Intellectual property law
fromIPWatchdog.com | Patents & Intellectual Property Law
8 years agoWhen Universities Patent Their Research
Most universities earn little from patent licensing despite some high-profile cases.
Modern scientific societies are increasingly vulnerable due to their dependence on membership fees and journal subscriptions, which are being challenged by the rise of virtual networking and open-access publishing.
Meta is working on two proprietary frontier models: Avocado, a large language model, and Mango, a multimedia file generator. The open-source variants are expected to be made available at a later date.
Computer programs that check mathematical arguments have existed for decades, but translating a human-written proof into the strict programming language of a computer is extremely time-consuming, often taking months or even years.
Librarians have been actively collaborating and talking about it almost every day, whether it's creating tutorials and digital learning objectives or thinking about the conversations to have with instructors. It can feel like cognitive dissonance to be actively working with AI on a regular basis and also saying we're constantly thinking about the harms and the biases.
His message is clear: our world is built on abundant energy, around 80% of which has come from fossil fuels over the past 50 years. Because supplies are limited, energy consumption will peak in decades - sooner if humans attempt to limit climate change. To keep global warming below 1.5 °C by 2100, the use of fossil fuels must fall by 5-8% each year - a pace that is too fast for low-carbon energy to keep up with.
Within a couple of years of ChatGPT coming out, I had come to rely on the artificial-intelligence tool, for my work as a professor of plant sciences at the University of Cologne in Germany. Having signed up for OpenAI's subscription plan, ChatGPT Plus, I used it as an assistant every day - to write e-mails, draft course descriptions, structure grant applications, revise publications, prepare lectures, create exams and analyse student responses, and even as an interactive tool as part of my teaching.
I'm less interested in topics than in questions, and I'm less interested in publishing than I am in curation. When I've testified before Congress or dealt with an appropriations bill or a budget negotiation, this question, of what is the return on investments when you're doing R&D, comes up quite often. It's been asked by economists in very formal ways since at least the 1950s, but the data and the methods that were available were really not very strong.
In 2023, Australia abandoned its expensive and bureaucratic scholar-led research-assessment programme. New Zealand followed suit soon after. The hope, according to a transition plan unveiled by the Australian federal government's Department of Education and the research sector, was to find a "more modern, data-driven approach". In the United Kingdom, where financial pressures on universities are especially acute, there are similar calls to reform the Research Excellence Framework (REF), the country's performance-based research-funding system.
If you've worked in a technical role in news for long enough, you likely remember when the "show your work" spirit was everywhere. Newsroom nerds shared code on GitHub, swapped tips on social media and unfurled long blogs guiding others on how to get things done. You might also have a vague sense that - like reaction GIFs, demotivational posters, and that guy who sang "Chocolate Rain" - you're seeing less of it these days.
That was a year or so ago, and my first brush with what generative AI could do. Like many, I started using it for fun: planning trips, finding nineteenth century authors I could recommend to fantasy-loving students (a genre I don't read), and making a holiday card starring my dog, Harry. But as work piled up, I didn't have time for new toys, so now I use AI for work.