Unlock the power of Artificial Intelligence! Our latest episode of AI Innovations Unleashed, "AI Demystified: Your Guide to Machine Learning & More," breaks down complex topics like machine learning, neural networks, NLP, and computer vision into easy-to-understand concepts. Perfect for beginners and anyone curious about the tech shaping our world.

Additional Resources

• TensorFlow: https://www.tensorflow.org/ [invalid URL removed]
• PyTorch: https://pytorch.org/ [invalid URL removed]
• Scikit-learn: https://scikit-learn.org/ [invalid URL removed]
• Keras: https://keras.io/ [invalid URL removed]
• Pandas: https://pandas.pydata.org/ [invalid URL removed]
• OpenCV: https://opencv.org/ [invalid URL removed]
• Amazon Web Services (AWS) AI Services: https://aws.amazon.com/machine-learning/ [invalid URL removed]
• Google Cloud Platform (GCP) AI Platform: https://cloud.google.com/ai-platform [invalid URL removed]
• Microsoft Azure AI: https://azure.microsoft.com/en-us/solutions/ai/ [invalid URL removed]
• A Brief History of AI (Article): You can search for articles on the history of AI on platforms like IEEE Spectrum, MIT Technology Review, or other reputable sources.
• Coursera: https://www.coursera.org/ (Offers various AI and machine learning courses)
• edX: https://www.edx.org/ (Offers various AI and machine learning courses)
• fast.ai: https://www.fast.ai/ (Provides free courses for coding deep learning)
• Google AI: https://ai.google/ (Resources and research from Google on AI)
• Elements of AI: https://www.elementsofai.com/ (A free online course that explains the basics of AI)
• Kaggle: https://www.kaggle.com/ (A platform for data science and machine learning competitions, also offers tutorials and datasets)

AI is changing the world! 🚀 Tune into the new episode of AI Innovations Unleashed to discover how AI's superpowers are revolutionizing healthcare, the environment, education, and business. Plus, we discuss the controversies & future outlook!

References

Davenport, T. H., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Harvard Business Review. Retrieved from [invalid URL removed]

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115-118.

Holmes, W., Bialik, M., Fadel, C., (2023). Artificial intelligence in education. Brookings Institution. Retrieved from [invalid URL removed]

McKinsey Global Institute. (2023). The economic potential of generative AI: The next productivity frontier. McKinsey & Company. Retrieved from https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier

O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.

Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., ... & Bengio, Y. (2022). Tackling climate change with machine learning. Nature Climate Change, 12(12), 1067-1077.

Additional Resources

1. AI for Good Global Summit. (n.d.). International Telecommunication Union (ITU). [invalid URL removed]
2. Partnership on AI. (n.d.). https://www.partnershiponai.org/
3. The AI Now Institute. (n.d.). https://ainowinstitute.org/
4. Future of Life Institute. (n.d.). https://futureoflife.org/
5. OECD AI Policy Observatory. (n.d.). https://oecd.ai/

Is AI taking over the world? (Spoiler: Not yet!) "AI Innovations Unleashed" cuts through the hype and explains the basics of Artificial Intelligence in a way everyone can understand. Subscribe and learn what AI actually is and how it's changing the world around us.

References

Auxier, B., & Anderson, M. (2023). AI and Americans' daily lives. Pew Research Center.

McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Magazine, 27(4), 12.

Metz, C. (2023, May 16). How A.I. is changing the way we shop online. The New York Times. [invalid URL removed]

Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., Mehta, H., Duan, T., ... & Langlotz, C. P. (2017). Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning. Nature, 544(7651), 317-321.

Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., ... & Hassabis, D. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587), 484-489.

Additional Resources

• Books:
  • Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
  • Tegmark, M. (2017). Life 3.0: Being human in the age of artificial intelligence. Knopf.
• Online Courses:
  • Coursera: "AI for Everyone" by Andrew Ng
  • edX: "Introduction to Artificial Intelligence (AI)" by Microsoft
  • fast.ai: "Practical Deep Learning for Coders"
• Websites:
  • AI Now Institute: https://ainowinstitute.org/
  • Partnership on AI: https://www.partnershiponai.org/

Who will win it all?

Who represents the AFC and NFC?

And who can stop the Chiefs 3-peat?

AI bots discuss who are contenders and who are pretenders. Taking into account MULTIPLE sources, the podcast breaks it down to fully understand it all.

So, sit back and relax. Listen to who the AI predicts will win it all!

Struggling to achieve your goals? This Motivation Monday, discover how AI can be your ultimate accountability partner! 🤖 Learn about AI-powered apps for productivity, fitness, and mental wellness that can help you stay on track and unlock your potential. We also dive into the ethical considerations and how these tools can be a game-changer for remote workers. Read the full post: #MotivationMonday #AI #Productivity #GoalSetting #HabitFormation #RemoteWork #FutureofWork #Tech

Reference

Michie, S., Yardley, L., West, R., Patrick, K., & Greaves, F. (2017). Developing and evaluating digital interventions to promote behavior change in health and health care: Recommendations resulting from an international workshop. Journal of Medical Internet Research, 19(6), e232. https://doi.org/10.2196/jmir.7126

Pasquale, F. (2020). New laws of robotics: Defending human expertise in the age of AI. Harvard University Press.

Additional Resources

• Future of Life Institute: https://futureoflife.org/ (Focuses on mitigating risks associated with advanced AI)
• Partnership on AI: https://www.partnershiponai.org/ (A multi-stakeholder organization working to ensure AI benefits people and society)
• AI Now Institute: https://ainowinstitute.org/ (Research institute examining the social implications of AI)
• OpenAI: https://openai.com/ (Leading AI research lab, provides resources and publications)
• Google AI: https://ai.google/ (Information on Google's AI research and projects)

From predictive analytics to VR training, AI is revolutionizing HR. 🤯 Dive into the cutting-edge technologies shaping the future of work in our new podcast episode, "The Future of HR: AI and the Human Touch." #AI #HR #Innovation #TechTrends #Podcast

Reference List (APA Format):

• Bughin, J., Hazan, E., Lund, S., Dahlström, P., Wiesinger, A., & Subramaniam, A. (2018). Skill shift: Automation and the future of the workforce. McKinsey Global Institute.
• Daugherty, P. R., & Wilson, H. J. (2018). Human + machine: Reimagining work in the age of AI. Harvard Business Review Press.
• Deloitte. (2022). Blockchain in human resources. Deloitte Insights.
• Dzieza, J. (2018, October 9). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G
• Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., ... & Rahwan, I. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14), 6531-6539.
• Kantor, J., & Streitfeld, D. (2021, May 2). The rise of the worker productivity score. The New York Times. [invalid URL removed]
• Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., ... & Sanghvi, S. (2017). Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. McKinsey Global Institute.
• Metcalf, H., Askay, D. A., & Rosenberg, L. B. (2020). Keeping up with the Quants: The evolving use of data and analytics in human resources. Sustainability, 12(10), 4083.
• Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42.
• World Economic Forum. (2020). The future of jobs report 2020. World Economic Forum.

Additional Resources:

• Books:
  • AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee
  • Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
  • The AI Advantage: How to Put the Artificial Intelligence Revolution to Work by Thomas H. Davenport
• Websites:
  • Society for Human Resource Management (SHRM): www.shrm.org
  • MIT Technology Review: www.technologyreview.com
  • Harvard Business Review: www.hbr.org

Think AI is too expensive or complex for your small business? Think again! 🤔 This episode of AI Innovations Unleashed breaks down how AI is transforming HR for SMBs. #AIinHR #SmallBusinessSolutions #TechforSMBs

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References

Culture Amp. (2022). Case study: Reducing employee turnover with Culture Amp. Culture Amp. https://www.cultureamp.com/customers

Deloitte. (2020). State of AI in the enterprise, 3rd edition. Deloitte Insights. https://www2.deloitte.com/us/en/insights/focus/cognitive-technologies/state-of-ai-and-intelligent-automation-in-business-survey.html 1

Forbes. (2023, April 4). Top 10 AI tools for talent acquisition in 2023. Forbes.

Ideal. (2023). How AI is revolutionizing recruiting. Ideal. https://ideal.com/

Lattice. (2023). The impact of Lattice on employee engagement. Lattice.

Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. Employee Relations, 41(6), 1258-1274.

W আহমে. (2024). About Us. W আহমে.

Additional Resources

• Society for Human Resource Management (SHRM): Provides articles, research reports, and other resources on AI in HR. (https://www.shrm.org)
• The AI Journal: A news website that covers the latest developments in AI, including its applications in HR. (https://aijourn.com/)
• Fetcher: (https://fetcher.ai/ )
• Zoho Recruit: (https://www.zoho.com/recruit/ )
• Textio: (https://textio.com/ )

From AI-powered sentiment analysis to personalized learning paths, AI is changing the HR game. But what about bias, privacy, and the human touch? 🤝 Our new podcast episode tackles these crucial questions and more. Tune in for expert insights and a list of further reading!

Additional Resources:

• AI Now Institute: A research institute examining the social implications of artificial intelligence. https://ainowinstitute.org/
• Partnership on AI: A non-profit coalition committed to the responsible use of AI. https://www.partnershiponai.org/
• The Alan Turing Institute: The UK's national institute for data science and artificial intelligence. https://www.turing.ac.uk/

References:

• Dastin, J. (2018, October 10). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters.
• IBM. (2021). The enterprise guide to closing the skills gap.
• Mezrich, R. (2023, June 7). How AI Will Revolutionize HR Practices. Forbes.
• Nguyen, H., & Huat, L. (2021). The Impact of Sentiment on Employee Performance. Journal of Organizational Behavior.
• PwC. (2022). AI in HR: Employee and Employer Perspectives.
• Raji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., ... & Barnes, P. (2020). Actionable auditing: Investigating the impact of publicly naming biased performance audits. In Proceedings of the 2020 AAAI/ACM Conference on AI, Ethics, and Society (pp. 228-234).
• Tambe, P., Cappelli, P., & Yakubovich, V. (2023, March-April). AI in HR: A Killer Combination or a Dangerous Game? Harvard Business Review.
• World Economic Forum. (2019). How to prevent discriminatory outcomes in machine learning.