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With Ilya, Chief Product Officer at Constructor, and Bhaskar, Senior Data Scientist at BlackRock, we discussed AI in education, including intelligent tutoring systems and challenges in model reliability. We explored assessing student understanding, the role of teachers and algorithms, and touched on AI in finance, concluding with reflections on interpretability and opportunities in both fields. - AI in education, focusing on intelligent tutoring systems for personalized learning. - Using language models like ChatGPT in building tutoring models and concerns about output quality. - Collaboration and social interaction in learning, along with the benefits of project-based learning and working with tutors. - AI applications in education, including creating synthetic students. They acknowledge challenges in visuals and scientifically accurate content. - Machine learning in finance, discussing stock predictions, fixed income trading, and emphasizing interpretability and risk management in portfolio optimization.

This is the 4th AiEdge Podcast! In this podcast, Benjamin and Landon discuss their backgrounds in machine learning, job roles, and the evolving field's challenges and opportunities. We touch on the overlap between data science and machine learning, the importance of practical experience, the limitations of language models, and the revolutionary potential of AI. - Discussion on the evolving definitions and roles of machine learning engineers and data scientists. - Challenges and considerations of pursuing a career in machine learning, including specialization and the need for practical experience. - The potential of machine learning technology and its impact on businesses and industries. - The revolutionary capabilities of AI, including its potential to act as a layer between humans and various tasks.

Working at a FAANG!

The Cost of Model Deployment! #ai #ml

Balancing Cost and Privacy in LLM Deployment #ai #llm

In this episode of the AiEdge podcast, guests Ryan and Alejandro discuss their experiences and interests in AI and machine learning. They delve into topics such as incorporating AI into their work, the potential applications of AI in network and cloud infrastructure, the use of deep learning frameworks, and the challenges of managing large-scale models. They also touch on the importance of privacy and security, the debate between on-premises deployment and cloud-based AI services, and the evolving job titles and career paths in the field. The conversation provides insights into the rapidly evolving nature of technology and offers advice on staying updated and adaptable. - Discussion on the potential of AI in the IT industry, including insights into system health and automation processes. - Emphasis on the importance of considering traditional machine learning algorithms alongside deep learning frameworks. - Exploration of the advantages of using pre-trained language models and the potential shift towards their use instead of fine-tuning. - Consideration of the challenges and considerations in deploying machine learning models, including data privacy and the need for specialized expertise.

The Privacy Concerns about OpenAI! #ai #openai #aws

People will know nothing about Traditional ML! #ai #ml