Zulfikar Ramzan, the former chief technology officer for cybersecurity giant RSA, holds a controversial belief regarding artificial intelligence …

The European Parliament's Legal Affairs (JURI) Committee, one of the 20 standing committees made up of a number of Members of the European Parliament, recently held a session discussing the EU Artificial Intelligence Act ("AI Act"). Here, we highlight key'thinking points' discussed to give an indication of where the AI Act may change from its current draft. The session was short, so potential answers will be the subject of further debate. For the background on the European Commission's proposed AI Act, see our articles "Artificial intelligence - EU Commission publishes proposed regulations" and "EU Artificial Intelligence Act - what has happened so far and what to expect next". AI has the potential to bring many benefits to users and wider society.

The board found that Thaler's AI-created image didn't include an element of "human authorship" -- a necessary standard, it said, for protection. Creativity Machine's work, seen above, is named "A Recent Entrance to Paradise." It's part of a series Thaler has described as a "simulated near-death experience" in which an algorithm reprocesses pictures to create hallucinatory images and a fictional narrative about the afterlife. A 1997 decision says that a book of (supposed) divine revelations, for instance, could be protected if there was (again, supposedly) an element of human arrangement and curation. This doesn't necessarily mean any art with an AI component is ineligible.

Institut für Theoretische Physik, Universität Heidelberg, Philosophenweg 16, 69120 Heidelberg, Germany Recent results suggest that flow-based algorithms may provide efficient sampling of field distributions for lattice field theory applications, such as studies of quantum chromodynamics and the Schwinger model. In this work, we provide a numerical demonstration of robust flow-based sampling in the Schwinger model at the critical value of the fermion mass. In contrast, at the same parameters, conventional methods fail to sample all parts of configuration space, leading to severely underestimated uncertainties. Many important physical systems across particle and condensed matter physics can be described in the language of quantum field theory (QFT). Autocorrelations may become especially severe if MCMC updates are configurations, which generates samples by continuously unlikely to generate transitions between modes that are evolving the fields through configuration space via Hamiltonian separated in configuration space.

Transformer-based methods have shown great potential in long-term time series forecasting. However, most of these methods adopt the standard point-wise self-attention mechanism, which not only becomes intractable for long-term forecasting since its complexity increases quadratically with the length of time series, but also cannot explicitly capture the predictive dependencies from contexts since the corresponding key and value are transformed from the same point. This paper proposes a predictive Transformer-based model called {\em Preformer}. Preformer introduces a novel efficient {\em Multi-Scale Segment-Correlation} mechanism that divides time series into segments and utilizes segment-wise correlation-based attention for encoding time series. A multi-scale structure is developed to aggregate dependencies at different temporal scales and facilitate the selection of segment length. Preformer further designs a predictive paradigm for decoding, where the key and value come from two successive segments rather than the same segment. In this way, if a key segment has a high correlation score with the query segment, its successive segment contributes more to the prediction of the query segment. Extensive experiments demonstrate that our Preformer outperforms other Transformer-based methods.

Quantum Annealing (QA) was originally intended for accelerating the solution of combinatorial optimization tasks that have natural encodings as Ising models. However, recent experiments on QA hardware platforms have demonstrated that, in the operating regime corresponding to weak interactions, the QA hardware behaves like a noisy Gibbs sampler at a hardware-specific effective temperature. This work builds on those insights and identifies a class of small hardware-native Ising models that are robust to noise effects and proposes a procedure for executing these models on QA hardware to maximize Gibbs sampling performance. Experimental results indicate that the proposed protocol results in high-quality Gibbs samples from a hardware-specific effective temperature. Furthermore, we show that this effective temperature can be adjusted by modulating the annealing time and energy scale. The procedure proposed in this work provides an approach to using QA hardware for Ising model sampling presenting potential new opportunities for applications in machine learning and physics simulation.

Early stopping is a simple and widely used method to prevent over-training neural networks. We develop theoretical results to reveal the relationship between the optimal early stopping time and model dimension as well as sample size of the dataset for certain linear models. Our results demonstrate two very different behaviors when the model dimension exceeds the number of features versus the opposite scenario. While most previous works on linear models focus on the latter setting, we observe that the dimension of the model often exceeds the number of features arising from data in common deep learning tasks and propose a model to study this setting. We demonstrate experimentally that our theoretical results on optimal early stopping time corresponds to the training process of deep neural networks.

Speaking at The Wall Street Journal's virtual CIO Network Summit event on Tuesday, Rep. Jim Langevin (D., R.I.), a senior member of the House Armed Services Committee, said he is taking an "all hands on deck approach" to prepare for possible cyber retaliation against the U.S. "We have to be realistic and understand that as we impose sanctions--we take actions--there could be blowback here," said Rep. Langevin. In preparing for possible cyberattacks, Rep. Langevin said, "private companies also have a role to play." He said they should be implementing testing procedures to back up and restore data, instituting multifactor authentication on devices connected to their networks, ensuring software is up-to-date and patching known vulnerabilities. Theresa Payton, founder and CEO of Fortalice Solutions and former CIO of the White House under President George W. Bush, said companies should consider locking accounts after two or three failed login attempts. "During challenging times such as these, the Russian operatives could be using password spraying attacks, recycling passwords from past password data dumps [and] using artificial intelligence" to access corporate networks, Ms. Payton said at the CIO Network Summit event.

Underwater robots help the military solve various tasks: clear mines, check underwater structures, map the bottom, deliver cargo, and provide communication between submarines and ships. The military is also interested in large underwater robots. Now, the U.S. Navy has showcased its new Snakehead Large Displacement Unmanned Undersea Vehicle (LDUUV) for the first time during the christening event at the Narragansett Bay Test Facility. The event was hosted by the Naval Undersea Warfare Center (NUWC) Division Newport and the Program Executive Office Unmanned and Small Combatants (PEO USC). The Snakehead is a modular, reconfigurable, multi-mission LDUUV deployed from submarine large ocean interfaces, with a government-owned architecture, mission autonomy, and vehicle software.

The Internal Revenue Service says it's giving taxpayers with individual accounts a new option to verify their identity: a live virtual interview with tax agents. This comes after the IRS backed away from a planned program to require account holders to verify their ID by submitting a selfie to a private company, a proposal that drew criticism from both parties in Congress and from privacy advocates. The agency says account holders can still choose the selfie option, administered by ID.Me. But if they'd rather not, the agency says, taxpayers will have the option of verifying their identity "during a live, virtual interview with agents; no biometric data – including facial recognition – will be required if taxpayers choose to authenticate their identity through a virtual interview." The IRS announced the new option on Monday. It says that ID.Me will destroy any selfie already submitted to the company, and that those selfies now on file will also be permanently deleted "over the course of the next few weeks."