John Ternus ascends the throne - but Cook will stay on to manage tech giant's foreign policy as executive chair Tim Cook becomes Apple's elder statesman Apple announced late on Monday that Tim Cook will step down as CEO but will not leave the iPhone maker. Head of hardware engineering John Ternus will succeed him on 1 September. "I love Apple with all of my being," Cook said in a press release announcing his succession. Cook, 65, who succeeded Apple co-founder Steve Jobs, has been CEO since 2011. With a reputation for operational and supply chain management, he has overseen the global expansion of the company and its steady series of new, updated devices, though he never attained the same visionary status as Jobs.

This Scammer Used an AI-Generated MAGA Girl to Grift'Super Dumb' Men A med student says he's made thousands of dollars selling photos and videos of a young conservative woman he created using generative tools. Like many medical school students, Sam was broke. The 22-year-old aspiring orthopedic surgeon from northern India got some money from his parents, but he says he spent most of it subsidizing his licensing exams, and he's still saving up to hopefully emigrate to the US after graduation. So he started searching for ways to make additional money online. Sam, who requested a pseudonym to avoid jeopardizing his medical career and immigration status, tried a few things, with varying degrees of legitimacy and success.

Japanet is expanding its venture capital fund with Pegasus Tech Ventures, after early investments in firms like SpaceX, OpenAI, Anthropic and xAI showed strong growth. Japanese home shopping company Japanet is expanding its venture capital fund with San Jose-based Pegasus Tech Ventures, following the success of early bets in SpaceX, OpenAI, Anthropic and xAI. The Nagasaki-based retailer known for infomercials targeting seniors in aging Japan will allocate $200 million to the fund, up from an initial $50 million in 2021, following significant growth" in investments so far, the companies said in a statement. The fund, of which Pegasus is general partner, will focus on areas such as generative AI, robotics and space technology. Its Japan portfolio includes startup Aillis, which seeks to use artificial intelligence to analyze medical scans. Asian companies have struggled to win stakes in promising startups in Silicon Valley, hampered by a lack of personal connections and reputation for slow decision-making. Pegasus also manages startup investments on behalf of Toyota Motor-affiliate Aisin, Japanese chemical maker Denka, Taiwan's Asustek Computer and Acer and Indonesia's pharma company Kalbe Farma. Everybody wants a piece of the Silicon Valley AI action," Pegasus Chief Executive Officer Anis Uzzaman said on a video call.

Ashlin McCourt clocks up 60 hours a week working as a civil servant, a waitress and a baker because life's so expensive, she says. The UK unemployment rate stands at 4.9% - however, increasing numbers of those in work are juggling more than one job. While working in multiple jobs and side hustles has long been a needs must for many households to manage the cost of living, there are now a record 1.35 million adults working at least two jobs. It is mostly Gen Z - adults aged up to 29 - driving this poly-employment trend - according to Deputy, a global workforce management platform, which analysed more than 20 million shifts done by over 300,000 UK workers. For 28-year-old Ashlin from Northern Ireland, having more than one job seems normal.

Attendees at the Canton Fair in Guangzhou, China, take pictures of various service robots on display. At the world's largest trade show, it's not just the clientele that had a different look this year. Despite the near absence of buyers wearing a traditional Arab headdress and robe at the Canton Fair, a vast showcase that started last week in China's southern metropolis of Guangzhou, a brash new generation of tech companies stood out just as much. Few wanted to dwell on the war. Even as the conflict in the Middle East once more fractures global commerce, interviews with more than a dozen exporters at the fair found many were already eager to look beyond the hostilities blamed for the worst energy disruption in generations.

Anthropic was founded in 2021 by several former employees of OpenAI. Amazon is investing an additional $5 billion in Anthropic, and may inject $20 billion more over time, a deal that deepens the companies' ties in an increasingly competitive artificial intelligence industry. Anthropic, which makes the Claude chatbot and coding tool, plans to spend more than $100 billion over the next 10 years on Amazon's cloud technologies and chips, the companies said in a statement on Monday. Amazon shares gained about 3% on the news in extended trading. Amazon was already one of Anthropic's biggest backers, with prior investments totaling $8 billion.

A TV screen shows the artist database on Nadou Pro, iQIYI's artificial intelligence product for professional film and television production, during the iQIYI World Conference in Beijing on Monday. Beijing - China's equivalent of Netflix, iQIYI, faced backlash on Monday over a new initiative that facilitates the use of actors' likenesses in artificially generated dramas and films. More than 100 celebrities have joined a platform to connect with makers of AI-generated content interested in using their image, a senior executive told a conference in Beijing. China's entertainment industry has rapidly embraced the use of artificial intelligence, with AI-generated films and shows a common feature on video platforms. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

The inverse Potts problem for estimating evolutionary single-site fields and pairwise couplings in homologous protein sequences from their single-site and pairwise amino acid frequencies observed in their multiple sequence alignment would be still one of useful methods in the studies of protein structure and evolution. Since the reproducibility of fields and couplings are the most important, the Boltzmann machine method is employed here, although it is computationally intensive. In order to reduce computational time required for the Boltzmann machine, parallel, persistent Markov chain Monte Carlo method is employed to estimate the single-site and pairwise marginal distributions in each learning step. Also, stochastic gradient descent methods are used to reduce computational time for each learning. Another problem is how to adjust the values of hyperparameters; there are two regularization parameters for evolutionary fields and couplings. The precision of contact residue pair prediction is often used to adjust the hyperparameters. However, it is not sensitive to these regularization parameters. Here, they are adjusted for the fields and couplings to satisfy a specific condition that is appropriate for protein conformations. This method has been applied to eight protein families.

Large language models (LLMs) using chain-of-thought reasoning often waste substantial compute by producing long, incorrect responses. Abstention can mitigate this by withholding outputs unlikely to be correct. While most abstention methods decide to withhold outputs before or after generation, dynamic mid-generation abstention considers early termination of unpromising reasoning traces at each token position. Prior work has explored empirical variants of this idea, but principled guidance for the abstention rule remains lacking. We present a formal analysis of dynamic abstention for LLMs, modeling abstention as an explicit action within a regularized reinforcement learning framework. An abstention reward parameter controls the trade-off between compute and information. We show that abstaining when the value function falls below this reward strictly outperforms natural baselines under general conditions. We further derive a principled and efficient method to approximate the value function. Empirical results on mathematical reasoning and toxicity avoidance tasks support our theory and demonstrate improved selective accuracy over existing methods.

As search depth increases in autonomous reasoning and embodied planning, the candidate action space expands exponentially, heavily taxing computational budgets. While heuristic pruning is a common countermeasure, it operates without formal safety guarantees when surrogate models (like LLMs) exhibit systematic evaluation biases. This paper frames the node expansion process as a localized Best-Arm Identification (BAI) problem over dynamic frontiers, subject to a bounded systematic bias $L$. By inverting the Lambert W function, we establish an additive sample complexity of $\mathcal{O}((Δ-4L)^{-2})$, which indicates that safe node elimination is only feasible when the empirical reward gap exceeds $4L$. We complement this with an information-theoretic lower bound of $Ω((Δ-2L)^{-2})$ to confirm the structural limits of biased search. Subsequent evaluations on both synthetic trees and complex reasoning tasks demonstrate that adhering to this local safety boundary successfully preserves optimal trajectories while maximizing sample allocation efficiency.