-
Autonomous synthesis robot uses AI to speed up chemical discovery
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.
-
Google DeepMind Researchers Propose WARM: A Novel Approach to Tackle Reward Hacking in Large Language Models Using Weight-Averaged Reward Models
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
-
This AI Paper from Sun Yat-sen University and Tencent AI Lab Introduces FUSELLM: Pioneering the Fusion of Diverse Large Language Models for Enhanced Capabilities
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…
-
Can we increase visibility into AI agents to make them safer?
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 upcoming EU AI Act Summit 2024
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…
-
Graphic Fake Images of Taylor Swift Spread on X
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 AI Releases Kan-Llama: A 7B Llama-2 LoRA PreTrained and FineTuned on ‘Kannada’ Tokens
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.
-
6 Best ChatGPT Alternatives in 2024
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…
-
RAND report says LLMs don’t increase risk of biological attacks
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…
-
Meet Medusa: An Efficient Machine Learning Framework for Accelerating Large Language Models (LLMs) Inference with Multiple Decoding Heads
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.