• On-device AI: Reimagining Fraud Prevention with lightweight Models

  • 2024/11/23
  • 再生時間: 19 分
  • ポッドキャスト

On-device AI: Reimagining Fraud Prevention with lightweight Models

  • サマリー

  • The theme of this podcast episode originates from an interesting project by Google called Dobby. I spent an afternoon discussing with our software engineers, and we envisioned how to use on-device AI technology, especially lightweight models, to enhance the ability to prevent phone scams.

    We talked about the advantages of on-device AI technology, including real-time processing, resource constraints, and privacy protection.

    We explored the foundations of this technology, including model compression, dedicated hardware, and efficient architecture design.

    We proposed a three-layer architecture for an anti-fraud system, including quick filtering, proactive analysis, and an interactive engine, and explained in detail how each layer operates.

    Of course, while mentioning specific solutions, we are more interested in identifying the technical challenges and future research directions the system faces, such as latency issues, memory capacity, and adaptability.

    I am sharing this idea with you, whether you are a startup founder or an investor, I have highlighted the directions you should focus on.

    References
    1. Kumar, A., & Soni, S. (2021). "Edge AI: Empowering Intelligent Applications at the Device
    Level." IEEE Internet of Things Journal.
    2. Yu, C., & Deng, L. (2020). "Deep Learning Applications in Speech and Audio Processing."
    IEEE Signal Processing Magazine.
    3. Google teases taking Pixel Call Screen 'even further' with AI
    4. How to use Android 12’s call screening features - The Verge
    5. Pixel Phone app preps contextual ‘AI Replies’ in Call Screen

    Content by Wei Sun
    Audio by Google
    Music by Dopestuff @MelodyLoops
    Download free music at https://www.melodyloops.com

    Disclaimer:
    This podcast is for informational purposes only. The technical content and market analysis shared here, including guest opinions, do not constitute professional or financial advice. We cannot guarantee accuracy or completeness of information. Listeners assume all risks from using our content. Consult professionals before making investment or technical decisions.

    Contact: victor@nexture.nz

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あらすじ・解説

The theme of this podcast episode originates from an interesting project by Google called Dobby. I spent an afternoon discussing with our software engineers, and we envisioned how to use on-device AI technology, especially lightweight models, to enhance the ability to prevent phone scams.

We talked about the advantages of on-device AI technology, including real-time processing, resource constraints, and privacy protection.

We explored the foundations of this technology, including model compression, dedicated hardware, and efficient architecture design.

We proposed a three-layer architecture for an anti-fraud system, including quick filtering, proactive analysis, and an interactive engine, and explained in detail how each layer operates.

Of course, while mentioning specific solutions, we are more interested in identifying the technical challenges and future research directions the system faces, such as latency issues, memory capacity, and adaptability.

I am sharing this idea with you, whether you are a startup founder or an investor, I have highlighted the directions you should focus on.

References
1. Kumar, A., & Soni, S. (2021). "Edge AI: Empowering Intelligent Applications at the Device
Level." IEEE Internet of Things Journal.
2. Yu, C., & Deng, L. (2020). "Deep Learning Applications in Speech and Audio Processing."
IEEE Signal Processing Magazine.
3. Google teases taking Pixel Call Screen 'even further' with AI
4. How to use Android 12’s call screening features - The Verge
5. Pixel Phone app preps contextual ‘AI Replies’ in Call Screen

Content by Wei Sun
Audio by Google
Music by Dopestuff @MelodyLoops
Download free music at https://www.melodyloops.com

Disclaimer:
This podcast is for informational purposes only. The technical content and market analysis shared here, including guest opinions, do not constitute professional or financial advice. We cannot guarantee accuracy or completeness of information. Listeners assume all risks from using our content. Consult professionals before making investment or technical decisions.

Contact: victor@nexture.nz

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