Recently, as Elon Musk filed a lawsuit against Sam Altman, early internal emails from OpenAI were exposed, drawing widespread attention to the power struggle among the company's founders. In the emails, OpenAI co-founder Ilya Sutskever expressed deep concerns about Musk's strong desire to control artificial intelligence. Image source note: Image generated by AI, image licensed from Midjourney. Sutskever reached out to Musk in September 2017.

Recently, The Wall Street Journal has been conducting a new experiment by introducing AI-generated article summaries that appear at the top of news reports in the form of 'key points.' The first test of this feature appeared in a report about Trump's Department of Education plans. To validate the effectiveness of this new feature, The Wall Street Journal has opened feedback channels to understand users' actual needs. The content of these 'key point' summaries is generated by AI tools and edited before publication. The summary box clearly indicates this.

In India, artificial intelligence is rapidly transforming the government's digital infrastructure, enabling more underserved communities to benefit. Recently, at the NVIDIA summit held in Mumbai, Sharmishtha Dasgupta, Deputy Director of the National Informatics Centre, shared the latest updates on how AI is enhancing e-governance. She mentioned that AI systems can now handle 500,000 to 700,000 queries per month, operating around the clock to ensure thousands of citizens receive timely assistance. These queries cover a wide range of topics, such as registration and eligibility.

Recently, ByteDance quietly launched an AI model sharing community called 'Lumi'. The platform integrates various functions including model sharing, workflow building, and LoRA training, although it is currently still in the internal testing phase. Product entrance: https://top.aibase.com/tool/lumi. The core highlight of Lumi is its model sharing and management features, allowing users to easily upload their developed AI models.

Xiaomi's upcoming Xiaomi 15 series smartphones will no longer offer an 8GB RAM version, instead, the base model's RAM configuration will start at 12GB, with a projected price increase. Xiaomi representative Wang Teng noted that future flagship models are likely to eliminate the 8GB RAM option due to the higher memory demands of on-device AI models. He suggested that as AI technology becomes more widespread in smartphones, users should opt for higher RAM versions whenever financial conditions permit. He also advised consumers to be aware of the pricing differences of RAM across different brands.

Vienna-based AI governance and compliance solutions provider Daiki GmbH today announced the completion of a €1.5 million seed funding round. The funds will be used to support the company's expansion into the European market and product development, marking a significant step for Daiki in promoting the responsible deployment of AI by European enterprises. Daiki offers SaaS compliance solutions tailored to the EU AI Act and ISO standards, including ISO 13485 certification for medical device manufacturers. The product, developed by a multidisciplinary team of experts, includes integrated documentation and quality management.

Dow Jones, the parent company of The Wall Street Journal, and the New York Post are suing AI-driven search startup Perplexity for using their news content to train its large language model. The publications from these two news groups accuse Perplexity of copyright infringement by generating answers to people's queries using their articles, thereby diverting traffic from the publications' websites. 'This lawsuit is brought by news publishers seeking compensation as Perplexity openly plans to provide services for free.'

Following the New York Times, the New York Post (NYP Holdings) and the Wall Street Journal (Dow Jones) have recently jointly filed a lawsuit against the AI company Perplexity AI in federal court in Manhattan, accusing it of 'mass illegal copying' of copyright works from these two media outlets. This AI startup, backed by Amazon founder Jeff Bezos, is facing serious copyright infringement charges. The lawsuit demands that Perplexity cease using these news articles to respond to queries.

A recent study led by the Technion-Israel Institute of Technology reveals that large language models (LLMs) may be more knowledgeable than they appear. Researchers found that LLMs' internal representations encode information about the correctness of their outputs, allowing them to identify the correct answer even when they ultimately generate an incorrect one. The research team focused on analyzing LLM errors in long text generation, which is more aligned with their real-world application scenarios. They constructed an error detection dataset to compare the model's outputs.

Recently, Perplexity introduced a new feature called 'Internal Knowledge Search', which allows its Pro and Enterprise Pro users to query both internet information and their internal databases on a single platform. This new functionality aims to enhance work efficiency for enterprises, enabling users to more conveniently access the information they need. However, it is important to note that users can only upload documents they deem important to the platform, and the Internal Knowledge Search feature will be limited to these uploaded documents.

Recently, the renowned media outlet The New York Times sent a cease-and-desist letter to an AI startup named Perplexity, demanding that the company stop using its content. This news was first reported by The Wall Street Journal and has drawn widespread attention. In fact, this is not the first time The New York Times has clashed with AI companies over content usage issues. Last year, the paper filed a lawsuit against OpenAI, accusing it of illegally using their content while training AI models.

Apple Inc. recently launched a significant update for its multimodal AI model MM1, upgrading it to version MM1.5. This upgrade represents more than just a simple change in version number; it is a comprehensive enhancement of capabilities, showcasing the model's stronger performance across various fields. The core upgrade of MM1.5 lies in its innovative data processing methods. The model utilizes a data-centric training approach, carefully selecting and optimizing the training dataset. Specifically, MM1.5 employs high-definition OCR data and synthetic image descriptions, along with optimizations.