Google AI Studio and Gemini API have recently launched the 'Real-Time Connection with Google Search' feature, aimed at helping developers improve the accuracy of AI model responses by integrating real-time data from Google Search. With this update, the Gemini 1.5 model can retrieve the latest information from Google Search, enhancing the accuracy and transparency of responses. Developers can directly access this feature in the 'Tools' section of Google AI Studio or in the Gemini API.

On the front lines of the fight against cancer, scientists at Harvard Medical School have exciting news. They have recently launched a super smart AI model called CHIEF that can accurately diagnose various types of cancer, predict patient outcomes, and even recommend treatment plans. This AI acts like an all-in-one medical assistant, providing clear guidance to doctors in the complex realm of cancer diagnosis. CHIEF is a specially trained AI system that is distinctly different from traditional AIs that can only perform single tasks.

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.

At the 2024 Inclusion · Bund Conference, Ant Group shared its latest progress in building knowledge-enhanced professional intelligent agents and launched the research and development achievement of combining knowledge graphs with large models—the Knowledge-Enhanced Large Model Service Framework KAG. This framework, introduced by Liang Lei, head of the knowledge graph at Ant Group, aims to guide decision-making and retrieval through graph logical symbols, significantly improving the precision and logical rigor of decisions in vertical domains.

Researchers at Harvard Medical School have developed an AI model named CHIEF, which is capable of handling various cancer diagnostic processes, providing more accurate diagnoses and assessments of different cancers, predicting patient survival rates, and offering treatment recommendations. Compared to existing AI systems, CHIEF represents a significant breakthrough in flexibility and multifunctionality, being able to perform multiple tasks and tested on 19 types of cancer. By analyzing large amounts of image data, including unmarked images and complete slice images, CHIEF excels in cancer detection and tumor origin identification.

Today, Mita AI Search announced an upgrade for programming-related inquiries. The new features of Mita AI Search include the ability to execute code with one click, allowing users to directly see the results of the AI-generated code. Additionally, Mita AI Search has enhanced its debug functionality for programming errors, assisting users in quickly fixing issues encountered during compilation or runtime.

Researchers at Binghamton University in New York, led by Ahmed Abdeen Hammed, have developed a machine learning algorithm called xFakeSci that can identify fabricated academic papers with up to 94% accuracy. Hammed and his team created 50 fake papers on topics including Alzheimer's disease, cancer, and depression, and conducted comparative analyses with genuine papers. They found that the number of bigrams in the fake papers was significantly lower than in the real papers, and the relevance of the content was much stronger. Hammed plans to expand the algorithm to more fields in response to A

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...

The Oklahoma City Police Department is experimenting with the AI chatbot 'Draft One' to generate reports in order to save time. Developed by Axon, the system utilizes ChatGPT technology to quickly produce reports from audio recordings. Supporters believe this could significantly improve efficiency, but critics are concerned about potential errors, biases, and the risks of power abuse that automation could bring. Activist Aurelius Francisco expresses discomfort with the use of AI and tasers from the same company, fearing potential misuse.

Zhejiang University and the University of Texas developed an AI algorithm that accurately predicts earthquakes in China, forecasting 14 quakes within a 300 km range a week in advance with a 70% accuracy rate, including intensity calculations. This breakthrough offers new hope for earthquake warning and disaster response. While global application of the algorithm remains uncertain, scientists are optimistic about improving prediction accuracy and ....

Text-to-SQL technology allows ordinary users to query databases easily through natural language, but accurately converting complex database structures into SQL commands poses challenges. A research team from South China University of Technology and Tsinghua University has proposed a new method—MAG-SQL (Multi-Agent Generative Model), aimed at enhancing the accuracy of this process. MAG-SQL achieves this through the collaboration of multiple agents, including a 'Soft Pattern Linker', a 'Goal-Condition Decomposer', a 'Sub-SQL Generator', and a 'Sub-SQL Refiner'.