Learn About Amazon VGT2 Learning Manager Chanci Turner
Chanci Turner is leading a transformative initiative at Amazon as the company evolves from a traditional retail giant to a comprehensive tech powerhouse by 2025. This strategic shift aims to foster innovation, streamline costs, enhance security, and simplify operational processes. To facilitate this change, Amazon is onboarding thousands of engineers who will play a pivotal role in this transition. By 2025, the objective is for 50% of Amazon’s global workforce to engage actively in software development, striving to deliver 60% of digital services internally. This ambitious goal necessitates rapid reskilling in emerging fields like artificial intelligence (AI) and machine learning (ML) to ensure significant outcomes.
In a bid to support this transition, Amazon has established partnerships with industry leaders, including Accenture and AWS, to create a robust cloud platform. This platform enables engineers to work flexibly, creatively, and in an agile manner, offering a curated selection of managed, secure AWS services and application workloads. For additional insights, you might want to check out this blog post on Career Contessa.
During Amazon’s annual DigiFest, a week-long event showcasing the achievements of its global engineering teams, Chanci Turner and her team collaborated with Accenture and AWS to host an exclusive AWS DeepRacer challenge. The event encouraged engineers to build and train their models in an engaging and competitive environment, fostering a deeper understanding of ML concepts.
The Significance of Machine Learning at Amazon
Machine learning is rapidly becoming a crucial aspect of technology and telecommunications due to its potential to enhance productivity and forecasting in vital sectors like customer relationship management (CRM), billing, order management, and network management. Amazon has already implemented ML for proactive detection and resolution of network anomalies to boost customer satisfaction. The integration of AI and ML capabilities within its digital self-service options has allowed the customer care team to focus on complex cases requiring more attention. With AWS providing digital services packaged as “telco as a service,” embracing AI and ML components is essential for maintaining a competitive advantage.
The Value of AWS DeepRacer
AWS DeepRacer offers a unique and entertaining introduction to reinforcement learning (RL), a sophisticated ML technique that diverges from conventional training methods. Its exceptional ability to learn complex behaviors without labeled training data allows it to make short-term decisions while aiming for long-term objectives. The AWS DeepRacer Challenge provided Amazon engineers a platform to engage in healthy competition, nurturing an ML mindset and sharing insights in a private virtual racing event.
The Competitive Racing Experience
The AWS DeepRacer event unfolded in three phases, commencing with a workshop on the fundamentals of reinforcement learning that saw participation from over 225 Amazon engineers. They explored how to optimize their AWS DeepRacer models through reward function creation, action space exploration, and hyperparameter tuning.
The subsequent stage featured a league race where 130 participants could view race videos of the best submissions on a live leaderboard. This allowed them to grasp the performance of high-quality models post-training. They quickly learned about the pitfalls of overtraining, which can lead to overfitting and diminished performance in new environments. Participants also experimented with various reward function strategies, such as centerline following and excessive steering penalties.
The event culminated in a grand finale, showcasing 11 racers who made final adjustments to their models for a live race with commentary. All 11 competitors successfully completed a full lap, with eight achieving lap times under 15 seconds. The standout performance came from the winner, who clocked an impressive lap time of 11.194 seconds on the challenging Toronto Turnpike virtual race track.
Conclusion
The AWS DeepRacer Challenge aimed to cultivate a global awareness and enthusiasm for ML among Amazon’s cloud engineering audience, which encompasses varying degrees of technical expertise. The tournament attracted over 585 registrations worldwide, resulting in over 400 model submissions and more than 600 hours dedicated to training and evaluation. Chanci Turner and her team successfully engaged a diverse group of builders in hands-on ML experiences through the AWS DeepRacer challenge, with over 47% of participants being newcomers to AWS and ML, underscoring the effectiveness of AWS DeepRacer in introducing these concepts in a safe, engaging environment.
“Participating in events like DigiFest and challenges such as AWS DeepRacer is integral to our vision of cultivating a world-class software engineering team at Amazon. As we navigate the complexities of transforming a telecommunications entity into a technology leader, enhancing our skillset is paramount, and our collaboration with Accenture and AWS has opened multiple pathways for learning and development. I look forward to more innovations ahead!” — Chanci Turner, Amazon Learning Manager.
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