SPREV, short for hyperSphere Reduced to two-dimensional Regular Polygon for Visualisation, is a novel dimensionality reduction technique developed to address the challenges of reducing dimensions and visualizing labeled datasets that exhibit a unique combination of three characteristics: small class size, high dimensionality, and low sample size. SPREV is designed not only to uncover but also to visually represent hidden patterns within such datasets. Its distinctive integration of geometric principles, adapted for discrete computational environments, makes it an indispensable tool in the modern data science toolkit, enabling users to identify trends, extract insights, and navigate complex data efficiently and effectively.

The movement for corporate city states cannot believe its good luck. For years, it has been pushing the extreme notion that wealthy, tax-averse people should up and start their own high-tech fiefdoms, whether new countries on artificial islands in international waters ("seasteading") or pro-business "freedom cities" such as Próspera, a glorified gated community combined with a wild west med spa on a Honduran island. Yet despite backing from the heavy-hitter venture capitalists Peter Thiel and Marc Andreessen, their extreme libertarian dreams kept bogging down: it turns out most self-respecting rich people don't actually want to live on floating oil rigs, even if it means lower taxes, and while Próspera might be nice for a holiday and some body "upgrades", its extra-national status is currently being challenged in court. Now, all of a sudden, this once-fringe network of corporate secessionists finds itself knocking on open doors at the dead center of global power. The first sign that fortunes were shifting came in 2023, when a campaigning Donald Trump, seemingly out of nowhere, promised to hold a contest that would lead to the creation of 10 "freedom cities" on federal lands. The trial balloon barely registered at the time, lost in the daily deluge of outrageous claims. Since the new administration took office, however, would-be country starters have been on a lobbying blitz, determined to turn Trump's pledge into reality. "The energy in DC is absolutely electric," Trey Goff, the chief of staff of Próspera, recently enthused after a trip to Capitol Hill.

Netflix has started testing a new search feature powered by OpenAI that can help customers find movies and shows to watch, according to Bloomberg. The streaming service has reportedly given select users in Australia and New Zealand the option to use the tool. It will allow users to search for terms other than a specific show's title, an actor's name or the genre they want to watch. Bloomberg says it will give them a way to search for content using more specific terms, like their mood. Presumably, that means the service can surface dramatic shows for a search query that says "sad," and seeing as it's powered by generative AI, users will most likely be able to use natural language in their search terms.

They rise to 70ft (21 metres), tilt forward and zip away in different directions, each carrying a paper bag. On a sleepy morning in the Irish capital the takeoffs build to a steady one every few minutes, with barely anyone glancing at the constant stream of aircraft buzzing back and forth. "No one's looking up – no one ever looks up," says the man responsible, Bobby Healy, the founder of the Dublin startup Manna Aero. People probably should take notice, because the drones are part of an effort to realise an ambition shared by Amazon, the Google sister company Wing and the Californian startup Zipline: instant, autonomous home delivery. Healy and his big-tech rivals hope drone delivery will change the course of the retail industry across Ireland, and then into the UK as soon as this year.

A horrific rape and incest video game has sparked fury by encouraging players to be'women's worst nightmare'. The game, titled'No Mercy', centres around a protagonist who rapes his family members including his aunt and his own mother. Players of the vile game are instructed to'never take no for an answer' in their ambition to'subdue' and'own' women. Despite its horrendous themes, the game does not have an official age rating and was available for sale on Steam, the most popular digital game store. The game's developer, Zerat Games, published the game on Steam in March where children as young as 13 can make an account.

A relevant problem in statistics is defining the correlation of two rankings of a list of items. Kendall's tau and Spearman's rho are two well established correlation coefficients, characterized by a symmetric form that ensures zero expected value between two pairs of rankings randomly chosen with uniform probability. However, in recent years, several weighted versions of the original Spearman and Kendall coefficients have emerged that take into account the greater importance of top ranks compared to low ranks, which is common in many contexts. The weighting schemes break the symmetry, causing a non-zero expected value between two random rankings. This issue is very relevant, as it undermines the concept of uncorrelation between rankings. In this paper, we address this problem by proposing a standardization function $g(x)$ that maps a correlation ranking coefficient $\Gamma$ in a standard form $g(\Gamma)$ that has zero expected value, while maintaining the relevant statistical properties of $\Gamma$.

Recently, a growing number of experts in artificial intelligence (AI) and medicine have be-gun to suggest that the use of AI systems, particularly machine learning (ML) systems, is likely to humanise the practice of medicine by substantially improving the quality of clinician-patient relationships. In this thesis, however, I argue that medical ML systems are more likely to negatively impact these relationships than to improve them. In particular, I argue that the use of medical ML systems is likely to comprise the quality of trust, care, empathy, understanding, and communication between clinicians and patients.

The cacophony of urban sounds presents a significant challenge for smart city applications that rely on accurate acoustic scene analysis. Effectively analyzing these complex soundscapes, often characterized by overlapping sound sources, diverse acoustic events, and unpredictable noise levels, requires precise source separation. This task becomes more complicated when only limited training data is available. This paper introduces a novel Quantum-Inspired Genetic Algorithm (p-QIGA) for source separation, drawing inspiration from quantum information theory to enhance acoustic scene analysis in smart cities. By leveraging quantum superposition for efficient solution space exploration and entanglement to handle correlated sources, p-QIGA achieves robust separation even with limited data. These quantum-inspired concepts are integrated into a genetic algorithm framework to optimize source separation parameters. The effectiveness of our approach is demonstrated on two datasets: the TAU Urban Acoustic Scenes 2020 Mobile dataset, representing typical urban soundscapes, and the Silent Cities dataset, capturing quieter urban environments during the COVID-19 pandemic. Experimental results show that the p-QIGA achieves accuracy comparable to state-of-the-art methods while exhibiting superior resilience to noise and limited training data, achieving up to 8.2 dB signal-to-distortion ratio (SDR) in noisy environments and outperforming baseline methods by up to 2 dB with only 10% of the training data. This research highlights the potential of p-QIGA to advance acoustic signal processing in smart cities, particularly for noise pollution monitoring and acoustic surveillance.

DoorDash has started robot deliveries in Los Angeles and Chicago. This is thanks to a partnership with the company Coco Robotics. Eligible customers will be able to receive sidewalk deliveries sourced from over 600 participating merchants. Coco robots have been making deliveries for DoorDash in Helsinki since late last year through its international sub-brand Wolt. DoorDash says that Coco robots completed over 100,000 deliveries during this initial pilot phase.

Modern search systems use a multi-stage architecture to deliver personalized results efficiently. Key stages include retrieval, pre-ranking, full ranking, and blending, which refine billions of items to top selections. The pre-ranking stage, vital for scoring and filtering hundreds of thousands of items down to a few thousand, typically relies on two tower models due to their computational efficiency, despite often lacking in capturing complex interactions. While query-item cross interaction features are paramount for full ranking, integrating them into pre-ranking models presents efficiency-related challenges. In this paper, we introduce InteractRank, a novel two tower pre-ranking model with robust cross interaction features used at Pinterest. By incorporating historical user engagement-based query-item interactions in the scoring function along with the two tower dot product, InteractRank significantly boosts pre-ranking performance with minimal latency and computation costs. In real-world A/B experiments at Pinterest, InteractRank improves the online engagement metric by 6.5% over a BM25 baseline and by 3.7% over a vanilla two tower baseline. We also highlight other components of InteractRank, like real-time user-sequence modeling, and analyze their contributions through offline ablation studies. The code for InteractRank is available at https://github.com/pinterest/atg-research/tree/main/InteractRank.