Neuro-symbolic artificial intelligence (NSAI) represents a transformative approach in artificial intelligence (AI) by combining deep learning's ability to handle large-scale and unstructured data with the structured reasoning of symbolic methods. By leveraging their complementary strengths, NSAI enhances generalization, reasoning, and scalability while addressing key challenges such as transparency and data efficiency. This paper systematically studies diverse NSAI architectures, highlighting their unique approaches to integrating neural and symbolic components. It examines the alignment of contemporary AI techniques such as retrieval-augmented generation, graph neural networks, reinforcement learning, and multi-agent systems with NSAI paradigms. This study then evaluates these architectures against comprehensive set of criteria, including generalization, reasoning capabilities, transferability, and interpretability, therefore providing a comparative analysis of their respective strengths and limitations. Notably, the Neuro > Symbolic < Neuro model consistently outperforms its counterparts across all evaluation metrics. This result aligns with state-of-the-art research that highlight the efficacy of such architectures in harnessing advanced technologies like multi-agent systems.

In a blog post on Friday, Perplexity introduced a new tool called Deep Research that it says can conduct "in-depth research and analysis" to deliver detailed reports in response to your questions, and it's free for limited use. It comes just a couple of weeks after OpenAI announced its own Deep Research feature for ChatGPT Pro users… which itself followed Google's December announcement of Deep Research for Gemini. Perplexity's tool is available only on the web to start, but it will hit the iOS, Android and Mac apps soon too. Deep Research lets you generate in-depth research reports on any topic. Perplexity says its Deep Research "excels at a range of expert-level tasks -- from finance and marketing to product research" and takes about 2-4 minutes to come up with an answer, during which it "performs dozens of searches, reads hundreds of sources, and reasons through the material."

President Trump announces the U.S. Stargate investment alongside three artificial intelligence industry leaders. BREAKING GROUND: Stargate, the massive artificial intelligence (AI) infrastructure project recently unveiled by President Donald Trump, has begun production in Texas -- with data center construction in other states expected to be announced in the coming months. ON ONE CONDITION: Elon Musk will withdraw his unsolicited bid of 97.4 billion to take over OpenAI if its board of directors stops the company's conversion into a for-profit entity. EXISTENTIAL THREAT: OPINION: Our socioeconomic system is facing an existential threat from AI. In our capitalist society, most people depend on jobs to sustain themselves.

Community detection is a cornerstone problem in social network analysis (SNA), aimed at identifying cohesive communities with minimal external links. However, the rise of generative AI and Metaverse introduce complexities by creating hybrid human-AI social networks (denoted by HASNs), where traditional methods fall short, especially in human-centric settings. This paper introduces a novel community detection problem in HASNs (denoted by MetaCD), which seeks to enhance human connectivity within communities while reducing the presence of AI nodes. Effective processing of MetaCD poses challenges due to the delicate trade-off between excluding certain AI nodes and maintaining community structure. To address this, we propose CUSA, an innovative framework incorporating AI-aware clustering techniques that navigate this trade-off by selectively retaining AI nodes that contribute to community integrity. Furthermore, given the scarcity of real-world HASNs, we devise four strategies for synthesizing these networks under various hypothetical scenarios. Empirical evaluations on real social networks, reconfigured as HASNs, demonstrate the effectiveness and practicality of our approach compared to traditional non-deep learning and graph neural network (GNN)-based methods.

System prompts have emerged as a critical control surface for specifying the behavior of LLMs in chat and agent settings. Developers depend on system prompts to specify important context, output format, personalities, guardrails, content policies, and safety countermeasures, all of which require models to robustly adhere to the system prompt, especially when facing conflicting or adversarial user inputs. In practice, models often forget to consider relevant guardrails or fail to resolve conflicting demands between the system and the user. In this work, we study various methods for improving system prompt robustness by creating realistic new evaluation and fine-tuning datasets based on prompts collected from from OpenAI's GPT Store and HuggingFace's HuggingChat. Our experiments assessing models with a panel of new and existing benchmarks show that performance can be considerably improved with realistic fine-tuning data, as well as inference-time interventions such as classifier-free guidance. Finally, we analyze the results of recently released reasoning models from OpenAI and DeepSeek, which show exciting but uneven improvements on the benchmarks we study. Overall, current techniques fall short of ensuring system prompt robustness and further study is warranted.

OpenAI on Friday rejected a 97.4bn bid from a consortium led by billionaire Elon Musk for the ChatGPT maker, saying the startup is not for sale. The unsolicited approach is Musk's latest attempt to block the startup he co-founded with CEO Sam Altman – but later left – from becoming a for-profit firm, as it looks to secure more capital and stay ahead in the AI race. "OpenAI is not for sale, and the board has unanimously rejected Mr Musk's latest attempt to disrupt his competition. Any potential reorganization of OpenAI will strengthen our nonprofit and its mission to ensure AGI benefits all of humanity," OpenAI said on X, quoting its chair Bret Taylor, on behalf of its board. On Tuesday, Altman told news website Axios that OpenAI was not for sale.

Elon Musk launched a 97.4 billion bid to take control of OpenAI. The Wall Street Journal reported a group of investors led by Musk's xAI submitted an unsolicited offer to the company's board of directors on Monday. The group wants to buy the nonprofit that controls OpenAI's for-profit arm. When asked for comment, an OpenAI spokesperson pointed Engadget to an X post from CEO Sam Altman. "No thank you but we will buy twitter for 9.74 billion if you want," Altman wrote on the social media platform Musk owns.

The Guardian Media Group, owner of The Guardian and The Observer newspapers, is partnering with OpenAI. The deal will see reporting from The Guardian appear as a news source within ChatGPT, alongside article extracts and short summaries. In return, OpenAI will provide the Guardian Media Group with access to ChatGPT Enterprise, which the company says it will use to develop new products, features and tools. "This new partnership with OpenAI reflects the intellectual property rights and value associated with our award-winning journalism, expanding our reach and impact to new audiences and innovative platform services," said Keith Underwood, chief financial and operating officer of the Guardian Media Group. The Guardian Media Group joins a growing list of news publishers that are now working with OpenAI after an initial period of uncertainty over the company and its business model.

Apple's artificial intelligence features for iPhones could be available in China as early as May, according to Bloomberg. The company reportedly established several teams in China and the US to make that happen, and it's also teaming up with local companies for its generative AI needs in the country. Joe Tsai, Alibaba Group's Chairman, recently confirmed that Apple will use his company's generative AI technology for Chinese iPhones during an event. Tsai didn't say when Apple intends to roll out the AI features that use Alibaba's tech, but The Information previously reported that the companies had already submitted them for approval to the country's regulators. Bloomberg says Apple will use Alibaba's technology for its on-device AI models, specifically as a layer on top that can censor certain materials and information for the Chinese government.

Chip designer Arm plans to unveil its own processor this year with Meta as the launch customer, The Financial Times reported. The chip would be a CPU designed for servers in data centers and would have the potential to be customized for clients. Manufacturing would be outsourced to a contract fab plant like TSMC (Taiwan Semiconductor Manufacturing Co.) and the first in-house chip could be revealed as early as this summer, according to the FT's sources. Last month, Arm parent Softbank announced the Stargate project, a partnership with OpenAI to build up to 500 billion worth of AI infrastructure. Arm, along with Microsoft and NVIDIA, is a key technology partner for the project.