Why: AI Executive Learning
Machine Learning
Machine Learning is a subset of AI that enables computers to learn from data and make decisions based on patterns. This tech shines in use cases like customer segmentation, where it groups consumers by behavior, making marketing more efficient. It's also key in predictive maintenance, detecting machine failures before they happen. Plus, it's a powerhouse in fraud detection, flagging unusual user activities for review.
Language Processing
Language Processing is a subfield of AI focused on helping computers understand and interact with human language. It's more than just reading text; it's about the computer really understanding what you're saying. This tech excels in tasks like sentiment analysis, scanning reviews or social mentions to adjust business strategy based on public opinion. It powers advanced customer support chatbots that go beyond scripts to resolve complex issues. It's also behind the smart content recommendations on streaming services and can even automate content moderation by understanding context, not just keywords.
Robotic Process Automation
Robotic Process Automation (RPA), is like your tireless virtual employee that takes care of repetitive, rule-based tasks. It's great for data entry, swiftly moving or inputting information with zero errors. It streamlines invoice processing by extracting and validating details. RPA simplifies employee onboarding, taking care of welcome emails and software setup. It helps in customer service by managing straightforward queries, leaving the complex stuff for your human reps. Plus, it can generate and submit compliance reports automatically, making regulatory headaches a thing of the past.
Generative AI
Generative AI is a type of AI that can create new content, whether it's text, images, music, or even entire virtual worlds. It's not just about understanding or analyzing data; it's about making something new from scratch. In product design, it can spit out multiple design variations in no time, saving you manual effort. It’s also invaluable in simulation and testing, crafting realistic virtual scenarios for anything from pharmaceuticals to auto safety. Personalization gets a boost too, like video games that adapt to your play style or music apps that generate songs to fit your mood. Plus, if you need more data for analysis, it can synthesize new data sets, giving you more to work with.
Testimonials: What Our Clients Are Saying
Without their help, we may have gone out of business. We saw a 1,000% increase over the maximum capacity of our legacy systems, over 48,000 orders per day, and an average of 75 million page views and 2.3 million unique users each month in 2017.
Asif is a brilliant computer scientist, a physicist, an original thinker, an erudite scholar, and an artist who can sculpt new algorithms, and paint new solutions, veritably a Leonardo da Vinci of our times, and a passionate educator with deep insight into AI/ML/DL/Data-Science/Big-Data topics.
When it comes to Big-data and machine learning, I would simply say he (Asif) knows A-Z in that. No matter what the domain is, he has machine-learning-based solutions for the problems involved. Working with him for years, I have realized how his predictions on the machine learning revolution in big data have come true.
We’ve done development in the past..the SolutionMap is a higher level way of defining a comprehensive approach to getting the success that you want.
It was not just about software…it was all about what is this going to do in your company, how are the people in your organization with your partners and with your other stakeholders going to interact with this piece of software and what are their expectations of it…it also helped us on the backside thinking about our business processes…it was really illuminating to me.
From the design through to the development detail, they listened, understood, and carefully tested before release, often pushing our initial ideas to a better outcome.
