Artificial Intelligence
A study by Canva and Sago shows that 45% of job seekers globally use AI to enhance their resumes. Surprisingly, 90% of hiring managers find this practice appropriate, with nearly half embracing AI’s use for interview content creation. It’s predicted that traditional text-only resumes may become obsolete in the near future. Additionally, research confirms that…
Midjourney offers AI image generation for customizable wall art, with a variety of styles available such as Ukrainian Folk Art, Eero Aarnio, Huichol Art, Victorian Era Cabinet Card, Yu-Gi-Oh, Joost Swarte, Dana Trippe, Marcel Janco, Milo Manara, and Nina Chanel Abney. These prompts help create unique and personalized AI wall art for your space.
The LangGraph library addresses the need for applications to maintain ongoing conversations, remember past interactions, and make informed decisions. It utilizes language models and supports cyclic data flow, enabling the creation of complex and responsive agent-like behaviors. This innovative approach streamlines development and opens new possibilities for crafting intelligent applications.
Adept AI researchers have introduced Fuyu-Heavy, a new multimodal model designed for digital agents. It is the world’s third-most-capable multimodal model, demonstrating commendable performance. The development faced challenges due to its scale but showed effectiveness in conversational AI. Researchers aim to enhance its base-model capabilities and connect it to build reliable products. Source: MarkTechPost.
Large-scale multilingual language models form the basis of many cross-lingual and non-English NLP applications. However, their use leads to a performance decline in individual languages due to inter-language competition for model capacity. To address this, researchers from the University of Washington, Charles University, and the Allen Institute propose Cross-lingual Expert Language Models (X-ELM), which aim…
Researchers from ETH Zurich, Google, and Max Planck Institute propose West-of-N, a novel strategy to improve reward model performance in RLHF. By generating synthetic preference data, the method significantly enhances reward model accuracy, surpassing gains from human feedback and other synthetic generation methods. The study showcases the potential of Best-of-N sampling and semi-supervised learning for…
Language models like GPT-4 are powerful but sometimes produce inaccurate outputs. Stanford and OpenAI researchers have introduced “meta-prompting,” enhancing these models’ capabilities. It involves breaking down complex tasks for specialized “expert” models within the LM framework. Meta-prompting, along with a Python interpreter, outperforms traditional methods, marking a significant advancement in language processing.
The text discusses the significance of foundation models like Large Language Models, Vision Transformers, and multimodal models in reshaping AI applications. These models, while versatile, require substantial resources for development and deployment. Research is focused on developing more resource-efficient strategies to minimize their environmental impact and cost, while maintaining performance.
The AI-generated deep fake images of Taylor Swift sparked widespread criticism and concerns over misinformation. Microsoft CEO Satya Nadella expressed alarm and urged action to implement stricter regulations and collaborative efforts between law enforcement and tech platforms. The incident also prompted public outrage and a digital manhunt, demonstrating the far-reaching impact of deep fake crimes.
Researchers found that people skeptical of human-caused climate change or the Black Lives Matter movement were initially disappointed after interacting with a popular AI chatbot. However, they left the conversation more supportive of the scientific consensus on climate change or BLM. The study focused on how chatbots engage with individuals from diverse cultural backgrounds.
The Quarkle development team recently launched “PriomptiPy,” a Python implementation of Cursor’s Priompt library, introducing priority-based context management to streamline token budgeting in large language model (LLM) applications. Despite some limitations, the library demonstrates promise for AI developers by facilitating efficient and cache-friendly prompts, with future plans to enhance functionality and address caching challenges.
Researchers at UCSD and Adobe have introduced the DITTO framework, enhancing control of pre-trained text-to-music diffusion models. It optimizes noise latents at inference time, allowing specific and stylized outputs. Leveraging extensive music datasets, the framework outperforms existing methods in control, audio quality, and efficiency, representing significant progress in music generation technology.
Generative models for text-to-image tasks have seen significant advancements, but extending this capability to text-to-video models presents challenges due to motion complexities. Google Research and other institutes introduced Lumiere, a text-to-video diffusion model, addressing motion synthesis challenges with a novel architecture. Lumiere outperforms existing models in video synthesis, providing high-quality results and aligning with textual…
The Orion-14B, a new multilingual language model, with its base model trained on 14 billion parameters and 2.5 trillion tokens spanning various languages, offers unique features for natural language processing tasks. It includes models tailored for specific applications, excelling in human-annotated tests and displaying strong multilingual capabilities, making it a significant advancement in large language…
ProtHyena, developed by researchers at Tokyo Institute of Technology, is a protein language model that addresses attention-based model limitations. Utilizing the Hyena operator, it efficiently processes long protein sequences and outperforms traditional models on various biological tasks. With subquadratic time complexity, ProtHyena marks a significant advancement in protein sequence analysis. [49 words]
Researchers in Japan have developed a two-legged biohybrid robot inspired by human gait, using a combination of muscle tissues and artificial materials. The robot is capable of walking, pivoting, and efficiently converting energy into movement, harnessing the flexibility and fine movements of the human body.
Chemists have created ‘RoboChem’, an autonomous chemical synthesis robot with integrated AI and machine learning capabilities. This benchtop device surpasses human chemists in speed, accuracy, and innovation. It has the potential to greatly expedite chemical discovery for pharmaceutical and various other purposes.
The article discusses the challenges of aligning Large Language Models (LLMs) with human preferences in reinforcement learning from human feedback (RLHF), focusing on the phenomenon of reward hacking. It introduces Weight Averaged Reward Models (WARM) as a novel, efficient strategy to mitigate these challenges, highlighting its benefits and empirical results. Reference: https://arxiv.org/pdf/2401.12187.pdf
The development of large language models (LLMs) like GPT and LLaMA has led to significant advances in natural language processing. A cost-effective alternative to creating these models from scratch is the fusion of existing pre-trained LLMs, as demonstrated by the FuseLLM approach. This method has shown superior performance in various tasks and offers promising advancements…
Researchers propose three measures to increase visibility into AI agents for safer functioning: agent identifiers, real-time monitoring, and activity logs. They identify potential risks, including malicious use, overreliance, delayed impacts, multi-agent risks, and sub-agents. The paper stresses the need for governance structures and improved visibility to manage and mitigate these risks.