Desination will be a red barn on the right 1. Continued on next page 18 Use Case Example rewrite Rewrite the following text to be more light-hearted: -- {very formal text} -- chat The following is a conversation with an AI assistant.

Considering the proliferation of responses to Piantadosi's original paper and the ongoing debate sparked by this special issue of the Italian Journal of Linguistics, it is clear that the discussion has touched a raw nerve in linguistic theorizing . In the original target paper (Chesi, this issue), I illustrated three prototypical (and in many respects, extreme) positions -- the computational, theoretical, and experimental perspectives -- without explicitly endorsing any of them. Instead, I attempted to highlight what I believe are the key weaknesses o f each of these prototypical stances, ultimately concluding that formal (i.e., ' generative ') linguistics -- more specifically, Minimalis m, my theoretical comfort zone -- must adopt practices and tools that are common in both computational and experimental fields . As noted by most respondents, the title and some of the more extreme statements were intended as mild provocations to draw attention to core issues affecting linguistic theorizing . M y position -- somehow obscured behind the ' three - body problem ' -- is that any relevant scientific progress is driven by theoretical insight, not by trawling using experimental or computational methods that are cost - inefficient, energy - intensive, and ultimately unsustainable . Moreover, in full agreement with most of the replies, I believe that the success of certain large language models (L L Ms), which are based on specific architectural assumptions, do es not constitute a refutation of the generative paradigm. On the contrary, it strongly supports several key intuitions that have emerged within the generative linguistic tradition (Rizzi this issue) . H owever, a concrete problem of ' incommensurability ' arises (Hao this issue), as differing methodologies and specialized jargon (Butt this issue) often result in circular, unresolved discussions .

Transducer models have emerged as a promising choice for end-to-end ASR systems, offering a balanced trade-off between recognition accuracy, streaming capabilities, and inference speed in greedy decoding. However, beam search significantly slows down Transducers due to repeated evaluations of key network components, limiting practical applications. This paper introduces a universal method to accelerate beam search for Transducers, enabling the implementation of two optimized algorithms: ALSD++ and AES++. The proposed method utilizes batch operations, a tree-based hypothesis structure, novel blank scoring for enhanced shallow fusion, and CUDA graph execution for efficient GPU inference. This narrows the speed gap between beam and greedy modes to only 10-20% for the whole system, achieves 14-30% relative improvement in WER compared to greedy decoding, and improves shallow fusion for low-resource up to 11% compared to existing implementations. All the algorithms are open sourced.

The model, called Ask Ruth Bader Ginsburg, is based on 27 years of Ginsburg's legal writings on the Supreme Court, along with a host of news interviews and public speeches.

An upcoming update for dating app Tinder will allow women to initiate all conversations with potential matches. During an interview with Marketwatch, Match Group CEO Mandy Ginsburg said it plans to add a "women-talk-first setting" to Tinder, where any time a woman is matched by swiping right, she starts the dialogue. The setting is similar to one found on rival dating app Bumble. The key difference is Tinder users can choose to flip this setting on or off. On Bumble, women always initiate the conversations.

It's hard to come up with ideas for Halloween costumes, especially when it seems like all the good ones are taken. And don't you hate showing up at a party only to discover that there's *another* pajama cardinalfish? I train neural networks, a type of machine learning algorithm, to write humor by giving them datasets that they have to teach themselves to mimic. They can sometimes do a surprisingly good job, coming up with a metal band called Chaosrug, a craft beer called Yamquak and another called The Fine Stranger (which now exists!), and a My Little Pony called Blue Cuss. So, I wanted to find out if a neural network could help invent Halloween costumes.

Much as Linux, Windows, and iOS coordinate the execution of computing applications, laws coordinate the execution of human society. When new kinds of interactions emerge – sharing our airspace with private drones, for example, or algorithmic trading on financial markets – new laws are encoded to regulate those activities. Laws respond to conflicts of interest, keep criminals and cheats in check, and temper the abuse of power. "Space law, tax law, online law, regulations for autonomous vehicles and artificial intelligence... if you think about laws and how they evolve to match the complexity of the functions they coordinate, laws become an interesting problem for complex systems science," says SFI President David Krakauer. During SFI's 2016 Applied Complexity Network (ACtioN) and Board of Trustees Symposium April 3-5, themed "Law OS," Krakauer announced the beginning of a new research program at SFI on "Complexity and the Law."

I'm Paul Thornton, The Times' letters editor, and it is Saturday, July 16. How much more terrorism can France take? After yet another attack in that country -- this time in Nice, where a driver plowed a truck into a crowd of Bastille Day revelers -- at least 84 people are dead and authorities are busy gathering evidence to determine how it happened. But in the United States, some talking heads seem to possess answers that French investigators have yet to produce. Newt Gingrich, for example, called for government monitoring of mosques, a recommendation that earned him the scorn of The Times' editorial board: In the face of such a threat, people need leaders adept at analyzing data and thinking creatively about intelligence gathering and risk reduction.