Microsoft unveiled exciting updates for Copilot Studio during Ignite, enhancing user experience and functionality across its platforms. This is great news for business and enterprises and makes it easy to create copilots, agents and more.. https://blogs.microsoft.com/blog/2024/11/19/ignite-2024-why-nearly-70-of-the-fortune-500-now-use-microsoft-365-copilot/ Highlights 🚀 Introduction of new AI features to streamline workflows. 🛠️ Enhanced customization options for Copilot tools. 📊 Improved data integration for better analytics insights. 🧠 Advanced natural language processing capabilities. 🌐 Integration with additional Microsoft 365 applications. 🔒 New security measures to protect user data. 🎓 Training resources made available for developers. 📅 Roadmap for upcoming features shared with the community. 🤝 Partnership announcements to extend Copilot’s reach. 🎤 Live demos showcasing practical applications of updates. 🔄 Feedback mechanisms introduced for user suggestions. 🌟 Focus on improving accessibility for all users. 📈 Emphasis on optimizing performance and efficiency. 💡 Insights on how AI can transform business productivity. 🖥️ New tools for developers to create custom Copilot experiences.

This week, let’s dive into specific ways generative AI is making a tangible impact in businesses: 1. Content Creation with Jasper: Marketing teams are using Jasper to generate blog posts and social media content. A company can input a topic like “sustainable packaging” and Jasper can produce an entire article in minutes. 2. Customer Support Automation: Companies like Shopify use AI agents such as Zendesk’s Answer Bot to handle frequently asked questions. This allows businesses to provide instant responses to customers, improving satisfaction and freeing up human agents for complex inquiries. 3. Design Innovation with Autodesk: Autodesk’s generative design software allows engineers to input specific design goals and constraints. For instance, a manufacturer can create a lightweight part by specifying weight limits and material types, and the software will generate multiple design options. 4. Data Analysis with Tableau: Businesses are leveraging Tableau’s AI features to analyse sales data. A retail company can use Tableau to identify purchasing trends for targeted marketing campaigns and inventory management based on customer preferences. Generative AI is driving efficiency and innovation across various business functions. If you have questions or need assistance with these tools, feel free to reach out!

Pretty wild to watch some of the videos that customers have shared, being charged for 200 orders of chicken McNuggets and things like that, when the AI order bot was struggling especially with accents or customers ordering Pepsi Co drinks when they only serve Coca Cola made beverages. I am quite surprised that this was so bad, on the other hand with the number of order going through these drive-throughs I suspect that by-and-large it was working "okay", just the errors when they happened were so egregious that they had to pull the whole thing. The other thing that surprises me is that how it could have been so bad actually. The domain is very narrow and when you contrast with the incredible quality of voice transcriptions from online meetings its somewhat unlikely. Of course the environment is different, with traffic and other background noise. At the same time: my partner and I have been recording conversations that we have while going on city walks in Hong Kong and those transcribe amazingly well with OpenAI's Whisper. Ok, IBM is not OpenAI, but that the gap could be that big is a surprise to me. https://www.cnbc.com/2024/06/17/mcdonalds-to-end-ibm-ai-drive-thru-test.html

This article I stumbled upon, titled "How A.I. Is Revolutionizing Drug Development" from The New York Times explores how companies like Terray Therapeutics are harnessing the power of generative AI to accelerate the drug development process. These AI-driven startups are building sophisticated labs to generate massive amounts of molecular and biochemical data, which is then used to train AI models to design new drug candidates more efficiently. Read the full article here: https://www.nytimes.com/2024/06/17/business/ai-drugs-development-terray.html

A recent opinion piece in the New York Times argues that major tech giants like Google, Microsoft, and Amazon are systematically stifling innovation by co-opting promising AI startups before they can become competitive threats. The article suggests these large firms are using tactics like strategic investments, acquisitions, and exploiting data/network access to undermine the ability of new players to truly disrupt the market. This is concerning news for the future of AI development and technological progress. What do you think can be done to restore a more vibrant, competitive landscape in the AI industry? Should policymakers step in with new regulations, or is the answer more complex? Share your thoughts and insights in the comments.