale. Users don't want to wonder where their voice commands are being stored." — Former Apple ML engineer who spoke on condition of anonymity
The timing matters. Apple's facing renewed scrutiny from EU regulators over data handling practices. An AI strategy that processes everything locally sidesteps those concerns entirely. It also cuts infrastructure costs — running inference on Apple's servers for billions of Siri requests per day isn't cheap.
What's Next for Siri
Apple's expected to demo major Siri improvements at WWDC 2026 in June. The DatakaLab acquisition won't deliver results overnight — integrating compression algorithms into Apple's existing ML stack takes months, not weeks. But by iPhone 17 launch in fall 2026, we could see Siri handling complex queries 3-5x faster than current performance, all without sending data off-device.
The question isn't whether Apple can make Siri smarter. It's whether users will notice the difference before they've already switched to ChatGPT or Gemini as their default assistant.
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