Industry research firm Gartner made an audacious prediction: that 85 percent of AI projects won’t deliver for CIOs. That means in 20 artificial intelligence projects, only three will succeed – 17 of them will fall short. One core reason for failure is the lack of talent since AI is still in the early stages, and not many are experienced enough to implement AI.
The methodical process to train the computer to learn specific task or process is understood by someone who has successfully built models and commercialized it. Look for the successes and ask questions before picking the right team or company.
Training AI models starts with capturing the data, and cleansing it to be ready for annotating. Inbuilt solutions for annotating can be helpful and subject matter experts helps to navigate and guide the annotators to label the data precisely.
Training the models can be done using several algorithms, from multi node recurring neural networks to complex pre-trained models like BERT.
The outcome of the models is crucial after it's trained and published. Source data and cleansing is crucial for accurate models.
Our team has combined 20+ years experience in AI, Machine Learning and Natural Language Processing. Our team has successfully built startups and commercialized models in the areas of automotive, real estate, travel and healthcare.
Choosing the team that has previous experience is crucial for the success of implementing AI solutions at your company.
