The Transformer, with its scaled dot-product attention mechanism, has become a foundational architecture in modern AI. However, this mechanism is computationally intensive and incurs substantial energy costs. We propose a new Transformer architecture EcoTransformer, in which the output context vector is constructed as the convolution of the values using a Laplacian kernel, where the distances are measured by the L1 metric between the queries and keys. Compared to dot-product based attention, the new attention score calculation is free of matrix multiplication. It performs on par with, or even surpasses, scaled dot-product attention in NLP, bioinformatics, and vision tasks, while consuming significantly less energy. (This version (v2) supersedes v1 and reflects the intended release and licensing.)

'The Big Sunday Show' highlights Elon Musk's upcoming interview with Tucker Carlson warning about the dangers of A.I.. The U.S. Patent and Trademark Office has launched a process that could determine whether artificial intelligence systems can get full or partial credit as inventors of new ideas that win patent protection. USPTO on Monday announced it would hold a "listening session" on this question in early May, and is accepting public comment on whether AI has now become so advanced that it should somehow be credited as an inventor when it produces an idea that has yet to be conceived by mankind. The question of whether and how to credit AI for new inventions is one that has emerged over the last few years. In 2019, USPTO asked for public comment on whether AI is now so advanced that federal laws need to be rewritten in order to protect inventions from "entities other than natural persons."

March 31, 2023 - Artificial Intelligence suddenly seems to be everywhere. ChatGPT is writing human-sounding sermons, news updates, and answers to law school exam questions, while Dall·E is generating images ranging from the lifelike to the surreal in response to virtually any prompt. With much less fanfare, AI has already become ubiquitous in myriad ways. AI curates social media feeds and generates purchasing suggestions to fill internet shopping carts. AI saves lives by identifying potential pharmaceutical compounds and by quickly and accurately interpreting medical scans and images.

Patent prosecutors should consider drafting claims to avoid the situation where the AI is the only entity providing an inventive contribution. Artificial intelligence (AI) is making an impact in our everyday life. AI helps us cut grass and vacuum living rooms. It helps us identify images for applications from waste sorting to medical diagnosis. AI also is making an impact in research and development.

Early-stage companies are innovating new artificial intelligence-based solutions, but they often face questions as to whether such technology can be protected and the best strategy for doing so. Without an understanding of how to protect their R&D investment and claim technology as proprietary, startup companies are leaving a tool behind, possibly forfeiting market share and investments as a result. The considerations below will be useful for companies trying to understand the opportunities to protect their innovation. AI software is patentable, and applicants are seeking protection at a remarkable rate. In 2000, the U.S. Patent and Trademark Office (USPTO) had received about 10,000 applications directed to artificial intelligence, and by 2020, that number reached about 80,000 applications, of which 77% were approved.

The Federal Circuit recently held as a matter of statutory interpretation that an artificial intelligence system cannot be named as an inventor on a US patent application. This holding, which effectively excludes AI systems from the category of "individuals" eligible to be named as inventors, may complicate the intellectual property strategies of innovators who use advanced AI for research and development. Here's what happened and why it matters. The Federal Circuit was asked to determine whether an AI system called DABUS could be named as the inventor on two separate patent applications. The first disclosed a light source that was calibrated with a specific frequency corresponding to, among other characteristics, certain human brainwave activity.

The US Court of Appeals for the Federal Circuit found that an artificial intelligence (AI) software system cannot be listed as an inventor on a patent application because the Patent Act requires an "inventor" to be a natural person. Stephen Thaler develops and runs AI systems that generate patentable inventions, including a system that he calls his "Device for the Autonomous Bootstrapping of Unified Science" (DABUS). In 2019, Thaler sought patent protection for two of DABUS's putative inventions by filing patent applications with the US Patent & Trademark Office (PTO). Thaler listed DABUS as the sole inventor on both applications. The PTO found that the patent applications lacked valid inventorship and sent a Notice of Missing Parts requesting that Thaler identify a valid inventor.

Artificial Intelligence (AI) is being seen as the "secret ingredient" to a multitude of difficult technical problems. In a specific example where AI has been successfully applied to a solution, Ravin AI has developed a product which allows fleet managers to track their vehicles and to determine if any have been damaged. This has a variety of economic benefits. Notably, the company has managed to obtain patent protection for their product in Europe. It is claimed that this is the first patent for drive-by visual inspection.

In the second of a series of blogs from our global offices, we provide a overview of key trends in artificial intelligence in France. What is France's strategy for Artificial Intelligence? The French president, Emmanuel Macron, announced in March 2018 his ambition for France to become a global leader of the artificial intelligence (AI) ecosystem. The first phase of the National Programme included an initial investment of €1.5 billion into the creation of a network of interdisciplinary institutes dedicated to artificial intelligence (the "3IA" institutes) and the financing of multiple AI projects overseen by Bpifrance. The second phase will provide for €2 billion of private and public funding to attract and train new talent.

We previously discussed which portions of an artificial intelligence/machine-learning ("AI/ML") platform can be patented. Under what circumstances, however, is it best to keep at least a portion of the platform a trade secret? And what are some best practices for protecting trade secrets? In this post, we explore important considerations and essential business practices to keep in mind when working to protect the value of trade secrets specific to AI/ML platforms, as well as the pros and cons of trade secret versus patent protection. What qualifies as a "trade secret" can be extraordinarily broad, depending on the relevant jurisdiction, as, generally speaking, a trade secret is information that is kept confidential and derives value from being kept confidential. This can potentially include anything from customer lists to algorithms.