IBM leads in machine learning research with 5400 patents
IBM is leading machine learning research with 5400 patents in the sector, according to a BanklessTimes data presentation.
The company registered 5400 different machine learning patents between 2017 and 2021, beating Microsoft and Google for the top spot, with Microsoft coming in second place with 2108 applications and Google in third with 1342. Samsung Electronics had 937 applications while Capital One came in at fifth with 921.
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 analyse large data sets.
"There's a lot of development that goes into making machine learning work well and become more intuitive. One indicator of the developments that companies are pursuing in this space is patent applications," the BanklessTimes presentation states.
"These point us to what they're working on, where they're trying to innovate, and the tech industry's future."
It's against that backdrop that IBM is ramping up investments in artificial intelligence. The firm says that its inventors are developing new tech to spur businesses in scaling their AI usage.
IBM is focusing on initiating change through natural language processing (NLP), automation, and developing trust in AI. Additionally, it is 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.
IBM's 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.
Meanwhile, IBM announced the acquisition of SXiQ, an Australian digital transformation services company specialising in cloud applications, cloud platforms and cloud cybersecurity.
According to a statement from the company, this move extends IBM's hybrid cloud and AI strategy by helping enterprises modernise and transform complex mission-critical applications on multiple clouds and platforms.
SXiQ works with Australian enterprises, as well as the Australian operations of large global companies, to migrate and modernise their cloud infrastructure and applications across multiple industries, including financial services, consumer products, energy, healthcare and the public sector.
