Generative AI & Machine Learning
Our partner service providers analyze how technology can help an organization’s business, do the necessary research legwork on their behalf, and implement practical solutions that impact the top and bottom line.
generative ai
Generative AI refers to a class of artificial intelligence systems designed to generate new content or information rather than simply analyzing or processing existing data. These systems employ generative models, which are trained on large datasets to learn patterns and structures inherent in the data. One prominent type of generative model is the Generative Adversarial Network (GAN), where two neural networks, a generator, and a discriminator, engage in a competitive learning process.
The generator creates new data instances, such as images, text, or other types of content, while the discriminator evaluates these instances for authenticity. Through iterative training, the generator improves its ability to produce content that is increasingly indistinguishable from real data. Generative AI has found applications in various fields, including image synthesis, text generation, and even creative tasks like art and music creation.
Despite its promising capabilities, generative AI also raises ethical concerns, particularly regarding the potential misuse of generated content for misinformation or deepfake creation. Ongoing research and development in the field aim to balance the positive applications of generative AI with safeguards against its misuse.
Machine Learning
Machine Learning can help businesses design systems that are better able to perform pattern recognition and make more accurate predictions. IDS approaches technology based on the financial ROI impact to your business. Here are three business vertical examples:
Retail:
AI helps inform better forecasts and increase transaction sizes through more personalized recommendations to eCommerce buyers.
Financial Services:
Machine Learning techniques can find non-obvious connections between leading indicators of how assets will react to various market conditions and events. While statistical analysis tools like SAS can help you create regression models on historical data, these models are often brittle, and unable to adapt to a constantly changing environment. This results in a drift of accuracy of predictions.
Supply Chain:
AI can help optimize inventory positioning into strategically located distribution centers and shorten delivery times.
Leverage IDS on your AI or machine learning journey
Organizations who engage in R&D projects can benefit by lowering their R&D costs, but the greatest benefit is time. We have a vast service provider team ready and able to work on your new concept. You will not need to recruit, hire, train and retain talent in an area that inherently has low supply.
Since the greatest benefit will come to the first to market, being able to innovate faster will enable you to grab market share before competitors can enter the space.