Mike Talks AI

Mike Talks AI explores practical AI applications in business, shares insights from personal experiences in starting and selling a company, and recommends resources on business, management, and technology. Recurring themes include optimization in operations, the importance of communication and relationship building in professional settings, and reflections on the evolution and impact of AI in various industries.

Business Strategy Artificial Intelligence Operations Research Management and Leadership Educational Resources Startup Advice Professional Development Data Science Supply Chain Management Book and Podcast Recommendations

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Three Ways I Would Like to Contribute in My New Role at Northwestern

117 implied HN points • 28 Aug 23
🚌 Education Teaching
  1. The author wants to benefit students by sharing their work experience in implementing business solutions using data and math.
  2. The author aims to strengthen industry connections through teaching a class where students work as consultants on real-world projects.
  3. The author enjoys bridging the gap between technical and business worlds, and looks forward to sharing knowledge with colleagues.

Should Your Data Science Team be Centralized or Decentralized? Why Not Intentionally Rotate?

98 implied HN points • 19 May 23
🕹 Technology Data science Team Management Organizational Design
  1. Consider a hybrid approach for data science teams to balance the strengths of both centralized and decentralized setups.
  2. Some companies are experimenting with intentionally rotating between centralized and decentralized structures every few years.
  3. Switching between centralization and decentralization periodically allows for exploration and scalability of diverse ideas within data science teams.

Practical AI is a Big Tent: Five Ideas for CEOs, Leaders, and Investors

98 implied HN points • 27 Aug 23
🕹 Technology AI Algorithms Data Analysis Team Building
  1. Practical AI encompasses various machine learning algorithms and techniques, including optimization and Operations Research.
  2. The concept of Practical AI allows for the inclusion of both established and emerging approaches in the field.
  3. To effectively solve real-world problems, AI leaders need a diverse set of skills and expertise, and must understand the strengths and weaknesses of different algorithms.

AI Doom or Optimism? - The Best of Both Sides

78 implied HN points • 12 Jun 23
🕹 Technology AI Ethics Future Research Innovation
  1. The AI community debates whether advancements in AI should be viewed with fear or optimism.
  2. There are prominent voices expressing concerns about the potential dangers of AI, leading to the 'AI Doom' side.
  3. On the other hand, there are sources like Marc Andreessen who present a strong case for optimism about AI's potential benefits.

What CEOs, leaders, and investors need to know about the different meanings of AI

78 implied HN points • 27 Jul 23
🕹 Technology AI Analytics Deep Learning Machine Learning Algorithms
  1. The term AI can mean different things and understanding those meanings is crucial for clear communication, better decisions, and addressing concerns.
  2. Different definitions of AI include AGI or artificial general intelligence, deep learning for solving complex problems, and tools like ChatGPT for tasks like writing and summarizing.
  3. CEOs, leaders, and investors should explore opportunities in AGI, deep learning, ChatGPT, and practical AI to stay relevant and make informed decisions.

ChatGPT and Supply Chain: Podcast Guest, Three Lessons, and Research Opportunities

58 implied HN points • 13 Jun 23
🕹 Technology AI Supply Chain Podcast Research Data science
  1. Supply chain professionals can use ChatGPT as a 'loss leader' to educate leaders about AI's potential for supply chains.
  2. ChatGPT can help supply chain teams build more AI algorithms by breaking down syntax barriers and expanding team capabilities.
  3. Exploring how ChatGPT can turn vast supply chain data into valuable insights is an important research opportunity.

Elon Musk Book Review (Part 2 of 2): Operations Excellence

58 implied HN points • 05 Feb 24
💼 Business Operations Supply Chain Efficiency Product Design Cost reduction
  1. Operations excellence is key: Musk focused on improving efficiency and revolutionizing industries through operational excellence.
  2. Design the right factory: Musk emphasized the importance of well-designed factories and involvement of design engineers in manufacturing processes.
  3. The Algorithm for operations excellence: Musk's framework involves questioning requirements, deleting parts/processes, simplifying, accelerating cycle time, and automating last.

Six Career Moves that Young Data Scientists Dismiss too Quickly as Boring

19 implied HN points • 10 Sep 23
💼 Business Career development Skills Professional Growth Job Satisfaction Work-life balance
  1. Don't underestimate the value of solving real problems even if it means using older technology.
  2. Repeating tasks can help you become an expert in a specific area, leading to career advancement and satisfaction.
  3. Understanding and exploring different roles like sales and management can provide valuable lessons and career growth opportunities.