TAI AHR #12 — Building Smarter Systems: From Edge AI to Drone Fleets

On November 19, Tokyo AI (TAI) hosted the 12th edition of TAI AHR, an evening focused on how intelligent systems are being built today—from edge devices, to biological data pipelines, to large-scale drone fleets.

Theme:

Building Smarter Systems: From Edge AI to Drone Fleets

This session explored practical ways AI is deployed across very different environments—small hardware, high-speed biological data workflows, and aerial robotics platforms operating at scale.

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Talk 1 — From Cloud to Edge

Practical Strategies for Deploying AI on Resource-Constrained Devices

Speaker: Eldar Sido

Abstract

As AI models move closer to sensors and physical devices, the need for efficient, private, and low-latency intelligence at the edge keeps growing.

Eldar’s talk covered:

• Why TinyML and Edge AI matter today
• How companies reduce cost and latency by moving computation away from the cloud
• Privacy and reliability advantages of on-device processing
• Foundational techniques for running AI on small hardware
• Real-world deployment examples in predictive maintenance, voice, and vision

The talk showed that Edge AI is now influencing multiple industries, and that organizations adopting it effectively are already seeing major returns.

Bio

Eldar Sido is a Staff AI Product Manager at Renesas Electronics, leading strategy for AI compilers, enablement tools, and platforms for resource-constrained edge hardware.

He holds a Master’s degree from the University of Tokyo and has led initiatives in computer vision, audio analytics, and real-time edge intelligence.

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Talk 2 — How In-Memory Processing Accelerates Bioinformatics

Speaker: Syrine Ben Driss

Abstract

"Biology outpaces the von Neumann machine."

Syrine explored why traditional compute architectures struggle with biological data—and how in-memory processing can break the bottleneck by bringing compute closer to data.

Her talk highlighted:

• The mismatch between biology’s complexity and current architectures
• How next-generation storage and compute designs improve throughput
• Why real-time biological insight requires rethinking system design

Bio

Syrine Ben Driss is the founder of Operon Technologies (currently in stealth).

Her background includes AI engineering in Japan, software development in Sierra Leone, and entrepreneurial work across Africa and Asia—converging around next-generation bio-compute systems.

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Talk 3 — IoT in the Sky

Designing Lightweight Safety-Critical Systems at Scale

Speaker: Whitney Huang

Abstract

We are used to IoT in homes—but what about IoT in the sky?

Whitney described how a fleet of thousands of drones, flying at over 100 km/h, maintains:

• Reliable communication with the cloud
• Safe coordination between vehicles
• Onboard AI for specific tasks
• Ultra-lightweight, safety-critical design that fits on tiny chips

She also explained what AI is used for in drone fleets—and what is not—highlighting the trade-offs between computation, weight, and safety.

Bio

Whitney Huang is a robotics software engineer and former Zipline engineer.

She holds a BS in Mechanical and Aerospace Engineering from Princeton and focuses on using technology to address real-world human challenges.

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Community and Networking

The event concluded with an hour of networking among founders, researchers, hardware engineers, bioinformatics experts, and enthusiasts exchanging ideas on edge compute, robotics, AI ecosystems, and next-generation infrastructure.

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Final Thoughts

TAI AHR #12 showcased how intelligent systems are evolving in three very different directions:

• At the edge (tiny, constrained hardware)
• Inside biological workflows (big, complex data)
• In the sky (large-scale autonomous fleets)

Despite the differences, one theme connected them all:

We are moving toward smarter, more efficient, and more adaptive systems—built closer to where data is born.