In the world of artificial intelligence, the possibilities of innovations in business value cases, such as augmented product research and development, personalized customer interactions and automation of business processes, are endless. This Column offers insights into seven possible scenarios for the future of artificial intelligence that is likely to have an impact in the near future Seven ways artificial intelligence could evolve, Silicon ANGLE
As AI research and development progress, Alibaba has invested a great deal in AI & ML for the enhancement of their business processes. This article sheds some light on some of the ways in which Alibaba is using artificial intelligence, machine learning, NLP, and network security to transform and upscale its business to heights.How does Alibaba use artificial intelligence and machine learning?, Analytics Insight
Natural language processing (NLP) is one of the new tools that investors and business analysis are using or trialing to mine financial data and corporate statements for information or Slip up. This article sheds some light on how the linguistic patterns and tone of CEOs and other managers are increasingly being scrutinized and analyzed by investors using artificial intelligence, thus opening up a new frontier for opportunities for slip-ups. AI can see through you: CEOs’ language under machine microscope, The Economic Times
As AI systems learn data, bias can creep in if the data that’s used to train the algorithm is not representative or has systemic bias. Furthermore, biased data leads to biased predictions. This article explores what ethical AI is and How has AI been regulated, if at all? The ethics of artificial intelligence, Tech Xplore
All the big tech companies are focusing their research and development progresses towards AI & ML and appear to have their hands on every conceivable area within deep learning. The article paints a bigger picture of where the research efforts of Big Tech companies are heading, discusses some of their recent work and their favorite Deep Learning Techniques in their respective niche/popularized areas. Big Tech & Their Favourite Deep Learning Techniques, Analytics India Magazine
Google announced the introduction of Pathways, a new artificial intelligence solution that brings together the capabilities of multiple machine learning solutions on one platform. This article discusses how the new Pathways solution solves the limitations of today’s AI models. Google’s new Architecture Pathways, Claims to Solve Limitations of Today’s AI, Analytics India Magazine
ML has the potential to revolutionize the way organizations approach problem-solving and day-to-day operations. However, developing and deploying an AI model is entirely different in laboratory or pilot projects and Real-world. Operational principles paired with Machine Learning Delivery Platform (MLDP) can help deploy and manage the Lifecycle of the AI model. The article discusses the potential of different operation principles, be it for DevOps for software, DataOps for data, or MLOps for AI models. Operational Principles Can Help Manage the Lifecycle of ML Engineering and Deployment, AiThority
AI boom is sparked with the introduction of the practical application of AI through “deep learning”. But AI is not easy to implement. Top-notch companies are not exempted from challenges and failures. This article discusses how providing AI education to the workforce can create a more significant impact and enable the workforce to participate and contribute to the process, accelerate the adoption of AI and create better AI systems. Artificial Intelligence: Should You Teach It To Your Employees? , Forbes.
AI has the most significant potential when it augments and amplifies human capabilities. AI may be better at synthesis and decision making in well-defined areas of a problem. However, a human may be better at understanding the implications of the data AI analyzes. This article discusses the key areas where AI is developing and making a difference in work and empowering people. Artificial intelligence success is tied to ability to augment, not just automate, ZD Net
The rise of the adoption of AI initiatives across the business’ functional areas has accelerated exponentially. Despite its glamour and promise, AI takes time to get accepted and adopted. Companies should schedule time and effort to conduct training sessions and continue to emphasize the advantages of using AI over the traditional methods. This article sheds some light on how collaboration and involvement of people from all enterprise disciplines are necessary to deliver AI success. Humans in the loop: it takes people to ensure artificial intelligence success, ZD Net
Hope you enjoy reading our Sparity News roundup — Oct 2021.
We’ll see you next month with more.