The Oscar nominations will be announced later, with Leonardo DiCaprio's politically-charged thriller One Battle After Another expected to lead the field. Marty Supreme, Frankenstein, Sentimental Value, Bugonia and The Secret Agent are also expected to perform strongly when the shortlists are announced from 13:30 GMT. It's a weaker year for UK talent - Wunmi Mosaku from vampire horror Sinners is one of the few British stars with a chance of securing an acting nomination. But Irish actors Jessie Buckley and Paul Mescal are expected to be recognised for their roles in the screen adaptation of Maggie O'Farrell's novel Hamnet. US comedian Conan O'Brien will return to host this year's Academy Awards ceremony, which takes place on 15 March.

Is It Really Worth It? Apple, Michigan taxpayers, and one of Detroit's wealthiest families spent roughly $30 million training hundreds of people to build iPhone apps. Two years ago, Lizmary Fernandez took a detour from studying to be an immigration attorney to join a free Apple course for making iPhone apps . The Apple Developer Academy in Detroit launched as part of the company's $200 million response to the Black Lives Matter protests and aims to expand opportunities for people of color in the country's poorest big city. But Fernandez found the program's cost-of-living stipend lacking--"A lot of us got on food stamps," she says--and the coursework insufficient for landing a coding job. "I didn't have the experience or portfolio," says the 25-year-old, who is now a flight attendant and preparing to apply to law school. "Coding is not something I got back to."

Initial participants in the new Apple Manufacturing Academy tell WIRED that the tech giant's surprising frankness and hands-on support are already benefiting their bottom lines. An instructor at the Apple Manufacturing Academy in Detroit demonstrates how an iPhone and optical inspection software can be used to photograph and automatically identify an issue with a part. About 10 Apple employees spent some of their valuable hours over recent months on a project that might seem unusual for the tech giant: customizing an open source AI tool for ImageTek, a small manufacturer in Springfield, Vermont whose lines of business include printing millions of labels for food packaging. The Apple engineers developed a computer vision system to automatically identify color errors, and on one run it picked up bacon labels with a far-too-pinkish beige before they got shipped, according to Marji Smith, ImageTek's president. She says the timely catch helped ImageTek from losing a crucial customer.

The names of two partial owners of firms linked to the Salt Typhoon hacker group also appeared in records for a Cisco training program--years before the group targeted Cisco's devices in a spy campaign. Cisco's Networking Academy, a global training program designed to educate IT students in the basics of IT networks and cybersecurity, proudly touts its accessibility to participants around the world: "We believe education can be the ultimate equalizer, enabling anyone, regardless of background, to develop expertise and shape their destiny in a digital era," reads the first line on its website. That laudable statement, however, reads a bit differently when the "destiny" of those students appears to be owning a majority stake in companies linked to one of the most successful Chinese state-sponsored hacking operations ever to target the West--and many of Cisco's own products . That's the surprising conclusion of Dakota Cary, a researcher at cybersecurity firm SentinelOne and the Atlantic Council, who, like many security analysts, has closely tracked the Chinese state-sponsored hacker group known as Salt Typhoon . That cyberespionage group gained notoriety last year when it was revealed that the hackers had penetrated at least nine telecom companies and gained the ability to spy on Americans' real-time calls and texts, specifically targeting then-presidential and vice presidential candidates Donald Trump and JD Vance, among many others.

Large Language Models (LLMs) are reshaping organizational knowing by unsettling the epistemological foundations of representational and practice-based perspectives. We conceptualize LLMs as Haraway-ian monsters, that is, hybrid, boundary-crossing entities that destabilize established categories while opening new possibilities for inquiry. Focusing on analogizing as a fundamental driver of knowledge, we examine how LLMs generate connections through large-scale statistical inference. Analyzing their operation across the dimensions of surface/deep analogies and near/far domains, we highlight both their capacity to expand organizational knowing and the epistemic risks they introduce. Building on this, we identify three challenges of living with such epistemic monsters: the transformation of inquiry, the growing need for dialogical vetting, and the redistribution of agency. By foregrounding the entangled dynamics of knowing-with-LLMs, the paper extends organizational theory beyond human-centered epistemologies and invites renewed attention to how knowledge is created, validated, and acted upon in the age of intelligent technologies.

Oscar nominations are an important factor in the movie industry because they can boost both the visibility and the commercial success. This work explores whether it is possible to predict Oscar nominations for screenplays using modern language models. Since no suitable dataset was available, a new one called Movie-O-Label was created by combining the MovieSum collection of movie scripts with curated Oscar records. Each screenplay was represented by its title, Wikipedia summary, and full script. Long scripts were split into overlapping text chunks and encoded with the E5 sentence em bedding model. Then, the screenplay embed dings were classified using a logistic regression model. The best results were achieved when three feature inputs related to screenplays (script, summary, and title) were combined. The best-performing model reached a macro F1 score of 0.66, a precision recall AP of 0.445 with baseline 0.19 and a ROC-AUC of 0.79. The results suggest that even simple models based on modern text embeddings demonstrate good prediction performance and might be a starting point for future research.

Abstract--The evolution toward Level 4 (L4) Autonomous Networks (AN) represents a strategic inflection point in telecommunications, where networks must transcend reactive automation to achieve genuine cognitive capabilities--fulfilling AN's vision of self-configuring, self-healing, and self-optimizing systems that deliver zero-wait, zero-touch, and zero-fault services. This work bridges the gap between architectural theory and operational reality by implementing Joseph Sifakis's AN Agent reference architecture in a functional cognitive system, deploying coordinated proactive-reactive runtimes driven by hybrid knowledge representation. Specifically, the system demonstrates sub-10 ms real-time control in 5G NR sub-6 GHz environments. Empirical results show a 4% increase in downlink throughput over Outer Loop Link Adaptation (OLLA) algorithms for enhanced mobile broadband (eMBB). Furthermore, for the ultra-reliable low-latency communication (URLLC) scenario, the agent achieves an 85% reduction in Block Error Rate (BLER). These improvements confirm the architecture's viability in overcoming traditional autonomy barriers and advancing critical L4-enabling capabilities toward next-generation objectives. UTONOMOUS Networks (AN), a purpose-specific telecommunications technology pioneered by the TM Forum (TMF) in 2019, target networks with intrinsic self-configuration, self-healing, and self-optimization capabilities--collectively termed the Three-Self Capabilities [1]. These fundamental properties enable the realization of zero-wait, zero-touch, and zero-fault network services, known as the Three-Zero Objectives, which collectively deliver optimal user experiences while maximizing resource utilization throughout the entire network lifecycle. By strategically integrating emerging general-purpose technologies including artificial intelligence (AI), digital twins, and big data analytics, AN not only transforms conventional network operations but fundamentally reorients value creation paradigms from traditional device-centric and management-centric models toward customer-oriented, service-driven, and business-focused frameworks.

The Academy said its new language around eligibility for films made using generative AI tools was recommended by its Science and Technology Council. Under further rule changes announced on Monday, Academy members must now watch all nominated films in each category in order to be able to take part in the final round of voting, which decides upon winners. The use of AI in film became a hot topic after Adrian Brody took home the award for Best Actor for his role in The Brutalist at this year's Oscars ceremony in March. The movie used generative AI to improve the actor's accent when he spoke Hungarian. It then emerged similar voice-cloning technology was used to enhance singing voices in the Oscar-winning musical Emilia Perez.

The Academy of Motion Picture Arts and Sciences has decide that its official stance towards AI-use in films is to take no stance at all, according to a statement the organization shared outlining changes to voting for the 98th Oscars. The issue of award-nominated films using AI was first raised in 2024 when the productions behind Best Picture nominees The Brutalist and Emilia Pérez admitted to using the tech to alter performances. "With regard to Generative Artificial Intelligence and other digital tools used in the making of the film, the tools neither help nor harm the chances of achieving a nomination, " AMPAS writes. "The Academy and each branch will judge the achievement, taking into account the degree to which a human was at the heart of the creative authorship when choosing which movie to award." While the organization at least reaffirms that human involvement is their primary concern, they also don't seem to believe that using AI -- potentially trained on the ill-gotten work of their membership -- is an existential problem.

This paper proposes the "Academy of Athens" multi-agent seven-layer framework, aimed at systematically addressing challenges in multi-agent systems (MAS) within artificial intelligence (AI) art creation, such as collaboration efficiency, role allocation, environmental adaptation, and task parallelism. The framework divides MAS into seven layers: multi-agent collaboration, single-agent multi-role playing, single-agent multi-scene traversal, single-agent multi-capability incarnation, different single agents using the same large model to achieve the same target agent, single-agent using different large models to achieve the same target agent, and multi-agent synthesis of the same target agent. Through experimental validation in art creation, the framework demonstrates its unique advantages in task collaboration, cross-scene adaptation, and model fusion. This paper further discusses current challenges such as collaboration mechanism optimization, model stability, and system security, proposing future exploration through technologies like meta-learning and federated learning. The framework provides a structured methodology for multi-agent collaboration in AI art creation and promotes innovative applications in the art field.