CERN’s new AI tools promise Major physics discoveries.
New observational data from the James Webb Space Telescope and simulation models have confirmed a new type of planet unlike anything found in the Solar System. This provides another piece of the puzzle to understand how planets and planetary systems form.
To date, more than 5,000 exoplanets have been confirmed around stars other than the Sun.
Many exoplanets are unlike any of the planets in the Solar System, making it difficult to guess their true natures.
A tool developed by Keele University researchers has been shown to help detect fake news with an impressive 99% level of accuracy, offering a vital resource in combating online misinformation.
The researchers Dr. Uchenna Ani, Dr. Sangeeta Sangeeta, and Dr. Patricia Asowo-Ayobode from Keele’s School of Computer Science and Mathematics, used a number of different machine learning techniques to develop their model, which can scan news content to give a judgment of whether a news source is trustworthy and genuine or not.
The method developed by the researchers uses an “ensemble voting” technique, which combines the predictions of multiple different machine learning models to give an overall score.
Shares of Denver-based software provider Palantir rose nearly 27% on February 4 following 2024 fourth quarter results featuring faster-than-expected growth and an optimistic forecast for the current quarter and the year 2025.
Having risen 368% in the last year and sporting a price-earnings ratio of 516, according to the Wall Street Journal, do shares of Palantir have more upside? If Wall Street analysts are right, the stock is about 26% too high. However, what matters most for the future of Palantir’s stock is whether the company can keep beating expectations and raising guidance.
That could happen – especially if Palantir – which counts Peter Thiel among the company’s early investors – can harness artificial intelligence to make its defense and commercial customers better off.
Palantir fourth quarter performance and prospects.
In recent years, the debate concerning the ontology of mind and body has been structured around an opposition between monistic, physicalist ontologies (both reductive and non-reductive) and some form of dualism (both of property types and of kinds of substance). This, however, has not always been the case. In the early twentieth century, a monistic, but non-physicalist, ontology
Neutral monism was also considered a serious contender, favoured especially by theorists working within what James characterises as the radical empiricist tradition. This paper outlines a new version of this third species of position in the mind-body debate. Unlike its predecessors, however, this version of neutral monism is motivated not by primarily epistemological considerations, but on the basis of recent developments on the ontology of properties. It is argued that, if one adopts the \.
Experts and thinkers signed open letter expressing concern over irresponsible development of technology.
NMR spectroscopy and imaging show that dendrites in a solid-state Li battery are formed from Li plating on the electrode and Li+ reduction at solid electrolyte grain boundaries, with an interlapped stalled growth period.
The problem of many-over-one asks how it can be that many properties are ever instantiated by one object. A putative solution might, for example, claim that the properties are appropriately bundled, or somehow tied to a bare particular. In this essay, the author argues that, surprisingly, an extant candidate solution to this problem is at the same time an independently developed candidate solution to the mind-body problem. Specifically, what is argued here to be the best version of the relata-specific bundle theory—the thesis that each instance of compresence has a special intrinsic nature in virtue of which it necessarily bundles its specific bundle-ees—is also a species of Russellian monism, labeled by David Chalmers as ‘constitutive Russellian panprotopsychism’. The upshot of this connection is significant for the metaphysics of the mind-body problem: a credible theory of property instantiation turns out to have a built-in account of how consciousness is grounded in certain (broadly) physical systems.
Tu et al. demonstrate that the unique integration of a convolutional neural network with an empirical model measured for an optical scattering system can unscramble the scattering and see through the opaque medium in an untrained fashion, featured as a deep empirical neural network.