Yes, but software must be tied to a specific technical improvement, such as a novel way of processing data or improving computer performance, rather than an abstract idea implemented on a generic computer. This distinction is the central challenge in software patent applications and the most common reason they're rejected.

Patenting software requires drafting claims around a specific technical mechanism or improvement, not just the end result the software achieves, since claims that read as an abstract idea (US) or a computer program "as such" (Europe) face rejection under current eligibility standards. A patent attorney experienced in software claims is particularly valuable here, given how frequently these rejections occur.

Software isn't always rejected, but it faces a higher bar than most other invention types, since claims need to demonstrate a genuine technical improvement rather than an abstract process running on a computer. Well-drafted software patents that anchor claims to specific technical mechanisms are granted regularly.

Granted software patents commonly cover specific technical improvements like novel data compression methods, unique ways of processing sensor data, or improved algorithms for a defined technical task like image recognition speed. Patents covering a generic "app that does X" without a specific technical mechanism are the ones most likely to be rejected.

No, the literal source code you write is protected automatically by copyright, not patent; a patent instead protects the underlying novel technical process or method the code implements. The two protections work together: copyright stops someone copying your code, a patent stops someone implementing the same process in different code.

AI patents protect specific, novel technical methods for training or applying machine learning models, such as a new model architecture or a technical improvement to accuracy or efficiency. The general concept of "using AI to do X" without a specific technical mechanism is unlikely to survive examination.

Patenting AI involves the same core requirements as any software patent, but claims typically need to describe specific architectural, training, or technical improvements to a model or system, rather than the general application of known machine learning techniques. This makes claim drafting for AI inventions particularly demanding.

A specific, novel technical method for training or applying a machine learning model can be patented, but the general mathematical concept underlying a model type typically cannot. Claims need to describe a concrete technical improvement, such as faster training or improved accuracy through a specific mechanism.

No, patent offices and courts worldwide, including the USPTO, EPO and UK courts in the DABUS cases, require a natural person to be named as inventor, and an invention generated entirely by AI without significant human contribution can't be patented. This remains an actively developing area of law as AI-assisted invention becomes more common.

A SaaS patent protects a specific novel technical method underlying a software-as-a-service product, such as a unique data processing or system architecture innovation, rather than the business model of delivering software over the internet itself. The same eligibility standards that apply to software generally apply here.

An app's underlying technical method can potentially be patented if it solves a specific technical problem, while the visual design of its interface may separately qualify for design patent protection. An app that simply displays existing information in a new arrangement, without a technical mechanism behind it, is unlikely to be patentable on its own.

Patenting a website itself is rare; what's typically patentable is a specific novel technical process the website implements, such as a unique method of processing transactions or personalising content, not the website's visual layout or general functionality. Purely presentational or business-method aspects face significant eligibility challenges everywhere, under Section 101 in the US and the "as such" exclusions in Europe.

Physical AI refers to AI systems that perceive and act in the physical world, such as robots and autonomous machines, and specific technical implementations of physical AI, like novel sensing, control or decision-making methods, can be patented under the same standards as other AI inventions. This is an emerging and fast-growing patent category as robotics and embodied AI development accelerates.

Current physical AI patent activity, sometimes referred to as physical intelligence patents, concentrates on novel sensor fusion methods, control algorithms for physical manipulation, and techniques for translating perception into physical action. As with all software and AI patents, claims need to describe a specific technical mechanism rather than the general goal of "AI that acts in the physical world."

Startups in physical AI should prioritise patenting the specific technical mechanisms that differentiate their system, such as unique control or perception methods, while considering trade secret protection for implementation details that don't need public disclosure. Given how fast this field is moving, filing priority applications early to lock in priority dates is particularly important.

A robotics patent protects a specific novel mechanical, control, or perception system used in a robot, rather than the general concept of robotics itself. Claims typically focus on a particular technical mechanism, such as a novel actuator design or a specific control algorithm.

Patenting a robot generally means identifying and claiming its specific novel elements, whether mechanical design, control software, or sensor systems, since "a robot that does X" alone is too broad and abstract to be patentable. A thorough invention disclosure describing exactly what's technically new is the essential first step.

An autonomous systems patent protects specific technical methods enabling a system to sense its environment, make decisions and act without continuous human control, such as novel navigation or decision-making algorithms. These patents span consumer, industrial and defense applications and face the same eligibility standards as other AI and robotics inventions.

An embodied AI patent protects specific technical implementations of AI systems that interact physically with the real world, distinct from purely software-based AI. As with other physical AI patents, claims need to describe a concrete technical mechanism rather than the broad concept of embodiment itself.

Robotics IP strategy typically combines patents on core mechanical and control innovations with trade secret protection for manufacturing know-how that doesn't need public disclosure. Given the pace of robotics development, many companies file priority applications early and refine claims as the technology matures.

Yes, specific novel mechanisms, control systems or manufacturing processes used in industrial robots are patentable under standard utility patent requirements. Broad claims covering "a robot for manufacturing" without a specific technical innovation are unlikely to be granted.

Specific novel technical elements of a humanoid robot, such as a particular balance control system, actuator design or perception method, can be patented, though the general concept of a humanoid robot itself cannot. As with other robotics patents, claim strength depends on how specifically the technical innovation is described.

Patenting hardware AI typically involves protecting specific chip architectures, sensor systems or physical components designed to run AI workloads efficiently, distinct from patenting the AI models or software that run on that hardware. Hardware and software AI innovations are often protected through separate, complementary patent filings.