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Recently, Cluely, a startup co-founded by two Columbia University dropouts, Chungin Roy Lee and Neel Shanmugam, announced the completion of a $5.3 million seed funding round led by Abstract Ventures and Susa Ventures. Cluely primarily launched an AI tool called Interview Coder, dubbed an "interview cheating tool."

A recent study from Columbia University's Tow Center for Digital Journalism sounds the alarm on the accuracy of AI search services. The research reveals significant accuracy issues in ChatGPT's citation of news sources, with even publishers directly cooperating with OpenAI not spared. The research team conducted a comprehensive test on 200 news citations from 20 different publishers, resulting in shocking findings: ChatGPT had errors or partially incorrect source information in as many as 153 cases.

Recently, the UK's digital regulator Ofcom released a compelling report exploring gender-based differences in online behavior. The report shows that men significantly surpass women in the usage of generative artificial intelligence (AI) and online dating platforms. According to the survey, approximately 50% of men reported using generative AI in the past year, whereas only 33% of women reported the same. Meanwhile, 29% of women stated they are unfamiliar with generative AI, and 30% indicated that they do not know how to use the technology.

With the rapid development of artificial intelligence technology, AI-generated videos are becoming increasingly realistic, posing serious security risks to society. Recently, a $25 million fraud case utilized a lifelike video created by AI. To address this challenge, a research team at Columbia Engineering has developed an innovative tool called DIVID (DIffusion-generated VIdeo Detector) designed to detect AI-generated videos.

A recent study by Ofcom shows that 80% of British teenagers use generative AI, making them early adopters of Generation Z. Snapchat's My AI and ChatGPT have become the most popular AI tools among teenagers and adult users. Ofcom is concerned about the potential impact of new cybersecurity regulations on AI tools and is urging companies to strengthen product safety measures. Generative AI is widely used in entertainment, work, and learning, but Ofcom has expressed concerns about the risks associated with AI.

Researchers from Apple and Columbia University have developed the Ferret multimodal language model, aimed at achieving advanced image understanding and description. The Ferret model possesses strong global understanding capabilities, able to handle free text and referenced regions, outperforming traditional models. The researchers created the GRIT dataset, which includes 1.1 million samples, to guide the model in reference and localization tasks. Ferret-Bench evaluations show that Ferret outperforms the best MLLM models by an average of 20.4% while reducing object-related errors.

The multi-modal large model 'Ferret' developed by Apple's AI/ML team in collaboration with Columbia University has successfully tackled Google's CAPTCHAs, being capable of recognizing traffic lights and improving the accuracy of large models in 'see-say-answer' tasks. Ferret's innovation lies in its ability to integrate spatial understanding of references and locations while comprehending semantics and targets, distinguishing it from traditional multi-modal models. By employing a hybrid regional representation method that combines discrete coordinates and continuous features, the model has demonstrated exceptional performance in multi-task evaluations, particularly in reference and visual grounding.

Harvard and Columbia have released the open dataset OpenProteinSet, containing 16 million protein multiple sequence alignments and related data to support AI model training. AlphaFold 2 has achieved a milestone in the accuracy of protein structure predictions, but its proprietary data has limited progress for other researchers. OpenProteinSet includes MSAs for all proteins in the PDB, providing ample precomputed MSA resources for the protein machine learning community. This dataset can be used for various tasks in structural biology.

The AI research assistant developed by researchers directly replaces you in writing papers, allowing humans to only focus on graduating.