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Training a machine-learning model to effectively perform a task, such as image classification, involves showing the model thousands, millions, or even billions of example images. Gathering such enormous datasets can be especially challenging when privacy is a concern, such as with medical images. Researchers from MIT and the MIT-born startup DynamoFL have now taken one …
Read more “Collaborative machine learning that preserves privacy”
The role of the AI engineer is rapidly evolving and gaining importance, and will be key to many companies’ adoption of the technology.Read More
It’s clear that Oracle is looking to use AI to compete with Salesforce, as well as fend off startups such as Gong and Salesloft.Read More
These AI startups are disrupting a variety of healthcare areas, from drug discovery and operational efficiency to disease detection.Read More
AI is very promising, but we need to make it simple to ensure it’s truly smart every step of the way to avoid real risk and even catastrophe.Read More
Reinforcement learning is the subset of ML by which an algorithm can be programmed to respond to complex environments for optimal results.Read More
A new study by Replicant shows 95% of contact centers have already adopted, are implementing, or plan to use automation within the next year.Read More
For the elderly, AI can enable independence and mobility, reduce need for caregivers, and detect important changes in health and activity.Read More
There is likely no future without AI. Ethical development and use of AI should not be contentious — it is a social responsibility.Read More
A holistic approach, good governance, and internal lifecycle automation are key factors of success in implementing conversational AI.Read More