Recently, Google.org announced an investment of over $25 million aimed at helping educators and students acquire essential AI skills, opening a door full of opportunities for them in this intelligent era. This substantial funding from the 'AI Opportunity Fund' is not just a number, but a testament to Google's commitment to educational equity. It will benefit over 500,000 educators and students, assisting them in navigating the challenges and opportunities brought by AI in the classroom. The experience of special education teacher Matthew Jones vividly illustrates this commitment.

Recently, Google announced a new feature in its search results aimed at helping users better understand how content is created and modified. This initiative follows Google's joining of the Content Provenance and Authenticity Alliance (C2PA), which includes major brands like Amazon, Adobe, and Microsoft, all dedicated to combating online misinformation. Google stated that this new feature will be gradually rolled out over the coming months, using current content credential standards (i.e., image metadata) to label AI-generated or edited images in search results.

Enterprise AI leader Glean raised over $260 million in its latest Series E financing round, with the company's valuation reaching $4.6 billion, doubling from $2.2 billion six months ago. This round was co-led by Altimeter and DST Global, with participation from several investment firms including Craft Ventures, Sapphire Ventures, and SoftBank Vision Fund 2. Along with the financing, Glean launched Work AI.

Recently, an analysis by The Guardian revealed that there may be serious misleading practices by tech companies in handling the environmental impact of their AI data centers. The emission data reported by tech giants like Microsoft, Google, Meta, and Apple significantly diverges from reality. According to this analysis, the actual emissions from these companies are 662% higher than the figures they officially disclose, and this is just the tip of the iceberg, as this study only covers data from 2020 to 2022. Image source note: Image generated by AI, image licensed from service provider Midjou.

Recently, Google was sued by a company named Gemini Data for its newly launched AI service 'Gemini'. Gemini Data is a company that offers an enterprise-level AI platform and believes that Google used their registered trademark without legal authorization. The sequence of events is as follows: in February 2023, Google changed the name of its generative AI service from 'Bard' to 'Gemini', and prior to this, in December 2023,

Recently, Google announced the launch of a new open-source AI model, DataGemma, aimed at addressing the 'hallucination' problem that large language models (LLMs) often encounter when handling statistical data. This hallucination phenomenon causes the model to potentially provide inaccurate answers to questions related to numbers and statistics. The release of the DataGemma model marks a significant advancement for Google in the field of AI. Image source note: Image generated by AI, image licensed by service provider Midjourney to reduce hallucinations during statistical queries.

EU regulators have launched an investigation into Google's PaLM2 language model, focusing on data privacy compliance. The Irish Data Protection Commission is assessing the risks posed to EU residents' personal data. This underscores the EU's commitment to AI privacy rules and the global trend towards stricter data protection for AI technologies.....

Google has recently launched an exciting experimental feature—AI-generated podcasts. This feature can transform your research materials into engaging podcast segments, featuring two 'hosts' discussing the information you have gathered.

At the 'All-In Summit 2024', Google co-founder and former Alphabet president Sergey Brin expressed his excitement about the latest advancements in AI and stated that he is working at Google almost every day. Brin confirmed his return to Google's headquarters last year to participate in AI projects, emphasizing the value of the rapid development in the AI field. He noted that algorithm improvements may have already surpassed the increase in computational power requirements, maintaining an optimistic view on AI and believing that future AI model training will not require a significant increase in computational capabilities. Brin's return has implications for Google's future development and AI.

At the recent Apple event, the company launched not only new iPhones, AirPods, and Apple Watch Series 10 but also introduced AI-driven visual intelligence for the first time. This innovative feature equips the iPhone camera with the ability to recognize and search for photographed subjects, such as objects or restaurant signs, providing relevant information through AI technology. Users can simply take a picture within the camera app to quickly obtain the needed data. Apple emphasized data privacy, ensuring that user data is stored securely in a private cloud.

Google has launched Illuminate, an innovative tool that transforms academic papers into engaging audio podcasts using the language model Gemini. Users can easily absorb knowledge through this platform, especially suitable for learning during fragmented time. Illuminate supports classic computer science papers and offers features like fast forward, rewind, and playback speed adjustment for convenient sharing. Currently, its functions mainly target English content, and it does not provide downloads or subtitles, but there are hopes for further optimization of user experience in the future.

Google is testing a new feature called 'Ask Photos', allowing users to explore their photo library in an innovative way. By asking questions such as 'Where did we camp last time at Yosemite?' or 'What did we eat at the hotel in Stanley?', users can receive answers and retrieve related images. Powered by Google's Gemini AI model, it analyzes photo content to provide answers and images, supports natural language searching, and sorting by date or relevance, with support for more languages rolling out in the coming weeks. This feature has been launched on Android and iOS platforms.

Google Photos has recently rolled out the AI-powered search tool 'Ask Photos' to select users in the U.S. through early access, revolutionizing interactions with digital albums. This feature allows users to query and retrieve photos using natural language, going beyond traditional keyword searches. The technology behind it is the Gemini AI model, which can understand photo content and metadata, providing deeper search results. Users can ask complex questions, and the AI will filter the best results based on various factors such as photo quality and location information.

Google's open-source RB-Modulation model has garnered attention in AI image processing for its training-free personalization, high fidelity, robust style description capability, and adaptability. It enables high-quality image style customization without additional training and directly supports mainstream image generation models. The model's core advantage lies in its innovative Attention Feature Aggregation (AFA) module, which effectively addres....

Google has made a major update to the Chrome browser by integrating an AI chatbot named Gemini into the address bar. Users can simply type '@gemini' followed by their query in the address bar to receive a response from Gemini. This integration makes AI a default part of the browsing experience for Chrome's vast user base, eliminating the need for extra navigation. Gemini uses a lightweight version of Google's advanced language model family, Gemini 1.5 Flash, offering significantly improved AI capabilities over its predecessor.

The Google DeepMind team, in collaboration with academic institutions, has developed an innovative method called Generative Reward Model (GenRM) aimed at improving the accuracy and reliability of generative AI in reasoning tasks. GenRM incorporates a validation process into text generation tasks, allowing the model to simultaneously generate and evaluate potential solutions while supporting Chain of Thought (CoT), enhancing the comprehensiveness of the validation process. Compared to traditional methods, GenRM has shown significant advantages in multiple tests, with accuracy improvements ranging from 16% to 64%, particularly in...

In modern relational databases, Cardinality Estimation (CE) techniques are crucial for optimizing query execution plans, directly affecting query efficiency and database performance. Traditional cardinality estimation methods are based on simplified assumptions and often perform poorly on complex query predictions, whereas learning-based CE models can provide more accurate predictions but face challenges such as long training times, requirement of large amounts of data, and lack of systematic evaluation. To address this challenge, the Google research team has launched the CardBench benchmarking framework, integrating over 20 real-world databases and thousands of queries.