Artificial Intelligence
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.
The EU AI Act Summit 2024, held in London on February 6, 2024, focuses on the groundbreaking EU AI Act, offering practical guidance for stakeholders. The Act introduces comprehensive AI regulations, categorized by risk levels, and revolving around compliance responsibilities and opportunities for the industry. The summit features notable speakers, sessions, and registration discounts. Visit…
The spread of explicit and fake AI-generated images of Taylor Swift on social media platform X has raised concerns about the challenge of controlling such content online. Despite platform rules, the images spread widely, leading to potential legal action by Swift and criticism of X’s response. Fans have used hashtags to share real content in…
Tensoic introduced Kannada Llama (Kan-LLaMA), aiming to overcome limitations of language models (LLMs) by emphasizing the importance of open models for natural language processing and machine translation. The paper presents the solution for enhancing efficiency of Llama-2 vocabulary for processing Kannada texts through low-level optimization, dataset pretraining, and collaboration for broader accessibility.
The post highlights the best ChatGPT alternatives and their key features. It covers GitHub Copilot’s code automation, Writesonic’s content marketing bots, Claude AI’s contextual writing, Perplexity AI’s research capabilities, Microsoft Copilot’s Microsoft 365 integration, and Poe AI’s diverse AI models. Each alternative’s pricing, best use, and unique features are outlined to aid in selecting a…
The recent RAND report concludes that current Large Language Models (LLMs) do not significantly increase the risk of a biological attack by non-state actors. Their research, conducted through a red-team exercise, found no substantial difference in the viability of plans generated with or without LLM assistance. However, the study emphasized the need for further research…
The latest advancement in AI, Large Language Models (LLMs), has shown great language production improvement but faces increased inference latency due to model size. To address this, researchers developed MEDUSA, a method that enhances LLM inference efficiency by adding multiple decoding heads. MEDUSA offers lossless inference acceleration and improved prediction accuracy for LLMs.
This week’s AI news highlights AI excelling in math tests and stirring debate about fake truths. Google unveiled its text-to-video model, while OpenAI ventured into education and faced criticism for data practices. Other developments include legal regulations for AI hiring and Samsung’s collaboration with Google in AI-rich mobile phones. Meanwhile, AI’s impact on healthcare and…
Significant progress has been made in utilizing Large Language Models like GPT-4 and Llama 2 in Artificial Intelligence, showing potential for various sectors. While challenges persist in integrating AI into agriculture due to limited specialized training data, the introduction of a pioneering pipeline by Microsoft researchers, combining Retrieval-Augmented Generation (RAG) and fine-tuning methods, has notably…
The text discusses challenges in model-based reinforcement learning (MBRL) due to imperfect dynamics models. It introduces COPlanner, an innovation using uncertainty-aware policy-guided model predictive control (UP-MPC) to address these challenges. Through comparisons and performance evaluations, COPlanner is shown to substantially improve sample efficiency and asymptotic performance in handling complex tasks, advancing the understanding and practical…