IBM Research released a 2018 retrospective that provides a sneak-peek into the future of AI. They have curated a collection of 100 IBM Research AI papers and have published this year, authored by researchers and scientists from 12 global labs.
These scientific advancements are core to their mission to invent the next set of fundamental AI technologies that will take them from today’s “narrow” AI to a new era of “broad” AI, where the potential of the technology can be unlocked across AI developers, enterprise adopters and end-users.
Broad AI will be characterized by the ability to learn and reason more broadly across tasks, to integrate information from multiple modalities and domains, all while being more explainable, secure, fair, auditable and scalable.
Three trends to watch out for:
- Trust and transparency will continue to drive the AI-conversation –with companies applying new anti-bias techniques, in combination with guidance from in-house and industry ethics advisory groups, to make their products and platforms fairer.
- Human intuition that helps one understand cause/effect, like flipping a switch will cause a light to turn on – presents an enormous obstacle to machines.
- An increased research into how quantum computing may help scale AI models – a key area of exploration as one continues to drive toward real-world use cases for quantum.
Highlights of 2018 include:
- Advances in training techniques that let us train AI vision models with less data.
- Important developments boost trust in AI systems, developing new ways to counter bias in data sets and shedding new light on how AI makes decisions.
- IBM Research is one of the world’s largest industrial research organizations, with thousands of researchers working across six continents on artificial intelligence, quantum computing, and other key technologies.
