Live vs. ImageNet: Webinar Recording
Lakera hosted a webinar focused on the complexities of creating comprehensive computer vision systems for practical use.
The session offered valuable insights into how to make these advanced systems safe, reliable, and efficient.
As artificial intelligence evolves swiftly, the creation of intricate computer vision technology grows steadily. Yet, this progress comes with significant challenges, notably in achieving fairness, eliminating bias, and ensuring safety.
Our discussion emphasized the importance of developing new tools and methods to tackle these issues in the development and implementation of expansive computer vision technology.
The session took place on February 15th, 2023 and was hosted by David Haber (Lakera, CEO & Co-founder) and Mateo Rojas (Lakera, CPO), with guests:
- Paul Rubenstein (Google)
- Richard Shen (Wayve AI)
- Tom Dyer (Genomics England)
- Peter Shulgin (Covariant AI)
- Santiago Arias (Lakera)
Key points:
- Rapid AI development paves the way for more powerful computer vision systems.
- These systems present challenges in ensuring fairness, unbiasedness, and safety.
- New tools and methodologies are essential for developing and deploying large-scale computer vision systems effectively.
- Cross-functional teams with expertise in machine learning and software engineering are fundamental for success.
- Data augmentation techniques enhance model robustness.
- Monitoring and auditing systems detect and mitigate bias and errors.
- Fostering a culture of safety and accountability within AI teams is indispensable.
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