Practical AI

Emily Robinson, a Senior Data Scientist at Warby Parker and co-author of 'Build a Career in Data Science', shares her expertise on optimizing the job search in data science. She discusses crafting resumes and cover letters that stand out, along with recognizing fair compensation for roles. Emily also highlights the importance of networking and adapting to various career paths, whether in startups or large firms. Her insights into navigating failures and the significance of communication in data-driven environments are invaluable for budding data scientists.

Matt Brems, Global lead data science instructor at General Assembly, dives into the ever-evolving world of data science. He clarifies its current definition and importance, while emphasizing the critical roles of foundational skills and practical problem-solving. Brems discusses the significant time spent on data cleaning and the necessity of adaptability in education. He also highlights diverse learning pathways for aspiring data scientists and addresses the ethical responsibilities in an age of rapid technological advancement.

Craig Wiley, Director of Product Management for Google Cloud AI Platform, shares insights from his extensive experience, including his time at AWS. He discusses the evolution of TensorFlow and its significant role within Google Cloud. The conversation highlights how enterprises leverage AI tools to enhance productivity, the balance between building custom solutions and buying existing ones, and the challenges organizations face with AI implementation. Craig also provides guidance for beginners eager to dive into TensorFlow and cloud AI technologies.

Dan Jeffries, Chief Technical Evangelist at Pachyderm, discusses the challenges of expanding AI to over 7,000 languages, focusing on issues like scarce data and connectivity. He emphasizes the need for collaboration between tech and local language experts to push voice technology into emerging markets. Jeffries also highlights the critical role AI can play in preserving linguistic diversity and the significant impact of innovative, open-source approaches for underrepresented languages. This approach could empower communities and enhance communication on a global scale.

In this engaging discussion, Mike McCourt, a data scientist at Invoca specializing in natural language processing, dives into the fascinating world of call analytics. He unveils how their Signal AI technology processes conversational data and the significant challenges it faces. Mike highlights the importance of linking phone interactions to marketing analytics and shares insights on training models using call data, addressing privacy and empathy. The conversation also explores unsupervised learning methods that enhance AI's ability to uncover themes and improve insights from diverse language patterns.

Doug Raymond, General Manager of Semantic Scholar at the Allen Institute for AI, dives into the world of AI-powered scientific research. He discusses the transformative role of AI in academia, particularly through tools like Semantic Scholar, which helps researchers navigate the overwhelming volume of literature. The conversation covers innovative features like personalized recommendations driven by language models and the importance of knowledge graphs in enhancing access to relevant studies. Doug also highlights the ongoing challenges and future aspirations for scholarly collaboration.

Dive into the AI Index 2019 Annual Report, revealing how AI is reshaping fields like healthcare and research. Discover technological advancements in transformers and milestones where AI outshines humans. The podcast delves into the growing demand for AI professionals, as students gravitate towards this specialization amid academia's shift to industry roles. Ethical considerations in AI also take center stage, discussing fairness and resource accessibility, reflecting the importance of responsible AI development in our society.

Tania Allard, a Developer Advocate at Microsoft and Google Machine Learning GDE, dives into the complexities of testing machine learning systems. She reveals a simple scoring formula to monitor system robustness while highlighting the continuous nature of model and infrastructure updates. The conversation touches on the collaboration needed between data scientists and engineers, the challenges of bias detection, and effective use of Jupyter Notebooks. Tania emphasizes the critical role of both manual and automated testing in ensuring quality over time.

In this engaging discussion, Costas Boulis, Chief Scientist at Bright Machines, delves into the world of AI-driven automation in manufacturing. He shares insights on how AI enhances production efficiency and the unique challenges posed by manufacturing data. Costas introduces the concept of microfactories and highlights the importance of advanced robotics and digital twins. He also discusses the potential impacts on workforce dynamics, emphasizing a shift towards more creative roles as automation evolves.

Greg Allen, Chief of Strategy and Communications at the U.S. Department of Defense's Joint Artificial Intelligence Center, shares insights into the military's approach to AI. He discusses the transformative potential of AI in national security and outlines key strategies and project areas. The conversation also delves into ethical implications, guiding principles for military operations, and the importance of collaboration with industry. Allen highlights the competitive landscape of AI technology amid global threats.