Businesses must have an AI strategy already in place: Gartner® predicts that these new software applications created for businesses will have ML models or services by the time 2027 rolls around – proof that the business realm recognizes and leverages data in vast quantities.
With the proliferation of tools such as ChatGPT, organizations are accelerating their consideration of how Artificial Intelligence (AI) and Machine Learning (ML) can revolutionize their operations. Analyzing the implications associated with these technologies is highly advantageous, influencing various elements from marketing to customer service.
Companies have yet to find real rewards from AI. Delivering real-time actions proves challenging, as data is often provided too slowly within intricate settings. With badly timed system updates and the need for an appropriate structure, effective use of AI is very difficult to achieve.
Unlock Your Business Potential with Winning AI Strategies & Data Analysis
Google, Netflix, and Uber all have different Artificial Intelligence (AI) strategies – engineered around real-time data operating at a massively large scale. This has led to the success of embedding ml models into their applications leveraging the same streaming data source generation.
They use streaming services to comprehensively aggregate events and actions in real-time, which are then used to feed into ML models. A durable database supports this with massive amounts of event data.
Ultimately, it’s about taking immediate action based on your data and providing top-notch experiences to millions of customers in real-time. We can show some examples here:
- Tracking users’ actions, Spotify utilizes this data to enhance its recommendation engine to match users with content they are most likely to enjoy.
- Gathering driver, rider, and partner data, Uber uses this information to inform its prediction engine. This assists customers in understanding wait times and directing drivers to the best route.
- Fed Ex uses billions of collected package events to manage their operations better and give customers visibility into their delivery progress. Through this, customers are better informed about the status of their orders.
How DataStax Helps Create a New Class of Apps
Working towards making real-time data available, DataStax has dedicated 12 years to the endeavor. Beginning with Apache Cassandra®, they catered to the large datasets of the world and eventually progressed to Astra DB and Astra Streaming, making real-time data a potentially achievable reality.
DataStax has added another element to the equation: Kaskada, a machine-learning firm. The combination of DataStax and Kaskada is an electrifying development that promises to bring even more support and solutions to the emerging field of ML.
Kaskada’s engine helps customers quickly access real-time data and gain tangible value. By incorporating their technological solutions, we’ll take a streamlined approach to bring machine learning capabilities directly into the existing data platform rather than in reversed direction.
By leveraging a unified open-source stack, it is possible to unlock a new range of applications providing customers instantaneous, personalized experiences. For example, we can look at the conversational AI company Uniphore: their AI assistant analyses sentiment on sales calls.
Uniphore relies on DataStax to provide its AI experience – with speed, scalability, and cost efficiency. This feature then enables sellers to establish stronger customer relationships and loyalty. Without real-time data processing capability, Uniphore’s resolution wouldn’t be viable.
The Future is Bright – Embrace It With Hope and Determination
As we move forward with our vision to bring AI within reach for all, we aim to make real-time artificial intelligence a reality at 3X the scale and at half the cost. We are confident we have the necessary data, timing, and structure to achieve this.
My vision with my customers, communities, and partners is now ours to bring to fruition. This initiative is of great thrill and anticipation for me as we work to make it a reality. Excitement abounds as we all join together in executing this journey.
The development of real-time artificial intelligence (AI) technology represents a significant advancement in computing and can potentially transform many industries. With real-time AI, businesses and individuals can access powerful and sophisticated algorithms that can process vast amounts of data and provide actionable insights in real-time.
This can lead to increased efficiency, productivity, and competitiveness. However, as with any emerging technology, some challenges must be addressed, such as adequate data privacy and security measures and the potential for bias in AI algorithms.
Source: CIO
