Machine Learning Innovations in Asia

Recently, Celcom Axiata and Cisco have partnered together to improve mobile connectivity across Malaysia through the implementation of artificial intelligence (AI) and machine learning technology innovations in Asia Pacific. This would be accomplished through the joint efforts of both companies. The updates are centred on the integrated software-defined network (SDN) transport infrastructure that is scheduled to be deployed in future. This will be done with the intention of “substantially improving” the service provisioning time for “businesses of all sizes as well as consumers.”

To understand how machine learning innovations in Asia Pacific are impacting the international economy, look at what APAC is doing to make their sectors successful. Less visible industries are equally ready for innovation as high-tech fields, including machine learning innovations that are filed as machine learning patents by machine learning patent attorneys in Asia, including machine learning patent attorney in Malaysia, machine learning in Singapore, and the like. The spread of mobile phones in Asia-Pacific is changing the banking sector, which effectively uses machine learning. Smartphone and tablet use is rising throughout the region. 

In Asia, technological and scientific advances have advanced innovations based on machine learning and artificial intelligence. Most countries lag behind in these areas. Lower original creativity and ineffective technology exchange policies are to blame. Also, implementing a machine learning innovation landscape in Asia-Pacific countries has increased investment and MNC involvement. As an example, Tsinghua University in China has surpassed Korea’s POSTECH as the region’s most innovative university. The Chinese institution vaulted three ranks to become Japan and China’s top university. The results match Japan’s overall performance on Reuters’ lists of innovative universities.   

Asia-Pacific innovation also includes Fintech Labs. Companies can try new ideas and improve machine learning processes in these collaborative spaces. Busan Daily employed AI to study its audience’s preferences and deliver customised onsite search. It’s also building community tools and standards. These measures, together with more platform services, will be vital to regional success. Digital transformation based on machine learning will drive future innovation in Asia-Pacific. A review of Machine Learning Patent Landscape in Asia provides insights on strong AI patents and ML patents drafted by patent attorneys in Asia, which include enforceable patent claims.

Machine Learning Patent Example

Nowadays, many companies are opting for a patent related to machine learning to gain control over the market. In terms of ML basics, inventors understand that there exist three types of machine-learning mainly, including, supervised learning, unsupervised learning, and reinforcement learning. For example, to provide exact and short answers to its users, Google has recently patented a machine-learning algorithm to include rich media for a specific type of answers and provide the best results for voice searches. Similarly, Amazon has filed a patent to capture details of conversations happening around its smart device Alexa and record them. After analyzing such data, it shall be used for advertising purposes. On the other hand, Samsung has filed a patent for a drone that is controlled via hand gestures and facial recognization to project customized ads to its customers. This drone comes with a flying display with the ability to detect a person’s hand gestures, face, and pupils. 

Many countries have been debating over the process to determine the scope of examination standards and legal protection in case innovation created by ML is granted a patent right. Another question is what the scope of patent rights for the inventions should be that AI creates and involves the determination of examination standards along with the scope of restrictions and authorizations. Similarly, lawmakers are pondering over what should be the legal status of the invention that AI creates or how to treat the relationship between a general inventor, ML inventor, and ML as an inventor. The third question is regarding the distribution of innovation that ML creates, i.e., distribution and redistribution benefits for ML investors, ML owners, and the public. 

Machine Learning Innovations

The machine learning invention is an information product that also covers the legitimacy of property in market value. The patent system should assist such innovators to coordinate the balance between transaction security and freedom that the innovation market provides. The patent system must provide a normative approach for machine learning inventions and clarify the patentability of innovations to create sustainable development of the computer-human collaborative approach in the ongoing technology era. 

Machine Learning Patent FAQs

Here are few important frequently asked questions pertaining to machine learning patents.

​​Can you patent a ML model?

A patent for a machine learning model will contain certain components. It will contain the title of the invention, its description, claims, and the name of one or more inventors. A patent will also identify the patent assignee, which is a person who owns the rights to the invention. A patent for a machine learning model is a complex process. If you want to protect your creation, it is important to follow the proper procedures.

First, inventors should file a patent for a machine learning model only if it can be used to identify patentable ideas. Patent office examiners are required to search for patents using their skills, and machine learning could help them focus on higher-level tasks. While large software companies have been patenting artificial intelligence-related technologies for decades, startups in fields outside of the software sector are quickly taking advantage of the technology. Adaptability: Another key aspect of a patent for a machine learning model is the ability to make the algorithm fit the specific technical implementation. Adaptation to a specific technical implementation means that the algorithm is adapted to the way a computer operates. A neural network training method will consider the features of the computer to determine when to cache information. By utilizing such considerations, an innovation using a machine learning model can be patent-protected.

Are patents good for innovation?

The role of patents in promoting innovation has often been discussed across various forums. CEOs of high-tech companies argue that a patent is essential for their businesses, while economists are less sure. Some researchers have found that patents can hinder innovation (by 13%). That is why it is crucial to understand the role of patents in promoting innovation before making sweeping policy changes. 

Having a patent protects the technology. Patents also promote downstream development through contracts and commercialisation. Patents reduce the gap between science and industrial innovation, enabling new ideas to be reproduced by others. Furthermore, patents can foster the diffusion of knowledge and help facilitate the exploitation and commercialisation of new technologies. 

How do you patent machine learning?

As AI and machine learning become more commonplace, many innovators are seeking ways to protect their work with patents. Patent applications for machine learning and artificial intelligence have increased dramatically in recent years, but patent attorneys have struggled with how to claim these innovations. Luckily, there are a few steps inventors can take to ensure their work remains protected. Below are some key steps that patent attorneys can take to strengthen their machine learning patents.

Patent applications relating to AI and machine learning are essential for scientific discovery, but many technologies are not suited for patent protection. The application process can pose several risks. Some abstract ideas cannot be protected through patents, such as mental processes, methods of organizing human activity, mathematical formulas, or calculations. The government, however, continues to seek input from a range of companies on the topic of AI and machine learning, which can potentially lead to new innovations. 

When pursuing patents for AI and machine learning, inventors should first consider whether their innovation is truly innovative. Patent applications should contain claims, titles, and descriptions. Typically, the machine learning patent will name one or more inventors, as well as the assignee (the person who owns the patent rights).

In addition to the crucial points stated here relating to machine learning patents in Asia Pacific, the future business models based on innovation may regularly need assistance for Patent Searching. The results of a patent search report can assist in determining if Patent Drafting is the next step for International Patent Filing along with USPTO Patent Filing. In case of blockchain based business models, utility token Legal Opinion Letters may also be needed, along with a set of applicable contracts and agreements.

Our team of advanced patent attorneys assists clients with patent searches, drafting patent applications, and patent (intellectual property) agreements, including licensing and non-disclosure agreements.

Advocate Rahul Dev is a Patent Attorney & International Business Lawyer practicing Technology, Intellectual Property & Corporate Laws. He is reachable at rd (at) patentbusinesslawyer (dot) com & @rdpatentlawyer on Twitter.

Quoted in and contributed to 50+ national & international publications (Bloomberg, FirstPost, SwissInfo, Outlook Money, Yahoo News, Times of India, Economic Times, Business Standard, Quartz, Global Legal Post, International Bar Association, LawAsia, BioSpectrum Asia, Digital News Asia, e27, Leaders Speak, Entrepreneur India, VCCircle, AutoTech).

Regularly invited to speak at international & national platforms (conferences, TV channels, seminars, corporate trainings, government workshops) on technology, patents, business strategy, legal developments, leadership & management.

Working closely with patent attorneys along with international law firms with significant experience with lawyers in Asia Pacific providing services to clients in US and Europe. Flagship services include international patent and trademark filings, patent services in India and global patent consulting services.

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