Sharing insightful tips to help you better plan your AI-first strategy and AI software development endeavor.
As the research shows, there are only 300,000 AI researchers and practitioners worldwide today, with the market demanding millions of jobs to bridge the skills gap. Check out what it takes to grow a new generation of AI software developers and how to fill the skills gap now while many nations have yet to realize the transformative power of AI.
Let’s take a look at top 3 challenges facing companies seeking to jump fast on the ML technology bandwagon and derive substantial business value from it, and let me show you on real-life examples how ML outsourcing can be a good way to overcome all 3 challenges.
As progressive technologies, personalization, artificial intelligence, and Big Data gain momentum, traditional banking and financial systems undergo a major overhaul.
Most of the data created in the process of DevOps is related directly to the application deployment. Application monitoring replenishes server logs, generates error messages, and transaction tracing. The only reasonable way to analyze this data and make the right conclusions in real time is to use machine learning (ML).