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A team from Martin Luther University Halle-Wittenberg, Johannes Gutenberg University Mainz, and Mainz University of Applied Sciences has unveiled an AI system capable of deciphering ancient cuneiform texts. This novel technology, leveraging 3D models, represents a significant advancement in understanding one of humanity’s earliest forms of writing.

Published in The Eurographics Association journal, the researchers’ study focused on a set of cuneiform tablets from the Frau Professor Hilprecht Collection. These tablets primarily originate from ancient Mesopotamia, a historical region in present-day Iraq. Often referred to as the cradle of civilization, this area is where some of the earliest human societies developed. These tablets, in particular, are inscribed with a series of symbols, signs, and wedges that form the languages of the region, such as Sumerian, Assyrian, and Akkadian.

Many are over 5,000 years old and offer a glimpse into ancient civilizations, covering a wide range of topics from everyday life to legal matters.

Target validation is a crucial step in pre-clinical drug discovery workflows that builds confidence on the identification of a genetic target as relevant to a disease. With recent advancements, CRISPR serves as a particularly powerful tool for this process, as it enables researchers to accurately modify genes and determine their function in a variety of experimental systems.

One scientist leveraging CRISPR gene editing in this way is Dr. Panos Zalmas, Head of the Open Targets Validation Lab based at the Wellcome Sanger Institute, whose work focuses on discovering and validating new putative disease targets for the development of safe and effective medicines.

In this SelectScience^® interview, we speak with Zalmas to learn how he is working to improve the rate of target adoption into drug discovery pipelines across therapy areas such as oncology, neurodegeneration, and immunology and inflammation. Here, Zalmas explains the importance of gene editing in his target validation workflows and highlights how CRISPR technologies in particular are key to the success of drug discovery.

Recent advances in the development of devices made of 2D materials are paving the way for new technological capabilities, especially in the field of quantum technology. So far, however, little research has been carried out into energy losses in strongly interacting systems.

With this in mind, the team led by Professor Ernst Meyer from the Department of Physics at the University of Basel used an atomic force microscope in pendulum mode to investigate a graphene device in greater detail. For this, the researchers utilized a two-layer graphene, fabricated by colleagues at LMU Munich, in which the two layers were twisted by 1.08°

When stacked and twisted relative to one another, the two layers of graphene produce “moiré” superstructures, and the material acquires new properties. For example, when the two layers are twisted by the so-called magic angle of 1.08°, graphene becomes a superconductor at very low temperatures, conducting electricity with almost no energy dissipation.

Altman seemed to understand his responsibility to run a viable, enduring organization and keep its employees happy. He was on his way to pulling off a tender offer–a secondary round of investment in AI that would give the company much-needed cash and provide employees with the opportunity to cash out their shares. He also seemed very comfortable engaging in industry-wide issues like regulation and standards. Finding a balance between those activities is part of the work of corporate leaders and perhaps the board felt that Altman failed to find such a balance in the months leading up to his firing.

Microsoft seems to be the most clear-eyed about the interests it must protect: Microsoft’s! By hiring Sam Altman and Greg Brockman (a co-founder and president of OpenAI who resigned from OpenAI in solidarity with Altman), offering to hire more OpenAI staff, and still planning to collaborate with OpenAI, Satya Nadella hedged his bets. He seems to understand that by harnessing both the technological promise of AI, as articulated by OpenAI, and the talent to fulfill that promise, he is protecting Microsoft’s interest, a perspective reinforced by the financial markets’ positive response to his decision to offer Altman a job and further reinforced by his own willingness to support Altman’s return to OpenAI. Nadella acted with the interests of his company and its future at the forefront of his decision-making and he appears to have covered all the bases amidst a rapidly unfolding set of circumstances.

OpenAI employees may not like the board’s dramatic retort that allowing the company to be destroyed would be consistent with the mission–but those board members saw it that way.

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A new AI system, Sturgeon, is redefining brain tumor surgeries.

Sturgeon is a pretrained neural network that uses incremental results from nanopore sequencing to rapidly classify central nervous system tumours and can be used to aid critical decision-making during surgery.

The notion of black holes is one that invokes terror and dread. They’re inescapable! They devour everything! Nothing ever comes out!

The accuracy of these beliefs falls on the spectrum of debatable to incorrect. And a pair of physicists has now calculated how proverbial blood might be wrung from the black hole stone. According to Zhan-Feng Mai and Run-Qiu Yang of Tianjin University in China, teeny tiny black holes could theoretically be used as a source of power.

Their calculations find that these ultradense objects could work as rechargeable batteries and nuclear reactors, providing energy on the scale of gigaelectronvolts.

Tesla CEO Elon Musk confirmed the company has begun to introduce the latest version of its ‘Full Self-Driving’ (FSD) semi-autonomous software in the US, with its ‘beta’ title – which refers to a product being tested by consumers – to be dropped.

Mr Musk confirmed Tesla employees are the first to experience the new system.

Known as version 12 (or v12), the new FSD could signify a major technological step forward in the industry – allowing the car’s computers to make its own judgements based on what its cameras see, rather than relying on “hard-coded programming”, website Not a Tesla App reports.