AI startup Anthropic's recent announcement that it detected the world's first artificial intelligence-led hacking campaign has prompted a multitude of responses from cybersecurity experts. In a report on Friday, Anthropic said its assistant Claude Code was manipulated to carry out 80-90 percent of a "large-scale" and "highly sophisticated" cyberattack, with human intervention required "only sporadically". Anthropic, the creator of the popular Claude chatbot, said the attack aimed to infiltrate government agencies, financial institutions, tech firms and chemical manufacturing companies, though the operation was only successful in a small number of cases. The San Francisco-based company, which attributed the attack to Chinese state-sponsored hackers, did not specify how it had uncovered the operation, nor identify the "roughly" 30 entities that it said had been targeted. Roman V Yampolskiy, an AI and cybersecurity expert at the University of Louisville, said there was no doubt that AI-assisted hacking posed a serious threat, though it was difficult to verify the precise details of Anthropic's account.

If 2023 was the year of AI fervor, following the late-2022 release of ChatGPT, 2024 was marked by a steady drumbeat of advances as systems got smarter, faster, and cheaper to run. AI also began to reason more deeply and interact via voice and video--trends that AI experts and leaders say will accelerate. Here's what to expect from AI in 2025. In 2025, we'll begin to see a shift from chatbots and image generators toward "agentic" systems that can act autonomously to complete tasks, rather than simply answer questions, says AI futurist Ray Kurzweil. In October, Anthropic gave its AI model Claude the ability to use computers--clicking, scrolling, and typing--but this may be just the start.

For over a decade, companies have bet on a tantalizing rule of thumb: that artificial intelligence systems would keep getting smarter if only they found ways to continue making them bigger. In 2017, researchers at Chinese technology firm Baidu demonstrated that pouring more data and computing power into machine learning algorithms yielded mathematically predictable improvements--regardless of whether the system was designed to recognize images, speech, or generate language. Noticing the same trend, in 2020, OpenAI coined the term "scaling laws," which has since become a touchstone of the industry. This thesis prompted AI firms to bet hundreds of millions on ever-larger computing clusters and datasets. The gamble paid off handsomely, transforming crude text machines into today's articulate chatbots.

Late last month, the US Treasury Department finalized new restrictions limiting what kinds of Chinese tech startups US venture capital firms can invest in for national security reasons. When they go into effect in January, the long-awaited measures will stop American VCs and other investors from pouring money into cutting-edge Chinese AI models. After president-elect Trump takes office a few weeks later, his administration may expand the rules and make them even tougher. While the US still leads the world in advanced AI development, the American government has grown increasingly concerned about China catching up soon. The new outbound investment restrictions are designed to work alongside other measures, such as export controls on advanced computer chips and the Committee on Foreign Investment in the United States (CFIUS), to collectively hamper--or at least slow down--the progress of Chinese AI companies.

The use of Autonomous Surface Vehicles, equipped with water quality sensors and artificial vision systems, allows for a smart and adaptive deployment in water resources environmental monitoring. This paper presents a real implementation of a vehicle prototype that to address the use of Artificial Intelligence algorithms and enhanced sensing techniques for water quality monitoring. The vehicle is fully equipped with high-quality sensors to measure water quality parameters and water depth. Furthermore, by means of a stereo-camera, it also can detect and locate macro-plastics in real environments by means of deep visual models, such as YOLOv5. In this paper, experimental results, carried out in Lago Mayor (Sevilla), has been presented as proof of the capabilities of the proposed architecture. The overall system, and the early results obtained, are expected to provide a solid example of a real platform useful for the water resource monitoring task, and to serve as a real case scenario for deploying Artificial Intelligence algorithms, such as path planning, artificial vision, etc.

Apple's big push into AI – which the company insists stands for "Apple Intelligence" – could spark an upgrade "supercycle", with the intense processing requirements for the souped-up Siri limiting it to only the most powerful iPhones currently on the market. The company risks angering users who will update to iOS 18 this autumn to discover that even a brand-new iPhone 15 is unable to run features such as automatic transcription, image generation and a smarter, more conversational voice assistant. Apple's new AI models will run on the iPhone 15 Pro and Pro Max, the only two devices the company has yet shipped with its A17 processor. Macs up to three years old will also be able to take advantage of the upgrade, provided they have a M1, 2 or 3 chip, and so too will iPad Pros with the same internal hardware. Critics have argued that the decision to not release a slower or less competent version of the AI system for older phones is motivated by profit.

Imagine if the world's response to climate change relied solely on speculative predictions from pundits and CEOs, rather than the rigorous--though still imperfect--models of climate science. "Two degrees of warming will arrive soon-ish but will change the world less than we all think," one might say. "Two degrees of warming is not just around the corner. This is going to take a long time," another could counter. This is more or less the world we're in with artificial intelligence, with OpenAI CEO Sam Altman saying that AI systems that can do any task a human can will be developed in the "reasonably close-ish future," while Yann LeCun, Chief AI Scientist at Facebook, argues that human-level AI systems are "going to take a long time."

In the last ten years, AI systems have developed at rapid speed. From the breakthrough of besting a legendary player at the complex game Go in 2016, AI is now able to recognize images and speech better than humans, and pass tests including business school exams and Amazon coding interview questions. Last week, during a U.S. Senate Judiciary Committee hearing about regulating AI, Senator Richard Blumenthal of Connecticut described the reaction of his constituents to recent advances in AI. "The word that has been used repeatedly is scary." The Subcommittee on Privacy, Technology, and the Law overseeing the meeting heard testimonies from three expert witnesses, who stressed the pace of progress in AI. One of those witnesses, Dario Amodei, CEO of prominent AI company Anthropic, said that "the single most important thing to understand about AI is how fast it is moving."

"With respect to the first two, no migratory entry or exit from our country has been registered," Migrations Superintendent Eduardo Sevilla told a news conference. Peru will check if the military officials have entered Peru and proceed in accordance with "the laws in place," Sevilla added, without offering specifics.

The use of computers and robots is becoming more prevalent in societies worldwide. More schools are integrating basic robotics and programming concepts in their lessons and curricula. Such initiative is true not only in advanced countries but also in third world countries like the Philippines. "Robotics must be integrated in the schools. It is one of the skills 21st century learners need in order to succeed in life," De La Salle Santiago Zobel School International Robotics Coordinator Genevieve Pillar told Philippine News Agency (PNA).