Today’s Top Picks:

Stay informed with our daily dose of AI news and industry insights to help you make informed business decisions.

• Are you investing a lot of resources in customer service chatbots? Microsoft Advertising has launched a chat API that allows you to monetize AI chat, helping you keep your customers happy and boost sales.

  • TL;DR - Selling without selling is the new black. Creating unforgettable customer experiences and turning customers into brand advocates is crucial for business success. As a business owner, you know your customers better than anyone else. You understand their problems, what they're looking for, and how they want to receive information. Use that knowledge to sell more without being pushy. Train your AI chatbots not only to answer customer inquiries but also to introduce advertisements that create meaningful connections with users, enhance brand perception, and ultimately drive better ROI.

• Do you want to grow your business' online presence? Try MetaGPT, the solution to web design with no previous coding experience.

  • TL;DR - In the age of the internet, having a website is the most profitable way to sell. It enables you to sell directly to your customers, cut costs, and eliminate intermediaries. But success is not just about having a website; it's also about how well and quickly you can execute your plans. AI tools like MetaGPT and AutoGPT, can help you build the perfect website using plain text without expensive web development fees, experiencing delays, or requiring coding expertise. All you need is the ability to ask the right questions, create proper prompts, and iterate on the outcomes.

• If you can't beat them, join them. While Hollywood writers took to the streets of LA to demand AI regulation, Grimes, a Canadian singer, has taken a different approach, creating an AI platform to generate songs and share royalties.

  • TL;DR - In business, turning problems into opportunities is the name of the game. Don't fear AI - it's here to improve, not destroy, your business. Get creative and identify the issues that humans can't solve alone. With AI-powered tools, you can supercharge your team's abilities, work smarter (not harder), break down cultural and language barriers, expand your reach, and create personalized experiences. If you're not sure where to start, join our waitlist for an AI toolkit designed specifically for businesses! We'll help you tackle your pain points and take your business to the next level.

AI Tip of the day:

Train your AI models with diverse data to avoid bias and improve accuracy using tools like Google AutoML and IBM Watson Studio.

To get the most out of AI, you need to train it. Training an AI model means teaching it how to recognize patterns or make predictions based on a set of examples. Let's say you're starting an online clothing store and you want to use AI to recommend products to your customers based on their browsing history. To do this, you would need to train the AI model on a large dataset of clothing items and customer preferences.

The process of training an AI model involves feeding it lots of data and tweaking its algorithms until it can accurately predict which items a customer is likely to buy. It's kind of like teaching a child to recognize different animals - the more examples you show it, the better it gets at distinguishing between them. Once you've trained your AI model, you can use it to make predictions, generate insights, or automate tasks that would be too time-consuming or complex for humans to do manually. It's a powerful tool that can help you take your business to the next level!

Diversity in training data is important because it helps ensure that the AI model can make accurate predictions and decisions across a wide range of situations and contexts. If an AI model is trained on a limited or biased dataset, it may not be able to recognize patterns or make predictions accurately in situations that are different from what it was trained on. For example, if a facial recognition AI model is trained only on pictures of people with light skin, it may not be able to accurately recognize faces of people with darker skin tones. On the other hand, if the AI model is trained on a diverse dataset that includes people of different skin tones, genders, ages, and backgrounds, it will be more accurate and fair in its predictions and decisions. This is because it has learned to recognize patterns that are relevant across a broader range of situations and contexts. By ensuring that training data is diverse and representative, we can help create AI models that are more accurate, fair, and inclusive.