Modern scientific discovery increasingly requires coordinating distributed facilities and heterogeneous resources, forcing researchers to act as manual workflow coordinators rather than scientists. Advances in AI leading to AI agents show exciting new opportunities that can accelerate scientific discovery by providing intelligence as a component in the ecosystem. However, it is unclear how this new capability would materialize and integrate in the real world. To address this, we propose a conceptual framework where workflows evolve along two dimensions which are intelligence (from static to intelligent) and composition (from single to swarm) to chart an evolutionary path from current workflow management systems to fully autonomous, distributed scientific laboratories. With these trajectories in mind, we present an architectural blueprint that can help the community take the next steps towards harnessing the opportunities in autonomous science with the potential for 100x discovery acceleration and transformational scientific workflows.

Computational models have emerged as powerful tools for energy modeling research, touting scalability and quantitative results. However, these models require a plethora of data, some of which is inaccessible, expensive, or raises privacy concerns. We introduce a modular multimodal framework to produce this data from publicly accessible residential information and images using generative artificial intelligence (AI). Additionally, we provide a pipeline demonstrating this framework, and we evaluate its generative AI components. Our experiments show that our framework's use of AI avoids common issues with generative models. Our framework produces realistic, labeled data. By reducing dependence on costly or restricted data sources, we pave a path towards more accessible and reproducible research.

Split Learning (SL) is a distributed learning approach that enables resource-constrained clients to collaboratively train deep neural networks (DNNs) by offloading most layers to a central server while keeping in- and output layers on the client-side. This setup enables SL to leverage server computation capacities without sharing data, making it highly effective in resource-constrained environments dealing with sensitive data. However, the distributed nature enables malicious clients to manipulate the training process. By sending poisoned intermediate gradients, they can inject backdoors into the shared DNN. Existing defenses are limited by often focusing on server-side protection and introducing additional overhead for the server. A significant challenge for client-side defenses is enforcing malicious clients to correctly execute the defense algorithm. We present ZORRO, a private, verifiable, and robust SL defense scheme. Through our novel design and application of interactive zero-knowledge proofs (ZKPs), clients prove their correct execution of a client-located defense algorithm, resulting in proofs of computational integrity attesting to the benign nature of locally trained DNN portions. Leveraging the frequency representation of model partitions enables ZORRO to conduct an in-depth inspection of the locally trained models in an untrusted environment, ensuring that each client forwards a benign checkpoint to its succeeding client. In our extensive evaluation, covering different model architectures as well as various attack strategies and data scenarios, we show ZORRO's effectiveness, as it reduces the attack success rate to less than 6\% while causing even for models storing \numprint{1000000} parameters on the client-side an overhead of less than 10 seconds.

Question answering (QA) plays a central role in financial education, yet existing large language model (LLM) approaches often fail to capture the nuanced and specialized reasoning required for financial problem-solving. The financial domain demands multistep quantitative reasoning, familiarity with domain-specific terminology, and comprehension of real-world scenarios. We present a multi-agent framework that leverages role-based prompting to enhance performance on domain-specific QA. Our framework comprises a Base Generator, an Evidence Retriever, and an Expert Reviewer agent that work in a single-pass iteration to produce a refined answer. We evaluated our framework on a set of 3,532 expert-designed finance education questions from Study.com, an online learning platform. We leverage retrieval-augmented generation (RAG) for contextual evidence from 6 finance textbooks and prompting strategies for a domain-expert reviewer. Our experiments indicate that critique-based refinement improves answer accuracy by 6.6-8.3% over zero-shot Chain-of-Thought baselines, with the highest performance from Gemini-2.0-Flash. Furthermore, our method enables GPT-4o-mini to achieve performance comparable to the finance-tuned FinGPT-mt_Llama3-8B_LoRA. Our results show a cost-effective approach to enhancing financial QA and offer insights for further research in multi-agent financial LLM systems.

Effective tool use is essential for large language models (LLMs) to interact meaningfully with their environment. However, progress is limited by the lack of efficient reinforcement learning (RL) frameworks specifically designed for tool use, due to challenges in constructing stable training environments and designing verifiable reward mechanisms. To address this, we propose an automated environment construction pipeline, incorporating scenario decomposition, document generation, function integration, complexity scaling, and localized deployment. This enables the creation of high-quality training environments that provide detailed and measurable feedback without relying on external tools. Additionally, we introduce a verifiable reward mechanism that evaluates both the precision of tool use and the completeness of task execution. When combined with trajectory data collected from the constructed environments, this mechanism integrates seamlessly with standard RL algorithms to facilitate feedback-driven model training. Experiments on LLMs of varying scales demonstrate that our approach significantly enhances the models' tool-use performance without degrading their general capabilities, regardless of inference modes or training algorithms. Our analysis suggests that these gains result from improved context understanding and reasoning, driven by updates to the lower-layer MLP parameters in models.

HGTV's Erin Napier erupts at fans after being slammed for refusing to'celebrate' Charlie Kirk's death Truth about America's murder hotspots... as map reveals surprising cities Trump may send National Guard City of vanishing children: Dark truth behind the THOUSANDS of missing kids in Rust Belt town... and the underworld they are plunged into Monkees musician Bobby Hart who wrote the band's theme and Last Train To Clarksville dies at 86 I didn't air any dirty laundry in public - my conscience is clear, says Prince Harry during visit to Ukraine: Duke reveals he wants to spend more time in the UK in the next year as'the focus really has to be on my dad' FBI tried to hide trans identity of Charlie Kirk suspect's lover after his chilling four-word response to investigators I've been lying to my husband about the thing he loves most. If I come clean, he'll be humiliated: DEAR JANE My HOA from hell fined me $1,000 per day for the pettiest issue imaginable inside my $600k home... then I realized they were spying on me Teen arrested'destroying' Charlie Kirk memorial as chilling copycat fantasy exposed Hollywood insiders lay bare'intimidation' tactics by woke celebrities branded worse than the Ku Klux Klan: 'Everyone is living in fear' NFL fans left in disbelief as Russell Wilson launches'mind blowing' touchdown pass for New York Giants Islanders claim they know the sinister truth about Amelia Earhart... and demand the proof is finally released Urgent warning as toxic fumes on major airlines' flights cause devastating brain injuries I dropped from a size 20 to a size 12 in five months - these'healthy' foods were making me overweight Who are the shortest actresses in Hollywood? Emotional Tucker Carlson reveals'close call' on his life as he breaks silence on Charlie Kirk: 'We're in a civil war' People are just realizing that they're pronouncing the name of America's biggest holiday wrong The three-word phrase to get people to listen'instantly,' according to a public speaking expert Capturing people's attention during a presentation, or in any crowded room, is often half the battle, and one many fail to win. Now, a public speaking expert has shared a three-word phrase he claimed will get people listening to you'instantly.' John Bowe, a speech trainer, said that starting with'Imagine this scenario...' will have the room perk up and pay attention. 'It works every time,' Bowe wrote for CNBC, breaking down how each word is highly engaging.

Grok claimed the location was Trafalgar Square. Grok claimed the location was Trafalgar Square. Musk's Grok AI bot falsely suggests police misrepresented footage of far-right rally in London The Metropolitan police has had to counter false suggestions by the artificial intelligence on Elon Musk's X platform that the force passed off footage from 2020 as being from Saturday's far-right rally in the city. The claim by the chatbot Grok was in answer to an X user's query about where and when footage of police clashing with crowds was filmed. Police seek man who called for Keir Starmer to be'assassinated' at far-right rally Grok, which has had a track record of giving false and misleading answers, replied: "This footage appears to be from an anti-lockdown protest in London's Trafalgar Square on 26 September 2020, during clashes between demonstrators and police over Covid restrictions."

How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? Russia and Ukraine have been engaging in major aerial battles, targeting energy and transportation infrastructure, as Moscow presses its fierce ground assault in the Ukrainian east in the war's fourth year and tests a type of hypersonic weapon. Russia's Ministry of Defence announced on Sunday that its air defences shot down 361 drones, four guided aerial bombs, and rockets from a US-made high mobility artillery rocket system (HIMARS) overnight.

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Romania says a Russian drone has breached its airspace - the second Nato country to report such an incursion. Romanian fighter jets were in the air monitoring a Russian attack in Ukraine on Saturday and were able to track the drone near Ukraine's southern border, the defence ministry said in a statement. Ukrainian President Volodymyr Zelensky said the incursion could not be a mistake - it was an obvious expansion of the war by Russia. Moscow has not commented on the Romanian claims. On Wednesday, Poland said it had shot down at least three Russian drones which had entered its airspace.