Machine Learning & Artificial Intelligence
Machine Learning and Artificial Intelligence have become important technologies in recent years, with these techniques maturing to practical use. ML is a subfield of AI, and both refer to a large array of sophisticated techniques that include logic, expert systems, probabilistic inference, dynamic Bayesian networks, and more recently, deep learning neural networks. Machine learning specifically refers to techniques in which software is not explicitly programmed, but the ML software learns from examples, similarly to the way humans and animals do.
The popularity of these techniques has led to job creation, new infrastructure spending, new IP development, patent filings, as well as to social and ethical concerns. At Sidespin Group, we have seen an increase in machine learning-oriented patent litigation and a need for machine learning experts and expert witnesses.
How We Help Clients
Startups and corporations looking to gain a competitive edge by commercializing machine learning innovation turn to us for help. We advise on high-level machine learning strategy, data strategy, team structuring, outsourcing, as well as low-level algorithm strategy.
Technical due diligence for investment, mergers, and acquisitions is critical in high-stakes transactions. With the popularity of Machine Learning and Artificial Intelligence, many organizations falsely claim to have such advanced technologies. We can confirm.
With the increased importance of Machine Learning and Artificial Intelligence in the commercial sector, there is an increase in patent filings and patent infringement lawsuits. We provide expert witness services for litigation support for patent infringement and trade secret misappropriation.
Types of Machine Learning Bias and the Legal Issues They Raise
As more people adopt consumer AI tools like ChatGPT, there’s growing concern about the potential bias in machine learning (ML). This bias can be more than just a source of embarrassment and anger among users. It can result in legal action. Here’s how to think about...
Why Litigation May Be Brewing Around Generative AI
Generative AI is having a moment. The last few months have seen rising use of image-generating apps like Lensa and Vana. Not only machine learning experts but regular people are using them to create AI-generated avatars and profile pictures. VCs are pouring money into...
Trade Secret Misappropriation
An early employee of a machine learning startup joined a leading technology company, where he developed similar algorithms to the ones he worked on at the startup. His original employer brought a trade secret misappropriation action and sought litigation financing. A leading litigation finance investor hired us to evaluate the merits of the case in support of their investment decision. Our machine learning expert witness evaluated the technology, separated the novel aspects from prior approaches, interviewed experts and attorneys involved with the case, analyzed all declarations submitted by either side, and reviewed related publications in the field.
The maker of a large open-source CMS was considering acquiring a social media analytics platform, and enlisted our help to conduct a thorough evaluation of the target company’s technology stack. Our experts analyzed the target’s machine learning technology stack to separate the in-house technology from open-source and 3rd party software. We looked for synergies between the offerings of the startup and the acquiring companies and made recommendations on future machine learning applications and features.
In addition, we analyzed the target’s open-source software exposure to copyleft licenses and cybersecurity vulnerability, we reviewed the software stack for scalability, extensibility, proper design principles, maintainability, evaluated their documentation, and software development life cycle practices.
Machine Learning Strategy
A medium-sized software vendor retained us to analyze opportunities to enhance their offerings by incorporating machine learning. We worked with the senior leadership to identify the company’s long-term goals and educate them about machine learning in general. We hosted a strategy workshop where we worked side-by-side with the leadership on how their vertical might be disrupted by machine learning in the future. Then, we worked with mid-level management to identify specific tactical initiatives and test the waters with pilot projects. We are engaged in the long run to help guide these new initiatives to full fruition.
Dr. Jonyer served as an assistant professor of computer science at OSU and had a National Science Foundation-funded research program in machine learning and artificial intelligence. His research focused on graph-based methods, social network analysis, genetic algorithms, genetic programming, and neural networks. He published 26 articles in machine learning, including an award-winning paper. Dr. Jonyer also founded two companies with data science at their core.
Dr. K., a Sidespin Group consulting expert, has worked in the area of neuromorphic computing, cellular neural/nonlinear networks, and contributed to both the algorithmic and implementation aspects of convolutional neural network (CNN) devices, advancing several aspects of computing techniques in the area of machine learning, partial differential equations, image decomposition, analysis, segmentation, and compression. He has also developed several applications in adaptive image processing for real-time image enhancement, image analysis, automatic target recognition, sensor fusion, and a range of high-performance military and commercial imaging systems.
Dr. Budavari is an Associate Professor of Applied Mathematics and Statistics at Johns Hopkins University, with secondary appointments in Computer Science, Physics, and Astronomy. He specializes in geographic information systems, GPS, database systems, analytics, and statistics. He has research interests in database systems, computational statistics, Bayesian inference, streaming and randomized algorithms, data-intensive parallel computing, scientific databases, data science in materials research, and survey astronomy. His research has been supported by the NSF, NASA, Google, the Army Research Office, NIH, DOD, Alfred P. Sloan Foundation, and the Hubble Space Telescope Science Institute, among others.
About Sidespin Group
Sidespin Group provides software experts for litigation support, technology commercialization, investment due diligence, technology strategy, and general software analysis services in a range of specializations, including in the areas of machine learning, telecommunications, and smartphones.
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