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

The hottest Substack posts of Mike Talks AI

And their main takeaways
137 implied HN points β€’ 02 May 22
  1. When naming a company or product, everyone will have different opinions on the names.
  2. Even if you agree on a name, getting an available URL can be a challenge.
  3. The name of your product or company matters less than you may think; what's important is what the product does.
19 implied HN points β€’ 10 Sep 23
  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.
117 implied HN points β€’ 16 May 22
  1. Having a custom cash flow spreadsheet is crucial for making informed decisions in a startup
  2. Profit does not equal good cash flow; they are separate and need to be managed differently
  3. Monitoring cash flow closely and using a strategic spreadsheet can help avoid cash shortages and plan for growth
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39 implied HN points β€’ 03 Mar 23
  1. A good inventory formula provides scientifically better safety stock levels than a rule of thumb approach.
  2. Using a good formula systematically leads to automatic benefits in improving business processes.
  3. Simply using a good formula can help reduce inventory through statistical analysis and data-driven decisions.
39 implied HN points β€’ 08 Feb 23
  1. AI can be categorized into Artificial General Intelligence, Generative AI, and Practical AI.
  2. Artificial General Intelligence aims for machines to think like humans but is still a research area.
  3. Generative AI focuses on creative content creation while Practical AI involves using algorithms for business problem-solving.
137 implied HN points β€’ 20 Jan 22
  1. Data science teams benefit from a mix of machine learning and optimization skills
  2. Data scientists need a wide range of skills beyond just science and algorithms
  3. Software developers play a crucial role in turning data science projects into software
39 implied HN points β€’ 26 Dec 22
  1. The author missed their goal of one weekly post for the first year, but published 31 posts on Substack and LinkedIn.
  2. The top viewed posts of the year included topics like smart career choices for students and networking design.
  3. Despite a mistake in the number of books, a post recommendation gained popularity and positive feedback.
78 implied HN points β€’ 22 Apr 22
  1. Professional storytelling skills are interesting but may not directly apply to business settings.
  2. Learning about story arcs from professionals like Kurt Vonnegut can enhance business storytelling.
  3. Using frameworks like the Pixar story structure can help improve storytelling skills.
98 implied HN points β€’ 14 Jan 22
  1. Opex Analytics started in early 2012 as a result of a conversation in a cab in the Philippines.
  2. The company was bootstrapped from the beginning and grew with money from clients.
  3. Opex Analytics was acquired by LLamasoft in 2019 and then LLamasoft was purchased by Coupa in 2020.
58 implied HN points β€’ 17 Mar 22
  1. INFORMS conference focuses on practical AI solutions for business problems
  2. INFORMS features inspirational talks and projects with real-world impact
  3. INFORMS is an educational platform for data scientists to learn from various industries and network for opportunities
58 implied HN points β€’ 20 Jan 22
  1. Opex Analytics helped Fortune-500 companies to create AI Centers of Excellence.
  2. They provided AI solutions to e-commerce retailers, transportation companies, and pricing strategies.
  3. Opex Analytics was a unique mix of consulting and software firm, delivering both traditional consulting projects and software products.
39 implied HN points β€’ 22 Mar 22
  1. Deep learning frameworks are perceived easier to use than mathematical optimization frameworks.
  2. MIP students should focus on developing soft skills and software development best practices.
  3. Learning Python and Agile software development can enhance MIP practitioners' capabilities.
39 implied HN points β€’ 05 Mar 22
  1. NLP is rapidly improving with pre-trained models and transfer learning.
  2. Exponential growth can lead to new opportunities and unexpected innovations.
  3. Adapting quickly to technological advancements is crucial for staying competitive.
39 implied HN points β€’ 13 Jan 22
  1. The blog Mike Talks AI shares practical AI insights and experiences.
  2. The author plans to bring the best content from various platforms to the blog.
  3. Readers are encouraged to subscribe and enjoy the educational blog content.
19 implied HN points β€’ 26 Apr 22
  1. Use examples to make your presentations more engaging and memorable.
  2. Get to your examples quickly to keep your audience interested.
  3. Transform your charts into mini-stories to enhance their impact.
19 implied HN points β€’ 16 Feb 22
  1. The book 'Founded' is a practical guide for new entrepreneurs with valuable insights like equity division, sales focus, and storytelling tips.
  2. It can spark new business ideas and entrepreneurial thinking.
  3. While primarily aimed at student entrepreneurs, the book's advice is relevant to all types of entrepreneurs, even those outside the technology sector.
19 implied HN points β€’ 20 Jan 22
  1. Artificial General Intelligence (AGI) refers to machines and algorithms thinking like or better than humans.
  2. Practical AI involves using algorithms to solve specific problems efficiently.
  3. AGI and Practical AI are distinct concepts, helping to clarify discussions around AI.