IBM is at the forefront of global research in machine learning(ML). According to a BanklessTimes data presentation, they registered 5400 different Machine learning patents between 2017 and 2021. They beat Microsoft and Google for the top spot, with Microsoft coming in second place with 2108 applications and Google in third with 1342.
Recently, the popularity of Machine learning tools has skyrocketed. This is due to both a growing trust in their accuracy and a reduction in costs. Many businesses now use ML to provide accurate predictions and quickly analyze large data sets.
It's against that backdrop that IBM is ramping up investments in AI. The firm says that its inventors are developing new tech to spur businesses in scaling their AI usage.
It’s focusing on initiating change through natural language processing (NLP), automation, and developing trust in AI. Additionally, it’s continuing to inject new abilities from its R&D arm into its products.
IBM says the next step in AI is what it calls fluid intelligence. The firm says that current machine learning technology is narrow. Consequently, using trained models for emerging needs requires significant time and new data training.
So we need AI that mixes a wide range of information, explores causal linkages, and discovers new experiences by itself.
Again it holds that people trust technology that they understand. That's because they've assessed it and believe in its safety. IBM also insists that users need to know that it's fair, reliable, and safe for users to trust an algorithm.
Its R&D department is pursuing different approaches that'll help it build future-centric AI systems. These align with societal values because they're solid, explainable, and accountable.
Moreover, IBM is developing new architectures and devices with vast processing abilities. That hardware is robust and fast enough to handle the massive reams of data we produce daily.
