Elon Musk's SpaceX is already one of the world's most valuable private companies. Elon Musk's SpaceX is already one of the world's most valuable private companies. Aerospace business and artificial intelligence firm to unite for IPO as world's most valuable private company Elon Musk's aerospace company SpaceX has acquired his artificial intelligence business xAI, in a $1.25tn (£910bn) merger that consolidates part of Musk's empire as SpaceX prepares to go public later this year. The two companies announced the deal on Monday in a statement on SpaceX's website, saying the merger would form "the most ambitious, vertically-integrated innovation engine on (and off) Earth, with AI, rockets, space-based internet, direct-to-mobile device communications and the world's foremost real-time information and free speech platform". SpaceX, one of the world's most valuable private companies, will gain xAI properties such as its Grok chatbot and the social media platform X.

Elon Musk's SpaceX is taking over his artificial intelligence (AI) start-up, as the billionaire continues to unify some of his many business interests. SpaceX confirmed the deal to acquire xAI, a smaller firm known for its Grok chatbot, posting a memo from Musk about the merger on its website. In the note, Musk said the combination would form an innovation engine putting AI, rockets, space-based internet, and media under one roof. Terms of the deal were not disclosed. However, a source familiar said it valued xAI at $125bn (£91bn) and SpaceX at $1tn, making it the most valuable private company ever.

The home secretary has announced a blueprint for reforming what she called the broken policing model in England and Wales. Shabana Mahmood confirmed the shake-up will create a new National Police Service (NPS) to fight the most complex cross-border crime and could also see the number of local forces in England and Wales cut by around two-thirds. She told the House of Commons she also intends to make better use of technology - including the largest-ever rollout of facial recognition. This government's reforms will ensure we have the right policing in the right place, Mahmood said. I set out reforms that are long overdue and define a new model for policing in this country, with local policing that protects our communities and national policing that protects us all.

This paper presents a systematic evaluation of racial bias in four major commercial automatic speech recognition (ASR) systems using the Pacific Northwest English (PNWE) corpus. We analyze transcription accuracy across speakers from four ethnic backgrounds (African American, Caucasian American, ChicanX, and Yakama) and examine how sociophonetic variation contributes to differential system performance. We introduce a heuristically-determined Phonetic Error Rate (PER) metric that links recognition errors to specific linguistically motivated variables derived from sociophonetic annotation. Our analysis of eleven sociophonetic features reveals that vowel quality variation, particularly resistance to the low-back merger and pre-nasal merger patterns, is systematically associated with differential error rates across ethnic groups, with the most pronounced effects for African American speakers across all evaluated systems. These findings demonstrate that acoustic modeling of dialectal phonetic variation, rather than lexical or syntactic factors, remains a primary source of bias in commercial ASR systems. The study establishes the PNWE corpus as a valuable resource for bias evaluation in speech technologies and provides actionable guidance for improving ASR performance through targeted representation of sociophonetic diversity in training data.

Cognitive maps provide a powerful framework for understanding spatial and abstract reasoning in biological and artificial agents. While recent computational models link cognitive maps to hippocampal-entorhinal mechanisms, they often rely on global optimization rules (e.g., backpropagation) that lack biological plausibility. In this work, we propose a novel cognitive architecture for structuring episodic memories into cognitive maps using local, Hebbian-like learning rules, compatible with neural substrate constraints. Our model integrates the Successor Features framework with episodic memories, enabling incremental, online learning through agent-environment interaction. We demonstrate its efficacy in a partially observable grid-world, where the architecture autonomously organizes memories into structured representations without centralized optimization. This work bridges computational neuroscience and AI, offering a biologically grounded approach to cognitive map formation in artificial adaptive agents.

London-listed miner Anglo American and Canada's Teck Resources plan to merge, marking the sector's second-biggest mergers and acquisitions deal ever and forging a new global copper-focused heavyweight. Under the proposed deal, which will require regulatory approvals and was announced on Tuesday, Anglo American shareholders will own 62.4 percent of the new company, Anglo Teck, while shareholders in Teck would hold 37.6 percent. The deal to form the world's fifth-largest copper company is also a big bet on copper by Anglo. Glencore's $90bn merger with Xstrata in 2013 remains the largest mining deal in history. Copper, used in the power and construction sectors, is set to benefit from burgeoning demand spurred by electric vehicles and artificial intelligence.

-- Enhancing simulation environments to replicate real-world driver behavior, i.e., more humanlike sim agents, is essential for developing autonomous vehicle technology. In the context of highway merging, previous works have studied the operational-level yielding dynamics of lag vehicles in response to a merging car at highway on-ramps. Other works focusing on tactical decision modeling generally consider limited action sets or utilize payoff functions with large parameter sets and limited payoff bounds. In this work, we aim to improve the simulation of the highway merge scenario by targeting a game theoretic model for tactical decision-making with improved payoff functions and lag actions. We couple this with an underlying dynamics model to have a unified decision and dynamics model that can capture merging interactions and simulate more realistic interactions in an explainable and interpretable fashion. The proposed model demonstrated good reproducibility of complex interactions when validated on a real-world dataset. The model was finally integrated into a high-fidelity simulation environment and confirmed to have adequate computation time efficiency for use in large-scale simulations to support autonomous vehicle development. Simulation-based evaluation has become an indispensable tool in the development and testing of Intelligent Transportation Systems (ITS), offering a safe and controllable environment for replicating complex real-world interactions.

AI-powered driving will help with a growing shortage of drivers, rising costs and relentless demand for faster deliveries. Artificial intelligence-powered self-driving trucks are no longer a distant concept. They are quickly becoming a real solution to some of the logistics industry's biggest challenges. As supply chains face growing pressure and the driver shortage deepens across the U.S. and Europe, Plus Automation is stepping up with bold ambitions and powerful AI. Recently, the Santa Clara, California-based startup announced it will go public through a merger with Churchill Capital Corp IX.

Diverse schools can help address implicit biases and increase empathy, mutual respect, and reflective thought by fostering connections between students from different racial/ethnic, socioeconomic, and other backgrounds. Unfortunately, demographic segregation remains rampant in US public schools, despite over 70 years since the passing of federal legislation formally outlawing segregation by race. However, changing how students are assigned to schools can help foster more integrated learning environments. In this paper, we explore "school mergers" as one such under-explored, yet promising, student assignment policy change. School mergers involve merging the school attendance boundaries, or catchment areas, of schools and subsequently changing the grades each school offers. We develop an algorithm to simulate elementary school mergers across 200 large school districts serving 4.5 million elementary school students and find that pairing or tripling schools in this way could reduce racial/ethnic segregation by a median relative 20% -- and as much as nearly 60% in some districts -- while increasing driving times to schools by an average of a few minutes each way. Districts with many interfaces between racially/ethnically-disparate neighborhoods tend to be prime candidates for mergers. We also compare the expected results of school mergers to other typical integration policies, like redistricting, and find that different policies may be more or less suitable in different places. Finally, we make our results available through a public dashboard for policymakers and community members to explore further (https://mergers.schooldiversity.org). Together, our study offers new findings and tools to support integration policy-making across US public school districts.

Nissan has more significant troubles than Honda and in recent years has slogged through management upheaval. In the United States, a critical market where Nissan used to earn significant profits, the company's market share has fallen sharply as it struggles to sell cars and trucks that haven't received significant upgrades in recent years. In the period from April to September, Nissan's operating profit plunged 90 percent, and the automaker recently said it aimed to lose 9,000 employees worldwide and cut global production by about 20 percent. A merger could help Honda and Nissan develop electric cars faster and at lower cost -- in theory. But other companies have struggled to achieve such gains in practice, often because the priorities of companies working together often shift and diverge. Ford Motor and Volkswagen teamed up a few years ago to work on electric vehicles and autonomous driving technology.